National Library of Energy BETA

Sample records for weather forecast models

  1. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

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

    E-Print Network [OSTI]

    Jamieson, Bruce

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

  4. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  5. Application of a new phenomenological coronal mass ejection model to space weather forecasting

    E-Print Network [OSTI]

    Howard, Tim

    to space weather forecasting T. A. Howard1 and S. J. Tappin2 Received 15 October 2009; revised 27 April with the Earth. Hence the model can be used for space weather forecasting. We present a preliminary evaluation to fully validate it for integration with existing tools for space weather forecasting. Citation: Howard, T

  6. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    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.

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

    E-Print Network [OSTI]

    Evans, Jason

    Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south, Australia. D Corresponding author. Email: h.clarke@student.unsw.edu.au Abstract. The fire weather of south of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual

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

    E-Print Network [OSTI]

    Niyogi, Dev

    (GEM) for Mesoscale Weather Forecasting Applications DEV NIYOGI Department of Agronomy, and Department form 13 May 2008) ABSTRACT Current land surface schemes used for mesoscale weather forecast models use model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM

  9. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

  10. Evaluation of the Weather Research and Forecasting Model on

    E-Print Network [OSTI]

    Basu, Sukanta

    are thus needed for precise assessment of wind resources, reliable prediction of power generation and robust design of wind turbines. However, mesoscale numerical weather prediction models face a chal- lenge: Implications for Wind Energy Brandon Storm*, Wind Science and Engineering Research Center, Texas Tech

  11. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

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

    2006-01-01

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  12. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  13. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

  14. Development and initial application of the global-through-urban weather research and forecasting model with chemistry

    E-Print Network [OSTI]

    Zhang, Yang

    Development and initial application of the global-through-urban weather research and forecasting application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem), J. In this work, a global-through-urban WRF/Chem model (i.e., GU-WRF/Chem) has been developed to provide

  15. Implementation of the Immersed Boundary Method in the Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, K A

    2006-12-07

    Accurate simulations of atmospheric boundary layer flow are vital for predicting dispersion of contaminant releases, particularly in densely populated urban regions where first responders must react within minutes and the consequences of forecast errors are potentially disastrous. Current mesoscale models do not account for urban effects, and conversely urban scale models do not account for mesoscale weather features or atmospheric physics. The ultimate goal of this research is to develop and implement an immersed boundary method (IBM) along with a surface roughness parameterization into the mesoscale Weather Research and Forecasting (WRF) model. IBM will be used in WRF to represent the complex boundary conditions imposed by urban landscapes, while still including forcing from regional weather patterns and atmospheric physics. This document details preliminary results of this research, including the details of three distinct implementations of the immersed boundary method. Results for the three methods are presented for the case of a rotation influenced neutral atmospheric boundary layer over flat terrain.

  16. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  18. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Raftery, Adrian

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  19. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

  20. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

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

    SciTech Connect (OSTI)

    Michalakes, J.

    1999-01-13

    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.

  2. The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model

    E-Print Network [OSTI]

    Heinemann, Detlev

    In countries showing high wind energy shares in the elec- trical power supply grid, a "wind power weatherThe Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model Laboratory, P.O. box 49, DK-4000 Roskilde, Tel/Fax: +45 4677 5095 / 5970 Gregor.Giebel@Risoe.DK Wind power

  3. Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA

    SciTech Connect (OSTI)

    Barker, D.; Huang, X. Y.; Liu, Z. Q.; Auligne, T.; Zhang, X.; Rugg, S.; Ajjaji, R.; Bourgeois, A.; Bray, J.; Chen, Y. S.; Demirtas, M.; Guo, Y. R.; Henderson, T.; Huang, W.; Lin, H. C.; Michalakes, J.; Rizvi, S.; Zhang, X. Y.

