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1

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

2

Weather Research and Forecasting Model 2.2 Documentation  

E-Print Network [OSTI]

................................................................................................. 20 3.1.2 Integrate's Flow of ControlWeather Research and Forecasting Model 2.2 Documentation: A Step-by-step guide of a Model Run .......................................................................................................................... 19 3.1 The Integrate Subroutine

Sadjadi, S. Masoud

3

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia  

E-Print Network [OSTI]

values were driven mainly by WRF errors in wind speed simulation. However, in both cases the qualityFire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009 has been simulated using the Weather Research and Forecasting (WRF) model

Evans, Jason

4

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations during ETEX 2  

E-Print Network [OSTI]

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations an operational numerical weather prediction model to forecast air quality are also investigated. These potential a numerical weather prediction (NWP) model independently of the CTM. The NWP output is typically archived

Dacre, Helen

5

HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson  

E-Print Network [OSTI]

and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1. INTRODUCTION Numerical Weather Prediction (NWP) models are widely used by avalanche practitioners. Their de

Jamieson, Bruce

6

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

7

PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico | Open  

Open Energy Info (EERE)

Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Jump to: navigation, search Name PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Agency/Company /Organization Pacific Northwest National Laboratory Sector Energy Topics Co-benefits assessment, - Environmental and Biodiversity, - Health, Background analysis Resource Type Publications Website http://www.pnl.gov/atmospheric Country Mexico UN Region Latin America and the Caribbean References PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico[1] PNNL Publications on WRF-Chem modeling in Mexico include: Fast JD, M Shrivastava, RA Zaveri, and JC. Barnard. 2010. "Modeling particulates and direct radiative forcing from urban to synoptic scales downwind of Mexico City." Annual European Geosciences Union Assembly,

8

USING SATELLITE OBSERVATIONS AND REANALYSES TO EVALUATE CLIMATE AND WEATHER FORECAST MODELS  

E-Print Network [OSTI]

USING SATELLITE OBSERVATIONS AND REANALYSES TO EVALUATE CLIMATE AND WEATHER FORECAST MODELS Richard Email: rpa@mail.nerc-essc.ac.uk ABSTRACT Satellite observations of water vapour and radiative fluxes are used in combination with reanalyses data to evaluate the Met Office weather and climate prediction

Allan, Richard P.

9

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network [OSTI]

. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surfaceAmending Numerical Weather Prediction forecasts using GPS Integrated Water Vapour: a case study to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents

Stoffelen, Ad

10

Prediction versus Projection: How weather forecasting and  

E-Print Network [OSTI]

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

11

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

MultiscaleNumericalWeatherPredictionModel. Progressassimilatingnumericalweatherpredictionmodelforsolarcustomizable numericalweatherpredictionmodelthatis

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

12

Resolved Turbulence Characteristics in Large-Eddy Simulations Nested within Mesoscale Simulations Using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

One-way concurrent nesting within the Weather Research and Forecasting Model (WRF) is examined for conducting large-eddy simulations (LES) nested within mesoscale simulations. Wind speed, spectra, and resolved turbulent stresses and turbulence ...

Jeff Mirocha; Branko Kosovi?; Gokhan Kirkil

2014-02-01T23:59:59.000Z

13

Design of a next-generation regional weather research and forecast model.  

SciTech Connect (OSTI)

The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies, fill physics numerical weather prediction, air-quality simulation, and regional climate. It will eventually supersede large, well-established but aging regional models now maintained by the participating institutions. The WRF effort includes re-engineering the underlying software architecture to produce a modular, flexible code designed from the outset to provide portable performance across diverse computing architectures. This paper outlines key elements of the WRF software design.

Michalakes, J.

1999-01-13T23:59:59.000Z

14

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Journals Connector (OSTI)

For over 30 years, weather forecasting for the Antarctic continent and adjacent Southern Ocean has relied on weather satellites. Significant advancements in forecasting skill have come via the weather satellite. The advent of the high-resolution ...

Matthew A. Lazzara; Linda M. Keller; Charles R. Stearns; Jonathan E. Thom; George A. Weidner

2003-02-01T23:59:59.000Z

15

Every cloud has a silver lining: Weather forecasting models could predict brain tumor  

E-Print Network [OSTI]

, and combine them with incoming data streams from weather stations and satellites. Now, an innovative new study methodology used to assimilate data for weather forecasting could be used to predict the spread of brain. Synthetic magnetic resonance images of a hypothetical tumor were used for this purpose. Data assimilation

Kuang, Yang

16

Incorporation of 3D Shortwave Radiative Effects within the Weather Research and Forecasting Model  

SciTech Connect (OSTI)

A principal goal of the Atmospheric Radiation Measurement (ARM) Program is to understand the 3D cloud-radiation problem from scales ranging from the local to the size of global climate model (GCM) grid squares. For climate models using typical cloud overlap schemes, 3D radiative effects are minimal for all but the most complicated cloud fields. However, with the introduction of ''superparameterization'' methods, where sub-grid cloud processes are accounted for by embedding high resolution 2D cloud system resolving models within a GCM grid cell, the impact of 3D radiative effects on the local scale becomes increasingly relevant (Randall et al. 2003). In a recent study, we examined this issue by comparing the heating rates produced from a 3D and 1D shortwave radiative transfer model for a variety of radar derived cloud fields (O'Hirok and Gautier 2005). As demonstrated in Figure 1, the heating rate differences for a large convective field can be significant where 3D effects produce areas o f intense local heating. This finding, however, does not address the more important question of whether 3D radiative effects can alter the dynamics and structure of a cloud field. To investigate that issue we have incorporated a 3D radiative transfer algorithm into the Weather Research and Forecasting (WRF) model. Here, we present very preliminary findings of a comparison between cloud fields generated from a high resolution non-hydrostatic mesoscale numerical weather model using 1D and 3D radiative transfer codes.

O'Hirok, W.; Ricchiazzi, P.; Gautier, C.

2005-03-18T23:59:59.000Z

17

Model error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4  

E-Print Network [OSTI]

numerical weather prediction mod­ els. A simple law is derived to relate model error to likely shadowingModel error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4 in the model, and inac­ curate initial conditions (Bjerknes, 1911). Because weather models are thought

Smith, Leonard A

18

A GIS tool for the evaluation of the precipitation forecasts of a numerical weather prediction model using satellite data  

Science Journals Connector (OSTI)

In this study, the possibility of implementing Geographic Information Systems (GIS) for developing an integrated and automatic operational system for the real-time evaluation of the precipitation forecasts of the numerical weather prediction model BOLAM (BOlogna Limited Area Model) in Greece, is examined. In fact, the precipitation estimates derived by an infrared satellite technique are used for real-time qualitative and quantitative verification of the precipitation forecasts of the model BOLAM through the use of a GIS tool named as precipitation forecasts evaluator (PFE). The application of the developed tool in a case associated with intense precipitation in Greece, suggested that PFE could be a very important support tool for nowcasting and very short-range forecasting of such events.

Haralambos Feidas; Themistoklis Kontos; Nikolaos Soulakellis; Konstantinos Lagouvardos

2007-01-01T23:59:59.000Z

19

Generalized Additive Models versus Linear Regression in Generating Probabilistic MOS Forecasts of Aviation Weather Parameters  

Science Journals Connector (OSTI)

The skill of probabilistic Model Output Statistics forecasts generated from Generalized Additive Models (GAM) is compared to that of traditional multiple linear regression techniques. Unlike linear regression, where each predictor term in the ...

Robert L. Vislocky; J. Michael Fritsch

1995-12-01T23:59:59.000Z

20

Using a Business Process Model as a Central Organizing Construct for an Undergraduate Weather Forecasting Course  

Science Journals Connector (OSTI)

For the last five years, the author has employed a business process model as a central organizing construct for the senior-level Forecasting Techniques course at Embry- Riddle Aeronautical University's Daytona Beach, Florida, campus. The process model ...

John M. Lanicci

2012-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

NOAA National Weather Service I'm a weather forecaster.  

E-Print Network [OSTI]

.S.D EPARTMENT OF COM M ERCE How Do You Make a Weather Satellite? How Do You Make a Weather Satellite? #12;Well you put a truck in orbit? So it can carry all the things needed to make a working weather satelliteNOAA National Weather Service I'm a weather forecaster. I need to see clouds and storms from way up

Waliser, Duane E.

22

Weather Forecasts Slowly Clearing Up  

Science Journals Connector (OSTI)

...Computer models fed by automated observing stations...produced more realistic simulations of the weather and thus...NWS's Environmental Modeling Center in College Park, Maryland...landfall, though ECMWF modeling gave an inkling a whopping...equations of motion allow rapid vertical acceleration...

Richard A. Kerr

2012-11-09T23:59:59.000Z

23

Weather Forecast Data an Important Input into Building Management Systems  

E-Print Network [OSTI]

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01T23:59:59.000Z

24

Lessons from Deploying NLG Technology for Marine Weather Forecast Text Generation  

E-Print Network [OSTI]

model along with other sources of weather data such as satellite pictures and their own forecastingLessons from Deploying NLG Technology for Marine Weather Forecast Text Generation Somayajulu G Language Generation (NLG) system that produces textual weather forecasts for offshore oilrigs from

Sripada, Yaji

25

Introduction An important goal in operational weather forecasting  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a priori102 Introduction An important goal in operational weather forecasting is to reduce the number

Haak, Hein

26

A soil moisture assimilation scheme using satellite-retrieved skin temperature in meso-scale weather forecast model  

Science Journals Connector (OSTI)

A thermodynamically consistent soil moisture assimilation scheme for clear sky and snow free conditions has been developed for the meso-scale modeling system in the Arctic region by using satellite-derived skin temperatures. Parallel control and sensitivity modeling experiments were designed and their results demonstrated that the assimilation scheme successfully improves the soil moistures that were deliberately perturbed initially, indicating capability of the scheme to correct bias in the soil moisture initialization. Moreover, the resultant benefit of this assimilation scheme does not only lie in the improvement of soil moisture; the skin temperature also consequently exhibits improvements in a thermodynamic consistency. A real application of the assimilation scheme with satellite-retrieved skin temperature exhibited noticeable positive impacts on the modeling simulation and weather forecast; the model obviously captured meso-scale features of soil moistures as well as the skin temperatures. The warming tendency bias in original model simulations was removed to a considerable extent by this assimilation scheme.

Jing Zhang; Xiangdong Zhang

2010-01-01T23:59:59.000Z

27

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network [OSTI]

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

28

Tracking tropical cloud systems - Observations for the diagnosis of simulations by the Weather Research and Forecasting (WRF) Model  

SciTech Connect (OSTI)

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the vicinity of the ARM Tropical Western Pacific sites. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest a computational paradox where, even though the size of the simulated systems are about half of that observed, their longevities are still similar. The explanation for this seeming incongruity will be explored.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E.; Jensen, M.; Zhang, M.

2010-03-15T23:59:59.000Z

29

Tracking tropical cloud systems for the diagnosis of simulations by the weather research and forecasting (WRF) model  

SciTech Connect (OSTI)

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the tropical warm pool. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest that the organization of the mesoscale convective systems is particularly sensitive to the cloud microphysics parameterization used.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E. P.; Jensen, M. P.; Zhang, M. H.; Boer, E.

2010-06-27T23:59:59.000Z

30

Study and implementation of mesoscale weather forecasting models in the wind industry.  

E-Print Network [OSTI]

?? As the wind industry is developing, it is asking for more reliable short-term wind forecasts to better manage the wind farms operations and electricity (more)

Jourdier, Bndicte

2012-01-01T23:59:59.000Z

31

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

iscriticalforcoastalCaliforniasolarforecasting. affectingsolarirradianceinsouthernCalifornia. solar photovoltaicgeneration(thesouthernCalifornia

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

32

ZHANG, XUEJIN. Adapting the Weather Research and Forecasting Model for the Simulation of Regional Climate in East Africa. (Under the direction of Dr. Lian Xie).  

E-Print Network [OSTI]

and society for regional climate information. The current Weather Research and Forecasting (WRF) RCM inherits several advantages of the original WRF model. For example, (1) it can be used for multiple scale infrastructure to distinguish the scientific problems from engineering problems. In order to adapt WRF for long

Liu, Paul

33

The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting  

SciTech Connect (OSTI)

The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity by assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.

Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory; Chen, Yue [Los Alamos National Laboratory; Koller, Josef [Los Alamos National Laboratory; Henderson, Michael G [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

34

Sunny outlook for space weather forecasters  

Science Journals Connector (OSTI)

... For decades, companies have tailored public weather data for private customers from farmers to airlines. On Wednesday, a group of businesses said that they ... utilities and satellite operators. But Terry Onsager, a physicist at the SWPC, says that private forecasting firms are starting to realize that they can add value to these predictions. ...

Eric Hand

2012-04-27T23:59:59.000Z

35

Weather Forecasting for Radio Astronomy  

E-Print Network [OSTI]

as complex refractivity..." (Liebe, 1985) For each layer of the atmosphere, calculate: Density of water of Maciolek' profiles Weather conditions for past observations Makes possible the generation of detailed Atmospheric pressure, temperature, and humidity as a function of height above a site (and much more). Derived

Groppi, Christopher

36

Weather-based forecasts of California crop yields  

SciTech Connect (OSTI)

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

Lobell, D B; Cahill, K N; Field, C B

2005-09-26T23:59:59.000Z

37

Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting  

E-Print Network [OSTI]

This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

Goto, Susumu

2007-01-01T23:59:59.000Z

38

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

Multiscale numerical weather prediction model. Progress inassimilating numerical weather prediction model for solarwith numerical weather prediction models. In: Solar Energy

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

39

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

Recently an actuator disk parameterization was implemented in the Weather Research and Forecasting (WRF) Model for large eddy simulation (LES) of wind turbine wakes. To thoroughly verify this model simulations of various types of turbines and atmospheric conditions must be evaluated against corresponding experimental data. In this work numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristicssuch as the velocity deficit centerline location and wake widthas metrics for model verification the simulations show good agreement with the observations. Notable results include a high average velocity deficit decreasing from 73% at a downwind distance x of 1.2 rotor diameters (D) to 25% at x?=?6.6D resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover the wake width expands from 1.4D at x?=?1.2D to 2.3D at x?=?6.6D. Finally new featuresnamely rotor tilt and drag from the nacelle and towerare added to the existing actuator disk model in WRF-LES. Compared to the rotor the effect of the tower and nacelle on the flow is relatively small but nevertheless important for an accurate representation of the entire turbine. Adding rotor tilt to the model causes the vertical location of the wake center to shift upward. Continued advancement of the actuator disk model in WRF-LES will help lead to optimized turbine siting and controls at wind farms.

Matthew L. Aitken; Branko Kosovi?; Jeffrey D. Mirocha; Julie K. Lundquist

2014-01-01T23:59:59.000Z

40

RACORO Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Daniel Hartsock CIMMS, University of Oklahoma ARM AAF Wiki page Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance...

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect (OSTI)

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-03-01T23:59:59.000Z

42

SUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud Reiter  

E-Print Network [OSTI]

Weathernews (UK) Ltd. Aberdeen iand@wni.com Abstract Numerical weather prediction (NWP) models produce time is done using guidance from Numerical Weather Prediction (NWP) models; time series data from the NWPSUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud

Reiter, Ehud

43

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe  

Science Journals Connector (OSTI)

Abstract This article combines and discusses three independent validations of global horizontal irradiance (GHI) multi-day forecast models that were conducted in the US, Canada and Europe. All forecast models are based directly or indirectly on numerical weather prediction (NWP). Two models are common to the three validation efforts the ECMWF global model and the GFS-driven WRF mesoscale model and allow general observations: (1) the GFS-based WRF- model forecasts do not perform as well as global forecast-based approaches such as ECMWF and (2) the simple averaging of models output tends to perform better than individual models.

Richard Perez; Elke Lorenz; Sophie Pelland; Mark Beauharnois; Glenn Van Knowe; Karl Hemker Jr.; Detlev Heinemann; Jan Remund; Stefan C. Mller; Wolfgang Traunmller; Gerald Steinmauer; David Pozo; Jose A. Ruiz-Arias; Vicente Lara-Fanego; Lourdes Ramirez-Santigosa; Martin Gaston-Romero; Luis M. Pomares

2013-01-01T23:59:59.000Z

44

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications  

Science Journals Connector (OSTI)

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011) the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems one vertically profiling and another operated over a variety of scanning modes were utilized to obtain forcing for the simulations and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20?W m?2 and 100?W m?2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011 whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. Validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

J. D. Mirocha; B. Kosovic; M. L. Aitken; J. K. Lundquist

2014-01-01T23:59:59.000Z

45

Improved forecasts of extreme weather events by future space borne Doppler wind lidar  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a prioriImproved forecasts of extreme weather events by future space borne Doppler wind lidar Gert

Marseille, Gert-Jan

46

Dynamic Algorithm for Space Weather Forecasting System  

E-Print Network [OSTI]

We propose to develop a dynamic algorithm that intelligently analyzes existing solar weather data and constructs an increasingly more accurate equation/algorithm for predicting solar weather accurately in real time. This dynamic algorithm analyzes a...

Fischer, Luke D.

2011-08-08T23:59:59.000Z

47

Effective Roughness Calculated from Satellite-Derived Land Cover Maps and Hedge-Information used in a Weather Forecasting Model  

Science Journals Connector (OSTI)

In numerical weather prediction, climate and hydrologicalmodelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamicroughness, surface temperature and surfa...

Charlotte B. Hasager; Niels W. Nielsen; Niels Otto Jensen

2003-12-01T23:59:59.000Z

48

Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather ...

Xin Zhang; Ying-Hwa Kuo; Shu-Ya Chen; Xiang-Yu Huang; Ling-Feng Hsiao

2014-09-01T23:59:59.000Z

49

Predicting Solar Generation from Weather Forecasts Using Machine Learning  

E-Print Network [OSTI]

Predicting Solar Generation from Weather Forecasts Using Machine Learning Navin Sharma, Pranshu Sharma, David Irwin, and Prashant Shenoy Department of Computer Science University of Massachusetts Amherst Amherst, Massachusetts 01003 {nksharma,pranshus,irwin,shenoy}@cs.umass.edu Abstract--A key goal

Shenoy, Prashant

50

Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,  

E-Print Network [OSTI]

Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

Shenoy, Prashant

51

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems  

E-Print Network [OSTI]

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

Shenoy, Prashant

52

Claudio Schepke: Online Parallel Mesh Refinement for Climatological Applications Weather forecasts for long periods of time have emerged as increasingly important.  

E-Print Network [OSTI]

Claudio Schepke: Online Parallel Mesh Refinement for Climatological Applications Weather forecasts, this presentation discusses how to explore parallelism at different levels for climatological models, like OLAM

Wichmann, Felix

53

Products and Service of Center for Weather Forecast and Climate Studies  

E-Print Network [OSTI]

) Seasonal Climate Forecast (1-6 months) #12;Weather Forecast Weather Bulletin PCD SCD1 SCD2 SX6 SatelliteLOG O Products and Service of Center for Weather Forecast and Climate Studies Simone Sievert da AND DEVELOP. DIVISION SATELLITE DIVISION ENVIROM. SYSTEM OPERATIONAL DIVISION CPTEC/INPE Msc / PHD &TRAINING

54

A real time model to forecast 24 hours ahead, ozone peaks and exceedance levels. Model based on artificial neural networks, neural classifier and weather predictions.  

E-Print Network [OSTI]

on artificial neural networks, neural classifier and weather predictions. Application in an urban atmosphere - will be solved. Keywords: Artificial neural network; Multilayer Perceptron; ozone modelling; statistical stepwise and Software 22, 9 (2007) 1261-1269" DOI : 10.1016/j.envsoft.2006.08.002 #12;Abstract A neural network combined

Paris-Sud XI, Université de

55

Impact of vegetation fraction from Indian geostationary satellite on short-range weather forecast  

Science Journals Connector (OSTI)

Indian economy is largely depending upon the agricultural productivity and thus influences the trade among the SAARC countries. High-resolution and good-quality regional weather forecasts are necessary for planners, resource managers, insurers and national agro-advisory services. In this study, high resolution updated land-surface state in terms of vegetation fraction (VF) from operational vegetation index products of Indian geostationary satellite (INSAT 3A) sensor (CCD) was utilized in numerical weather prediction (NWP) model (e.g. WRF) to investigate its impact on short-range weather forecast over the control run. Results showed that the updated vegetation fraction from INSAT 3A CCD improved the low-level 24h temperature (?18%) and moisture (?10%) forecast in comparison to control run. The 24h rainfall forecast was also improved (more than 5%) over central and southern India with the use of updated vegetation fraction compared to control experiment. INSAT 3A VF based experiment also showed a net improvement of 27% in surface sensible heat fluxes from WRF in comparison to control experiment when both were compared with area-averaged measurements from Large Aperture Scintillometer (LAS). This triggers the need of more and more use of realistic and updated land surface states through satellite remote sensing data as well as in situ micrometeorological measurements to improve the forecast quality, skill and consistency.

Prashant Kumar; Bimal K. Bhattacharya; P.K. Pal

2013-01-01T23:59:59.000Z

56

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications  

E-Print Network [OSTI]

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange­based surface evapotranspiration

Niyogi, Dev

57

Weather Research and Forecasting prevision model as a tool to search for the best sites for astronomy: application to La Palma, Canary Islands  

Science Journals Connector (OSTI)

......the capability of WRF to predict the...Palma. Maps of the wind velocity, cloudiness...the use of the WRF model in an astronomical...launched on our local computer every...at 0600-ut (local time is equal to...C_N^2$ The WRF model gives vertical...temperature and the wind velocity forecast......

C. Giordano; J. Vernin; H. Trinquet; C. Muoz-Tun

2014-01-01T23:59:59.000Z

58

Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States  

E-Print Network [OSTI]

fornumericalweatherpredictionandclimatemodels. Abstract: Numericalweatherprediction(NWP)modelsareModeloutputstatistics(MOS),NumericalWeatherPrediction(

Mathiesen, Patrick; Kleissl, Jan

2011-01-01T23:59:59.000Z

59

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network [OSTI]

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

60

Analysis of moisture variability in the European Centre for Medium-Range Weather Forecasts 15-year  

E-Print Network [OSTI]

Analysis of moisture variability in the European Centre for Medium-Range Weather Forecasts 15-year Centre for Medium-Range Weather Forecasts 15-year reanalysis (ERA-15) moisture over the tropical oceans. Introduction [2] Because water vapor is the most significant green- house gas and it exhibits a strong

Allan, Richard P.

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Weather Forecasting by Interactive Analysis of Radar and Satellite Imagery [and Discussion  

Science Journals Connector (OSTI)

...1988 research-article Weather Forecasting by Interactive Analysis of Radar and Satellite Imagery [and Discussion...presenting the current weather situation quickly enough...processing of the radar and satellite data is highly automated...very busy in active weather situations, can keep...

1988-01-01T23:59:59.000Z

62

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

E-Print Network [OSTI]

from numerical weather prediction models, which is based on a state-of-the-art circular-processing techniques for forecasts from numerical weather prediction models tend to become ineffective or inapplicableBias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction Le

Washington at Seattle, University of

63

Weather satellites and the economic value of forecasts: evidence from the electric power industry  

Science Journals Connector (OSTI)

Data from weather satellites have become integral to the weather forecast process in the United States and abroad. Satellite data are used to derive improved forecasts for short-term routine weather, long-term climate change, and for predicting natural disasters. The resulting forecasts have saved lives, reduced weather-related economic losses, and improved the quality of life. Weather information routinely assists in managing resources more efficiently and reducing industrial operating costs. The electric energy industry in particular makes extensive use of weather information supplied by both government and commercial suppliers. Through direct purchases of weather data and information, and through participating in the increasing market for weather derivatives, this sector provides measurable indicators of the economic importance of weather information. Space weather in the form of magnetic disturbances caused by coronal mass ejections from the sun creates geomagnetically induced currents that disturb the electric power grid, sometimes causing significant economic impacts on electric power distribution. This paper examines the use of space-derived weather information on the U.S. electric power industry. It also explores issues that may impair the most optimum use of the information and reviews the longer-term opportunities for employing weather data acquired from satellites in future commercial and government activity.

Henry R. Hertzfeld; Ray A. Williamson; Avery Sen

2004-01-01T23:59:59.000Z

64

Multivariate Probabilistic Analysis and Predictability of Medium-Range Ensemble Weather Forecasts  

Science Journals Connector (OSTI)

Ensemble weather forecasting has been operational for two decades now. However, the related uncertainty analysis in terms of probabilistic postprocessing still focuses on single variables, grid points, or stations. Inevitable dependencies in space ...

Jessica Keune; Christian Ohlwein; Andreas Hense

2014-11-01T23:59:59.000Z

65

Exploring Variations in Peoples Sources, Uses, and Perceptions of Weather Forecasts  

Science Journals Connector (OSTI)

Past research has shown that individuals vary in their attitudes and behaviors regarding weather forecast information. To deepen knowledge about these variations, this article explores 1) patterns in peoples sources, uses, and perceptions of ...

Julie L. Demuth; Jeffrey K. Lazo; Rebecca E. Morss

2011-07-01T23:59:59.000Z

66

Fusion of artificial neural network and fuzzy system for short term weather forecasting  

Science Journals Connector (OSTI)

Weather forecasting is the challenging problem for the modern life. Some researches have been conducted to design the accurate prediction in some past years but still it is incomplete. In this paper, we propose the system of short period weather forecasting designed based on the current weather parameter consisted of temperature, humidity, air pressure, wind direction and speed and present weather condition. This system uses fusion of feed forward artificial neural network (ANN) and fuzzy system architecture as main algorithm of weather prediction, Lavendberg-Marquadt as learning algorithm and fuzzy C-mean (FCM) as clustering method in initialisation step. Based on the system architecture, this method can predict the weather continuously despite the change of unpredictable patterns. Furthermore, this system has clear reasoning logic on the fuzzy logic instead of its adaptation ability on its neural network architecture. The performance of proposed system has accuracy up to 78% for validity among three possible weathers, i.e., shiny, cloudy and rainy.

Budiman Putra; Bagus Tris Atmaja; Syahroni Hidayat

2012-01-01T23:59:59.000Z

67

Short-Range Direct and Diffuse Irradiance Forecasts for Solar Energy Applications Based on Aerosol Chemical Transport and Numerical Weather Modeling  

Science Journals Connector (OSTI)

This study examines 23-day solar irradiance forecasts with respect to their application in solar energy industries, such as yield prediction for the integration of the strongly fluctuating solar energy into the electricity grid. During cloud-...

Hanne Breitkreuz; Marion Schroedter-Homscheidt; Thomas Holzer-Popp; Stefan Dech

2009-09-01T23:59:59.000Z

68

Data Assimilation in Weather Forecasting: A Case Study in PDE ...  

E-Print Network [OSTI]

Variational data assimilation is used at major weather prediction centers to .... the globe, tending to be clustered on satellite paths and densely populated areas.

69

EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD-RADIATION INTERACTIONS OVER THE SOUTHERN GREAT PLAINS  

E-Print Network [OSTI]

EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD- RADIATION INTERACTIONS OVER.bnl.gov ABSTRACT Numerical weather prediction (NWP) is the basis for present-day weather forecasts, and NWP- and satellite- based observations over the Southern Great Plains to evaluate how well cloud

Johnson, Peter D.

70

Aggregate vehicle travel forecasting model  

SciTech Connect (OSTI)

This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

1995-05-01T23:59:59.000Z

71

Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware  

Science Journals Connector (OSTI)

A reduction of computational cost would allow higher resolution in numerical weather predictions within the same budget for computation. This paper investigates two approaches that promise significant savings in computational cost: the use of ...

Peter D. Dben; T. N. Palmer

2014-10-01T23:59:59.000Z

72

Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD  

E-Print Network [OSTI]

weather phenomena such as tor- nadoes, severe storms and flash floods. The June 1990 outbreak that spawned: ATM-0331594 (Oklahoma), ATM-0331591 (Colorado State), ATM-0331574 (Millersville), ATM-0331480 (Indiana

Plale, Beth

73

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

74

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

United States California Solar Initiative Coastally Trappedparticipants in the California Solar Initiative (CSI)on location. In California, solar irradiance forecasts near

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

75

Mountain Weather Research and Forecasting Chapter 12: Bridging the Gap between Operations and Research to  

E-Print Network [OSTI]

and Research to Improve Weather Prediction in Mountainous Regions W. James Steenburgh Department of Atmospheric tools, and numerical models, and inhibits researchers from fully evaluating weaknesses in current integrated collaboration to address critical challenges for weather prediction in mountainous regions

Steenburgh, Jim

76

Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 00: 115 (0000) Controlling model error of underdamped forecast models in  

E-Print Network [OSTI]

-dependent predictability, ensemble methods have become popular for producing numerical weather forecasts (Molteni weather prediction or climate dynamics. In such simulations numerical codes tend to produce large errors of the forecast model and a numerical model error due to the choice of the numerical method used to simulate those

Gottwald, Georg A.

77

Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts  

Science Journals Connector (OSTI)

The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (...

Felix Fundel; Andre Walser; Mark A. Liniger; Christoph Frei; Christof Appenzeller

2010-01-01T23:59:59.000Z

78

CCPP-ARM Parameterization Testbed Model Forecast Data  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

Klein, Stephen

79

Chapter 4 The use of satellite surface wind data to improve weather analysis and forecasting at the NASA Data Assimilation Office  

Science Journals Connector (OSTI)

One important application of satellite surface wind observations is to improve the accuracy of weather analyses and forecasts. The first satellite to measure surface wind over the ocean was SeaSat in 1978. The initial impact of satellite surface wind data on weather analysis and forecasting was very small, but extensive research has been conducted since SeaSat to improve data accuracy and utilization of these data in atmospheric models. Satellite surface wind data are now used to detect intense storms over the ocean as well as to improve the overall representation of the wind field in numerical weather prediction models. Satellite wind data contribute to improved warnings for ships at sea and to more accurate global weather forecasts. Experiments with the Goddard Earth Observing System atmospheric general circulation model and data assimilation system indicate that the impact of satellite wind data measured by the National Aeronautics and Space Administration Scatterometer was approximately twice as large as the impact of Special Sensor Microwave Imager or European Remote-sensing Satellite wind data. Locations of cyclones over the ocean were up to 500 km more accurate, and the useful forecast skill in the Southern Hemisphere extratropics was extended by 24 hours.

R. Atlas; R.N. Hoffman

2000-01-01T23:59:59.000Z

80

Multi-objective calibration of forecast ensembles using Bayesian model averaging  

E-Print Network [OSTI]

weather prediction models. The BMA predictive probability density function (PDF) of any weather quantity but complementary metrics of forecast skill, and uses a numerical algorithm to solve for the Pareto set of parameters that have consistently good performance across multiple performance metrics. Two illustrative case

Vrugt, Jasper A.

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Assessing the Capability of a Regional-Scale Weather Model to Simulate Extreme Precipitation Patterns and Flooding in Central Texas  

Science Journals Connector (OSTI)

A regional-scale weather model is used to determine the potential for flood forecasting based on model-predicted rainfall. Extreme precipitation and flooding events are a significant concern in central Texas, due to both the high occurrence and ...

Marla R. Knebl Lowrey; Zong-Liang Yang

2008-12-01T23:59:59.000Z

82

A multi-spectral spatial convolution approach of rainfall forecasting using weather satellite imagery  

Science Journals Connector (OSTI)

Flood forecasting has long been a major topic of hydrologic research. Recent events and studies indicate that the success of flood forecasting in Taiwan depends heavily on the accuracy of real-time rainfall forecasting. In this study, we demonstrate a multi-spectral spatial convolution approach for real-time rainfall forecasting using geostationary weather satellite images. The approach incorporates cloud-top temperatures of three infrared channels in a spatial convolution context. It not only characterizes the inputoutput relationship between cloud-top temperature and rainfall at the ground level, but also is more consistent with physical and remote sensing principles than single-pixel matches. Point rainfall measurements at raingauge sites are up-scaled to pixel-average-rainfall by block kriging, then related to multi-spectral cloud-top temperatures derived from Geostationary Meteorological Satellite images by spatial convolution. The kernel function of the multispectral spatial convolution equation is solved by the least squares method. Through a cross-validation procedure, we demonstrate that the proposed approach is capable of achieving high accuracy for 1- to 3-h-lead pixel-average-rainfall forecasting.

Chiang Wei; Wei-Chun Hung; Ke-Sheng Cheng

2006-01-01T23:59:59.000Z

83

New Concepts in Wind Power Forecasting Models  

E-Print Network [OSTI]

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

84

Log-normal distribution based EMOS models for probabilistic wind speed forecasting  

E-Print Network [OSTI]

Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles, they are usually under-dispersive and uncalibrated and require statistical post-processing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind speed forecasts based on the log-normal (LN) distribution, and we also show a regime-switching extension of the model which combines the previously studied truncated normal (TN) distribution with the LN. Both presented models are applied to wind speed forecasts of the eight-member University of Washington mesoscale ensemble, of the fifty-member ECMWF ensemble and of the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service, and their predictive performances are compared to those of the TN and general extreme value (GEV) distribution based EMOS methods an...

Baran, Sndor

2014-01-01T23:59:59.000Z

85

ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS  

SciTech Connect (OSTI)

During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.

Chiswell, S.; Buckley, R.

2009-01-15T23:59:59.000Z

86

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network [OSTI]

competing numerical weather prediction centers such as the European Center for MediumRange Weather Forecasts (ECMWF). For most sensibleweather metrics, we lag 1 to 1.5 days (i.e., they make a 3.5day of NOAA's current investment in weather satellites. Without a modern data assimilation system

Hamill, Tom

87

The origins of computer weather prediction and climate modeling  

SciTech Connect (OSTI)

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Lynch, Peter [Meteorology and Climate Centre, School of Mathematical Sciences, University College Dublin, Belfield (Ireland)], E-mail: Peter.Lynch@ucd.ie

2008-03-20T23:59:59.000Z

88

Warm weather's a comin'! Performance Dependence on Closure  

E-Print Network [OSTI]

contributed also by Aaron Rosenberg!! #12;Wind Forecasting using Numerical Weather Prediction (NWP) Mesoscale weather models often predict the height of the LLJ too high and the magnitude too low Overwhelming 18-hr.forecasts initialized at 18Z Weather Research and Forecast (WRF) Model #12;Dissipation

McCalley, James D.

89

Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database  

E-Print Network [OSTI]

Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use have come to expect. Potato late blight risk models were some of the earliest weather-based models. This analysis compares two types of potato late blight risk models that were originally trained on location

Douches, David S.

90

The Dynamics of Deterministic Chaos in Numerical Weather Prediction Models  

E-Print Network [OSTI]

Atmospheric weather systems are coherent structures consisting of discrete cloud cells forming patterns of rows/streets, mesoscale clusters and spiral bands which maintain their identity for the duration of their appreciable life times in the turbulent shear flow of the planetary Atmospheric Boundary Layer. The existence of coherent structures (seemingly systematic motion) in turbulent flows has been well established during the last 20 years of research in turbulence. Numerical weather prediction models based on the inherently non-linear Navier-Stokes equations do not give realistic forecasts because of the following inherent limitations: (1) the non-linear governing equations for atmospheric flows do not have exact analytic solutions and being sensitive to initial conditions give chaotic solutions characteristic of deterministic chaos (2) the governing equations do not incorporate the dynamical interactions and co-existence of the complete spectrum of turbulent fluctuations which form an integral part of the large coherent weather systems (3) limitations of available computer capacity necessitates severe truncation of the governing equations, thereby generating errors of approximations (4) the computer precision related roundoff errors magnify the earlier mentioned uncertainties exponentially with time and the model predictions become unrealistic. The accurate modelling of weather phenomena therefore requires alternative concepts and computational techniques. In this paper a universal theory of deterministic chaos applicable to the formation of coherent weather structures in the ABL is presented.

A. Mary Selvam

2003-10-07T23:59:59.000Z

91

Ensemble typhoon quantitative precipitation forecasts model in Taiwan  

Science Journals Connector (OSTI)

In this study, an ensemble typhoon quantitative precipitation forecast (ETQPF) model was developed to provide typhoon rainfall forecasts for Taiwan. The ETQPF rainfall forecast is obtained by averaging the pick-out cases, which are screened at a ...

Jing-Shan Hong; Chin-Tzu Fong; Ling-Feng Hsiao; Yi-Chiang Yu; Chian-You Tzeng

92

Impact of large scale circulation on European summer surface ozone and consequences for modelling forecast  

E-Print Network [OSTI]

of using day-to-day varying chemical boundary conditions produced by a global chemical weather forecast platform instead of climatological monthly means at the frontiers of a regional model. We performed two- transport models (CTMs) that represent physical and chemical processes controlling ozone concentrations

Menut, Laurent

93

AMPS, a real-time mesoscale modeling system, has provided a decade of service for scientific and logistical needs and has helped advance polar numerical weather prediction  

E-Print Network [OSTI]

and logistical needs and has helped advance polar numerical weather prediction as well as understanding support for the USAP. The concern at the time was the numerical weather prediction (NWP) guidance-time implementation of the Weather Research and Forecasting model (WRF; Skamarock et al. 2008) to support the U

Howat, Ian M.

94

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

95

Weather  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and the variations in atmospheric conditions that produce weather. The Weather Machine, LANL's meteorological monitoring program, supports Laboratory operations and...

96

Gridded Operational Consensus Forecasts of 2-m Temperature over Australia CHERMELLE ENGEL  

E-Print Network [OSTI]

-resolution grid. Local and in- ternational numerical weather prediction model inputs are found to have coarse by numerical weather prediction (NWP) model forecasts. As NWP models improve, public weather forecasting University of Melbourne, Melbourne, Victoria, Australia ELIZABETH E. EBERT Centre for Australia Weather

Ebert, Beth

97

Probabilistic Verification of Global and Mesoscale Ensemble Forecasts of Tropical Cyclogenesis  

Science Journals Connector (OSTI)

Probabilistic forecasts of tropical cyclogenesis have been evaluated for two samples: a near-homogeneous sample of ECMWF and Weather Research and Forecasting (WRF) Modelensemble Kalman filter (EnKF) ensemble forecasts during the National Science ...

Sharanya J. Majumdar; Ryan D. Torn

2014-10-01T23:59:59.000Z

98

Improving an Accuracy of ANN-Based Mesoscale-Microscale Coupling Model by Data Categorization: With Application to Wind Forecast for Offshore and Complex Terrain Onshore Wind Farms  

Science Journals Connector (OSTI)

The ANN-based mesoscale-microscale coupling model forecasts wind speed and wind direction with high accuracy for wind parks located in complex terrain onshore, yet some weather regimes remains unresolved and f...

Alla Sapronova; Catherine Meissner

2014-01-01T23:59:59.000Z

99

18 Bureau of Meteorology Annual Report 201314 Hazards, warnings and forecasts  

E-Print Network [OSTI]

and numerical prediction models. #12;19Bureau of Meteorology Annual Report 2013­14 2 Performance Performance programs: · Weather forecasting services; · Flood forecasting and warning services; · Hazard prediction, Warnings and Forecasts portfolio provides a range of forecast and warning services covering weather, ocean

Greenslade, Diana

100

Research of least squares support vector regression based on differential evolution algorithm in short-term load forecasting model  

Science Journals Connector (OSTI)

To improve the accuracy of short-term load forecasting a differential evolution algorithm (DE) based least squares support vector regression (LSSVR) method is proposed in this paper. Through optimizing the regularization parameter and kernel parameter of the LSSVR by DE a short-term load forecasting model which can take load affected factors such as meteorology weather and date types into account is built. The proposed LSSVR method is proved by implementing short-term load forecasting on the real historical data of Yangquan power system in China. The average forecasting error is less than 1.6% which shows better accuracy and stability than the traditional LSSVR and Support vector regression. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system more efficiently.

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION  

E-Print Network [OSTI]

in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

Boyer, Edmond

102

Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States  

E-Print Network [OSTI]

andvalidation. SolarEnergy. 73:5,307? Perez,R. ,irradianceforecastsforsolarenergyapplicationsbasedonforecastdatabase. SolarEnergy. 81:6,809?812.

Mathiesen, Patrick; Kleissl, Jan

2011-01-01T23:59:59.000Z

103

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

Logistics parks demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks demand, a combination forecasting ... Keywords: Logistics parks' demand, combine, simulated annealing algorithm, grey forecast model, exponential smoothing method

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

104

VALIDATION OF SHORT AND MEDIUM TERM OPERATIONAL SOLAR RADIATION FORECASTS IN THE US  

E-Print Network [OSTI]

, and medium term forecasts (up to seven days ahead) from numerical weather prediction models [1]. Forecasts radiation forecasting. One approach relies on numerical weather prediction (NWP) models which can be global modeling of the atmosphere. NWP models cannot, at this stage of their development, predict the exact

Perez, Richard R.

105

Eye Tracking: Evaluating the impact of gesturing during televised weather forecasts.  

Science Journals Connector (OSTI)

Televised media is one of the most frequently accessed sources of weather information. The local weathercaster is the link between weather information and the public, and as such weathercaster characteristics, from vocal cadence to physical ...

Robert Drost; Jay Trobec; Christy Steffke; Julie Libarkin

106

Interactive Weather Simulation and Visualization on a Display Wall  

E-Print Network [OSTI]

.hoai.ha,john.markus.bjorndalen,otto.anshus}@uit.no, {tormsh,daniels}@cs.uit.no Abstract. Numerical Weather Prediction models (NWP) used for op- erational Weather Model, WRF, Tiled Display Walls, Live Data Sets, On-Demand Computation. 1 Introduction Numerical Weather Prediction models for use in weather forecasting centers are often computed for a fixed static

Ha, Phuong H.

107

Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction  

E-Print Network [OSTI]

. Current weather radar detection and prediction sys- tems primarily rely on numerical models. We proposeOpen problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1, #12;Dynamic Relational Models for Improved Hazardous Weather Prediction Radar velocity Radar

McGovern, Amy

108

The temporal cascade structure of reanalyses and Global Circulation models  

E-Print Network [OSTI]

and stochastic forecasting. 1. Introduction "Weather prediction by Numerical Process" (Richardson, 1922 equations. While these equations are deterministic, numerical weather prediction has been increasingly of the deterministic models. Interestingly, Richardson is not only the father of numerical weather forecasting, he

Lovejoy, Shaun

109

ORIGINAL PAPER Coupled weather research and forecastingstochastic  

E-Print Network [OSTI]

ORIGINAL PAPER Coupled weather research and forecasting�stochastic time-inverted lagrangian numerical weather prediction model, the Weather Research and Forecasting (WRF) model, and a Lagrangian for a wide range of applications, including inverse flux estimates, flight plan- ning, satellite validation

Lin, John Chun-Han

110

Low Clouds Contribute to Weather Prediction Model Bias | U.S. DOE Office of  

Office of Science (SC) Website

2 2 » Low Clouds Contribute to Weather Prediction Model Bias Biological and Environmental Research (BER) BER Home About Research Facilities Science Highlights Searchable Archive of BER Highlights External link Benefits of BER Funding Opportunities Biological & Environmental Research Advisory Committee (BERAC) News & Resources Contact Information Biological and Environmental Research U.S. Department of Energy SC-23/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3251 F: (301) 903-5051 E: sc.ber@science.doe.gov More Information » November 2012 Low Clouds Contribute to Weather Prediction Model Bias Long-term measurement records improve the representation of clouds in climate and weather forecast models. Print Text Size: A A A Subscribe

111

Weather Forecasting System Based on Satellite Imageries Using Neuro-fuzzy Techniques  

Science Journals Connector (OSTI)

We have built an automated Satellite Images Forecasting System with Neuro-Fuzzy techniques. Firstly, Subtractive Clustering is applied on to a satellite image to extract the locations of the clouds. This is follo...

Chien-Wan Tham; Sion-Hui Tian; Liya Ding

2002-01-01T23:59:59.000Z

112

Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction  

E-Print Network [OSTI]

Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction Supervisors). Background: Numerical Weather Prediction (NWP) has seen significant gains in accuracy in recent years due is directed at achieving real-world impact in numerical weather prediction by addressing fundamental issues

Wirosoetisno, Djoko

113

Evaluation of Mixed-Phase Cloud Parameterizations in Short-Range Weather Forecasts with CAM3 and AM2 for Mixed-Phase Arctic Cloud Experiment  

SciTech Connect (OSTI)

By making use of the in-situ data collected from the recent Atmospheric Radiation Measurement Mixed-Phase Arctic Cloud Experiment, we have tested the mixed-phase cloud parameterizations used in the two major U.S. climate models, the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory climate model (AM2), under both the single-column modeling framework and the U.S. Department of Energy Climate Change Prediction Program-Atmospheric Radiation Measurement Parameterization Testbed. An improved and more physically based cloud microphysical scheme for CAM3 has been also tested. The single-column modeling tests were summarized in the second quarter 2007 Atmospheric Radiation Measurement metric report. In the current report, we document the performance of these microphysical schemes in short-range weather forecasts using the Climate Chagne Prediction Program Atmospheric Radiation Measurement Parameterizaiton Testbest strategy, in which we initialize CAM3 and AM2 with realistic atmospheric states from numerical weather prediction analyses for the period when Mixed-Phase Arctic Cloud Experiment was conducted.

Xie, S; Boyle, J; Klein, S; Liu, X; Ghan, S

2007-06-01T23:59:59.000Z

114

Measuring the forecasting accuracy of models: evidence from industrialised countries  

Science Journals Connector (OSTI)

This paper uses the approach suggested by Akrigay (1989), Tse and Tung (1992) and Dimson and Marsh (1990) to examine the forecasting accuracy of stock price index models for industrialised markets. The focus of this paper is to compare the Mean Absolute Percentage Error (MAPE) of three models, that is, the Random Walk model, the Single Exponential Smoothing model and the Conditional Heteroskedastic model with the MAPE of the benchmark Naive Forecast 1 case. We do not evidence that a single model to provide better forecasting accuracy results compared to other models.

Athanasios Koulakiotis; Apostolos Dasilas

2009-01-01T23:59:59.000Z

115

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height  

Science Journals Connector (OSTI)

The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with ...

Adam J. Deppe; William A. Gallus Jr.; Eugene S. Takle

2013-02-01T23:59:59.000Z

116

Solar shield: forecasting and mitigating space weather effects on high-voltage power transmission systems  

Science Journals Connector (OSTI)

In this paper, central elements of the Solar Shield project, launched to design and establish ... about space weather conditions to the member power utilities. EPRI also evaluates the economic impacts of ... tran...

Antti Pulkkinen; Michael Hesse; Shahid Habib; Luke Van der Zel

2010-05-01T23:59:59.000Z

117

Very short range local area weather forecasting using measurements from geosynchronous meteorological satellites  

Science Journals Connector (OSTI)

Quantitative radiance measurements from NASA's ATS-3 geosynchronous satellite have been used to develop and test ... a statistical forecst method to predict air terminal weather over the very short range (06 ......

Gerald J. Sikula; Dr. Thomas H. Vonder Haar

1973-01-01T23:59:59.000Z

118

Use of Weather and Occupancy Forecasts for Optimal Building Climate Control Part II  

E-Print Network [OSTI]

that predictive control presents a promising option to enhance the energy efficiency and comfort of buildings office building. The proposed project presents a follow-up to the forerunner project "Use of Weather-site event targeted at professionals from the building, energy and educational sectors. Project risks relate

Fischlin, Andreas

119

Streamflow Forecasting Based on Statistical Applications and Measurements Made with Rain Gage and Weather Radar  

E-Print Network [OSTI]

measurements taken with weather radar. In addition, accurate estimates of lag time can be made from radar observations. For a storm which is unevenly distributed over the watershed, it is demonstrated that a better estimation of lag time may be made from radar...

Hudlow, M.D.

120

Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)  

SciTech Connect (OSTI)

Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

2014-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Network Bandwidth Utilization Forecast Model on High Bandwidth Network  

SciTech Connect (OSTI)

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Yoo, Wucherl; Sim, Alex

2014-07-07T23:59:59.000Z

122

Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.  

E-Print Network [OSTI]

??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecasts (more)

Mavromatis, Peter George

2013-01-01T23:59:59.000Z

123

A model for short term electric load forecasting  

E-Print Network [OSTI]

A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

Tigue, John Robert

1975-01-01T23:59:59.000Z

124

Bandwidth allocation in a multiservice satellite network based on long-term weather forecast scenarios  

Science Journals Connector (OSTI)

The paper compares two alternative hierarchical bandwidth allocation and admission control schemes suited for the multiservice Ka-band satellite environment, where the attenuation of the transmitted signals due to bad weather conditions has a heavy impact on the system's performance. The two schemes are compared by using data derived from a real case study. The aim is to demonstrate that a high level control mechanism for the assignment of the satellite bandwidth to earth stations, which takes into consideration the rain attenuation probabilities of a certain geographical area, improves the system's performance, with respect to an assignment mechanism insensitive to the geographical fade probabilities.

Raffaele Bolla; Nedo Celandroni; Franco Davoli; Erina Ferro; Mario Marchese

2002-01-01T23:59:59.000Z

125

On the Use of QuikSCAT Scatterometer Measurements of Surface Winds for Marine Weather Prediction  

E-Print Network [OSTI]

and ECMWF global numerical weather prediction models considerably underestimated the spatial variability Centre for Medium-Range Weather Forecasts (ECMWF) global numerical weather prediction (NWP) modelsOn the Use of QuikSCAT Scatterometer Measurements of Surface Winds for Marine Weather Prediction

Kurapov, Alexander

126

Forecasting correlated time series with exponential smoothing models  

Science Journals Connector (OSTI)

This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection criterion is introduced into the forecasting scheme for selecting the most adequate multivariate model for describing the behaviour of the time series under study. The forecasting performance of this procedure is tested using some real examples.

Ana Corbern-Vallet; Jos D. Bermdez; Enriqueta Vercher

2011-01-01T23:59:59.000Z

127

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

128

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

129

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems

130

Exponential smoothing model selection for forecasting  

Science Journals Connector (OSTI)

Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using criteria such as the mean absolute percentage error. A second approach is to rely on the most appropriate general case of the three methods. For annual series this is trend corrected exponential smoothing: for sub-annual series it is the seasonal adaptation of trend corrected exponential smoothing. The rationale for this approach is that a general method automatically collapses to its nested counterparts when the pertinent conditions pertain in the data. A third approach may be based on an information criterion when maximum likelihood methods are used in conjunction with exponential smoothing to estimate the smoothing parameters. In this paper, such approaches for selecting the appropriate forecasting method are compared in a simulation study. They are also compared on real time series from the M3 forecasting competition. The results indicate that the information criterion approaches provide the best basis for automated method selection, the Akaike information criteria having a slight edge over its information criteria counterparts.

Baki Billah; Maxwell L. King; Ralph D. Snyder; Anne B. Koehler

2006-01-01T23:59:59.000Z

131

24 More Years of Numerical Weather Prediction: A Model Performance Model  

E-Print Network [OSTI]

24 More Years of Numerical Weather Prediction: A Model Performance Model Gerard Cats May 26, 2008 Abstract For two formulations of currently usual numerical weather prediction models the evolution in such a model is much 1 #12;24 More Years of Numerical Weather Prediction Gerard Cats higher than in a sis

Stoffelen, Ad

132

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA  

SciTech Connect (OSTI)

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing quasi-deterministic components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27T23:59:59.000Z

133

Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs  

E-Print Network [OSTI]

Production forecasting in shale (ultra-low permeability) gas reservoirs is of great interest due to the advent of multi-stage fracturing and horizontal drilling. The well renowned production forecasting model, Arps? Hyperbolic Decline Model...

Statton, James Cody

2012-07-16T23:59:59.000Z

134

Use of Weather and Occupancy Forecasts for Optimal Building Climate Control  

E-Print Network [OSTI]

·Electric lighting ·Heating: radiators ·Cooling: slow ceiling ­ mechanical chiller ­ free cooling with wet of buildings; reducing peak electricity demand. Expected Results: ·Methods ·Software/tools ·Benefit Version 15. Jan. 2009 4 OptiControl ­ Research Partners · ETH Systems Ecology Group Modeling

Fischlin, Andreas

135

SPC Fire Weather Forecast Criteria Critical for temperature, wind, and relative humidity  

E-Print Network [OSTI]

the Energy Release Component (ERC) for fuel model G and 100 hr fuel moistures, which are available from: - Sustained winds 20 mph or greater (15 mph Florida) - Minimum relative humidity at or below regional thresholds (Fig. 1) - Temperatures above 50-60° F, depending on the season - Dry fuels (as defined below

136

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE  

E-Print Network [OSTI]

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE Wensheng Zhang1,* , Hongfu Chen1 and excessive fluctuation of agricultural and livestock products price is not only harmful to residents' living, but also affects CPI (Consumer Price Index) values, and even leads to social crisis, which influences

Boyer, Edmond

137

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation  

E-Print Network [OSTI]

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed

Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

2012-01-01T23:59:59.000Z

138

The origins of computer weather prediction and climate modeling  

Science Journals Connector (OSTI)

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models ... Keywords: Climate modelling, History of NWP, Numerical weather prediction

Peter Lynch

2008-03-01T23:59:59.000Z

139

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect (OSTI)

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

140

Testing Linear Diagnostics of Ensemble Performance on a Simplified Global Circulation Model  

E-Print Network [OSTI]

Ensemble weather forecast systems are used to account for the uncertainty in the initial conditions of the atmosphere and the chaotic dynamics of the models. It has been previously found that forecast performance of an ensemble forecast system...

Nelson, Ethan

2011-04-21T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Forecast Calls for Better Models: Examining the Core  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecast Calls for Better Models: Examining the Core Forecast Calls for Better Models: Examining the Core Components of Arctic Clouds to Clear Their Influence on Climate For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Predicting how atmospheric aerosols influence cloud formation and the resulting feedback to climate is a challenge that limits the accuracy of atmospheric models. This is especially true in the Arctic, where mixed-phase (both ice- and liquid-based) clouds are frequently observed, but the processes that determine their composition are poorly understood. To obtain a closer look at what makes up Arctic clouds, scientists characterized cloud droplets and ice crystals collected at the North Slope of Alaska as part of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) field study

142

Winter Weather Outlook  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

to predict exactly how these climate factors will affect the nation's winter weather extremes. Forecasters are expecting large temperature and precipitation swings across the...