    2012-06-01

    Data assimilation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency Weather Research and Forecasting (WRF) model effort has had a strong data assimilation component, dedicating two working groups to the subject. This article documents the history of the WRF data assimilation effort, and discusses the challenges associated with balancing academic, research, and operational data assimilation requirements in the context of the WRF effort to date. The WRF Model's Community Variational/Ensemble Data Assimilation System (WRFDA) has evolved over the past 10 years, and has resulted in over 30 refereed publications to date, as well as implementation in a wide range of real-time and operational NWP systems.

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

    SciTech Connect (OSTI)

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

    2005-03-18

    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.

  5. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author Fort Collins, Colorado7 October 20128 (submitted to Weather and Forecasting)9 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt

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

    SciTech Connect (OSTI)

    Michalakes, J.; Chen, S.; Dudhia, J.; Hart, L.; Klemp, J.; Middlecoff, J.; Skamarock, W.

    2001-02-05

    The Weather Research and Forecast (WRF) project is a multi-institutional effort to develop an advanced mesoscale forecast and data assimilation system that is accurate, efficient, and scalable across a range of scales and over a host of computer platforms. The first release, WRF 1.0, was November 30, 2000, with operational deployment targeted for the 2004-05 time frame. This paper provides an overview of the project and current status of the WRF development effort in the areas of numerics and physics, software and data architecture, and single-source parallelism and performance portability.

  7. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author, Guangzhou 510301, China9 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological10, China20 21 22 23 24 Submitted to Weather and Forecasting25 2014. 12. 2826 27 Corresponding author: Dr

  8. Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts

    E-Print Network [OSTI]

    Raftery, Adrian

    Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts VERONICA ensembles that generates calibrated probabilistic forecast products for weather quantities at indi- vidual perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather

  9. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

    Stochastic Weather Generator Based Ensemble Streamflow Forecasting by Nina Marie Caraway B of Civil Engineering 2012 #12;This thesis entitled: Stochastic Weather Generator Based Ensemble Streamflow mentioned discipline. #12;iii Caraway, Nina Marie (M.S., Civil Engineering) Stochastic Weather Generator

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    transport and  numerical weather modeling.   J.  Applied cross correlations.    Weather and Forecasting, 8:4, 401?of radiation for numerical weather prediction and climate 

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    cycle:  The RUC.  Monthly Weather  Review.   132, 495?518.  th  Conference on  Numerical Weather Prediction.   American closure schemes.   Monthly Weather Review.   122, 927?945.  

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

    E-Print Network [OSTI]

    Ganguly, Auroop Ratan

    2002-01-01

    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. ...

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

    SciTech Connect (OSTI)

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

    2010-06-27

    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.

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

    SciTech Connect (OSTI)

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

    2010-03-15

    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.

  15. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

    to communicate numeric weather data. A corpus-based analysis of how humans write forecasts showed that there wereTime- Mousam weather-forecast generator to use consistent data-to-word rules, which avoided words which were weather forecast texts from numerical weather pre- diction data (SumTime-Mousam in fact is used

  16. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  17. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

  18. Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting Model with Chemistry (GU-WRF/Chem)2

    E-Print Network [OSTI]

    Nenes, Athanasios

    1 Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting-cloud-radiation-precipitation-climate interactions. In this work, a global-through-urban33 WRF/Chem model (i.e., GU-WRF/Chem) has been developed photolysis rate, near-surface temperature, wind speed at 10-m, planetary boundary layer height,40

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

    SciTech Connect (OSTI)

    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

    2008-01-01

    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.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  1. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

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

    2005-09-26

    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.