143

Solar forecasting review  

E-Print Network [OSTI]

of all Numerical Weather Prediction (NWP models). First aof all Numerical Weather Prediction (NWP models). First apersistence models, numerical weather predictions as well as

Inman, Richard Headen

2012-01-01T23:59:59.000Z

144

The Uncoordinated Giant: Why U.S. Weather Research and Prediction  

E-Print Network [OSTI]

's Global Forecast System (GFS) model, are producing far more accurate forecasts of major cyclones and other and forecasts. But in spite of these advances, there is a growing sentiment in the community that weather developing essential technologies, and unproductive or inappropriate use of #12;4 limited manpower

Mass, Clifford F.

145

Temporal Changes in Wind as Objects for Evaluating Mesoscale Numerical Weather Prediction  

E-Print Network [OSTI]

a method of evaluating numerical weather prediction models by comparing the characteristics of temporal for biases in features forecast by the model. 1. Introduction Verification of numerical weather predictionTemporal Changes in Wind as Objects for Evaluating Mesoscale Numerical Weather Prediction DARAN L

Knievel, Jason Clark

146

Continuous Model Updating and Forecasting for a Naturally Fractured Reservoir  

E-Print Network [OSTI]

CONTINUOUS MODEL UPDATING AND FORECASTING FOR A NATURALLY FRACTURED RESERVOIR A Thesis by HISHAM HASSAN S. ALMOHAMMADI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... guidance and support throughout my time here in Texas A&M University. I also would like to thank my committee members, Dr. Eduardo Gildin and Dr. Michael Sherman, for providing valued insight and help during the course of this research. I am indebted...

Almohammadi, Hisham

2013-07-26T23:59:59.000Z

147

ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS  

SciTech Connect (OSTI)

Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-time level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.

Chiswell, S

2009-01-11T23:59:59.000Z

148

A Comparison of Precipitation Forecast Skill between Small Convection-Allowing and Large Convection-Parameterizing Ensembles  

E-Print Network [OSTI]

Submitted to Weather and Forecasting in October 2008, Accepted in January 2009 * Corresponding author) Weather Research and Forecasting (WRF) model ensemble, which cover a similar domain over the central-convection resolution (PCR) ensembles. Computation of various precipitation skill metrics for probabilistic

Droegemeier, Kelvin K.

149

USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS,  

E-Print Network [OSTI]

USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS simulation by means of a Numerical Weather Prediction Model (NWP), Skiron. After that, we have made spatial solar resource map. 2.1. Meteorological simulation The numerical weather prediction model used is SKIRON

Paris-Sud XI, Université de

150

DREAM tool increases space weather predictions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

using real-time space weather observations and an interactive user interface to support satellite operators and space weather forecasters. For national security applications,...

151

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

SciTech Connect (OSTI)

The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

2010-11-02T23:59:59.000Z

152

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network [OSTI]

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation...

Lang, K.

1982-01-01T23:59:59.000Z

153

Crude oil prices and petroleum inventories : remedies for a broken oil price forecasting model.  

E-Print Network [OSTI]

??The empirical relationship between crude oil prices and petroleum inventories has been exploited in a number of short-term oil price forecasting models. Some of the (more)

Grimstad, Dan

2007-01-01T23:59:59.000Z

154

Characterizing uncertainty in species distribution models derived from interpolated weather station data  

E-Print Network [OSTI]

metrics of uncertainty in interpolated weather station data have varying contributions to over- and underCharacterizing uncertainty in species distribution models derived from interpolated weather station distribution models derived from interpolated weather station data. Ecosphere 4(5):61. http://dx.doi.org/10

Kueppers, Lara M.

155

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

156

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

157

High resolution weather modeling for improved fire management  

Science Journals Connector (OSTI)

A critical element to the accurate prediction of fire/weather behaviour is the knowledge of near-surface weather. Weather variables, such as wind, temperature, humidity and precipitation, make direct impacts on the practice of managing prescribed burns ... Keywords: fire behavior, numerical weather prediction, parallel computing

Kevin Roe; Duane Stevens; Carol McCord

2001-11-01T23:59:59.000Z

158

An Evaluation of Tropical Cyclone Genesis Forecasts from Global Numerical Models  

Science Journals Connector (OSTI)

Tropical cyclone (TC) forecasts rely heavily on output from global numerical models. While considerable research has investigated the skill of various models with respect to track and intensity, few studies have considered how well global models ...

Daniel J. Halperin; Henry E. Fuelberg; Robert E. Hart; Joshua H. Cossuth; Philip Sura; Richard J. Pasch

2013-12-01T23:59:59.000Z

159

International Polar Year (IPY) Student Traineeships: Investigation of the impact of western arctic volcanic eruption on weather and climate  

E-Print Network [OSTI]

if the eruptions are not very large. Four aspects of volcanic eruptions on local weather were explored: 1) heat of the four aspects has the greatest impact on local weather during an eruption. Evaluation with observational data was performed to assess whether routine Weather Research and Forecasting (WRF) model data can

Moelders, Nicole

160

Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation Forecasts  

E-Print Network [OSTI]

Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation uncertainty. Machine learning methods can produce calibrated probabilistic forecasts from the raw ensemble and machine learning are working to address these challenges. Numerical weather prediction (NWP) models

Xue, Ming

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Wintertime sub-kilometer numerical forecasts of near-surface variables in the Canadian Rocky Mountains  

Science Journals Connector (OSTI)

Numerical Weather Prediction (NWP) systems operational at many national centers are nowadays used at kilometer scale. The next generation of NWP models will provide forecasts at sub-kilometrer scale. Large impacts are expected in mountainous ...

Vincent Vionnet; Stphane Blair; Claude Girard; Andr Plante

162

Ensemble Forecasts and their Verification  

E-Print Network [OSTI]

· Ensemble forecast verification ­ Performance metrics: Brier Score, CRPSS · New concepts and developments of weather Sources: Insufficient spatial resolution, truncation errors in the dynamical equations

Maryland at College Park, University of

163

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis  

E-Print Network [OSTI]

analyses of regional mod- eling with Polar WRF have been performed with results compared to selected localEvaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air.1.1 of the Weather Research and Forecasting model (WRF), a highresolution regional scale model, is used to simulate

Howat, Ian M.

164

Application of Improved Grey Model in Long-term Load Forecasting of Power Engineering  

Science Journals Connector (OSTI)

Grey model is usually been used for long-term load forecasting in power engineering, but it has significant limitations. If the moving average method and Markov model are connected with grey model, the accuracy of this improved grey model used for long-term load forecasting in power engineering can be effectively increased. In this paper, ordinary grey model and improved grey model are all chosen and used for long-term power load forecasting in power engineering, and the power load data of Qingdao in the past decade is selected for the analysis. The result of the analysis shows that the accuracy of improved grey model is significant higher than ordinary model, so the improved grey model can be used for long-term load forecasting in power engineering.

Junjie Kang; Huijuan Zhao

2012-01-01T23:59:59.000Z

165

Atmospheric and seeing forecast: WRF model validation with in situ measurements at ORM  

Science Journals Connector (OSTI)

......orographic data to initialize WRF. 6 CONCLUSION For the first time, the WRF model, coupled with the...used to forecast not only local meteorological parameters...relative humidity and wind speed at ground level...simultaneous forecasts, the WRF-in situ instrument agreement......

C. Giordano; J. Vernin; H. Vzquez Rami; C. Muoz-Tun; A. M. Varela; H. Trinquet

2013-01-01T23:59:59.000Z

166

Precipitation Forecasting with Gamma Distribution Models for Gridded Precipitation Events in Eastern Oklahoma and Northwest Arkansas  

Science Journals Connector (OSTI)

An elegant and easy to implement probabilistic quantitative precipitation forecasting model that can be used to estimate the probability of exceedance (POE) is presented. The model was built using precipitation data collected across eastern ...

Steven A. Amburn; Andrew S.I.D. Lang; Michael A. Buonaiuto

167

Understanding space weather to shield society  

E-Print Network [OSTI]

, initially prioritizing post-event solar eruption modeling to develop multi-day forecasts of geomagnetic, involving the coupling of the solar wind disturbances to internal magnetospheric processes agencies and communities! i) Implement open space-weather data and information policy;! j) Provide access

Schrijver, Karel

168

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation  

E-Print Network [OSTI]

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation Cyril a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly@gmail.com #12;Abstract. We propose in this paper an original technique to predict global radiation using

Paris-Sud XI, Université de

169

ANL Software Improves Wind Power Forecasting | Department of...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

principal investigator for the project. For wind power point forecasting, ARGUS PRIMA trains a neural network using data from weather forecasts, observations, and actual wind...

170

Modelling of space weather effects on satellite drag  

Science Journals Connector (OSTI)

For satellites on low Earth orbits, aerodynamic drag provides an important contribution to the spectrum of perturbing forces. Aerodynamic drag is only of second order magnitude or less, as compared to the first order Earth oblateness perturbation to the orbit. However, due to its energy dissipating nature, it is the driving effect for altitude decay and associated along-track dispersions. Determining parameters for the drag force are the local air densities, the projected cross-section, and a drag coefficient which describes the interaction between impinging molecules and the spacecraft surface in the regime of free-molecular flow. The local and exospheric temperature, the atmospheric composition, and the resulting densities are strongly driven by space weather effects from solar extreme ultraviolet radiation, and from coronal mass ejections which may lead to geomagnetic storms. Thermospheric models are currently the limiting factor in the accuracy of orbit determination and prediction. Any improvement in these models would greatly aid in applications such as re-entry prediction, ground-track maintenance and gravity field and geodetic science missions. This paper gives an overview of many aspects of satellite drag modelling for orbit determination. The performance of current thermosphere models is analysed using tracking data, and recent developments such as model calibration are described.

E. Doornbos; H. Klinkrad

2006-01-01T23:59:59.000Z

171

Short-term solar irradiance forecasting using exponential smoothing state space model  

Science Journals Connector (OSTI)

Abstract We forecast high-resolution solar irradiance time series using an exponential smoothing state space (ESSS) model. To stationarize the irradiance data before applying linear time series models, we propose a novel Fourier trend model and compare the performance with other popular trend models using residual analysis and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) stationarity test. Using the optimized Fourier trend, an ESSS model is implemented to forecast the stationary residual series of datasets from Singapore and Colorado, USA. To compare the performance with other time series models, autoregressive integrated moving average (ARIMA), linear exponential smoothing (LES), simple exponential smoothing (SES) and random walk (RW) models are tested using the same data. The simulation results show that the ESSS model has generally better performance than other time series forecasting models. To assess the reliability of the forecasting model in real-time applications, a complementary study of the forecasting 95% confidence interval and forecasting horizon of the ESSS model has been conducted.

Zibo Dong; Dazhi Yang; Thomas Reindl; Wilfred M. Walsh

2013-01-01T23:59:59.000Z

172

Coupled Climate and Earth System Models  

Science Journals Connector (OSTI)

We are all familiar with weather forecasts that predict the local weather for the next few days. These are made using a high-resolution numerical model of the atmosphere, and sometimes extend out as far as 10 ...

Peter R. Gent

2012-01-01T23:59:59.000Z

173

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

174

Radiation fog forecasting using a 1-dimensional model  

E-Print Network [OSTI]

measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing... measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing...

Peyraud, Lionel

2012-06-07T23:59:59.000Z

175

Weather Regime Prediction Using Statistical Learning  

E-Print Network [OSTI]

most advanced numerical weather prediction models still havefor numerical weather prediction models. Acknowledgements It

A. Deloncle; R. Berk; F. D'Andrea; M. Ghil

2011-01-01T23:59:59.000Z

176

Dynamics and Structure of Forecast Error Covariance in the Core of a Developing Hurricane  

E-Print Network [OSTI]

of cloud-resolving forecasts from the Weather Research and Forecasting model (WRF) was used to study error gradients of wind, temperature, and pressure to be concentrated farther from the mean vortex center share a similar axisymmetric transition about the origin, while maintaining a large degree of local

177

The Uncoordinated Giant: Why U.S. Weather Research and Prediction  

E-Print Network [OSTI]

accurate forecasts of major cyclones and other large-scale features. High-resolution mesoscale models of the Internet as a means for distributing weather information and forecasts. But in spite of these advances technologies, inadequate interactions with user communities, and unproductive or inappropriate use of limited

Mass, Clifford F.

178

Hydrometeorological aspects of the Real-Time Ultrafinescale Forecast Support during the Special Observing Period of MAP Hydrology and Earth System Sciences, 7(6), 877889 (2003) EGU  

E-Print Network [OSTI]

-Italian border region were predicted correctly by data from the numerical weather models linked application of numerical weather prediction data to forecast flows over a very large, multinational domain points, covering the whole of theAlpine region. These high resolution numerical weather prediction data

Paris-Sud XI, Université de

179

An Evaluation of Decadal Probability Forecasts from State-of-the-Art Climate Models  

Science Journals Connector (OSTI)

While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the ...

Emma B. Suckling; Leonard A. Smith

2013-12-01T23:59:59.000Z

180

CONUS-Wide Evaluation of National Weather Service Flash Flood Guidance Products  

Science Journals Connector (OSTI)

This study quantifies the skill of the National Weather Services (NWS) flash flood guidance (FFG) product. Generated by River Forecast Centers (RFCs) across the United States, local NWS Weather Forecast Offices compare estimated and forecast ...

Robert A. Clark; Jonathan J. Gourley; Zachary L. Flamig; Yang Hong; Edward Clark

2014-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Adjoint Sensitivity Analysis for Numerical Weather Prediction  

E-Print Network [OSTI]

Sep 2, 2011 ... Adjoint Sensitivity Analysis for Numerical Weather Prediction: Applications to ... weather variables using numerical weather prediction models.

Alexandru Cioaca

2011-09-02T23:59:59.000Z

182

Investigation of model parameters for high-resolution wind energy forecasting: Case studies over simple and complex terrain  

Science Journals Connector (OSTI)

Abstract Wind power forecasting, turbine micrositing, and turbine design require high-resolution simulations of atmospheric flow. Case studies at two West Coast North American wind farms, one with simple and one with complex terrain, are explored using the Weather Research and Forecasting (WRF) model. Both synoptically and locally driven events that include some ramping are considered. The performance of the model with different grid nesting configurations, turbulence closures, and grid resolutions is investigated through comparisons with observation data. For the simple terrain site, no significant improvement in the simulation results is found when using higher resolution. In contrast, for the complex terrain site, there is significant improvement when using higher resolution, but only during the locally driven event. This suggests the possibility that computational resources could be spared under certain conditions, for example when the topography is adequately resolved at coarser resolutions. Physical parameters such as soil moisture have a very large effect, but mostly for the locally forced events for both simple and complex terrain. The effect of the PBL scheme choice varies significantly depending on the meteorological forcing and terrain. On average, prognostic TKE equation schemes perform better than non-local eddy viscosity schemes.

Nikola Marjanovic; Sonia Wharton; Fotini K. Chow

2014-01-01T23:59:59.000Z

183

The Impact of Satellite Data on Global Numerical Weather Prediction  

Science Journals Connector (OSTI)

The European Centre for Medium Range Weather Forecasts (ECMWF) produces operational global forecasts ... state of the atmosphere at 12Z. The satellite data used in a global Numerical Weather Prediction (NWP) syst...

J. Pailleux

1987-01-01T23:59:59.000Z

184

TRACKING TROPICAL CLOUD SYSTEMS FOR THE DIAGNOSIS OF SIMULATIONS BY THE WEATHER RESEARCH AND  

E-Print Network [OSTI]

TRACKING TROPICAL CLOUD SYSTEMS FOR THE DIAGNOSIS OF SIMULATIONS BY THE WEATHER RESEARCH using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using

185

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?  

Science Journals Connector (OSTI)

...Department of Energy, Office of Science. See http://science...nature12534 ) 11 The Met Office. 2014 The recent storms...floods in the UK. Met Office Briefing Paper. See...climate models missing?. Science 340, 1053-1054...

2014-01-01T23:59:59.000Z

186

Research on the risk forecast model in the coal mine system based on GSPA-Markov  

Science Journals Connector (OSTI)

Safety accidents in the coal mine occurred frequently, that how to reduce them became an important national task, which the hazards identification and the risk forecast work in the coal mine system can solve. In the process of risk forecast in the coal mine system, considering characteristics that system risk is different in different period, the IDO (identification, difference, opposition) change rule of the set pair which has element weight is analyzed, and on the basis of which, the system risk forecast model based on GSPA-MARKOV is put forward. The application example shows that the risk state in the coal mine system is forecasted by the transition probability and the ergodicity in the model, which embodies fully dynamic, predictable and so on , thus it provides a new method to determine the risk state in the coal mine system.

LI De-shun; XU Kai-li

2011-01-01T23:59:59.000Z

187

An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street  

Science Journals Connector (OSTI)

Short-term forecasting of travel time is essential for the success of intelligent transportation system. In this paper, we review the state-of-art of short-term traffic forecasting models and outline their basic ideas, related works, advantages and disadvantages of each model. An improved adaptive exponential smoothing (IAES) model is also proposed to overcome the drawbacks of the previous adaptive exponential smoothing model. Then, comparing experiments are carried out under normal traffic condition and abnormal traffic condition to evaluate the performance of four main branches of forecasting models on direct travel time data obtained by license plate matching (LPM). The results of experiments show each model seems to have its own strength and weakness. The forecasting performance of IASE is superior to other models in shorter forecasting horizon (one and two step forecasting) and the IASE is capable of dealing with all kind of traffic conditions.

Zhi-Peng LI; Hong YU; Yun-Cai LIU; Fu-Qiang LIU

2008-01-01T23:59:59.000Z

188

A hybrid dynamic and fuzzy time series model for mid-term power load forecasting  

Science Journals Connector (OSTI)

Abstract A new hybrid model for forecasting the electric power load several months ahead is proposed. To allow for distinct responses from individual load sectors, this hybrid model, which combines dynamic (i.e., air temperature dependency of power load) and fuzzy time series approaches, is applied separately to the household, public, service, and industrial sectors. The hybrid model is tested using actual load data from the Seoul metropolitan area, and its predictions are compared with those from two typical dynamic models. Our investigation shows that, in the case of four-month forecasting, the proposed model gives the actual monthly power load of every sector with only less than 3% absolute error and satisfactory reduction of forecasting errors compared to other models from previous studies.

Woo-Joo Lee; Jinkyu Hong

2015-01-01T23:59:59.000Z

189

Suitability of the Weather Research and Forecasting (WRF) Model to Predict the June 2005 Fire Weather for Interior Alaska  

E-Print Network [OSTI]

temperature, and daily accumulated shortwave radiation well. Daily minimum (maximum) temperature and relative to local fire management authorities on the potential for wild- fires to plan prescribed burns, alert of fire control into fire indices that reflect protection require- ments. The National Fire Danger Rating

Moelders, Nicole

190

An Improved Model To Forecast Co2 Leakage Rates Along A Wellbore | Open  

Open Energy Info (EERE)

Model To Forecast Co2 Leakage Rates Along A Wellbore Model To Forecast Co2 Leakage Rates Along A Wellbore Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: An Improved Model To Forecast Co2 Leakage Rates Along A Wellbore Details Activities (0) Areas (0) Regions (0) Abstract: Large-scale geological storage of CO2 is likely to bring CO2 plumes into contact with a large number of existing wellbores. Wellbores that no longer provide proper zonal isolation establish a primary pathway for a buoyant CO2-rich phase to escape from the intended storage formation. The hazard of CO2 leakage along these pathways will depend on the rate of leakage. Thus a useful component of a risk assessment framework is a model of CO2 leakage. Predicting the flux of CO2 along a leaking wellbore requires a model of fluid properties and of transport along the leakage

191

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations the Northern Study Area.  

SciTech Connect (OSTI)

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

Finley, Cathy [WindLogics

2014-04-30T23:59:59.000Z

192

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

Science Journals Connector (OSTI)

Wind direction is an angular variable, as opposed to weather quantities such as temperature, quantitative precipitation, or wind speed, which are linear variables. Consequently, traditional model output statistics and ensemble postprocessing ...

Le Bao; Tilmann Gneiting; Eric P. Grimit; Peter Guttorp; Adrian E. Raftery

2010-05-01T23:59:59.000Z

193

Analysis of Precipitation Using Satellite Observations and Comparisons with Global Climate Models  

E-Print Network [OSTI]

is investigated by comparisons with satellite observa- iv tions. Speci cally, six-year long (2000-2005) simulations are performed using a high- resolution (36-km) Weather Research Forecast (WRF) model and the Community Atmosphere Model (CAM) at T85 spatial... . . . . . . . . . . . . . . . . 31 B. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 1. Satellite data . . . . . . . . . . . . . . . . . . . . . . . 33 2. Weather research and forecast model simulations . . . 34 3. Community atmosphere model simulations...

Murthi, Aditya

2011-08-08T23:59:59.000Z

194

Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling  

E-Print Network [OSTI]

in the numerical weather prediction (NWP) and climate models through parameterisation. For parameterisation, data. The effect of lakes should be parameterised in numerical weather prediction (NWP) and climate modellingEstimation of the mean depth of boreal lakes for use in numerical weather prediction and climate

Paris-Sud XI, Université de

195

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change  

SciTech Connect (OSTI)

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

2013-06-28T23:59:59.000Z

196

Evaluation of Precipitation from Numerical Weather Prediction Models and Satellites Using Values Retrieved from Radars  

Science Journals Connector (OSTI)

Precipitation is evaluated from two weather prediction models and satellites, taking radar-retrieved values as a reference. The domain is over the central and eastern United States, with hourly accumulated precipitation over 21 days for the ...

Slavko Vasi?; Charles A. Lin; Isztar Zawadzki; Olivier Bousquet; Diane Chaumont

2007-11-01T23:59:59.000Z

197

Ensemble Kalman Filter Analyses and Forecasts of a Severe Mesoscale Convective System Using Different Choices of Microphysics Schemes  

Science Journals Connector (OSTI)

A Weather Research and Forecasting Model (WRF)-based ensemble data assimilation system is used to produce storm-scale analyses and forecasts of the 45 July 2003 severe mesoscale convective system (MCS) over Indiana and Ohio, which produced ...

Dustan M. Wheatley; Nusrat Yussouf; David J. Stensrud

2014-09-01T23:59:59.000Z

198

Characterizing and Optimizing Precipitation Forecasts from a Convection-Permitting Ensemble Initialized by a Mesoscale Ensemble Kalman Filter  

Science Journals Connector (OSTI)

Convection-permitting Weather Research and Forecasting (WRF) Model forecasts with 3-km horizontal grid spacing were produced for a 50-member ensemble over a domain spanning three-quarters of the contiguous United States between 25 May and 25 June ...

Craig S. Schwartz; Glen S. Romine; Kathryn R. Smith; Morris L. Weisman

2014-12-01T23:59:59.000Z

199

Intercomparison and Coupling of Ensemble and Four-Dimensional Variational Data Assimilation Methods for the Analysis and Forecasting of Hurricane Karl (2010)  

Science Journals Connector (OSTI)

This study examines the performance of ensemble and variational data assimilation systems for the Weather Research and Forecasting (WRF) Model. These methods include an ensemble Kalman filter (EnKF), an incremental four-dimensional variational ...

Jonathan Poterjoy; Fuqing Zhang

2014-09-01T23:59:59.000Z

200

Relative Short-Range Forecast Impact from Aircraft, Profiler, Radiosonde, VAD, GPS-PW, METAR, and Mesonet Observations via the RUC Hourly Assimilation Cycle  

Science Journals Connector (OSTI)

An assessment is presented on the relative forecast impact on the performance of a numerical weather prediction model from eight different observation data types: aircraft, profiler, radiosonde, velocity azimuth display (VAD), GPS-derived ...

Stanley G. Benjamin; Brian D. Jamison; William R. Moninger; Susan R. Sahm; Barry E. Schwartz; Thomas W. Schlatter

2010-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Importance of Horizontally Inhomogeneous Environmental Initial Conditions to Ensemble Storm-Scale Radar Data Assimilation and Very Short-Range Forecasts  

Science Journals Connector (OSTI)

The assimilation of operational Doppler radar observations into convection-resolving numerical weather prediction models for very short-range forecasting represents a significant scientific and technological challenge. Numerical experiments over ...

David J. Stensrud; Jidong Gao

2010-04-01T23:59:59.000Z

202

HEAT EXCHANGE AND WEATHER FORECASTING  

Science Journals Connector (OSTI)

...energy into kinetic energy. In the scheme of...that the potential energy has to be re- stored...time, search for energy sources and sinks...earth's surfaces as a converter of radiation into...where K is the thermal diffusivity; in...the mobility of the ocean waters, we see that...

Sverre Petterssen

1959-01-01T23:59:59.000Z

203

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies  

SciTech Connect (OSTI)

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation. We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.; Diao, Ruisheng; Lu, Ning

2014-04-14T23:59:59.000Z

204

A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting  

Science Journals Connector (OSTI)

Abstract Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily.

Zhongyue Su; Jianzhou Wang; Haiyan Lu; Ge Zhao

2014-01-01T23:59:59.000Z

205

Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty  

E-Print Network [OSTI]

with official flu estimates. We also compare the prediction accuracy between model-level fusion of differentForecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty using neighbor- hood embedding to predict flu case counts. Comparing our proposed ensemble method

Ryder, Barbara G.

206

Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project  

E-Print Network [OSTI]

1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

Paris-Sud XI, Université de

207

Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting  

E-Print Network [OSTI]

and substorms; 2784 Magnetospheric Physics: Solar wind/magnetosphere interactions; 3210 Mathematical Geophysics in the solar wind-magnetosphere interaction, de- veloping first principles models that encompass allGlobal and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting

Sitnov, Mikhail I.

208

Climate-Weather Modeling Studies Using a Prototype Global Cloud-System  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Climate-Weather Modeling Studies Using a Prototype Global Cloud-System Resolving Model Climate-Weather Modeling Studies Using a Prototype Global Cloud-System Resolving Model Climate-Weather Modeling Studies Using a Prototype Global Cloud-System Resolving Model PI Name: Venkatramani Balaji PI Email: balaji@princeton.edu Institution: Geophysical Fluid Dynamics Laboratory Allocation Program: ESP Allocation Hours at ALCF: 150 Million Year: 2010 to 2013 Research Domain: Earth Science We expect our understanding of the role of clouds in climate to undergo a qualitative change as the resolutions of global models begin to encompass clouds. At these resolutions, non-hydrostatic dynamics become significant and deep convective processes are resolved. We are poised at the threshold of being able to run global scale simulations that include direct, non-parameterized, simulations of deep convective clouds. The goal of this

209

Calibrating DOE-2 to Weather and Non-Weather-Dependent Loads for a Commercial Building: Data Processing Routines to Calibrate a DOE-2 Model, Volume II  

E-Print Network [OSTI]

ESL-TR-92-04/02 CALIBRATING DOE-2 TO WEATHER AND NON-WEATHER-DEPENDENT LOADS FOR A COMMERCIAL BUILDING, VOLUME 2: DATA PROCESSING ROUTINES TO CALIBRATE A DOE-2 MODEL Written by: John Douglas Bronson May 1992 (C) Copyright 1992 Texas Engineering... Plots 8 Temperature-Specific Humidity Carpet Plots 11 'PACKING' SITE MONITORED WEATHER DATA INTO TRY 16 APPENDIX A -- Data Processing Routines' Example Data Files and Routine Hard-copies 21 APPENDIX B -- Example Data Files and Progam Hard-copies to Pack...

Bronson, J. D.

1992-01-01T23:59:59.000Z

210

Discussion of long-range weather prediction  

SciTech Connect (OSTI)

A group of scientists at Los Alamos have held a series of discussions of the issues in and prospects for improvements in Long-range Weather Predictions Enabled by Proving of the Atmosphere at High Space-Time Resolution. The group contained the requisite skills for a full evaluation, although this report presents only an informal discussion of the main technical issues. The group discussed all aspects of the proposal, which are grouped below into the headings: (1) predictability; (2) sensors and satellites, (3) DIAL and atmospheric sensing; (4) localized transponders; and (5) summary and integration. Briefly, the group agreed that the relative paucity of observations of the state of the atmosphere severely inhibits the accuracy of weather forecasts, and any program that leads to a more dense and uniform observational network is welcome. As shown in Long-range Weather more dense and uniform observational network is welcome. As shown in Long-range Weather Predictions, the pay-back of accurate long-range forecasts should more than justify the expenditure associated with improved observations and forecast models required. The essential step is to show that the needed technologies are available for field test and space qualification.

Canavan, G.H.

1998-09-10T23:59:59.000Z

211

Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models  

Science Journals Connector (OSTI)

Ukraine is one of the most developed agriculture countries and one of the biggest crop producers in the world. Timely and accurate crop yield forecasts for Ukraine at regional level become a key element in providing support to policy makers in food security. In this paper, feasibility and relative efficiency of using moderate resolution satellite data to winter wheat forecasting in Ukraine at oblast level is assessed. Oblast is a sub-national administrative unit that corresponds to the NUTS2 level of the Nomenclature of Territorial Units for Statistics (NUTS) of the European Union. NDVI values were derived from the MODIS sensor at the 250m spatial resolution. For each oblast NDVI values were averaged for a cropland map (Rainfed croplands class) derived from the ESA GlobCover map, and were used as predictors in the regression models. Using a leave-one-out cross-validation procedure, the best time for making reliable yield forecasts in terms of root mean square error was identified. For most oblasts, NDVI values taken in AprilMay provided the minimum RMSE value when comparing to the official statistics, thus enabling forecasts 23 months prior to harvest. The NDVI-based approach was compared to the following approaches: empirical model based on meteorological observations (with forecasts in AprilMay that provide minimum RMSE value) and WOFOST crop growth simulation model implemented in the CGMS system (with forecasts in June that provide minimum RMSE value). All three approaches were run to produce winter wheat yield forecasts for independent datasets for 2010 and 2011, i.e. on data that were not used within model calibration process. The most accurate predictions for 2010 were achieved using the CGMS system with the RMSE value of 0.3tha?1 in June and 0.4tha?1 in April, while performance of three approaches for 2011 was almost the same (0.50.6tha?1 in April). Both NDVI-based approach and CGMS system overestimated winter wheat yield comparing to official statistics in 2010, and underestimated it in 2011. Therefore, we can conclude that performance of empirical NDVI-based regression model was similar to meteorological and CGMS models when producing winter wheat yield forecasts at oblast level in Ukraine 23 months prior to harvest, while providing minimum requirements to input datasets.

Felix Kogan; Nataliia Kussul; Tatiana Adamenko; Sergii Skakun; Oleksii Kravchenko; Oleksii Kryvobok; Andrii Shelestov; Andrii Kolotii; Olga Kussul; Alla Lavrenyuk

2013-01-01T23:59:59.000Z

212

DREAM tool increases space weather predictions  

E-Print Network [OSTI]

and an interactive user interface to support satellite operators and space weather forecasters. For national security- 1 - DREAM tool increases space weather predictions April 13, 2012 Predicting space weather in an article published in Space Weather, a journal of the American Geophysical Union. Space environment and its

213

Characteristics of Target Areas Selected by the Ensemble Transform Kalman Filter for Medium-Range Forecasts of High-Impact Winter Weather  

Science Journals Connector (OSTI)

The characteristics of target locations of tropospheric wind and temperature identified by a modified version of the ensemble transform Kalman filter (ETKF), in order to reduce 07-day forecast errors over North America, are explored from the ...

Sharanya J. Majumdar; Kathryn J. Sellwood; Daniel Hodyss; Zoltan Toth; Yucheng Song

2010-07-01T23:59:59.000Z

214

An Examination of the Uncertainty in Interpolated Winds and Its Effect on the Validation and Intercomparison of Forecast Models  

Science Journals Connector (OSTI)

Meteorological models need to be compared to long-term, routinely collected meteorological data. Whenever numerical forecast models are validated and compared, verification winds are normally interpolated to individual model grid points. To be ...

J. Scott Greene; W. Ethan Cook; David Knapp; Patrick Haines

2002-03-01T23:59:59.000Z

215

Another step to the full GPU implementation of the weather research and forecasting model  

Science Journals Connector (OSTI)

Uruguay is currently undergoing a gradual process of inclusion of wind energy in its matrix of electric power generation. In this context, a computational tool has been developed to predict the electrical power that will be injected into the grid. The ... Keywords: GPU, WRF, Wind power, bdy_interp1 routine, sintb routine

Juan Pablo Silva, Jos Hagopian, Marcel Burdiat, Ernesto Dufrechou, Martn Pedemonte, Alejandro Gutirrez, Gabriel Cazes, Pablo Ezzatti

2014-11-01T23:59:59.000Z

216

A COMPARISON OF CLOUD MICROPHYSICAL QUANTITIES WITH FORECASTS FROM CLOUD PREDICTION MODELS  

E-Print Network [OSTI]

of the Atmospheric System Research (ASR) Program, Bethesda, MD March 15-19, 2010 Environmental Sciences Department/Atmospheric Plains (SGP) site. Cloud forecasts generated by the models are compared with cloud microphysical and radiosonde) are used to derive the cloud microphysical quantities: ice water content, liquid water content

217

Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of Virginia, USA  

E-Print Network [OSTI]

Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of seawater intrusion from natural and anthropo- genic causes. The characteristics of transition zones between. Computer speed and storage capabilities have increased dramatically in the last few decades, to the point

218

Seasonal Maize Forecasting for South Africa and Zimbabwe Derived from an Agroclimatological Model  

E-Print Network [OSTI]

Seasonal Maize Forecasting for South Africa and Zimbabwe Derived from an Agroclimatological Model, with a hindcast correlation over 16 seasons of 0.92 for South Africa and 0.62 for Zimbabwe. Over 17 seasons and actual maize water-stress in South Africa, and a correlation of 0.79 for the same relationship

Martin, Randall

219

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics  

E-Print Network [OSTI]

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics MAURICE J. SCHMEITS, KEES J. KOK, AND DAAN H. P. VOGELEZANG Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands (Manuscript received 29 April 2004, in final form 7 September 2004

Schmeits, Maurice

220

Improved one day-ahead price forecasting using combined time series and artificial neural network models for the electricity market  

Science Journals Connector (OSTI)

The price forecasts embody crucial information for generators when planning bidding strategies to maximise profits. Therefore, generation companies need accurate price forecasting tools. Comparison of neural network and auto regressive integrated moving average (ARIMA) models to forecast commodity prices in previous researches showed that the artificial neural network (ANN) forecasts were considerably more accurate than traditional ARIMA models. This paper provides an accurate and efficient tool for short-term price forecasting based on the combination of ANN and ARIMA. Firstly, input variables for ANN are determined by time series analysis. This model relates the current prices to the values of past prices. Secondly, ANN is used for one day-ahead price forecasting. A three-layered feed-forward neural network algorithm is used for forecasting next-day electricity prices. The ANN model is then trained and tested using data from electricity market of Iran. According to previous studies, in the case of neural networks and ARIMA models, historical demand data do not significantly improve predictions. The results show that the combined ANN??ARIMA forecasts prices with high accuracy for short-term periods. Also, it is shown that policy-making strategies would be enhanced due to increased precision and reliability.

Ali Azadeh; Seyed Farid Ghaderi; Behnaz Pourvalikhan Nokhandan; Shima Nassiri

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL  

E-Print Network [OSTI]

EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL by Tempei This study develops a scheme for explicit simulation of ice particle habits in Cloud Resolving Models (CRMs is called Spectral Ice Habit Prediction System (SHIPS), which represents a continuous-property approach

Wisconsin at Madison, University of

222

Artificial neural network based models for forecasting electricity generation of grid connected solar PV power plant  

Science Journals Connector (OSTI)

This paper presents an artificial neural network (ANN) approach for forecasting the performance of electric energy generated output from a working 25-kWp grid connected solar PV system and a 100-kWp grid connected PV system installed at Minicoy Island of Union Territory of Lakshadweep Islands. The ANN interpolates among the solar PV generation output and relevant parameters such as solar radiation, module temperature and clearness index. In this study, three ANN models are implemented and validated with reasonable accuracy on real electric energy generation output data. The first model is univariate based on solar radiation and the output values. The second model is a multivariate model based on module temperature along with solar radiation. The third model is also a multivariate model based on module temperature, solar radiation and clearness index. A forecasting performance measure such as percentage root mean square error has been presented for each model. The second model, which gives the most accurate results, has been used in forecasting the generation output for another PV system with similar accuracy.

Imtiaz Ashraf; A. Chandra

2004-01-01T23:59:59.000Z

223

Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models  

SciTech Connect (OSTI)

We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

2008-01-24T23:59:59.000Z

224

Satellites Monitor the Weather from 22,300 Miles in Space  

Science Journals Connector (OSTI)

We rely on weather forecasts for everything from planting crops to deciding how to dress. With the help of weather satellites, such as GOES, meteorologists have improved their...

Viets, Patricia W

1997-01-01T23:59:59.000Z

225

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation > Table 1 Evaluation > Table 1 Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to 2002 Average Absolute Percent Error Variable AEO82 to AEO97 AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 Consumption Total Energy Consumption 1.6 1.7 1.7 1.8 1.9 1.9 Total Petroleum Consumption 2.8 2.9 2.8 2.9 3.0 2.9 Total Natural Gas Consumption 5.8 5.7 5.6 5.6 5.5 5.5 Total Coal Consumption 2.7 3.0 3.2 3.3 3.5 3.6 Total Electricity Sales 1.6 1.7 1.8 1.9 2.4 2.5 Production Crude Oil Production 4.2 4.3 4.5 4.5 4.5 4.5 Natural Gas Production 5.0 4.8 4.7 4.6 4.6 4.4 Coal Production 3.7 3.6 3.6 3.5 3.7 3.6 Imports and Exports Net Petroleum Imports 10.1 9.5 8.8 8.4 7.9 7.4 Net Natural Gas Imports 17.4 16.7 16.0 15.9 15.8 15.8 Net Coal Exports

226

Building Energy Software Tools Directory: Energy Usage Forecasts  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy Usage Forecasts Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides free 14-day ahead energy usage forecasts based on the degree day forecasts for 1,200 stations in the U.S. and Canada. The user enters the daily non-weather base load and the usage per degree day weather factor; the tool applies the degree day forecast and displays the total energy usage forecast. Helpful FAQs explain the process and describe various options for the calculation of the base load and weather factor. Historical degree day reports and 14-day ahead degree day forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature, load calculation, energy simulation Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700.

227

A New Forecasting Model for USD/CNY Exchange Rate  

E-Print Network [OSTI]

This paper models the return series of USD/CNY exchange rate by considering the conditional mean and conditional volatility simultaneously. An index type functional-coefficient model is adopted to model the conditional ...

Cai, Zongwu; Chen, Linna; Fang, Ying

2012-09-18T23:59:59.000Z

228

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model  

E-Print Network [OSTI]

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model of Technology Bhubaneswar, Odisha, India A. ROUTRAY National Centre for Medium Range Weather Forecasting, Noida The performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real

229

HEURISTIC APPROACH FOR OPTIMAL PARAMETER ESTIMATION OF ELECTRIC LOAD FORECAST MODEL  

Science Journals Connector (OSTI)

Load forecasting is a crucial aspect of electric power system planning and operation. This paper presents a heuristic approach for optimal parameter estimation of long term load forecast models. The problem is viewed as an optimization one in which the goal is to minimize the total estimation error by properly adjusting the model coefficients. A particle swarm optimization algorithm is developed to minimize the error associated with the estimated model parameters. Real data of Egyptian network is used to perform this study. Results are reported and compared to those obtained using the well known least error squares estimation technique. Comparison results are in favor of the proposed approach which signifies its potential as a promising estimation tool.

M. R. AlRashidi; K. M. EL?Naggar

2009-01-01T23:59:59.000Z

230

A model for improving ocean wind forecasts using satellite  

E-Print Network [OSTI]

Using the dynamical model from previous talk we now want to assimilate the satellite measurements Using the dynamical model from previous talk we now want to assimilate the satellite measurements now want to assimilate the satellite measurements into this model. We will discuss the measurement

Malmberg, Anders

231

Title: Development of Statistical and Data Drive Models to Predict Flares for Space Weather Predictions  

E-Print Network [OSTI]

D and civilian assets in both space and ground. The current state of predictability of solar flares is basedTitle: Development of Statistical and Data Drive Models to Predict Solar Flares for Space Weather Collaborator: Dr. K. S. Balasubramaniam, Air Force Research Laboratory Summary: Solar flares impact Do

Johnson, Eric E.

232

MODELLING SURFACE HOAR FORMATION AND EVOLUTION ON MOUNTAIN SLOPES Simon Horton1  

E-Print Network [OSTI]

. Weather station data and forecasted data from the GEM15 numerical weather prediction model were used evaluates surface hoar size predictions made with empirical weather based models and discusses how buried and south facing slopes in the Columbia Mountains. Two models were developed to predict crystal size, one

Jamieson, Bruce

233

Assessing the Capability of a Regional-Scale Weather Model to Simulate Extreme Precipitation Patterns and Flooding in Central Texas  

E-Print Network [OSTI]

Assessing the Capability of a Regional-Scale Weather Model to Simulate Extreme Precipitation Patterns and Flooding in Central Texas MARLA R. KNEBL LOWREY AND ZONG-LIANG YANG Department of Geological 3 March 2008) ABSTRACT A regional-scale weather model is used to determine the potential for flood

Yang, Zong-Liang

234

Regional forecasting with global atmospheric models; Final report  

SciTech Connect (OSTI)

The purpose of the project was to conduct model simulations for past and future climate change with respect to the proposed Yucca Mtn. repository. The authors report on three main topics, one of which is boundary conditions for paleo-hindcast studies. These conditions are necessary for the conduction of three to four model simulations. The boundary conditions have been prepared for future runs. The second topic is (a) comparing the atmospheric general circulation model (GCM) with observations and other GCMs; and (b) development of a better precipitation data base for the Yucca Mtn. region for comparisons with models. These tasks have been completed. The third topic is preliminary assessments of future climate change. Energy balance model (EBM) simulations suggest that the greenhouse effect will likely dominate climate change at Yucca Mtn. for the next 10,000 years. The EBM study should improve rational choice of GCM CO{sub 2} scenarios for future climate change.

Crowley, T.J.; Smith, N.R. [Applied Research Corp., College Station, TX (United States)

1994-05-01T23:59:59.000Z

235

Modelling and forecasting Oman crude oil prices using Box-Jenkins techniques  

Science Journals Connector (OSTI)

The Box-Jenkins' Auto Regressive Integrated Moving Average (ARIMA) modelling approach has been applied for the time series analysis of monthly average prices of Oman crude oil taken over a period of 10 years. Several seasonal and non-seasonal ARIMA models were identified. These models were then estimated and compared for their adequacy using the significance of the parameter estimates, mean square errors and Modified Box-Pierce (Ljung-Box) Chi-Square statistic. Based on these criterion a multiplicative seasonal model of the form ARIMA (1,1,5)x(1,1,1) was recommended for short term forecasting.

M.I. Ahmad

2012-01-01T23:59:59.000Z

236

Short-term load forecasting using generalized regression and probabilistic neural networks in the electricity market  

SciTech Connect (OSTI)

For the economic and secure operation of power systems, a precise short-term load forecasting technique is essential. Modern load forecasting techniques - especially artificial neural network methods - are particularly attractive, as they have the ability to handle the non-linear relationships between load, weather temperature, and the factors affecting them directly. A test of two different ANN models on data from Australia's Victoria market is promising. (author)

Tripathi, M.M.; Upadhyay, K.G.; Singh, S.N.

2008-11-15T23:59:59.000Z

237

Introduction. Stochastic physics and climate modelling  

E-Print Network [OSTI]

become a backbone of numerical weather prediction and is used not only by weather forecasters but also. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical history, the present era, whereby predictions are made from numerical solutions of the underlying dynamic

Williams, Paul

238

Detecting Dependence in the Sensitive Parameter Space of a Model Using Statistical Inference and Large Forecast Ensembles  

Science Journals Connector (OSTI)

This study looks for evidence of correlation among model physical parameters in the sensitive parameter space defined by those randomly sampled physical parameter vectors that induce the most notable response in some forecast metric. These ...

J. G. McLay; M. Liu

2014-10-01T23:59:59.000Z

239

Evolving an Information Diffusion Model Using a Genetic Algorithm for Monthly River Discharge Time Series Interpolation and Forecasting  

Science Journals Connector (OSTI)

The identification of the rainfallrunoff relationship is a significant precondition for surfaceatmosphere process research and operational flood forecasting, especially in inadequately monitored basins. Based on an information diffusion model (...

Chengzu Bai; Mei Hong; Dong Wang; Ren Zhang; Longxia Qian

2014-12-01T23:59:59.000Z

240

Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices  

E-Print Network [OSTI]

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Efficient Modeling and Forecasting of Electricity Spot Prices  

Science Journals Connector (OSTI)

Abstract The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices. Hence, this paper introduces an econometric model for the hourly time series of electricity prices of the European Power Exchange (EPEX) which incorporates specific features like renewable energy. The model consists of several sophisticated and established approaches and can be regarded as a periodic VAR-TARCH with wind power, solar power, and load as influences on the time series. It is able to map the distinct and well-known features of electricity prices in Germany. An efficient iteratively reweighted lasso approach is used for the estimation. Moreover, it is shown that several existing models are outperformed by the procedure developed in this paper.

Florian Ziel; Rick Steinert; Sven Husmann

2014-01-01T23:59:59.000Z

242

Bayesian model selection for dark energy using weak lensing forecasts  

Science Journals Connector (OSTI)

......cosmic shear surveys show exceptional...constraining the dark energy equation of state...potential for a survey to constrain dark energy parameters for...The fiducial survey will be able...between dynamical dark energy models and lambdaCDM......

Ivan Debono

2014-01-01T23:59:59.000Z

243

On model selection forecasting, dark energy and modified gravity  

Science Journals Connector (OSTI)

......be achieved with the dark energy survey (DES) (Wester et...considered. DES is the Dark Energy Survey, PS1 is the Pan-STARRS...imaging (weak lensing) surveys should be able decisively distinguish a dark energy GR model from a DGP......

A. F. Heavens; T. D. Kitching; L. Verde

2007-09-21T23:59:59.000Z

244

Evaluation of artificial neural networks as a model for forecasting consumption of wood products  

Science Journals Connector (OSTI)

In specific sciences, such as forest policy, the need for anticipation becomes more urgent because it has to manage valuable natural resources whose protection and sustainable management is rendered essential. In this paper, a modern method has been used, known as artificial neural networks (ANNs). In order to forecast the necessary future volumes of timber in Greece, a neural network has been developed and trained, using a variety of time series derived from the database of the Food and Agriculture Organisation of the United Nations (FAO) (concerning Greece) as external values and as internal value the Consumer Price Index has been used. Comparing the results of this project with linear and non-linear econometric forecasting models, it has been found that neural networks correspond, as confirmed by the econometric indicators MAPE (average absolute percentage error) and RMSE (the square root of the percentage by the average sum of squares differences).

Giorgos Tigas; Panagiotis Lefakis; Konstantinos Ioannou; Athanasios Hasekioglou

2013-01-01T23:59:59.000Z

245

Online short-term solar power forecasting  

SciTech Connect (OSTI)

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

246

Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)  

Reports and Publications (EIA)

The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

1998-01-01T23:59:59.000Z

247

Novel effects of demand side management data on accuracy of electrical energy consumption modeling and long-term forecasting  

Science Journals Connector (OSTI)

Abstract Worldwide implementation of demand side management (DSM) programs has had positive impacts on electrical energy consumption (EEC) and the examination of their effects on long-term forecasting is warranted. The objective of this study is to investigate the effects of historical DSM data on accuracy of EEC modeling and long-term forecasting. To achieve the objective, optimal artificial neural network (ANN) models based on improved particle swarm optimization (IPSO) and shuffled frog-leaping (SFL) algorithms are developed for EEC forecasting. For long-term EEC modeling and forecasting for the U.S. for 20102030, two historical data types used in conjunction with developed models include (i) EEC and (ii) socio-economic indicators, namely, gross domestic product, energy imports, energy exports, and population for 19672009 period. Simulation results from IPSO-ANN and SFL-ANN models show that using socio-economic indicators as input data achieves lower mean absolute percentage error (MAPE) for long-term EEC forecasting, as compared with EEC data. Based on IPSO-ANN, it is found that, for the U.S. EEC long-term forecasting, the addition of DSM data to socio-economic indicators data reduces MAPE by 36% and results in the estimated difference of 3592.8 MBOE (5849.9TWh) in EEC for 20102030.

F.J. Ardakani; M.M. Ardehali

2014-01-01T23:59:59.000Z

248

Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models  

SciTech Connect (OSTI)

Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

Vrugt, Jasper A [Los Alamos National Laboratory; Wohling, Thomas [NON LANL

2008-01-01T23:59:59.000Z

249

Coupling the High Complexity Land Surface Model ACASA to the Mesoscale Model WRF  

E-Print Network [OSTI]

In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional ...

Xu, L.

250

UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM  

SciTech Connect (OSTI)

We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.

Werth, D.; Garrett, A.

2009-04-15T23:59:59.000Z

251

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin  

SciTech Connect (OSTI)

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.; Buizza, Roberto; Schaake, John

2011-08-15T23:59:59.000Z

252

Forecasting wireless communication technologies  

Science Journals Connector (OSTI)

The purpose of the paper is to present a formal comparison of a variety of multiple regression models in technology forecasting for wireless communication. We compare results obtained from multiple regression models to determine whether they provide a superior fitting and forecasting performance. Both techniques predict the year of wireless communication technology introduction from the first (1G) to fourth (4G) generations. This paper intends to identify the key parameters impacting the growth of wireless communications. The comparison of technology forecasting approaches benefits future researchers and practitioners when developing a prediction of future wireless communication technologies. The items of focus will be to understand the relationship between variable selection and model fit. Because the forecasting error was successfully reduced from previous approaches, the quadratic regression methodology is applied to the forecasting of future technology commercialisation. In this study, the data will show that the quadratic regression forecasting technique provides a better fit to the curve.

Sabrina Patino; Jisun Kim; Tugrul U. Daim

2010-01-01T23:59:59.000Z

253

Sandia National Laboratories: solar forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

254

Long-term Industrial Energy Forecasting (LIEF) model (18-sector version)  

SciTech Connect (OSTI)

The new 18-sector Long-term Industrial Energy Forecasting (LIEF) model is designed for convenient study of future industrial energy consumption, taking into account the composition of production, energy prices, and certain kinds of policy initiatives. Electricity and aggregate fossil fuels are modeled. Changes in energy intensity in each sector are driven by autonomous technological improvement (price-independent trend), the opportunity for energy-price-sensitive improvements, energy price expectations, and investment behavior. Although this decision-making framework involves more variables than the simplest econometric models, it enables direct comparison of an econometric approach with conservation supply curves from detailed engineering analysis. It also permits explicit consideration of a variety of policy approaches other than price manipulation. The model is tested in terms of historical data for nine manufacturing sectors, and parameters are determined for forecasting purposes. Relatively uniform and satisfactory parameters are obtained from this analysis. In this report, LIEF is also applied to create base-case and demand-side management scenarios to briefly illustrate modeling procedures and outputs.

Ross, M.H. [Univ. of Michigan, Ann Arbor, MI (US). Dept. of Physics; Thimmapuram, P.; Fisher, R.E.; Maciorowski, W. [Argonne National Lab., IL (US)

1993-05-01T23:59:59.000Z

255

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Journals Connector (OSTI)

This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend ...

Thomas J. Galarneau Jr.; Christopher A. Davis

2013-02-01T23:59:59.000Z

256

Forecasting 65+ travel : an integration of cohort analysis and travel demand modeling  

E-Print Network [OSTI]

Over the next 30 years, the Boomers will double the 65+ population in the United States and comprise a new generation of older Americans. This study forecasts the aging Boomers' travel. Previous efforts to forecast 65+ ...

Bush, Sarah, 1973-

2003-01-01T23:59:59.000Z

257

Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models: Introduction to the JAS Special Collection  

Science Journals Connector (OSTI)

To date, the assimilation of satellite measurements in numerical weather prediction (NWP) models has focused on the clear atmosphere. But satellite observations in the visible, infrared, and microwave provide a great deal of information on clouds ...

Ronald M. Errico; George Ohring; Fuzhong Weng; Peter Bauer; Brad Ferrier; Jean-Franois Mahfouf; Joe Turk

2007-11-01T23:59:59.000Z

258

Development of short-term forecast quality for new offshore wind farms  

Science Journals Connector (OSTI)

As the rapid wind power build-out continues, a large number of new wind farms will come online but forecasters and forecasting algorithms have little experience with them. This is a problem for statistical short term forecasts, which must be trained on a long record of historical power production exactly what is missing for a new farm. Focus of the study was to analyse development of the offshore wind power forecast (WPF) quality from beginning of operation up to one year of operational experience. This paper represents a case study using data of the first German offshore wind farm "alpha ventus" and first German commercial offshore wind farm "Baltic1". The work was carried out with measured data from meteorological measurement mast FINO1, measured power from wind farms and numerical weather prediction (NWP) from the German Weather Service (DWD). This study facilitates to decide the length of needed time series and selection of forecast method to get a reliable WPF on a weekly time axis. Weekly development of WPF quality for day-ahead WPF via different models is presented. The models are physical model; physical model extended with a statistical correction (MOS) and artificial neural network (ANN) as a pure statistical model. Selforganizing map (SOM) is investigated for a better understanding of uncertainties of forecast error.

M Kurt; B Lange

2014-01-01T23:59:59.000Z

259

Building Energy Software Tools Directory: Degree Day Forecasts  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecasts Forecasts Degree Day Forecasts example chart Quick and easy web-based tool that provides free 14-day ahead degree day forecasts for 1,200 stations in the U.S. and Canada. Degree Day Forecasts charts show this year, last year and three-year average. Historical degree day charts and energy usage forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700. Expertise Required No special expertise required. Simple to use. Users Over 1,000 weekly users. Audience Anyone who needs degree day forecasts (next 14 days) for the U.S. and Canada. Input Select a weather station (1,200 available) and balance point temperature. Output Charts show (1) degree day (heating and cooling) forecasts for the next 14

260

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities  

Science Journals Connector (OSTI)

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Carolina Garca-Martos; Julio Rodrguez; Mara Jess Snchez

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

AN APPLICATION OF URBANSIM TO THE AUSTIN, TEXAS REGION: INTEGRATED-MODEL FORECASTS FOR THE YEAR 2030  

E-Print Network [OSTI]

AN APPLICATION OF URBANSIM TO THE AUSTIN, TEXAS REGION: INTEGRATED-MODEL FORECASTS FOR THE YEAR, as well as energy consumption and greenhouse gas emissions. This work describes the modeling of year-2030 policies significantly impact the region's future land use patterns, traffic conditions, greenhouse gas

Kockelman, Kara M.