  2. Development of an Immersed Boundary Method to Resolve Complex Terrain in the Weather Research and Forecasting Model

    SciTech Connect (OSTI)

    Lunquist, K A; Chow, F K; Lundquist, J K; Mirocha, J D

    2007-09-04

    Flow and dispersion processes in urban areas are profoundly influenced by the presence of buildings which divert mean flow, affect surface heating and cooling, and alter the structure of turbulence in the lower atmosphere. Accurate prediction of velocity, temperature, and turbulent kinetic energy fields are necessary for determining the transport and dispersion of scalars. Correct predictions of scalar concentrations are vital in densely populated urban areas where they are used to aid in emergency response planning for accidental or intentional releases of hazardous substances. Traditionally, urban flow simulations have been performed by computational fluid dynamics (CFD) codes which can accommodate the geometric complexity inherent to urban landscapes. In these types of models the grid is aligned with the solid boundaries, and the boundary conditions are applied to the computational nodes coincident with the surface. If the CFD code uses a structured curvilinear mesh, then time-consuming manual manipulation is needed to ensure that the mesh conforms to the solid boundaries while minimizing skewness. If the CFD code uses an unstructured grid, then the solver cannot be optimized for the underlying data structure which takes an irregular form. Unstructured solvers are therefore often slower and more memory intensive than their structured counterparts. Additionally, urban-scale CFD models are often forced at lateral boundaries with idealized flow, neglecting dynamic forcing due to synoptic scale weather patterns. These CFD codes solve the incompressible Navier-Stokes equations and include limited options for representing atmospheric processes such as surface fluxes and moisture. Traditional CFD codes therefore posses several drawbacks, due to the expense of either creating the grid or solving the resulting algebraic system of equations, and due to the idealized boundary conditions and the lack of full atmospheric physics. Meso-scale atmospheric boundary layer simulations, on the other hand, are performed by numerical weather prediction (NWP) codes, which cannot handle the geometry of the urban landscape, but do provide a more complete representation of atmospheric physics. NWP codes typically use structured grids with terrain-following vertical coordinates, include a full suite of atmospheric physics parameterizations, and allow for dynamic synoptic scale lateral forcing through grid nesting. Terrain following grids are unsuitable for urban terrain, as steep terrain gradients cause extreme distortion of the computational cells. In this work, we introduce and develop an immersed boundary method (IBM) to allow the favorable properties of a numerical weather prediction code to be combined with the ability to handle complex terrain. IBM uses a non-conforming structured grid, and allows solid boundaries to pass through the computational cells. As the terrain passes through the mesh in an arbitrary manner, the main goal of the IBM is to apply the boundary condition on the interior of the domain as accurately as possible. With the implementation of the IBM, numerical weather prediction codes can be used to explicitly resolve urban terrain. Heterogeneous urban domains using the IBM can be nested into larger mesoscale domains using a terrain-following coordinate. The larger mesoscale domain provides lateral boundary conditions to the urban domain with the correct forcing, allowing seamless integration between mesoscale and urban scale models. Further discussion of the scope of this project is given by Lundquist et al. [2007]. The current paper describes the implementation of an IBM into the Weather Research and Forecasting (WRF) model, which is an open source numerical weather prediction code. The WRF model solves the non-hydrostatic compressible Navier-Stokes equations, and employs an isobaric terrain-following vertical coordinate. Many types of IB methods have been developed by researchers; a comprehensive review can be found in Mittal and Iaccarino [2005]. To the authors knowledge, this is the first IBM approach that is able to

  3. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

    and Winter, S. G. : 1960, Weather Information and EconomicThe ENSO Signal 7, 4–6. WEATHER FORECASTS ARE FOR WIMPSWEATHER FORECASTS ARE FOR WIMPS ? : WHY WATER RESOURCE

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

    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 ...