262

Multi-scale modeling and evaluation of urban surface energy balance in the Phoenix metropolitan area  

Science Journals Connector (OSTI)

Physical mechanisms of incongruency between observations and Weather Research and Forecasting (WRF) model predictions are examined. Limitations of evaluation are constrained by: i) parameterizations of model physics, ii) parameterizations of input ...

S.R. Shaffer; W.T.L. Chow; M. Georgescu; P. Hyde; G.D. Jenerette; A. Mahalov; M. Moustaoui; B.L. Ruddell

263

WRF Model Simulation of Two Alberta Flooding Events and the Impact of Topography  

Science Journals Connector (OSTI)

This study examines simulations of two flooding events in Alberta, Canada, during June 2005, made using the Weather Research and Forecasting Model (WRF). The model was used in a manner readily accessible to nonmeteorologists (e.g., accepting ...

Thomas K. Flesch; Gerhard W. Reuter

2012-04-01T23:59:59.000Z

264

Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling  

Science Journals Connector (OSTI)

Abstract Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states. The different sources of information are weighted according to their accuracy by the means of error covariance matrices. Our purpose here is to evaluate the efficiency of variational data assimilation for the xenon induced oscillations forecasts in nuclear cores. In this paper we focus on the comparison between 3DVAR schemes with optimised background error covariance matrix B and a 4DVAR scheme. Tests were made in twin experiments using a simulation code which implements a mono-dimensional coupled model of xenon dynamics, thermal, and thermalhydraulic processes. We enlighten the very good efficiency of the 4DVAR scheme as well as good results with the 3DVAR one using a careful multivariate modelling of B.

Anglique Ponot; Jean-Philippe Argaud; Bertrand Bouriquet; Patrick Erhard; Serge Gratton; Olivier Thual

2013-01-01T23:59:59.000Z

265

A Non Parametric Model for the Forecasting of the Venezuelan Oil Prices  

E-Print Network [OSTI]

A neural net model for forecasting the prices of Venezuelan crude oil is proposed. The inputs of the neural net are selected by reference to a dynamic system model of oil prices by Mashayekhi (1995, 2001) and its performance is evaluated using two criteria: the Excess Profitability test by Anatoliev and Gerko (2005) and the characteristics of the equity curve generated by a trading strategy based on the neural net predictions. ----- Se introduce aqui un modelo no parametrico para pronosticar los precios del petroleo Venezolano cuyos insumos son seleccionados en base a un sistema dinamico que explica los precios en terminos de dichos insumos. Se describe el proceso de recoleccion y pre-procesamiento de datos y la corrida de la red y se evaluan sus pronosticos a traves de un test estadistico de predictibilidad y de las caracteristicas del Equity Curve inducido por la estrategia de compraventa bursatil generada por dichos pronosticos.

Costanzo, Sabatino; Dehne, Wafaa; Prato, Hender

2007-01-01T23:59:59.000Z

266

Correcting and combining time series forecasters  

Science Journals Connector (OSTI)

Combined forecasters have been in the vanguard of stochastic time series modeling. In this way it has been usual to suppose that each single model generates a residual or prediction error like a white noise. However, mostly because of disturbances not ... Keywords: Artificial neural networks hybrid systems, Linear combination of forecasts, Maximum likelihood estimation, Time series forecasters, Unbiased forecasters

Paulo Renato A. Firmino; Paulo S. G. De Mattos Neto; Tiago A. E. Ferreira

2014-02-01T23:59:59.000Z

267

Applications of satellite remote sensing in numerical weather and climate prediction  

Science Journals Connector (OSTI)

The year 2000 marks the 40th anniversary of the launch of the first weather satellite. The images of cloud systems from the early satellites enabled forecasters to locate and monitor the movements of storms. Today's satellites provide a wealth of quantitative information about the constantly changing state of the Earth's atmosphere, ocean, and land surface. Significant strides are being made by operational centers around the world to effectively use these remotely-sensed observations in forecast models. The satellite measurements are used to initialize, provide boundary conditions for, and verify predictions of models. As an example of the state of the art, this paper reviews how satellite observations are used in the numerical weather and climate prediction models of the U.S. National Weather Service. The National Weather Service, National Centers for Environmental Prediction (NCEP), Environmental Modeling Center (EMC) develops regional and global weather prediction models, coupled ocean-atmosphere models for seasonal to interannual climate predictions, and a coastal ocean forecast model. A three dimensional variational data assimilation system is used to specify the initial conditions for the forecast models. Data from the following satellite instruments are currently used in one or more of these models: High Resolution Infrared Sounder (HIRS), Microwave Sounding Unit (MSU), Advanced Microwave Sounding Unit-A (AMSU-A), Geostationary Operational Environmental Satellites (GOES) sounder, GOES, METEOSAT, and Geostationary Meteorology Satellite (GMS) imagers, Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave/Imager (SSM/I), ESA Remote-sensing Satellite-2 (ERS-2) scatterometer, Solar Backscatter Ultraviolet Spectrometer/2 (SBUV/2), and Oceanic Topography Experiment (TOPEX) and ERS-2 altimeters.

G. Ohring; S. Lord; J. Derber; K. Mitchell; M. Ji

2002-01-01T23:59:59.000Z

268

Forecasting the monthly volume of orders for southern pine lumber - an econometric model  

E-Print Network [OSTI]

to measure various aspects of the California redwood lumber industry. The first sought to explain the economic struc- ture of the short-run market for redwood lumber by preparing short-range forecasts of price, new orders, shipments, produc- tion, stocks... regression coefficients (20) . The second study was directed at developing a short-run forecast of new orders for redwood lumber (21) . Several forecasting techniques were developed, but econometrics, i. e. , multiple regression analysis, provided...

Jackson, Ben Douglas

2012-06-07T23:59:59.000Z

269

Holts exponential smoothing and neural network models for forecasting interval-valued time series  

Science Journals Connector (OSTI)

Interval-valued time series are interval-valued data that are collected in a chronological sequence over time. This paper introduces three approaches to forecasting interval-valued time series. The first two approaches are based on multilayer perceptron (MLP) neural networks and Holts exponential smoothing methods, respectively. In Holts method for interval-valued time series, the smoothing parameters are estimated by using techniques for non-linear optimization problems with bound constraints. The third approach is based on a hybrid methodology that combines the MLP and Holt models. The practicality of the methods is demonstrated through simulation studies and applications using real interval-valued stock market time series.

Andr Luis Santiago Maia; Francisco de A.T. de Carvalho

2011-01-01T23:59:59.000Z

270

Forecasting a large number of tropical cyclone intensities around Japan using a high-resolution atmosphere-ocean coupled model  

Science Journals Connector (OSTI)

This work quantifies the benefits of using a high-resolution atmosphere-ocean coupled model in the tropical cyclone (TC) intensity forecasts in the vicinity of Japan. To do so, a large number of high-resolution calculations were performed by ...

Kosuke Ito; Tohru Kuroda; Kazuo Saito; Akiyoshi Wada

271

Accuracy of near real time updates in wind power forecasting  

E-Print Network [OSTI]

· advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

Heinemann, Detlev

272

Inverse modeling and forecasting for the exploitation of the Pauzhetsky geothermal field, Kamchatka, Russia  

SciTech Connect (OSTI)

A three-dimensional numerical model of the Pauzhetsky geothermal field has been developed based on a conceptual hydrogeological model of the system. It extends over a 13.6-km2 area and includes three layers: (1) a base layer with inflow; (2) a geothermal reservoir; and (3) an upper layer with discharge and recharge/infiltration areas. Using the computer program iTOUGH2 (Finsterle, 2004), the model is calibrated to a total of 13,675 calibration points, combining natural-state and 1960-2006 exploitation data. The principal model parameters identified and estimated by inverse modeling include the fracture permeability and fracture porosity of the geothermal reservoir, the initial natural upflow rate, the base-layer porosity, and the permeabilities of the infiltration zones. Heat and mass balances derived from the calibrated model helped identify the sources of the geothermal reserves in the field. With the addition of five makeup wells, simulation forecasts for the 2007-2032 period predict a sustainable average steam production of 29 kg/s, which is sufficient to maintain the generation of 6.8 MWe at the Pauzhetsky power plant.

Finsterle, Stefan; Kiryukhin, A.V.; Asaulova, N.P.; Finsterle, S.

2008-04-01T23:59:59.000Z

273

Scientist warns against overselling climate change Climate change forecasters should admit that they cannot predict how global warming will affect  

E-Print Network [OSTI]

forward on climate change, he said the data produced by models used to project weather changes risks beingScientist warns against overselling climate change Climate change forecasters should admit climate ­ with dangerous results. Related Articles Second biggest wind farm to be built off UK (/earth

Stevenson, Paul

274

Comparing NWS PoP Forecasts to Third-Party Providers  

Science Journals Connector (OSTI)

In this paper, the authors verify probability of precipitation (PoP) forecasts provided by the National Weather Service (NWS), The Weather Channel (TWC), and CustomWeather (CW). The n-day-ahead forecasts, where n ranges from 1 to 3 for the NWS, ...

J. Eric Bickel; Eric Floehr; Seong Dae Kim

2011-10-01T23:59:59.000Z

275

The Landfall and Inland Penetration of a Flood-Producing Atmospheric River in Arizona. Part II: Sensitivity of Modeled Precipitation to Terrain Height and Atmospheric River Orientation  

Science Journals Connector (OSTI)

This manuscript documents numerical modeling experiments based on a January 2010 atmospheric river (AR) event that caused extreme precipitation in Arizona. The control experiment (CNTL), using the Weather Research and Forecasting (WRF) Model with ...

Mimi Hughes; Kelly M. Mahoney; Paul J. Neiman; Benjamin J. Moore; Michael Alexander; F. Martin Ralph

2014-10-01T23:59:59.000Z

276

Optimization of numerical weather/wave prediction models based on information geometry and computational techniques  

Science Journals Connector (OSTI)

The last years a new highly demanding framework has been set for environmental sciences and applied mathematics as a result of the needs posed by issues that are of interest not only of the scientific community but of today's society in general: global warming renewable resources of energy natural hazards can be listed among them. Two are the main directions that the research community follows today in order to address the above problems: The utilization of environmental observations obtained from in situ or remote sensing sources and the meteorological-oceanographic simulations based on physical-mathematical models. In particular trying to reach credible local forecasts the two previous data sources are combined by algorithms that are essentially based on optimization processes. The conventional approaches in this framework usually neglect the topological-geometrical properties of the space of the data under study by adopting least square methods based on classical Euclidean geometry tools. In the present work new optimization techniques are discussed making use of methodologies from a rapidly advancing branch of applied Mathematics the Information Geometry. The latter prove that the distributions of data sets are elements of non-Euclidean structures in which the underlying geometry may differ significantly from the classical one. Geometrical entities like Riemannian metrics distances curvature and affine connections are utilized in order to define the optimum distributions fitting to the environmental data at specific areas and to form differential systems that describes the optimization procedures. The methodology proposed is clarified by an application for wind speed forecasts in the Kefaloniaisland Greece.

2014-01-01T23:59:59.000Z

277

Weatherization and Intergovernmental Program: Weatherization Assistance  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Weatherization Assistance Program to someone by E-mail Weatherization Assistance Program to someone by E-mail Share Weatherization and Intergovernmental Program: Weatherization Assistance Program on Facebook Tweet about Weatherization and Intergovernmental Program: Weatherization Assistance Program on Twitter Bookmark Weatherization and Intergovernmental Program: Weatherization Assistance Program on Google Bookmark Weatherization and Intergovernmental Program: Weatherization Assistance Program on Delicious Rank Weatherization and Intergovernmental Program: Weatherization Assistance Program on Digg Find More places to share Weatherization and Intergovernmental Program: Weatherization Assistance Program on AddThis.com... Plans, Implementation, & Results Weatherization Assistance Program Weatherization Services

278

Modeling of atmospheric corrosion behavior of weathering steel in sulfur dioxide-polluted atmospheres  

SciTech Connect (OSTI)

Atmospheric corrosion resistance of carbon steel (CS) and high-phosphorus weathering steel (WS, Acr-Ten A) was compared after exposure for up to 6 years in Taiwan. In an industrial atmosphere, corrosion kinetics of WS after 3 years of exposure deviated from behavior predicted by the well-known bilogarithmic law. This deviation was simulated using a laboratory accelerated test under cyclic wet/dry conditions with addition of 1 ppm sulfur dioxide (SO{sub 2}). In-situ electrochemical impedance measurements also were carried out in a modified three-electrode cell covered by a thin electrolyte layer to investigate corrosion behavior of WS in SO{sub 2}-polluted environments. Three impedance models were proposed to explain the characteristic corrosion behavior of WS in various stages of exposure.

Wang, J.H.; Shih, H.C. [National Tsing Hua Univ., Hsinchu (Taiwan, Province of China). Dept. of Materials Science and Engineering; Wei, F.I. [China Steel Corp., Kaoshiung (Taiwan, Province of China)

1996-12-01T23:59:59.000Z

279

Residential Weatherization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Showerheads Residential Weatherization Performance Tested Comfort Systems Ductless Heat Pumps New Construction Residential Marketing Toolkit Retail Sales Allocation Tool...

280

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Perturbations  

Science Journals Connector (OSTI)

The wind speed response to mesoscale SST variability is investigated over the Agulhas Return Current region of the Southern Ocean using the Weather Research and Forecasting (WRF) Model and the U.S. Navy Coupled OceanAtmosphere Mesoscale ...

Natalie Perlin; Simon P. de Szoeke; Dudley B. Chelton; Roger M. Samelson; Eric D. Skyllingstad; Larry W. ONeill

2014-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Stochastic Models Applied to Operation of Reservoirs in the Upper Colorado River Basin in Texas  

E-Print Network [OSTI]

A hydrometeorological model is presented that utilizes 30-day meteorological forecasts of temperature and precipitation issued every 15 days by the National Weather service to provide an estimate of the future hydrometeorological conditions of a...

Clark, R. A.; O'Connor, G. E.; Curry, G. L.; Helm, J. C.

282

The Value of a Variable Resolution Approach to Numerical Weather Prediction  

Science Journals Connector (OSTI)

It is shown that a numerical weather prediction system with variable resolution, higher in the early forecast range and lower afterward, provides more skilful forecasts than a system with constant resolution. Results indicate that the advantage ...

Roberto Buizza

2010-04-01T23:59:59.000Z

283

Weatherization and Intergovernmental Program: Apply for Weatherization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Apply Apply for Weatherization Assistance to someone by E-mail Share Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on Facebook Tweet about Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on Twitter Bookmark Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on Google Bookmark Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on Delicious Rank Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on Digg Find More places to share Weatherization and Intergovernmental Program: Apply for Weatherization Assistance on AddThis.com... Plans, Implementation, & Results Weatherization Assistance Program Weatherization Services

284

Weatherization and Intergovernmental Program: Weatherization Services  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Services to someone by E-mail Services to someone by E-mail Share Weatherization and Intergovernmental Program: Weatherization Services on Facebook Tweet about Weatherization and Intergovernmental Program: Weatherization Services on Twitter Bookmark Weatherization and Intergovernmental Program: Weatherization Services on Google Bookmark Weatherization and Intergovernmental Program: Weatherization Services on Delicious Rank Weatherization and Intergovernmental Program: Weatherization Services on Digg Find More places to share Weatherization and Intergovernmental Program: Weatherization Services on AddThis.com... Plans, Implementation, & Results Weatherization Assistance Program Weatherization Services History Goals & Metrics Allocation Formula Apply for Weatherization Assistance WAP - Sustainable Energy Resources for Consumers Grants

285

Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting  

Science Journals Connector (OSTI)

Because poor visibility conditions have a considerable influence on airport traffic, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL)-Interactions between Soil, Biosphere, and Atmosphere (...

Samuel Rmy; Thierry Bergot

2010-05-01T23:59:59.000Z

286

A Transaction Choice Model for Forecasting Demand for Alternative-Fuel Vehicles  

E-Print Network [OSTI]

Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tlus is

Brownstone, David; Bunch, David S.; Golob, Thomas F.; Ren, Weiping

1996-01-01T23:59:59.000Z

287

A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles  

E-Print Network [OSTI]

Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tlus is

Brownstone, David; Bunch, David S; Golob, Thomas F; Ren, Weiping

1996-01-01T23:59:59.000Z

288

Oil and Gas CDT Development of a SUNTANS Baroclinic Model for 3D Oil  

E-Print Network [OSTI]

Oil and Gas CDT Development of a SUNTANS Baroclinic Model for 3D Oil Pollution Tracking Heriot) Key Words Oil Spill, HF Radar, Trajectory Forecasting, Hydrodynamic Modelling, Oil Chemistry Overview In an oil spill emergency, an operational system must forecast ocean and weather conditions in addition

Henderson, Gideon

289

Dynamical and Microphysical Evolution during Mixed-Phase Cloud Glaciation Simulated Using the Bulk Adaptive Habit Prediction Model  

Science Journals Connector (OSTI)

A bulk microphysics scheme predicting ice particle habit evolution has been implemented in the Weather Research and Forecasting Model. Large-eddy simulations are analyzed to study the effects of ice habit and number concentration on the bulk ice ...

Kara J. Sulia; Hugh Morrison; Jerry Y. Harrington

2014-11-01T23:59:59.000Z

290

Object-Based Analysis and Verification of WRF Model Precipitation in the Low- and Midlatitude Pacific Ocean  

Science Journals Connector (OSTI)

An extended version of the Method for Object-based Diagnostic Evaluation (MODE) was used to perform a verification of precipitation provided by the Weather Research and Forecasting (WRF) model Tropical Channel Simulation (performed by NCAR). ...

Gregor Skok; Joe Tribbia; Joe Rakovec

2010-12-01T23:59:59.000Z

291

Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques  

Science Journals Connector (OSTI)

Abstract Nowadays, as an arena of politics, social media ignites political protests, so analyzing topics discussed negatively in the social media has increased in importance for detecting a nation's political risk. In this context, this paper designs and examines an automatic approach to forecast the daily outbreak of political risk from social media at a topic level. It evaluates the forecasting performances of topic features, investigated among the previous works that analyze social media data for politics, hidden Markov model (HMM)-based techniques, widely used for the anomaly detection with time-series data, and detection models, into which the topic features and the detection techniques are combined. When applied to South Korea's Web forum, Daum Agora, statistical comparisons with the constraints of false positive rate of political risk, and eventually the predictive governance benefits the people.

Jong Hwan Suh

2014-01-01T23:59:59.000Z

292

The CCPP-ARM Parameterization Testbed (CAPT): Where Climate Simulation Meets Weather Prediction  

SciTech Connect (OSTI)

To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands, in particular, that the GCM parameterizations of unresolved processes should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provied that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be similarly tested. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the USDOE is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM. Numerical weather prediction methods show promise for improving parameterizations in climate GCMs.

Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J

2003-11-21T23:59:59.000Z

293

Depositional sequences and integrated recovery efficiency forecast models for San Andres and Clearfork Units in the Central Basin Platform and the Northern Shelf, west Texas  

E-Print Network [OSTI]

This paper develops depositional sequences of the carbonate ramp and the carbonate shelf models for an idealized cycle and multiple cycles of depositions. Based on the developed depositional sequences, the integrated recovery efficiency forecast...

Shao, Hongbin

2012-06-07T23:59:59.000Z

294

Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model  

Science Journals Connector (OSTI)

Abstract Electricity consumption forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction may cause wastes of scarce energy resource or electricity shortages. However, forecasting electricity consumption has proven to be a challenging task due to various unstable factors. Especially, China is undergoing a period of economic transition, which highlights this difficulty. This paper proposes a time-varying-weight combining method, i.e. High-order Markov chain based Time-varying Weighted Average (HM-TWA) method to predict the monthly electricity consumption in China. HM-TWA first calculates the in-sample time-varying combining weights by quadratic programming for the individual forecasts. Then it predicts the out-of-sample time-varying adaptive weights through extrapolating these in-sample weights using a high-order Markov chain model. Finally, the combined forecasts can be obtained. In addition, to ensure that the sample data have the same properties as the required forecasts, a reasonable multi-step-ahead forecasting scheme is designed for HM-TWA. The out-of-sample forecasting performance evaluation shows that HM-TWA outperforms the component models and traditional combining methods, and its effectiveness is further verified by comparing it with some other existing models.

Weigang Zhao; Jianzhou Wang; Haiyan Lu

2014-01-01T23:59:59.000Z

295

A Comparison of Precipitation Forecast Skill between Small Convection-Allowing and Large Convection-Parameterizing Ensembles  

E-Print Network [OSTI]

-km grid-spacing (ENS4) and a 15-member, 20-km grid-spacing (ENS20) Weather Research and Forecasting of various precipitation skill metrics for probabilistic and deterministic forecasts reveals that ENS4 Centre for Medium-Range Weather Forecasts (ECMWF; Molteni et al. 1996) Ensemble Prediction System

Xue, Ming

296

CLIMAGE: A New Software for the Prediction of Short-Term Weather with the Help of Satellite Data and Neuro-Fuzzy Clustering  

Science Journals Connector (OSTI)

Weather is an essential part of decision making ... amenities of any region also depend on daily weather variations. That is why short-range weather forecasting has a direct impact on the ... capacity involved in...

Mrinmoy Majumder; Tilottama Chackraborty

2013-01-01T23:59:59.000Z

297

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology  

E-Print Network [OSTI]

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau-Russian blocking 2010, predicted out to 10d) 1st-10th Aug 2010 #12;Extreme heat definition Lack of common metrics forecasts SEDI for DJF, all forecasts SEDI for JJA, all forecasts #12;The Centre for Australian Weather

Marshall, Andrew

298

An Aggregate Air Traffic Forecasting Model subject to Stochastic Christabelle S. Bosson  

E-Print Network [OSTI]

at Dallas Fort-Worth International airport under weather and reduced airport capacity. Almost 60, 000, Boston, MA AIAA 2013-5032 Copyright © 2013 by the American Institute of Aeronautics and Astronautics, Inc

Sun, Dengfeng

299

Forecasting GHG emissions using an optimized artificial neural network model based on correlation and principal component analysis  

Science Journals Connector (OSTI)

Abstract The prediction of GHG emissions is very important due to their negative impacts on climate and global warming. The aim of this study was to develop a model for GHG forecasting emissions at the national level using a new approach based on artificial neural networks (ANN) and broadly available sustainability, economical and industrial indicators acting as inputs. The ANN model architecture and training parameters were optimized, with inputs being selected using correlation analysis and principal component analysis. The developed ANN models were compared with the corresponding multiple linear regression (MLR) model, while an ANN model created using transformed inputs (principal components) was compared with a principal component regression (PCR) model. Since the best results were obtained with the ANN model based on correlation analysis, that particular model was selected for the actual 2011 GHG emissions forecasting. The relative errors of the 2010 GHG emissions predictions were used to adjust the ANN model predictions for 2011, which subsequently resulted in the adjusted 2011 predictions having a MAPE value of only 3.60%. Sensitivity analysis showed that gross inland energy consumption had the highest sensitivity to GHG emissions.

Davor Z. Antanasijevi?; Mirjana ?. Risti?; Aleksandra A. Peri?-Gruji?; Viktor V. Pocajt

2014-01-01T23:59:59.000Z

300

Cloud system resolving model simulations of tropical cloud systems observed during the Tropical  

E-Print Network [OSTI]

the Weather Research and Forecasting (WRF) model. The WRF model is configured with a highest-resolving domain convection. The second regime is a monsoon break, which contains intense localized systems that are rep-based observational systems including a polarimetric weather radar, cloud radar, wind profilers, radi- ation

Jakob, Christian

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Weatherization and Intergovernmental Program: Weatherization Innovation  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Innovation Pilot Program to someone by E-mail Innovation Pilot Program to someone by E-mail Share Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on Facebook Tweet about Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on Twitter Bookmark Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on Google Bookmark Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on Delicious Rank Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on Digg Find More places to share Weatherization and Intergovernmental Program: Weatherization Innovation Pilot Program on AddThis.com... Plans, Implementation, & Results Weatherization Assistance Program

302

Weatherization and Intergovernmental Program: Weatherization Assistance  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Weatherization Assistance Program Allocation Formula to someone by E-mail Share Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on Facebook Tweet about Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on Twitter Bookmark Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on Google Bookmark Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on Delicious Rank Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on Digg Find More places to share Weatherization and Intergovernmental Program: Weatherization Assistance Program Allocation Formula on

303

Weatherization and Intergovernmental Program: National Weatherization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Information Resources Information Resources Site Map Printable Version Share this resource Send a link to Weatherization and Intergovernmental Program: National Weatherization Training Portal to someone by E-mail Share Weatherization and Intergovernmental Program: National Weatherization Training Portal on Facebook Tweet about Weatherization and Intergovernmental Program: National Weatherization Training Portal on Twitter Bookmark Weatherization and Intergovernmental Program: National Weatherization Training Portal on Google Bookmark Weatherization and Intergovernmental Program: National Weatherization Training Portal on Delicious Rank Weatherization and Intergovernmental Program: National Weatherization Training Portal on Digg Find More places to share Weatherization and Intergovernmental

304

Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report  

SciTech Connect (OSTI)

This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

Eto, J.H.; Moezzi, M.M.

1993-12-01T23:59:59.000Z

305

Copula Based Stochastic Weather Generator as an Application for Crop Growth Models and Crop Insurance  

E-Print Network [OSTI]

Stochastic Weather Generators (SWG) try to reproduce the stochastic patterns of climatological variables characterized by high dimensionality, non-normal probability density functions and non-linear dependence relationships. However, conventional...

Juarez Torres, Miriam 77-

2012-08-31T23:59:59.000Z

306

Study of Climate Change Impact on Flood Frequencies: A Combined Weather Generator and Hydrological Modeling Approach  

Science Journals Connector (OSTI)

Climate change is expected to lead to more frequent and intensive flooding problems for watersheds in the south part of China. This study presented a coupled Long Ashton Research Station Weather Generator (LARS-WG) and Semidistributed Land Use...

X. S. Qin; Y. Lu

2014-06-01T23:59:59.000Z

307

Which Way Will The Wind Blow? Networked Computer Tools For Studying The Weather  

E-Print Network [OSTI]

school level. These tools give students access to live satellite images, weather maps, and otherWhich Way Will The Wind Blow? Networked Computer Tools For Studying The Weather Barry J. Fishman scientific data dealing with the weather, and make it easy for students to make their own weather forecasts

Fishman, Barry

308

Results of the Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California  

Science Journals Connector (OSTI)

...given in Table 1, as well as background earthquakes...in the test region as well as forecasts that excluded...about 50 km south of the MexicoUnited States border...this is the Cerra Prieto geothermal area...earthquake in northern Mexico. This earthquake occurred...

Ya-Ting Lee; Donald L. Turcotte; James R. Holliday; Michael K. Sachs; John B. Rundle; Chien-Chih Chen; Kristy F. Tiampo

2011-01-01T23:59:59.000Z

309

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multimodel Ensemble Forecasts  

Science Journals Connector (OSTI)

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 17-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 ...

Jianguo Liu; Zhenghui Xie

2014-04-01T23:59:59.000Z

310

Representing Forecast Error in a Convection-Permitting Ensemble System  

Science Journals Connector (OSTI)

Ensembles provide an opportunity to greatly improve short-term prediction of local weather hazards, yet generating reliable predictions remain a significant challenge. In particular, convection-permitting ensemble forecast systems (CPEFSs) have ...

Glen S. Romine; Craig S. Schwartz; Judith Berner; Kathryn R. Fossell; Chris Snyder; Jeff L. Anderson; Morris L. Weisman

2014-12-01T23:59:59.000Z

311

Weatherizing America  

Broader source: Energy.gov [DOE]

As Recovery Act money arrives to expand home weatherization programs across the country, Zachary Stewart of Phoenix, Ariz., and others have found an exciting opportunity not only to start working...

312

A comparison between a hydro-wind plant and wind speed forecasting using ARIMA models  

Science Journals Connector (OSTI)

In this paper we will present a comparison between two options for harnessing wind power. We will first analyze the behaviour of a wind farm that goes to the electricity market having previously made a forecast of wind speed while accepting the deviation penalties that these may incur. Second we will study the possibility of the wind farm not going to the market individually but as part of a hydro-wind plant.

2014-01-01T23:59:59.000Z

313

The Impact of Assimilating Surface Pressure Observations on Severe Weather Events in a WRF Mesoscale Ensemble System  

Science Journals Connector (OSTI)

Surface pressure observations are assimilated into a Weather Research and Forecast ensemble using an ensemble Kalman filter (EnKF) approach and the results are compared with observations for two severe weather events. Several EnKF experiments are ...

Dustan M. Wheatley; David J. Stensrud

2010-05-01T23:59:59.000Z

314

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and  

E-Print Network [OSTI]

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave a systematic evaluation of clouds in forecast models. Clouds and their associated microphysical processes for end users of weather forecasts, who may be interested not only in cloud cover, but in other variables

Hogan, Robin

315

Soil moisture in complex terrain: quantifying effects on atmospheric boundary layer flow and providing improved surface boundary conditions for mesoscale models  

E-Print Network [OSTI]

compressible numerical weather prediction model incompressible numerical weather prediction model withcompressible numerical weather prediction model in

Daniels, Megan Hanako

2010-01-01T23:59:59.000Z

316

Flood forecasting with the A&M watershed model: a hydrometeorological study  

E-Print Network [OSTI]

is questionable. Researchers have shown that techniques which combine rain gages (one gage per 1000 ? 2000 km~) with radar produce smaller measurement errors (10 ? 304) than either rain gages or weather radar when used alone. (Wilson and Brandes, 1979...) Higgs (&9)2) Blanchnrd i&9531 Jones (1355) Liivinov 1&956& Atlas and Chmela (1957) i, m' ~ li n Washington, D. C. Washington, D. C. Ynyslas, Great Brumn Shoeburyness, England Hawaii Various locations Venous locations Canada Cambridge, Mass...

Robinson, Cedric Glynn

1990-01-01T23:59:59.000Z

317

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

318

Weatherized in May 2010  

Broader source: Energy.gov (indexed) [DOE]

**Homes Weatherized in May 2010 (Recovery Act) Total Number of Homes Weatherized through May 2010 (Recovery Act) ***Total Number of Homes Weatherized Calendar Year 2009 - May 2010...

319

Weather Extremes  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Extremes Extremes Nature Bulletin No. 45 December 15, 1945 Forest Preserve District of Cook County Clayton F. Smith, President Roberts Mann, Superintendent of Conservation WEATHER EXTREMES Chicago lies in a temperate zone. We are fortunate. The lowest temperature recorded here since the establishment of the Weather Bureau in 1870 was -- 23 F on Dec. 24, 1872. The lowest records elsewhere in the United States are--66 F at Riverside Ranger Station, Yellowstone Park, Wyoming, on Feb. 9, 1933; and -- 78 F at Fort Yukon, Alaska, on Jan. 14, 1934. The lowest record anywhere on earth is 90 F at Verkhoyansk, Siberia, Feb. 5 and 7, 1892. The greatest snowfall recorded in Chicago in one 24-hour period was 14.9 inches on Jan. 30, 1939; but 19.2 inches fell between 1:10 a.m. on March 24 and 8:33 p.m. on March 26, 1930.

320

Fixed points, stable manifolds, weather regimes, and their predictability  

DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the models fixed points in phase space. The model dynamics is characterized by the coexistence of multiple weather regimes. To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, bred vectors and singular vectors. These results are then verified in the framework of ensemble forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael [Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics

2009-10-27T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.  

SciTech Connect (OSTI)

We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

2009-10-09T23:59:59.000Z

322

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and  

E-Print Network [OSTI]

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and European scales control measures that could be taken for managing such episodes, European-scale air quality forecasting

Paris-Sud XI, Université de

323

Sandia National Laboratories: Solar Energy Forecasting and Resource...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

324

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

SciTech Connect (OSTI)

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

325

DOE Workshop; Pan-Gass Conference on the Representation of Atmospheric Processes in Weather and Climate Models  

SciTech Connect (OSTI)

This is the first meeting of the whole new GEWEX (Global Energy and Water Cycle Experiment) Atmospheric System Study (GASS) project that has been formed from the merger of the GEWEX Cloud System Study (GCSS) Project and the GEWEX Atmospheric Boundary Layer Studies (GABLS). As such, this meeting will play a major role in energizing GEWEX work in the area of atmospheric parameterizations of clouds, convection, stable boundary layers, and aerosol-cloud interactions for the numerical models used for weather and climate projections at both global and regional scales. The representation of these processes in models is crucial to GEWEX goals of improved prediction of the energy and water cycles at both weather and climate timescales. This proposal seeks funds to be used to cover incidental and travel expenses for U.S.-based graduate students and early career scientists (i.e., within 5 years of receiving their highest degree). We anticipate using DOE funding to support 5-10 people. We will advertise the availability of these funds by providing a box to check for interested participants on the online workshop registration form. We will also send a note to our participants' mailing lists reminding them that the funds are available and asking senior scientists to encourage their more junior colleagues to participate. All meeting participants are encouraged to submit abstracts for oral or poster presentations. The science organizing committee (see below) will base funding decisions on the relevance and quality of these abstracts, with preference given to under-represented populations (especially women and minorities) and to early career scientists being actively mentored at the meeting (e.g. students or postdocs attending the meeting with their advisor).

Morrison, PI Hugh

2012-09-21T23:59:59.000Z

326

Continuous reservoir simulation model updating and forecasting using a markov chain monte carlo method  

E-Print Network [OSTI]

).......................58 Fig. 29 - Mixed well objective function value vs. model number (static case) ....59 Fig. 30 - Histogram of cumulative oil production made by static case ................60 Fig. 31 - CDF of cumulative production by mixed well models...-well sampled models in the chain to quantify the uncertainty in future oil production. We use all the models in Fig. 2 except for the first 7,000 models, whose objective function value is significantly high. Unfortunately, even though the MCMC method is a...

Liu, Chang

2009-05-15T23:59:59.000Z

327

Atmospheric Environment 39 (2005) 13731382 A hierarchical Bayesian model to estimate and forecast ozone  

E-Print Network [OSTI]

reserved. Keywords: Statistical model; Space­time models; Air pollution; Ozone; Meteorology 1. Introduction describing the spatial­temporal behavior of ambient air pollutants such as ozone (O3) and particulate matter. Statistical space­time models are useful for illuminating relationships between different air pollutants

Irwin, Mark E.

328

Generating and Calibrating Probabilistic Quantitative Precipitation Forecasts from the High-Resolution NWP Model COSMO-DE  

Science Journals Connector (OSTI)

Statistical postprocessing is an integral part of an ensemble prediction system. This study compares methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium ...

Sabrina Bentzien; Petra Friederichs

2012-08-01T23:59:59.000Z

329

Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of  

E-Print Network [OSTI]

of soil hydraulic models Thomas Wo¨hling1 and Jasper A. Vrugt2 Received 12 May 2008; revised 8 September

Vrugt, Jasper A.

330

Power System Load Forecasting Based on EEMD and ANN  

Science Journals Connector (OSTI)

In order to fully mine the characteristics of load data and improve the accuracy of power system load forecasting, a load forecasting model based on Ensemble Empirical Mode ... is proposed in this paper. Firstly,...

Wanlu Sun; Zhigang Liu; Wenfan Li

2011-01-01T23:59:59.000Z

331

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

This paper presents the National Energy Boards long term energy demand forecasting model in its present state of ... results of recent research at the NEB. Energy demand forecasts developed with the aid of this....

R. A. Preece; L. B. Harsanyi; H. M. Webster

1980-01-01T23:59:59.000Z

332

Evolutionary neural network modeling for forecasting the field failure data of repairable systems  

Science Journals Connector (OSTI)

An accurate product reliability prediction model can not only learn and track the product's reliability and operational performance, but also offer useful information for managers to take follow-up actions to improve the product' quality and cost. This ... Keywords: Genetic algorithms, Neural network model, Reliability prediction, Repairable system

L. Yi-Hui

2007-11-01T23:59:59.000Z

333

Time Series Models to Simulate and Forecast Wind Speed and Wind Power  

Science Journals Connector (OSTI)

A general approach for modeling wind speed and wind power is described. Because wind power is a function of wind speed, the methodology is based on the development of a model of wind speed. Values of wind power are estimated by applying the ...

Barbara G. Brown; Richard W. Katz; Allan H. Murphy

1984-08-01T23:59:59.000Z

334

Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system  

Science Journals Connector (OSTI)

...parametrizations: impact on the coupled ECMWF...Stochastic modelling and energy-efficient computing...effects of sub-grid-scale variability...present results of the impact of these schemes...and near-surface winds. Positive impact...Stochastic modelling and energy-efficient computing...

2014-01-01T23:59:59.000Z

335

Spatial postprocessing of ensemble forecasts for temperature using nonhomogeneous Gaussian regression  

Science Journals Connector (OSTI)

Statistical postprocessing techniques are commonly used to improve the skill of ensembles of numerical weather forecasts. This paper considers spatial extensions of the well-established nonhomogeneous Gaussian regression (NGR) postprocessing ...

Kira Feldmann; Michael Scheuerer; Thordis L. Thorarinsdottir

336

High Resolution Atmospheric Modeling for Wind Energy Applications  

SciTech Connect (OSTI)

The ability of the WRF atmospheric model to forecast wind speed over the Nysted wind park was investigated as a function of time. It was found that in the time period we considered (August 1-19, 2008), the model is able to predict wind speeds reasonably accurately for 48 hours ahead, but that its forecast skill deteriorates rapidly after 48 hours. In addition, a preliminary analysis was carried out to investigate the impact of vertical grid resolution on the forecast skill. Our preliminary finding is that increasing vertical grid resolution does not have a significant impact on the forecast skill of the WRF model over Nysted wind park during the period we considered. Additional simulations during this period, as well as during other time periods, will be run in order to validate the results presented here. Wind speed is a difficult parameter to forecast due the interaction of large and small length scale forcing. To accurately forecast the wind speed at a given location, the model must correctly forecast the movement and strength of synoptic systems, as well as the local influence of topography / land use on the wind speed. For example, small deviations in the forecast track or strength of a large-scale low pressure system can result in significant forecast errors for local wind speeds. The purpose of this study is to provide a preliminary baseline of a high-resolution limited area model forecast performance against observations from the Nysted wind park. Validating the numerical weather prediction model performance for past forecasts will give a reasonable measure of expected forecast skill over the Nysted wind park. Also, since the Nysted Wind Park is over water and some distance from the influence of terrain, the impact of high vertical grid spacing for wind speed forecast skill will also be investigated.

Simpson, M; Bulaevskaya, V; Glascoe, L; Singer, M

2010-03-18T23:59:59.000Z

337

Artificial Neural Network Model for Forecasting the Stock Price of Indian IT Company  

Science Journals Connector (OSTI)

The central issue of the study is to model the movement of stock price for Indian Information Technology (IT) companies. It has been observed that IT industry has some promising role in Indian economy. We apply t...

Joydeep Sen; Arup K. Das

2014-01-01T23:59:59.000Z

338

Marginalization and aggregation of exponential smoothing models in forecasting portfolio volatility  

Science Journals Connector (OSTI)

This paper examines exponentially weighted moving average models for predicting volatility and assessing risk in portfolios. It proposes a method that identifies the decay factors of the marginal volatility mo...

Giacomo Sbrana; Andrea Silvestrini

2012-01-01T23:59:59.000Z

339

Hydrologic modeling using triangulated irregular networks : terrain representation, flood forecasting and catchment response  

E-Print Network [OSTI]

Numerical models are modern tools for capturing the spatial and temporal variability in the land-surface hydrologic response to rainfall and understanding the physical relations between internal watershed processes and ...

Vivoni, Enrique R. (Enrique Rafael), 1975-

2003-01-01T23:59:59.000Z

340

The Application of Improved Grey GM(1,1) Model in Power System Load Forecast  

Science Journals Connector (OSTI)

According to existing Grey prediction model GM (1,1) in the data fluctuation, mutation, turning under uncertainty such as the problem of poor prediction accuracy, this paper presents an original data sequence ...

Zhengyuan Jia; Zhou Fan; Chuancai Li

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Upscale error growth in a high-resolution simulation of a summertime weather event over Europe  

Science Journals Connector (OSTI)

The growth of small amplitude, spatially uncorrelated perturbations has been studied in a weather forecast of a four day period in Summer 2007, using a large domain covering Europe and eastern Atlantic and with explicitly resolved deep convection. ...

Tobias Selz; George C. Craig

342

Essays on macroeconomics and forecasting  

E-Print Network [OSTI]

explanatory variables. Compared to Stock and Watson (2002)â??s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor...

Liu, Dandan

2006-10-30T23:59:59.000Z

343

Cathy Zoi on Weatherization  

SciTech Connect (OSTI)

Right now, the Weatherization Assistance Program is now weatherizing 25,000 homes each month. So far 10,000 jobs have been created under the Recovery Act.

Zoi, Cath

2010-01-01T23:59:59.000Z

344

Weatherization Pilot Projects  

Broader source: Energy.gov [DOE]

Webinars, fact sheets, and other information on Weatherization Assistance Program's Sustainable Energy Resources for Consumers and Weatherization Innovation Pilot Program projects.

345

Wind resource assessment using numerical weather prediction models and multi-criteria decision making technique: case study (Masirah Island, Oman)  

Science Journals Connector (OSTI)

The Authority for Electricity Regulation in Oman has recently announced the implementation of a 500 kW wind farm pilot project in Masirah Island. Detailed wind resource assessment is then required to identify the most suitable location for this project. This paper presents wind resource assessment using nested ensemble numerical weather prediction (NWP) model's approach at 2.8 km resolution and multi-criteria decision making (MCDM) technique. A case study based on the proposed approach is conducted over Masirah Island, Oman. The resource assessment over the island was based on the mean wind speed and wind power distribution over the entire island at different heights. In addition, important criteria such as turbulence intensity and peak hour matching are also considered. The NWP model results were verified against the available 10 m wind data observations from the meteorological station in the northern part of the island. The resource assessment criteria were evaluated using MCDM technique to score the locations over the island based on their suitability for wind energy applications. Two MCDM approaches namely equally weighted and differently weighted criteria were implemented in this paper.

Sultan Al-Yahyai; Yassine Charabi; Abdullah Al-Badi; Adel Gastli

2013-01-01T23:59:59.000Z

346

A critical evaluation of the use of the profile model in calculating mineral weathering rates  

Science Journals Connector (OSTI)

The PROFILE model is used extensively in the European Critical Loads programme as an aid to international negotiations on SO2 emission abatement. PROFILE calculates the rates of cation release by mineral weatheri...

Mark E. Hodson; Simon J. Langan; M. Jeff Wilson

1997-08-01T23:59:59.000Z

347

a critical evaluation of the use of the PROFILE model in calculating mineral weathering rates  

Science Journals Connector (OSTI)

The PROFILE model is used extensively in the European Critical Loads programme as an aid to international negotiations on SO2 emission abatement. PROFILE calculates the rates of cation release by mineral weatheri...

MARK E. HODSON; SIMON J. LANGAN; M. JEFF WILSON

1997-08-01T23:59:59.000Z

348

Application of Grossberg and Mingolla Neural Vision Model to Satellite Weather Imagery  

Science Journals Connector (OSTI)

Recent neural models of natural vision systems are defined in sufficiently concrete terms as to be immediately applicable to practical image processing tasks. In particular the Boundary Contour System and Feature...

Steve Lehar; Tim Howells; Ira Smotroff

1990-01-01T23:59:59.000Z

349

ARM - Measurement - Longwave broadband net irradiance  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Range Weather Forecasts Diagnostic Analyses ECMWF : European Centre for Medium Range Weather Forecasts Model Data GMS : Geostationary Meteorological Satellite GOES :...

350

Revised {open_quotes}LEPS{close_quotes} scores for assessing climate model simulations and long-range forecasts  

SciTech Connect (OSTI)

The most commonly used measures for verifying forecasts or simulations of continuous variables are root-mean-squared error (rmse) and anomaly correlation. Some disadvantages of these measures are demonstrated. Existing assessment systems for categorical forecasts are discussed briefly. An alternative unbiased verification measure is developed, known as the linear error in probability space (LEPS) score. The LEPS score may be used to assess forecasts of both continuous and categorical variables and has some advantages over rmse and anomaly correlation. The properties of the version of LEPS discussed here are reviewed and compared with an earlier form of LEPS. A skill-score version of LEPS may be used to obtain an overall measure of the skill of a number of forecasts. This skill score is biased, but the bias is negligible if the number of effectively independent forecasts or simulations is large. Some examples are given in which the LEPS skill score is compared with rmse and anomaly correlation. 14 refs., 10 figs., 7 tabs.

Potts, J.M. [IACR-Rothamsted, Hertfordshire (United Kingdom)] [IACR-Rothamsted, Hertfordshire (United Kingdom); Folland, C.K. [Hadley Centre for Climate Prediction and Research, Berkshire (United Kingdom)] [Hadley Centre for Climate Prediction and Research, Berkshire (United Kingdom); Jolliffe, I.T. [Univ. of Aberdeen (United Kingdom)] [and others] [Univ. of Aberdeen (United Kingdom); and others

1996-01-01T23:59:59.000Z

351

Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model  

Science Journals Connector (OSTI)

By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.

Duk Hee Lee; Sang Yong Park; Jong Chul Hong; Sang Jin Choi; Jong Wook Kim

2013-01-01T23:59:59.000Z

352

A hybrid FLANN and adaptive differential evolution model for forecasting of stock market indices  

Science Journals Connector (OSTI)

This paper presents a computationally efficient functional link artificial neural network CEFLANN based adaptive model for financial time series prediction of leading Indian stock market indices. Financial time-series data are usually non-stationary ... Keywords: Adaptive Differential Evolution Ade, Artificial Neural Network, Functional Link Neural Network Flann, Least Mean Squares Lms, Technical Indicators

Ajit Kumar Rout; Birendra Biswal; Pradipta Kishore Dash

2014-01-01T23:59:59.000Z

353

A warranty forecasting model based on piecewise statistical distributions and stochastic simulation  

E-Print Network [OSTI]

industry and has a specific application to automotive electronics. The warranty prediction model is based is demonstrated using a case study of automotive electronics warranty returns. The approach developed b CALCE Electronic Products and Systems Center, Department of Mechanical Engineering, University

Sandborn, Peter

354

Modeling Utility Load and Temperature Relationships for Use with Long-Lead Forecasts  

Science Journals Connector (OSTI)

Models relating system-wide average temperature to total system load were developed for the Virginia Power and Duke Power service areas in the southeastern United States. Daily data for the 198591 period were used. The influence of temperature ...

Peter J. Robinson

1997-05-01T23:59:59.000Z

355

WeatherSeptember2009,Vol.64,No.9 Can dispersion model predictions  

E-Print Network [OSTI]

into the atmosphere, with each particle representing a fixed mass of pollutant. Particles are transported due Office, Exeter 2 University of Reading Introduction In the case of a major pollution incident, terrorist attack, or a radioactive event such as the Chernobyl disaster in 1986, dispersion models are used

Dacre, Helen

356

Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines  

Science Journals Connector (OSTI)

Oil monitoring is an important and useful method for predicting wear failure, and has been used in diesel engines successfully. The diesel engine is the key power equipment in ships and it is a complicated tribological system with uncertainty and indetermination. Grey system theory is suitable for systems in which some information is clear and some is not, so it is feasible to study the wear process of diesel engines with this theory. The unequal interval revised grey model (UIRGM) (1,1) is presented in this paper, which is applicable to original series with unequal intervals and sharp variation. The model that is built is applied to fit and predict element concentration as determined by oil spectrometric analysis. It is proved that UIRGM (1,1) determines the exact turning point, and the fitting and prediction results are acceptable.

Hong Zhang; Zhuguo Li; Zhaoneng Chen

2003-01-01T23:59:59.000Z

357

AFFILIATIONS: HULTQUIST--NOAA/National Weather Service, Marquette, Michigan; DUTTER--NOAA/National Weather Service,  

E-Print Network [OSTI]

with modern numerical weather prediction models to provide detailed hindcasts of conditions throughoutAFFILIATIONS: HULTQUIST--NOAA/National Weather Service, Marquette, Michigan; DUTTER--NOAA/National Weather Service, Cleveland, Ohio; SCHWAB--NOAA/Great Lakes Environmental Research Laboratory, Ann Arbor

358

Predicting the microbial "weather" | Argonne National Laboratory  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

News News Press Releases Feature Stories In the News Experts Guide Media Contacts Social Media Photos Videos Fact Sheets, Brochures and Reports Summer Science Writing Internship Predicting the microbial "weather" By Louise Lerner * April 16, 2012 Tweet EmailPrint ARGONNE, Ill.-New computer models are letting scientists forecast changes in the population of microbes in the English Channel up to a week in advance. Environmental microbiologist Jack Gilbert of the U.S. Department of Energy's Argonne National Laboratory heads the Earth Microbiome Project, an initiative to sample and analyze DNA from bacteria, viruses, algae and fungi across the world. Our environment is full of microbes that affect everything from human health to climate change, and these microbes are

359

A Displacement-Based Error Measure Applied in a Regional Ensemble Forecasting System  

Science Journals Connector (OSTI)

Errors in regional forecasts often take the form of phase errors, where a forecasted weather system is displaced in space or time. For such errors, a direct measure of the displacement is likely to be more valuable than traditional measures. A ...

Christian Keil; George C. Craig

2007-09-01T23:59:59.000Z

360

American Solar Energy Society Proc. ASES Annual Conference, Raleigh, NC, EVALUATION OF NUMERICAL WEATHER PREDICTION  

E-Print Network [OSTI]

© American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, EVALUATION;© American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, irradiance forecasts over OF NUMERICAL WEATHER PREDICTION SOLAR IRRADIANCE FORECASTS IN THE US Richard Perez ASRC, Albany, NY, Perez

Perez, Richard R.

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Weatherization and Intergovernmental Activities  

Office of Energy Efficiency and Renewable Energy (EERE)

Weatherization and Intergovernmental Activities Annual Performance Results and Targets FY 2008 Congressional Budget

362

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

363

Weatherization and Intergovernmental Program: History of the Weatherization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

History History of the Weatherization Assistance Program to someone by E-mail Share Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on Facebook Tweet about Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on Twitter Bookmark Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on Google Bookmark Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on Delicious Rank Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on Digg Find More places to share Weatherization and Intergovernmental Program: History of the Weatherization Assistance Program on AddThis.com...

364

Forecasting wind speed financial return  

E-Print Network [OSTI]

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

365

A suite of metrics for assessing the performance of solar power forecasting  

Science Journals Connector (OSTI)

Abstract Forecasting solar energy generation is a challenging task because of the variety of solar power systems and weather regimes encountered. Inaccurate forecasts can result in substantial economic losses and power system reliability issues. One of the key challenges is the unavailability of a consistent and robust set of metrics to measure the accuracy of a solar forecast. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, and applications) that were developed as part of the U.S. Department of Energy SunShot Initiatives efforts to improve the accuracy of solar forecasting. In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design-of-experiments methodology in conjunction with response surface, sensitivity analysis, and nonparametric statistical testing methods. The three types of forecasting improvements are (i) uniform forecasting improvements when there is not a ramp, (ii) ramp forecasting magnitude improvements, and (iii) ramp forecasting threshold changes. Day-ahead and 1-hour-ahead forecasts for both simulated and actual solar power plants are analyzed. The results show that the proposed metrics can efficiently evaluate the quality of solar forecasts and assess the economic and reliability impacts of improved solar forecasting. Sensitivity analysis results show that (i) all proposed metrics are suitable to show the changes in the accuracy of solar forecasts with uniform forecasting improvements, and (ii) the metrics of skewness, kurtosis, and Rnyi entropy are specifically suitable to show the changes in the accuracy of solar forecasts with ramp forecasting improvements and a ramp forecasting threshold.

Jie Zhang; Anthony Florita; Bri-Mathias Hodge; Siyuan Lu; Hendrik F. Hamann; Venkat Banunarayanan; Anna M. Brockway

2015-01-01T23:59:59.000Z

366

Operational Forecasts of Cloud Cover and Water Vapour  

E-Print Network [OSTI]

of the forecast programme, which involved the additional use of 10.7 µm GOES-8 satellite data and surface weather cirrus cloud cover 15 5. A satellite-derived extinction parameter 17 5.1 Background 17 5.2 Previous work 20 5.3 Continued development of a satellite-derived 22 extinction parameter 6. Suggestions

367

Measuring forecast skill: is it real skill or  

E-Print Network [OSTI]

samples, then many verification metrics will credit a forecast with extra skill it doesn't deserve islands, zero meteorologists Imagine a planet with a global ocean and two isolated islands. Weather three metrics... (1) Brier Skill Score (2) Relative Operating Characteristic (3) Equitable Threat Score

Hamill, Tom

368

Satellite Data Assimilation in Numerical Weather Prediction Models. Part I: Forward Radiative Transfer and Jacobian Modeling in Cloudy Atmospheres  

Science Journals Connector (OSTI)

Satellite data assimilation requires rapid and accurate radiative transfer and radiance gradient models. For a vertically stratified scattering and emitting atmosphere, the vector discrete-ordinate radiative transfer model (VDISORT) was developed ...

Fuzhong Weng; Quanhua Liu

2003-11-01T23:59:59.000Z

369

A Web Service Model for Providing Weather Information through Sensor Networks Using a Fermat Point Based Data Forwarding Scheme  

Science Journals Connector (OSTI)

Web services providing weather information are not new. The existing web services working on this kind of fields can provide more prcised information if the concerned data is collected in a distributed fashion using a sensor network. Longer the lifetime of the sensor network longer is the service provided without interruption. In this paper we propose a web service for providing weather information with a sensor network as the backbone. We have used a Fermat point based forwarding technique to minimize the energy consumption of the sensor network which eventually helps the web service work in an uninterrupted fashion for a longer duration as the life time of the network has prolonged.

2010-01-01T23:59:59.000Z

370

Modeling for Tsunami Forecast  

E-Print Network [OSTI]

, accuracy, special operating environment needs, ease-of-use, and documentation #12;December 26, 2004 Sumatra

371

On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model  

SciTech Connect (OSTI)

This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

2010-01-01T23:59:59.000Z

372

Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)  

SciTech Connect (OSTI)

A model evaluation approach is proposed where weather and climate prediction models are analyzed along a Pacific Ocean cross-section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade-winds, to the deep convection regions of the ITCZ: the GCSS/WGNE Pacific Cross-section Intercomparison (GPCI). The main goal of GPCI is to evaluate, and help understand and improve the representation of tropical and sub-tropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross-section from the sub-tropics to the tropics for the season JJA of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the ECMWF Re-Analysis (ERA40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical crosssections of cloud properties (in particular), vertical velocity and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA40 in the stratocumulus regions (as compared to ISCCP) is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade-wind Lagrangian trajectory. Histograms of cloud cover along the cross-section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, Jason N.; DelGenio, Anthony D.; DeMott, C.; Franklin, A.; Hannay, Cecile; Jakob, Christian; Jiao, Y.; Karlsson, J.; Kitagawa, H.; Koehler, M.; Kuwano-Yoshida, A.; LeDrian, C.; Lock, Adrian; Miller, M.; Marquet, P.; Martins, J.; Mechoso, C. R.; Meijgaard, E. V.; Meinke, I.; Miranda, P.; Mironov, D.; Neggers, Roel; Pan, H. L.; Randall, David A.; Rasch, Philip J.; Rockel, B.; Rossow, William B.; Ritter, B.; Siebesma, A. P.; Soares, P.; Turk, F. J.; Vaillancourt, P.; Von Engeln, A.; Zhao, M.

2011-11-01T23:59:59.000Z

373

Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy  

Science Journals Connector (OSTI)

Abstract Buildings are the dominant source of energy consumption and environmental emissions in urban areas. Therefore, the ability to forecast and characterize building energy consumption is vital to implementing urban energy management and efficiency initiatives required to curb emissions. Advances in smart metering technology have enabled researchers to develop sensor based approaches to forecast building energy consumption that necessitate less input data than traditional methods. Sensor-based forecasting utilizes machine learning techniques to infer the complex relationships between consumption and influencing variables (e.g., weather, time of day, previous consumption). While sensor-based forecasting has been studied extensively for commercial buildings, there is a paucity of research applying this data-driven approach to the multi-family residential sector. In this paper, we build a sensor-based forecasting model using Support Vector Regression (SVR), a commonly used machine learning technique, and apply it to an empirical data-set from a multi-family residential building in New York City. We expand our study to examine the impact of temporal (i.e., daily, hourly, 10min intervals) and spatial (i.e., whole building, by floor, by unit) granularity have on the predictive power of our single-step model. Results indicate that sensor based forecasting models can be extended to multi-family residential buildings and that the optimal monitoring granularity occurs at the by floor level in hourly intervals. In addition to implications for the development of residential energy forecasting models, our results have practical significance for the deployment and installation of advanced smart metering devices. Ultimately, accurate and cost effective wide-scale energy prediction is a vital step towards next-generation energy efficiency initiatives, which will require not only consideration of the methods, but the scales for which data can be distilled into meaningful information.

Rishee K. Jain; Kevin M. Smith; Patricia J. Culligan; John E. Taylor

2014-01-01T23:59:59.000Z

374

Constructing Ionospheric Irregularity Threat Model for Korean SBAS  

E-Print Network [OSTI]

GNSS augmentation system and space weather forecasting for GNSS application. Jiyun Lee is an Assistant metrics which measure the density and uniformity of IPP distribution in a region. Thus, the threat model metrics, which characterize threatening undersampled geometries including the density of IPP distribution

Stanford University

375

Forecasting energy markets using support vector machines  

Science Journals Connector (OSTI)

Abstract In this paper we investigate the efficiency of a support vector machine (SVM)-based forecasting model for the next-day directional change of electricity prices. We first adjust the best autoregressive SVM model and then we enhance it with various related variables. The system is tested on the daily Phelix index of the German and Austrian control area of the European Energy Exchange (???) wholesale electricity market. The forecast accuracy we achieved is 76.12% over a 200day period.

Theophilos Papadimitriou; Periklis Gogas; Efthimios Stathakis

2014-01-01T23:59:59.000Z

376

Solar forecasting review  

E-Print Network [OSTI]

numerical weather predictions as well as satellite xv andweather analyses. Accordingly interest shifted from PLEO to GSO satellites.

Inman, Richard Headen

2012-01-01T23:59:59.000Z

377

Connecticut: Bridgeport Multifamily Weatherization  

Office of Energy Efficiency and Renewable Energy (EERE)

A multifamily facility in Bridgeport that provides safe housing for individuals, veterans and the homeless, received weatherization services with funding from EERE's Weatherization Assistance Program, estimated to save nearly $7,000 in energy costs annually.

378

6961 weather resistance [n  

Science Journals Connector (OSTI)

constr. (Property of materials which are unaffected by the deteriorating effects of weather, including rain, sun, frost, etc.; in U.S., w. r., rather than weather proofing, is a term used to prot...

2010-01-01T23:59:59.000Z

379

WEATHER HAZARDS Basic Climatology  

E-Print Network [OSTI]

) Wildfires (Jun 02) Recent Declared Disasters in Colorado No Map from FEMA provided #12;National WeatherWEATHER HAZARDS Basic Climatology Colorado Climate Center Funding provided by NOAA Sectoral

380

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Weatherization Assistance Program  

Broader source: Energy.gov [DOE]

This fact sheet provides an overview of the U.S. Department of Energys Weatherization Assistance Program.

382

Weather Data Gamification  

E-Print Network [OSTI]

. With the huge amount of weather data available, we have designed and developed a fantasy weather game. People manage a team of cities with the goal of predicting weather better than other players in their league, and in the process gain an understanding...

Gargate, Rohit

2013-07-25T23:59:59.000Z

383

Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email List Self Supplied Balancing Reserves Dynamic...

384

Solar forecasting review  

E-Print Network [OSTI]

2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

Inman, Richard Headen

2012-01-01T23:59:59.000Z

385

Wind Power Forecasting  

Science Journals Connector (OSTI)

The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble...

Sue Ellen Haupt; William P. Mahoney; Keith Parks

2014-01-01T23:59:59.000Z

386

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

387

Quantifying Uncertainty for Climate Change and Long-Range Forecasting Scenarios with Model Errors. Part I: Gaussian Models  

E-Print Network [OSTI]

of a turbulent tracer with a mean gradient with the background turbulent field velocity generated by the first. An important feature of all the current computer Atmosphere Ocean Science (AOS) models (Neelin et al. 2006 or the limitations of computing power with the necessary parameterization of subgrid processes. Examples of important

Majda, Andrew J.

388

Multigrid methods for improving the variational data assimilation in numerical weather prediction  

E-Print Network [OSTI]

conditions are needed to solve numerical weather prediction models: initial condition and boundary conditionMultigrid methods for improving the variational data assimilation in numerical weather prediction: numerical weather prediction, variational data assimilation, minimization procedure, multigrid methods, cell

Kwak, Do Young

389

Improving Inventory Control Using Forecasting  

E-Print Network [OSTI]

This project studied and analyzed Electronic Controls, Inc.s forecasting process for three high-demand products. In addition, alternative forecasting methods were developed to compare to the current forecast method. The ...

Balandran, Juan

2005-12-16T23:59:59.000Z

390

GPU Acceleration of Numerical Weather John Michalakes  

E-Print Network [OSTI]

GPU Acceleration of Numerical Weather Prediction John Michalakes National Center for Atmospheric parallelism will prove ineffective for many scenarios. We present an alternative method of scaling model Exponentially increasing processor power has fueled fifty years of continuous improvement in weather and climate

Colorado at Boulder, University of

391

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

392

Q. J. R. Meteorol. Soc. (2006), 132, pp. 29052923 doi: 10.1256/qj.06.25 Measuring forecast skill: is it real skill or is it the varying climatology?  

E-Print Network [OSTI]

that many commonly used systems of measurement (`metrics') in weather forecast verification are capable of weather forecasts from an accumulation of samples spanning many locations and dates. In calculating many is approximately invariant over all samples. If the event frequency actually varies among the samples, the metrics

Hamill, Tom

393

Technology Forecasting Scenario Development  

E-Print Network [OSTI]

Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

394

CAPP 2010 Forecast.indd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecast, Markets & Pipelines 1 Crude Oil Forecast, Markets & Pipelines June 2010 2 CANADIAN ASSOCIATION OF PETROLEUM PRODUCERS Disclaimer: This publication was prepared by the...

395

Weather-based yield forecasts developed for 12 California crops  

E-Print Network [OSTI]

Climate Change Center at the Scripps Institution of Oceanography (M. Tyree, staff scientist, personal communication).

Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

2006-01-01T23:59:59.000Z

396

Theoretical Impact Assessment of Satellite Data on Weather Forecasts  

Science Journals Connector (OSTI)

The global meteorological observing system is extremely expensive and in the present economical situation some conventional observations such as radiosondes begin to be severely reduced. At the same time improved...

O. M. Pokrovsky

2003-01-01T23:59:59.000Z

397

Weather Forecasting using GPU-based Large-Eddy Simulations  

Science Journals Connector (OSTI)

Since the advent of computers midway through the 20th century, computational resources have increased exponentially. It is likely they will continue to do so, especially when accounting for recent trends in multi-core processors. History has shown that ...

Jerme Schalkwijk; Harmen J.J. Jonker; A. Pier Siebesma; Erik van Meijgaard

398

TESLA: Taylor Expanded Solar Analog Forecasting Bengu Ozge Akyurek, Alper Sinan Akyurek, Jan Kleissl and Tajana Simunic Rosing  

E-Print Network [OSTI]

TESLA: Taylor Expanded Solar Analog Forecasting Bengu Ozge Akyurek, Alper Sinan Akyurek, Jan- ergy resources within the Smart Grid, solar forecasting has become an important problem for hour]. It is difficult to obtain an accurate result from the weather and solar predictions. Accurate fore- casting

Simunic, Tajana

399

Atmos Energy - Natural Gas and Weatherization Efficiency Program |  

Broader source: Energy.gov (indexed) [DOE]

Atmos Energy - Natural Gas and Weatherization Efficiency Program Atmos Energy - Natural Gas and Weatherization Efficiency Program Atmos Energy - Natural Gas and Weatherization Efficiency Program < Back Eligibility Low-Income Residential Residential Savings Category Heating & Cooling Commercial Heating & Cooling Heating Home Weatherization Sealing Your Home Construction Commercial Weatherization Design & Remodeling Ventilation Appliances & Electronics Water Heating Windows, Doors, & Skylights Program Info State Kentucky Program Type Utility Rebate Program Rebate Amount Forced Air Furnace: $250 - $400 Boiler: $250 High Efficiency Tank Water Heater: $200 - $300 Tankless Model: $400 Programmable Thermostat: $25 Weatherization Assistance: Up to $3,000 Provider Atmos Energy Kentucky Rebate Offer Atmos Energy provides rebates to residential and commercial for natural gas

400

July08.pdf  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

data will significantly improve weather forecasting by direct integration into numerical weather prediction models used to compute weather forecasts. For more information, visit...

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Intercomparison of Bulk Microphysics Schemes in Model Simulations of Polar Lows  

Science Journals Connector (OSTI)

Four spiraliform polar lows, two over the Sea of Japan and two over the Nordic Seas, were simulated with the Weather Research and Forecasting (WRF) model. Five mixed-phase bulk microphysics schemes (BMS) provided with WRF were run respectively in ...

Longtao Wu; Grant W. Petty

2010-06-01T23:59:59.000Z

402

Modelled and observed variability of the atmospheric circulation the Peruvian Current System: 2000-2005  

E-Print Network [OSTI]

on the characteristics of the local equatorward atmospheric circulation. Resolving the mesoscale variability of the heat Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) that were run over the Peruvian Current System (PCS) [0N-19°S; 83°W-68°W] from November 2000- October 2005. Wind data as derived from

403

Block-structured adaptive meshes and reduced grids for atmospheric general circulation models  

Science Journals Connector (OSTI)

...grids are widely used for local weather predictions and...Research Forecasting Model WRF (Skamarock et al...small time steps if high wind speeds are present in...m and (c) meridional wind v (m1) at day 10 (McDonald...the advanced research WRF Version 2National Center...

2009-01-01T23:59:59.000Z

404

Calculation of the far range atmospheric transport of radionuclides after the Fukushima accident with the atmospheric dispersion model MATCH of the JRODOS system  

Science Journals Connector (OSTI)

The paper presents estimates of the far-range atmospheric dispersion of radionuclides after the accident at Fukushima Daiichi Nuclear Power Plant (NPP), obtained using the long-range atmospheric dispersion model MATCH. Software tools were developed to run MATCH in the EU nuclear emergency response system JRODOS using freely available numerical weather prediction (NWP) data of the Global Forecasting System (GFS) operated by the United States National Center of Environmental Prediction (NCEP). Comparisons are made of results with JRODOS/MATCH and a standalone MATCH operated by Swedish Meteorological and Hydrological Institute (SMHI) driven by the European Center for Medium-Range Weather Forecasts (ECMWF) NWP data.

Ivan V. Kovalets; Lennart Robertson; Christer Persson; Svitlana N. Didkivska; Ievgen A. Ievdin; Dmytro Trybushnyi

2014-01-01T23:59:59.000Z

405

Weather Charts - Hanford Site  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

406

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology  

E-Print Network [OSTI]

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau Ensemble Initialisation Scheme (breeding) Lack of common metrics We use weekly-mean rainfall* / max experimental forecasts (poama.bom.gov.au) #12;The Centre for Australian Weather and Climate Research

Marshall, Andrew

407

A robust automatic phase-adjustment method for financial forecasting  

Science Journals Connector (OSTI)

In this work we present the robust automatic phase-adjustment (RAA) method to overcome the random walk dilemma for financial time series forecasting. It consists of a hybrid model composed of a qubit multilayer perceptron (QuMLP) with a quantum-inspired ... Keywords: Financial forecasting, Hybrid models, Quantum-inspired evolutionary algorithm, Qubit multilayer perceptron, Random walk dilemma

Ricardo de A. Arajo

2012-03-01T23:59:59.000Z

408

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

409

The Weatherization Training program at Pennsylvania College  

ScienceCinema (OSTI)

A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia;

2013-05-29T23:59:59.000Z

410

The Weatherization Training program at Pennsylvania College  

SciTech Connect (OSTI)

A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia

2010-01-01T23:59:59.000Z

411

Distributed Numerical Weather Prediction via Satellite  

Science Journals Connector (OSTI)

This paper describes a recent undertaking in distributed numerical weather prediction via high data rate networks. The governing project involved the operation of a coupled mesoscale modeling system on widely separated supercomputers, and ...

Jordan G. Powers; Mark T. Stoelinga; William S. Boyd

1997-12-01T23:59:59.000Z

412

Weatherization and Intergovernmental Program: About  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

About About Site Map Printable Version Share this resource Send a link to Weatherization and Intergovernmental Program: About to someone by E-mail Share Weatherization and Intergovernmental Program: About on Facebook Tweet about Weatherization and Intergovernmental Program: About on Twitter Bookmark Weatherization and Intergovernmental Program: About on Google Bookmark Weatherization and Intergovernmental Program: About on Delicious Rank Weatherization and Intergovernmental Program: About on Digg Find More places to share Weatherization and Intergovernmental Program: About on AddThis.com... Plans, Implementation, & Results Weatherization Assistance Program WAP - Sustainable Energy Resources for Consumers Grants WAP - Weatherization Innovation Pilot Program State Energy Program

413

Valuing Climate Forecast Information  

Science Journals Connector (OSTI)

The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...

Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon

1987-09-01T23:59:59.000Z

414

Comparing Forecast Skill  

Science Journals Connector (OSTI)

A basic question in forecasting is whether one prediction system is more skillful than another. Some commonly used statistical significance tests cannot answer this question correctly if the skills are computed on a common period or using a common ...

Timothy DelSole; Michael K. Tippett

2014-12-01T23:59:59.000Z

415

A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting  

Science Journals Connector (OSTI)

In existing researches, the investigations of oil price volatility are always performed based on daily data and squared daily return is always taken as the proxy of actual volatility. However, it is widely accepted that the popular realized volatility (RV) based on high frequency data is a more robust measure of actual volatility than squared return. Due to this motivation, we investigate dynamics of daily volatility of Shanghai fuel oil futures prices employing 5-minute high frequency data. First, using a nonparametric method, we find that RV displays strong long-range dependence and recent financial crisis can cause a lower degree of long-range dependence. Second, we model daily volatility using RV models and GARCH-class models. Our results indicate that RV models for intraday data overwhelmingly outperform GARCH-class models for daily data in forecasting fuel oil price volatility, regardless the proxy of actual volatility. Finally, we investigate the major source of such volatile prices and found that trader activity has major contribution to fierce variations of fuel oil prices.

Li Liu; Jieqiu Wan

2012-01-01T23:59:59.000Z

416

Forecast of Advanced Technology for Coal Power Generation Towards the Year of 2050 in CO2 Reduction Model of Japan  

Science Journals Connector (OSTI)

Abstract In the fossil fuel, coal is enough to get easily because it has supply and price stability brought about its ubiquitously. Coal is used for power generation as the major fuel in the world. However it is true that control of global warming should be applied to coal power generations. Therefore, many people expect CO2 reduction by technical innovation such as efficiency improvement, Carbon dioxide Capture and Storage (CCS). In case of coal power plant are considered for improving efficiency. Some of them have already put into commercial operation but others are still under R&D stage. Especially, the technical development prospect of the power plant is very important for planning the energy strategy in the resource-importing country. Japan Coal Energy Center (JCOAL) constructed a program to forecast the share of advanced coal fired plants/natural gas power plants towards the year of 2050. Then, we simulated the future prediction about 2 cases (the Japanese scenario and the world scenario). The fuel price and the existence of CCS were considered in the forecast of the technical development of the thermal power generation. Especially in the Japanese scenario, we considered the CO2 reduction target which is 80% reduction in 1990. In the world scenario, coal price had almost no influence on the share of coal fired plant. However, when the gas price increased 1.5% or more, the share of coal fired plant increased. In that case, CO2 emissions increased because coal-fired plant increased. Compared with both cases, the amount of CO2 in 2050 without CCS case was 50% higher than that of with CCS case. In Japanese scenario, achievement of 80% CO2 reduction target is impossible without CCS. If CCS is introduced into all the new establishment coal fired plant, CO2 reduction target can be attained. In the Japanese scenario, the gas price more expensive than a coal price so that the amount of the coal fired plant does not decline. Since the reduction of the amount of CO2 will be needed in all over the world, introductory promotion and technical development of CCS are very important not only Japan but also all over the world.

Takashi Nakamura; Keiji Makino; Kunihiko Shibata; Michiaki Harada

2013-01-01T23:59:59.000Z

417

Weatherization and minority energy use: A preliminary analysis  

SciTech Connect (OSTI)

This paper presents an analysis of the patterns of minority and non-minority energy consumption with and without weatherization measures. The behavior of the household in response to a weatherization-induced income gain is modeled using ANL`s Minority Economic Assessment Model (MEAM). Weatherization is then examined from a programmatic perspective in light of the MEAM findings. This work is the first part of a larger analysis to assess the economic impact of weatherization on minority households and to examine the reallocation of LIHEAP funds to weatherization. Several limitations of this analysis are discussed.

Earl, E.V.; Collins, N.E.

1992-06-01T23:59:59.000Z

418

Weatherization and minority energy use: A preliminary analysis  

SciTech Connect (OSTI)

This paper presents an analysis of the patterns of minority and non-minority energy consumption with and without weatherization measures. The behavior of the household in response to a weatherization-induced income gain is modeled using ANL's Minority Economic Assessment Model (MEAM). Weatherization is then examined from a programmatic perspective in light of the MEAM findings. This work is the first part of a larger analysis to assess the economic impact of weatherization on minority households and to examine the reallocation of LIHEAP funds to weatherization. Several limitations of this analysis are discussed.

Earl, E.V.; Collins, N.E.

1992-01-01T23:59:59.000Z

419

Paintball Summer Weather  

E-Print Network [OSTI]

Highlights · Paintball · Summer Weather · Birthdays · Manners TheELIWeekly Paintball! Come out France Iraq Japan Korea Kuwait Libya Netherlands Niger Peru Qatar Saudi Arabia Spain Taiwan Thailand Turkey United States Venezuela Summer Weather Safety We've come to realize in the past that not all

Pilyugin, Sergei S.

420

HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL  

SciTech Connect (OSTI)

The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

2011-05-10T23:59:59.000Z

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

weather | OpenEI  

Open Energy Info (EERE)

weather weather Dataset Summary Description A csv containing hourly weather data at NREL's Research and Support Facility (RSF) for 2011. Source NREL Date Released February 07th, 2013 (10 months ago) Date Updated Unknown Keywords 2011 data NREL RSF weather Data text/csv icon rsf_weather_data_2011.csv (csv, 851.2 KiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Time Period License License Open Data Commons Attribution License Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote Ease of access Average vote Your vote Overall rating Average vote Your vote Comments Login or register to post comments If you rate this dataset, your published comment will include your rating.

422

Weatherized in January  

Broader source: Energy.gov (indexed) [DOE]

**Number of Homes **Number of Homes Weatherized in January 2011 (Recovery Act) Total Number of Homes Weatherized through January 2011 (Recovery Act) ***Total Number of Homes Weatherized through January 2011 Calendar Year 2009 - January 2011 (Recovery Act + Annual Program Funding) U.S. Department of Energy Weatherization Assistance Program Homes Weatherized By Grantee in January 2011 (Calendar Year) (Recovery Act) (Recovery Act Annual Program Funding) Alabama 323 4,036 4,780 1 Alaska 21 231 1,850 Arizona 289 4,000 5,187 Arkansas 179 3,545 5,263 California 1,469 24,620 28,197 Colorado 401 7,188 12,926 Connecticut 530 3,689 4,758 2 2 Delaware 519 689 District of Columbia 30 661 972 Florida 799 8,895 9,971 Georgia 526 7,718 8,476 Hawaii 13 419 774 Idaho 244 3,996 5,963 Illinois

423

NEWTON's Weather Archive  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Weather Archive: Weather Archive: Loading Most Recent Weather Questions: Acid Rain and Evaporation Effects Ground Temperature for Snow to 'Stick' Clouds and Time of Day Chart Scales on Vertical Velocity Chart Aneroid Barometers: Aircraft; Meteorology Air and Saturation Pressure Tornado Size and Vortex Spin Rate Polar Air Pressure Coldest Temperature in Atmosphere; Elevation Snow Clump Formation Relative Humidity, Temperature, Amount of Water Polar Weather Systems Bergeron Process Cloud Formation and Time of Day Hailstone Shape Threshold Values for Classifying Pressure Systems Rain Shadow Range Cloud Suspension Measuring Rainfall Why Does It Rain? Measuring Rainfall Dew Point and Dogs Size of Cloud from Shadow What is dBZ in Meteorology? Daily Temperature Lag To see all entries in the Weather

424

What is Weatherization | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

What is Weatherization Weatherization as defined by the Weatherization Assistance Program (WAP) differs in many ways from what is commonly called "weatherizing your...

425

Impact of Infrared, Microwave, and Radio Occultation Satellite Observations on Operational Numerical Weather Prediction  

Science Journals Connector (OSTI)

A comparison of the impact of infrared (IR), microwave (MW), and radio occultation (RO) observations on NCEPs operational global forecast model over the month of March 2013 is presented. Analyses and forecasts with only IR, MW, and RO ...

L. Cucurull; R. A. Anthes

2014-11-01T23:59:59.000Z

426

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

Piwko, 2010: Western wind and solar integration study. NRELsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

427

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

and appropriately dispatch load-following power plants. Whenrequirements. Overall, load-following capacity requirementsto determine scheduling for load-following power plants and

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

428

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

fluctuations in renewable energy production (such as when aof renewable resources into the energy production portfolioof renewable energy are implemented, energy production is

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

429

BUILDING A STOCHASTIC TERMINAL AIRSPACE CAPACITY FORECAST FROM CONVECTIVE WEATHER FORECASTS  

E-Print Network [OSTI]

open from the east into Boston Logan Airport at 5PM, or if flights should incur delay on the ground International Airport (ATL) termi- nal a that there is a 30% chance of rain in Boston today, for instance, does not help to determine if there will be a route

Gummadi, Ramakrishna

430

Do quantitative decadal forecasts from GCMs provide  

E-Print Network [OSTI]

' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

Stevenson, Paul

431

Plan for the Joint Ensemble Forecast System (JEFS)  

E-Print Network [OSTI]

(in coordination) Maj F. Anthony Eckel, PhD Chief, Air and Space Models Branch HQ Air Force Weather................................................................................................................................. 11 Products..................................................................................................................................... 13 Phase I Products

Mass, Clifford F.

432

Reforecasts: An Important Dataset for Improving Weather Predictions  

Science Journals Connector (OSTI)

A reforecast (retrospective forecast) dataset has been developed. This dataset is comprised of a 15-member ensemble run out to a 2-week lead. Forecasts have been run every day from 0000 UTC initial conditions from 1979 to the present. The model ...

Thomas M. Hamill; Jeffrey S. Whitaker; Steven L. Mullen

2006-01-01T23:59:59.000Z

433

Weatherizing Wilkes-Barre  

ScienceCinema (OSTI)

Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

Calore, Joe

2013-05-29T23:59:59.000Z

434

Initial conditions estimation for improving forecast accuracy in exponential smoothing  

Science Journals Connector (OSTI)

In this paper we analyze the importance of initial conditions in exponential smoothing models on forecast errors and prediction intervals. We work with certain exponential smoothing models, namely Holts additive...

E. Vercher; A. Corbern-Vallet; J. V. Segura; J. D. Bermdez

2012-07-01T23:59:59.000Z

435

Wind Speed Forecasting Using a Hybrid Neural-Evolutive Approach  

Science Journals Connector (OSTI)

The design of models for time series prediction has found a solid foundation on statistics. Recently, artificial neural networks have been a good choice as approximators to model and forecast time series. Designing a neural network that provides a good ...

Juan J. Flores; Roberto Loaeza; Hctor Rodrguez; Erasmo Cadenas

2009-11-01T23:59:59.000Z

436

Neighborhood Weatherization, Houston  

E-Print Network [OSTI]

with industry groups 5. Referrals http://www.click2houston.com/video/24501979/index.html 2010 CLEAResult. All rights reserved. Milestone Celebration 2010 CLEAResult. All rights reserved. 10,000 Homes Weatherized 2010 CLEAResult. All rights... with industry groups 5. Referrals http://www.click2houston.com/video/24501979/index.html 2010 CLEAResult. All rights reserved. Milestone Celebration 2010 CLEAResult. All rights reserved. 10,000 Homes Weatherized 2010 CLEAResult. All rights...

Fowler, M.

2011-01-01T23:59:59.000Z

437

Weatherization Assistance Program  

Broader source: Energy.gov [DOE]

The U.S. Department of Energy (DOE) Weatherization Assistance Program provides grants to states, territories, and some Indian tribes to improve the energy efficiency of the homes of low-income families. These governments, in turn, contract with local governments and nonprofit agencies to provide weatherization services to those in need using the latest technologies for home energy upgrades. Since the program began in 1976, DOE has helped improve the lives of than 7 million families by reducing their energy bills.

438

An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1  

E-Print Network [OSTI]

into the numerical weather prediction model COSMO, BorealCurrent numerical weather prediction (NWP) models, regionalof lakes in numerical weather prediction and climate models:

Subin, Z.M.

2013-01-01T23:59:59.000Z

439

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012  

E-Print Network [OSTI]

there is significant uncertainty in its future intensity, the current forecast is for a slowly strengthening TC which, 3) forecast output from global models, 4) the current and projected state of the Madden with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all

Gray, William

440

Ensemble-based air quality forecasts: A multimodel approach applied to ozone  

E-Print Network [OSTI]

Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1., and B. Sportisse (2006), Ensemble-based air quality forecasts: A multimodel approach applied to ozone, J, the uncertainty in chem- istry transport models is a major limitation of air quality forecasting. The source

Boyer, Edmond

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Consensus Coal Production Forecast for  

E-Print Network [OSTI]

Rate Forecasts 19 5. EIA Forecast: Regional Coal Production 22 6. Wood Mackenzie Forecast: W.V. Steam to data currently published by the Energy Information Administration (EIA), coal production in the state in this report calls for state production to decline by 11.3 percent in 2009 to 140.2 million tons. During

Mohaghegh, Shahab

442

False Alarms and Close Calls: A Conceptual Model of Warning Accuracy LINDSEY R. BARNES*  

E-Print Network [OSTI]

of the key metrics for verifying National Weather Service (NWS) weather warnings. The national FAR, Health, & Hazards Center, Colorado Springs, Colorado Submitted to Weather and Forecasting Forecasters. In addition, we argue that the metrics used to evaluate false alarms do not accurately represent the numbers

Schultz, David

443

Improving the forecasting function for a Credit Hire operator in the UK  

Science Journals Connector (OSTI)

This study aims to test on the predictability of Credit Hire services for the automobile and insurance industry. A relatively sophisticated time series forecasting procedure, which conducts a competition among exponential smoothing models, is employed to forecast demand for a leading UK Credit Hire operator (CHO). The generated forecasts are compared against the Naive method, resulting that demand for CHO services is indeed extremely hard to forecast, as the underlying variable is the number of road accidents a truly stochastic variable.

Nicolas D. Savio; K. Nikolopoulos; Konstantinos Bozos

2009-01-01T23:59:59.000Z

444

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

445

The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models  

SciTech Connect (OSTI)

The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratio of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (~;;25percent total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator.

Zhou, Shujia; Duffy, Daniel; Clune, Thomas; Suarez, Max; Williams, Samuel; Halem, Milton

2009-01-10T23:59:59.000Z

446

On Sequential Probability Forecasting  

E-Print Network [OSTI]

at the same time. [Probability, Statistics and Truth, MacMillan 1957. page 11] ... the collective "denotes a collective wherein the attribute of the single event is the number of points thrown. [Probability, StatisticsOn Sequential Probability Forecasting David A. Bessler 1 David A. Bessler Texas A&M University

McCarl, Bruce A.

447

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

448

Storm-in-a-Box Forecasting  

Science Journals Connector (OSTI)

...But the WRF has no immediate...being tuned to local conditions...temperatures and winds with altitude...resulting WRF forecasts...captured the local sea-breeze winds better...spread the local operation of mesoscale...to be the WRF model now...

Richard A. Kerr

2004-05-14T23:59:59.000Z

449

Weatherization Training for South Carolina's Muggy Weather | Department of  

Broader source: Energy.gov (indexed) [DOE]

Weatherization Training for South Carolina's Muggy Weather Weatherization Training for South Carolina's Muggy Weather Weatherization Training for South Carolina's Muggy Weather June 22, 2010 - 3:46pm Addthis Trident Technical College in Charleston, SC., has added another sustainability component to its curriculum: weatherization. A program already filled with renewable energy courses, TTC Green, now offers training and certification for technicians. This training, available for anyone from novices to the experienced, teaches how to weatherize the diverse array of homes in the muggy Charleston area to be more energy efficient. Two of the school's continuing education courses, both under three weeks in length, offer certification to individuals with weatherization backgrounds, giving them additional credentials and skills in the industry. TTC Green

450

Can agent-based models forecast spot prices in electricity markets? Evidence from the New Zealand electricity market  

Science Journals Connector (OSTI)

Abstract Modelling price formation in electricity markets is a notoriously difficult process, due to physical constraints on electricity generation and transmission, and the potential for market power. This difficulty has inspired the recent development of bottom-up agent-based algorithmic learning models of electricity markets. While these have proven quite successful in small models, few authors have attempted any validation of their model against real-world data in a more realistic model. In this paper we develop the SWEM model, where we take one of the most promising algorithms from the literature, a modified version of the Roth and Erev algorithm, and apply it to a 19-node simplification of the New Zealand electricity market. Once key variables such as water storage are accounted for, we show that our model can closely mimic short-run (weekly) electricity prices at these 19 nodes, given fundamental inputs such as fuel costs, network data, and demand. We show that agents in SWEM are able to manipulate market power when a line outage makes them an effective monopolist in the market. SWEM has already been applied to a wide variety of policy applications in the New Zealand market.22 This research was partly funded by a University of Auckland FDRF Grant #9554/3627082. The authors would like thank Andy Philpott, Golbon Zakeri, Anthony Downward, an anonymous referee, and participants at the EPOC Winter Workshop 2010 for their helpful comments.

David Young; Stephen Poletti; Oliver Browne

2014-01-01T23:59:59.000Z

451

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

452

GatorWeather: Student Production of Television/Online Video Eric Gose, San Francisco State University, San Francisco, CA; and E.  

E-Print Network [OSTI]

GatorWeather: Student Production of Television/Online Video Forecasts Eric Gose, San Francisco, students of the meteorology program who were interested in practicing on-air techniques created "Gator Weather". The term "Gator" comes from the fact that the San Francisco State mascot is an alligator (GATOR

453

Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe  

Science Journals Connector (OSTI)

Snow cover has a strong effect on the surface and lower atmosphere in NWP models. Because the progress of in situ observations has stalled, satellite-based snow analyses are becoming increasingly important. Currently, there exist several products ...

Otto Hyvrinen; Kalle Eerola; Niilo Siljamo; Jarkko Koskinen

2009-06-01T23:59:59.000Z

454

Cold Weather Hazards  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

0 0 Cold Weather Hazards June 2010 NSA_cwh_Rev10.doc 1 Atmospheric Radiation Measurement Climate Research Facility/ North Slope of Alaska/Adjacent Arctic Ocean (ACRF/NSA/AAO) Cold Weather Hazards Winter Conditions at the North Slope of Alaska The North Slope of Alaska is north of the Arctic Circle at latitudes ranging from 69 to 72 degrees. Barrow, the largest town on the North Slope (pop. 4500), is the site of a National Weather Service Station, which has been active for several decades, so the climatology of the Alaska arctic coastal region as represented by Barrow is relatively well known. The North Slope is covered with ice and snow typically eight months of the year (October-May). During part of November, all of December, and most of January, the sun does not come above the horizon; this

455

A Bayesian approach to forecast intermittent demand for seasonal products  

Science Journals Connector (OSTI)

This paper investigates the forecasting of a large fluctuating seasonal demand prior to peak sale season using a practical time series, collected from the US Census Bureau. Due to the extreme natural events (e.g. excessive snow fall and calamities), sales may not occur, inventory may not replenish and demand may set off unrecorded during the peak sale season. This characterises a seasonal time series to an intermittent category. A seasonal autoregressive integrated moving average (SARIMA), a multiplicative exponential smoothing (M-ES) and an effective modelling approach using Bayesian computational process are analysed in the context of seasonal and intermittent forecast. Several forecast error indicators and a cost factor are used to compare the models. In cost factor analysis, cost is measured optimally using dynamic programming model under periodic review policy. Experimental results demonstrate that Bayesian model performance is much superior to SARIMA and M-ES models, and efficient to forecast seasonal and intermittent demand.

Mohammad Anwar Rahman; Bhaba R. Sarker

2012-01-01T23:59:59.000Z

456

Weatherization and Intergovernmental Program: News  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

News News Site Map Printable Version Share this resource Send a link to Weatherization and Intergovernmental Program: News to someone by E-mail Share Weatherization and Intergovernmental Program: News on Facebook Tweet about Weatherization and Intergovernmental Program: News on Twitter Bookmark Weatherization and Intergovernmental Program: News on Google Bookmark Weatherization and Intergovernmental Program: News on Delicious Rank Weatherization and Intergovernmental Program: News on Digg Find More places to share Weatherization and Intergovernmental Program: News on AddThis.com... News December 9, 2013 Improving Energy Efficiency and Creating Jobs Through Weatherization Since 2009, when the Energy Department seized a major opportunity to invest $5 billion through our Weatherization Assistance Program (WAP) to stimulate

457

Coal production forecast and low carbon policies in China  

Science Journals Connector (OSTI)

With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production.

Jianzhou Wang; Yao Dong; Jie Wu; Ren Mu; He Jiang

2011-01-01T23:59:59.000Z

458

Reconstruction and forecast experiments of a statistical-dynamical model of the Western Pacific subtropical high and Eastern Asian summer monsoon factors  

Science Journals Connector (OSTI)

Abnormal activity of the Western Pacific Subtropical High (WPSH) may result in extreme weather events in East Asia. However, because the relationship between the WPSH and other components of the East Asian Summer Monsoon (EASM) system is unknown, ...

Mei Hong; Dong Wang; Ren Zhang; Xi Chen; Jing-Jing Ge; Dandan Yu

459

Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting  

SciTech Connect (OSTI)

The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to measure in order to get the maximum positive impact on forecast performance for a particular site and short-term look-ahead period. Both tools rely on the use of NWP models to assess the sensitivity of a forecast for a particular location to measurements made at a prior time (i.e. the look-ahead period) at points surrounding the target location. The fundamental hypothesis is that points and variables with high sensitivity are good candidates for measurements since information at those points are likely to have the most impact on the forecast for the desired parameter, location and look-ahead period. One approach is called the adjoint method (Errico and Vukicevic, 1992; Errico, 1997) and the other newer approach is known as Ensemble Sensitivity Analysis (ESA; Ancell and Hakim 2007; Torn and Hakim 2008). Both approaches have been tested on large-scale atmospheric prediction problems (e.g. forecasting pressure or precipitation over a relatively large region 24 hours ahead) but neither has been applied to mesoscale space-time scales of winds or any other variables near the surface of the earth. A number of factors suggest that ESA is better suited for short-term wind forecasting applications. One of the most significant advantages of this approach is that it is not necessary to linearize the mathematical representation of the processes in the underlying atmospheric model as required by the adjoint approach. Such a linearization may be especially problematic for the application of short-term forecasting of boundary layer winds in complex terrain since non-linear shifts in the structure of boundary layer due to atmospheric stability changes are a critical part of the wind power production forecast problem. The specific objective of work described in this paper is to test the ESA as a tool to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the wind generation area of California's Tehachapi Pass during the warm (high generation) season. The paper is organized

Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

2010-02-21T23:59:59.000Z

460

Upper Air Wind Measurements by Weather Radar Iwan Holleman, Henk Benschop, and Jitze van der Meulen  

E-Print Network [OSTI]

or assimilated into numerical weather prediction (NWP) models. Un- der the assumption of a linear wind field background statistics of the weather radar wind profiles against the Hirlam NWP model are at least as good of the VVP wind profiles against the Hirlam NWP model demonstrate the high quality of weather radar wind

Stoffelen, Ad

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Weatherization Works!: Weatherization Assistance Program Close-Up Fact Sheet  

SciTech Connect (OSTI)

The United States demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

D& R International

2001-10-10T23:59:59.000Z

462

Intelligent weather agent for aircraft severe weather avoidance  

E-Print Network [OSTI]

Severe weather conditions pose a large threat to the safety of aircraft, since they are responsible for a large percentage of aviation related accidents. With the advent of the free flight environment, the exigency for an autonomous severe weather...

Bokadia, Sangeeta

2012-06-07T23:59:59.000Z

463

Proceedings: US Hydrographic Conference 2013, New Orleans, LA, 25-28 March 2013 Oceanographic Weather Maps: Using Oceanographic Models to Improve Seabed  

E-Print Network [OSTI]

: · Designing survey layout and prescribing line spacing and/or orientation. · Determining when to conduct the operation based on traffic, weather, and other environmental factors. · Selecting calibration sites

New Hampshire, University of

464

Location-specific weather predictions for Sriharikota (13.72N, 80.22E) through numerical atmospheric models during satellite launch campaigns  

Science Journals Connector (OSTI)

Accurate knowledge of different meteorological parameters over a launch site is very crucial for efficient management of satellite launch operations. Local weather over the Indian satellite launch site located at...

D. Bala Subrahamanyam; Radhika Ramachandran; S. Indira Rani

2012-04-01T23:59:59.000Z

465

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

466

2007 National Hurricane Center Forecast Verification Report James L. Franklin  

E-Print Network [OSTI]

storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first

467

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network [OSTI]

......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

468

Evolutionary Optimization of an Ice Accretion Forecasting System  

Science Journals Connector (OSTI)

The ability to model and forecast accretion of ice on structures is very important for many industrial sectors. For example, studies conducted by the power transmission industry indicate that the majority of failures are caused by icing on ...

Pawel Pytlak; Petr Musilek; Edward Lozowski; Dan Arnold

2010-07-01T23:59:59.000Z

469

Diagnosing the Origin of Extended-Range Forecast Errors  

Science Journals Connector (OSTI)

Experiments with the ECMWF model are carried out to study the influence that a correct representation of the lower boundary conditions, the tropical atmosphere, and the Northern Hemisphere stratosphere would have on extended-range forecast skill ...

T. Jung; M. J. Miller; T. N. Palmer

2010-06-01T23:59:59.000Z

470

Improvements of the shock arrival times at the Earth model STOA  

E-Print Network [OSTI]

Prediction of the shocks' arrival times (SATs) at the Earth is very important for space weather forecast. There is a well-known SAT model, STOA, which is widely used in the space weather forecast. However, the shock transit time from STOA model usually has a relative large error compared to the real measurements. In addition, STOA tends to yield too much `yes' prediction, which causes a large number of false alarms. Therefore, in this work, we work on the modification of STOA model. First, we give a new method to calculate the shock transit time by modifying the way to use the solar wind speed in STOA model. Second, we develop new criteria for deciding whether the shock will arrive at the Earth with the help of the sunspot numbers and the angle distances of the flare events. It is shown that our work can improve the SATs prediction significantly, especially the prediction of flare events without shocks arriving at the Earth.

Liu, H -L

2015-01-01T23:59:59.000Z

471

Weatherized in November  

Broader source: Energy.gov (indexed) [DOE]

November November 2010 Total Number of Homes Weatherized through November 2010 ***Total Number of Homes Weatherized through November 2010 Calendar Year 2009 November 2010 U.S. Department of Energy Weatherization Assistance Program Homes Weatherized By State in November 2010 (Calendar Year) November 2010 (Recovery Act) November 2010 (Recovery Act) Calendar Year 2009 - November 2010 (Recovery Act + Annual Program Funding) Alabama 262 3,433 4,141 1 Alaska 14 113 1,646 Arizona 326 3,420 4,581 Arkansas 248 3,162 4,670 California 1,495 21,185 23,153 Colorado 414 6,317 11,819 , , Connecticut 2,363 3,432 2 Delaware 940 1,110 District of Columbia 30 614 872 Florida 643 7,446 8,522 Georgia 580 6,780 7,495 Hawaii 18 398 766 Idaho 212 3,552 5,482 Illi i 1 674 18 862 26 340 Illinois 1,674 18,862 26,340

472

Weather and Joints  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Weather and Joints Weather and Joints Name: Brittany Location: N/A Country: N/A Date: N/A Question: Why do people feel the weather changin in their joints? Is it just a superstition? Replies: People feel weather changes in their bodies because storm systems are accompanied by lower air pressure. When a storm system is approaching the barometric pressure or air pressure will drop. Inside the body is air pressure also. The pressure inside the body is approximately 15 lbs per square inch. Normal air pressure on the outside is approximately the same. When both numbers are equal most people don't feel anything. However, when the low pressure system approaches or the air pressure drops, the pressure on the inside of the body is greater than outside and that air on the inside tries to get out because air flows from high pressure to low pressure. This causes swelling and discomfort in some people's joints, especially in the elderly or people who have suffered injuries to those areas (those areas are weakened somewhat due to the injury and less resistant to the changes in pressure).

473

Weatherized in October  

Broader source: Energy.gov (indexed) [DOE]

October October 2010 Total Number of Homes Weatherized through October 2010 ***Total Number of Homes Weatherized through October 2010 Calendar Year 2009 October 2010 U.S. Department of Energy Weatherization Assistance Program Homes Weatherized By State in October 2010 (Calendar Year) October 2010 (Recovery Act) October 2010 (Recovery Act) Calendar Year 2009 - October 2010 (Recovery Act + Annual Program Funding) Alabama 313 3,171 3,879 1 Alaska 16 99 1,632 Arizona 279 3,094 4,255 Arkansas 215 2,914 4,422 California 1,880 19,690 21,658 Colorado 451 5,903 11,405 , , Connecticut 367 2,363 3,432 2 Delaware 940 1,110 District of Columbia 102 584 842 Florida 725 6,803 7,879 Georgia 698 6,200 6,915 Hawaii 20 380 748 Idaho 198 3,340 5,270 Illi i 1 973 17 188 24 666 Illinois 1,973 17,188 24,666 Indiana

474

Value of Weather Information in Cranberry Marketing Decisions  

Science Journals Connector (OSTI)

Econometric techniques are used to establish a functional relationship between cranberry yields and important precipitation, temperature, and sunshine variables. Crop forecasts are derived from the model and are used to establish posterior ...

Bernard J. Morzuch; Cleve E. Willis

1982-04-01T23:59:59.000Z

475

6962 weather-resistant [adj  

Science Journals Connector (OSTI)

constr. (Descriptive term applied to surfaces of walls, roofs, pavements, wood, etc. exposed to the weather, which have powers of resistance to effects of weather; ? nonrotting [US]/non...

2010-01-01T23:59:59.000Z

476

Weatherization Assistance Program Allocation Formula  

Broader source: Energy.gov [DOE]

Weatherization Assistance Program (WAP) uses and allocation formula to calculate the weatherization grants to the states based on the amount of funding Congress appropriates to the program in a given year.

477

A Guide to Weather Satellites  

Science Journals Connector (OSTI)

Whenever there is a live weather satellite image (amateur radio enthusiasts use the term ... comment referred to amateur radio hams discussing the weather around the world in the early 1960s, ... could now be mad...

Lawrence Harris

2010-01-01T23:59:59.000Z

478

The science of space weather  

Science Journals Connector (OSTI)

...magnetic reconnection|space weather| 1. Introduction Fifty...31 January 1958, the satellite Explorer 1 was launched...et al. 2005). (e) Satellite anomalies Space weather can cause a variety of satellite anomalies such as surface...

2008-01-01T23:59:59.000Z

479

Weatherization Assistance Program Success Stories  

Broader source: Energy.gov [DOE]

Office of Energy Efficiency and Renewable Energy (EERE) success stories and blog entries for the Weatherization Assistance Program (WAP).

480

The Annals of Applied Statistics 2008, Vol. 2, No. 4, 11701193  

E-Print Network [OSTI]

. Operationally, short-range forecasts of precipitation are based on numerical weather prediction (NWP) models of agricultural, hydrological, ecological and other applications. Forecasts from numerical weather prediction forecast, Gamma distribu- tion, latent Gaussian process, numerical weather prediction, power truncated

Raftery, Adrian

Note: This page contains sample records for the topic "weather forecast models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Modelling agricultural ammonia emissions: impact on particulate matter Hamaoui-Laguel L.1  

E-Print Network [OSTI]

: air/soil temperature, air/soil humidity, wind speed and rainfall are provided to Volt'Air by the outputs of the meteorological mesoscale model WRF (Weather Research and Forecasting; http://www.wrf- model://www.orleans.inra.fr/les_unites/us_infosol) are available at local scale and have been interpolated on the chosen grid scale (0.15° X 0.10°). Data about

Paris-Sud XI, Université de

482

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network [OSTI]

of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute...-6, 2000 NEMS The NEMS industrial module is the official forecasting model for EIA and thus the Department of Energy. For this reason, the energy prices and output forecasts used to drive the ITEMS model were taken from EIA's AEO 2000. Understanding...

Roop, J. M.; Dahowski, R. T

483

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

Forecasting Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels MICHAEL YE, ∗ JOHN ZYREN, ∗∗ AND JOANNE SHORE ∗∗ Abstract This paper presents a short-term monthly forecasting model of West Texas Intermedi- ate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigat- ing the impacts of changes on price, should inventories,

484

Exponential smoothing with covariates applied to electricity demand forecast  

Science Journals Connector (OSTI)

Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponential smoothing, while the within-year cycle is modelled using covariates, specifically two harmonic explanatory variables. Calendar effects, such as national and local holidays and vacation periods, are also introduced using covariates. [Received 28 September 2010; Revised 6 March 2011, 2 October 2011; Accepted 16 October 2011

José D. Bermúdez

2013-01-01T23:59:59.000Z

485

The Weatherization Training program at Pennsylvania College | Department of  

Broader source: Energy.gov (indexed) [DOE]

The Weatherization Training program at Pennsylvania College The Weatherization Training program at Pennsylvania College The Weatherization Training program at Pennsylvania College Addthis Description A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone. Speakers Jeff Melville, Jack Wilson, John Manz, Kirk Gannett, Franzenia Smith, Duration 4:07 Topic Home Weatherization Education & Training Credit Energy Department Video JEFF MEVILLE: I'm Jeff Meville. I live in Montgomery, which is local to the area, about 10 miles south of here. I own a company called Jenpro (sp) Incorporated. We are a subcontractor in the weatherization business. We've got four guys right now working 40 hours a week plus,

486

Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary  

SciTech Connect (OSTI)

The U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Programs Office (WIPO) launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of low-income residences without the utilization of additional taxpayer funding. Sixteen WIPP grantees were awarded a total of $30 million in Weatherization Assistance Program (WAP) funds in September 2010. These projects focused on: including nontraditional partners in weatherization service delivery; leveraging significant non-federal funding; and improving the effectiveness of low-income weatherization through the use of new materials, technologies, behavior-change models, and processes.

Hollander, A.

2014-09-01T23:59:59.000Z

487

Solar Wind Forecasting with Coronal Holes  

E-Print Network [OSTI]

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

488

States Celebrate National Weatherization Day  

Broader source: Energy.gov [DOE]

States across the country celebrated National Weatherization Day October 30 with formal proclamations from governors and special events to recognize the importance of weatherization and the dedication of local weatherization service providers, state and local agencies, and researchers dedicated to improving the energy efficiency of American homes.

489

Atmospheric corrosion data of weathering steels. A review  

Science Journals Connector (OSTI)

Abstract Extensive information on the atmospheric corrosion of weathering steel has been published in the scientific literature. The contribution of the present work is to provide a bibliographic review of the reported information, which mostly concerns the weathering steel ASTM A-242. This review addresses issues such as rust layer stabilisation times, steady-state steel corrosion rates, and situations where the use of unpainted weathering steel is feasible. It also analyses the effect of exposure conditions. Finally it approaches the important matter of predicting the long-term behaviour of weathering steel reviewing the different prediction models published in the literature.

M. Morcillo; B. Chico; I. Daz; H. Cano; D. de la Fuente

2013-01-01T23:59:59.000Z

490

Price forecasting for notebook computers.  

E-Print Network [OSTI]

??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a (more)

Rutherford, Derek Paul

2012-01-01T23:59:59.000Z

491

Weatherization Training for South Carolina's Muggy Weather | Department of  

Broader source: Energy.gov (indexed) [DOE]

Training for South Carolina's Muggy Weather Training for South Carolina's Muggy Weather Weatherization Training for South Carolina's Muggy Weather June 22, 2010 - 3:46pm Addthis Trident Technical College in Charleston, SC., has added another sustainability component to its curriculum: weatherization. A program already filled with renewable energy courses, TTC Green, now offers training and certification for technicians. This training, available for anyone from novices to the experienced, teaches how to weatherize the diverse array of homes in the muggy Charleston area to be more energy efficient. Two of the school's continuing education courses, both under three weeks in length, offer certification to individuals with weatherization backgrounds, giving them additional credentials and skills in the industry. TTC Green

492

Developing hourly weather data for locations having only daily weather data  

SciTech Connect (OSTI)

A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

1983-06-01T23:59:59.000Z

493

VALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS  

E-Print Network [OSTI]

and for improving parameterization cloud processes in numerical weather prediction (NWP) models or assimilation in these models. Although operational networks of Weather Radars are expanding over Europe and the United StatesVALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS R. A. Roebeling

Stoffelen, Ad

494

ARM - Measurement - Shortwave broadband total net irradiance  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Range Weather Forecasts Diagnostic Analyses ECMWF : European Centre for Medium Range Weather Forecasts Model Data Value-Added Products ARMBE : ARM Best Estimate Data Products...

495

ORNL Weatherization Program Evaluation | Open Energy Information  

Open Energy Info (EERE)

ORNL Weatherization Program Evaluation ORNL Weatherization Program Evaluation (Redirected from Weatherization Program Evaluation) Jump to: navigation, search Tool Summary Name: Weatherization Program Evaluation Agency/Company /Organization: Oak Ridge National Laboratory Sector: Energy Focus Area: Buildings Topics: Policies/deployment programs Website: weatherization.ornl.gov/WeatherizationProgramEvaluations.htm References: Weatherization Program Evaluation [1] Logo: Weatherization Program Evaluation Oak Ridge National Laboratory provides weatherization program evaluations as part of the U.S. Department of Energy's Weatherization Assistance Program. This evaluation program is also available to international organizations. This article is a stub. You can help OpenEI by expanding it. Oak Ridge National Laboratory provides weatherization program evaluations

496

Probabilistic manpower forecasting  

E-Print Network [OSTI]

- ing E. Results- Probabilistic Forecasting . 26 27 Z8 29 31 35 36 38 39 IV. CONCLUSIONS. V. GLOSSARY 42 44 APPENDICES REFERENCES 50 70 LIST OF TABLES Table Page Outline of Job-Probability Matrix Job-Probability Matrix. Possible... Outcomes of Job A Possible Outcomes of Jobs A and B 10 Possible Outcomes of Jobs A, B and C II LIST GF FIGURES Figure Page Binary Representation of Numbers 0 Through 7 12 First Cumulative Probability Table 14 3. Graph of Cumulative Probability vs...

Koonce, James Fitzhugh

1966-01-01T23:59:59.000Z

497

Connecticut's Health Impact Study Rapidly Increasing Weatherization...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

of Weatherization Assistance Program Technical Assistance Center Donna Hawkins Technology Transfer Specialist, Weatherization Assistance Program Floris Weston Project Officer,...

498

Accelerating Clean Energy Adoption (Fact Sheet), Weatherization...  

Broader source: Energy.gov (indexed) [DOE]

Accelerating Clean Energy Adoption (Fact Sheet), Weatherization and Intergovernmental Program (WIP) Accelerating Clean Energy Adoption (Fact Sheet), Weatherization and...

499

Mid-term electricity market clearing price forecasting: A hybrid LSSVM and ARMAX approach  

Science Journals Connector (OSTI)

Abstract A hybrid mid-term electricity market clearing price (MCP) forecasting model combining both least squares support vector machine (LSSVM) and auto-regressive moving average with external input (ARMAX) modules is presented in this paper. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. Currently, there are many techniques available for short-term electricity market clearing price (MCP) forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples. The proposed hybrid model showed improved forecasting accuracy compared to a forecasting model using a single LSSVM.

Xing Yan; Nurul A. Chowdhury

2013-01-01T23:59:59.000Z

500

Project Profile: Forecasting and Influencing Technological Progress...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of...