  5. DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through

    E-Print Network [OSTI]

    Isaacs, Rufus

    1 DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through Thursday by ~225. Complete weather summaries and forecasts are at available enviroweather.msu.edu GDD (from March 1.isaacslab.ent.msu.edu/blueberryscout/blueberryscout.htm Contents · Crop Stages · Weather Notes · Disease Update · Scouting the Major Diseases of Highbush

  6. THE GALACTIC CENTER WEATHER FORECAST

    SciTech Connect (OSTI)

    Moscibrodzka, M. [Department of Physics and Astronomy, University of Nevada, 4505 South Maryland Parkway, Las Vegas, NV 89154 (United States); Shiokawa, H.; Gammie, C. F. [Astronomy Department, University of Illinois, 1002 West Green Street, Urbana, IL 61801 (United States); Dolence, J. C., E-mail: monikam@physics.unlv.edu [Department of Astrophysical Sciences, Princeton University, Peyton Hall, 4 Ivy Lane, Princeton, NJ 08544 (United States)

    2012-06-10

    In accretion-based models for Sgr A*, the X-ray, infrared, and millimeter emission arise in a hot, geometrically thick accretion flow close to the black hole. The spectrum and size of the source depend on the black hole mass accretion rate M-dot . Since Gillessen et al. have recently discovered a cloud moving toward Sgr A* that will arrive in summer 2013, M-dot may increase from its present value M-dot{sub 0}. We therefore reconsider the 'best-bet' accretion model of Moscibrodzka et al., which is based on a general relativistic MHD flow model and fully relativistic radiative transfer, for a range of M-dot . We find that for modest increases in M-dot the characteristic ring of emission due to the photon orbit becomes brighter, more extended, and easier to detect by the planned Event Horizon Telescope submillimeter Very Long Baseline Interferometry experiment. If M-dot {approx}>8 M-dot{sub 0}, this 'silhouette' of the black hole will be hidden beneath the synchrotron photosphere at 230 GHz, and for M-dot {approx}>16 M-dot{sub 0} the silhouette is hidden at 345 GHz. We also find that for M-dot > 2 M-dot{sub 0} the near-horizon accretion flow becomes a persistent X-ray and mid-infrared source, and in the near-infrared Sgr A* will acquire a persistent component that is brighter than currently observed flares.

  7. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect (OSTI)

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

    2009-03-01

    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.

  8. On-line economic optimization of energy systems using weather forecast information.

    SciTech Connect (OSTI)

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

    2009-01-01

    We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of numerical weather prediction solar irradiance forecastsof numerical weather prediction solar irradiance forecastsnumerical weather prediction model for solar irradiance

  10. Numerical weather forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Site, Aiken, SC (United States)

    1998-12-31

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND system, a system of computer models and monitors that collects data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space- and time-dependent meteorological data for use in the WIND system dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications. A prognostic mesoscale model, the regional atmospheric modeling system (RAMS), is used to provide these forecasts. Use of RAMS allows for incorporation of mesoscale features such as the sea breeze, which has been shown to affect local weather conditions. This paper discusses the mesoscale model and its configuration for the operational simulation, as well as an application using a dispersion model at the SRS.

  11. Diagnosis of the summertime warm and dry bias over the U. S. Southern Great Plains in the GFDL climate model using a weather forecasting approach

    SciTech Connect (OSTI)

    Klein, S A; Jiang, X; Boyle, J; Malyshev, S; Xie, S

    2006-07-11

    Weather forecasts started from realistic initial conditions are used to diagnose the large warm and dry bias over the United States Southern Great Plains simulated by the GFDL climate model. The forecasts exhibit biases in surface air temperature and precipitation within 3 days which appear to be similar to the climate bias. With the model simulating realistic evaporation but underestimated precipitation, a deficit in soil moisture results which amplifies the initial temperature bias through feedbacks with the land surface. The underestimate of precipitation is associated with an inability of the model to simulate the eastward propagation of convection from the front-range of the Rocky Mountains and is insensitive to an increase of horizontal resolution from 2{sup o} to 0.5{sup o} latitude.

  12. DEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA)

    E-Print Network [OSTI]

    in a data base and graphic representation with tile standard meteorological icons on a map, e.g. iconsDEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA) by BENGT SIGURD, Sweden E-mail: linglund@gemini.ldc.lu.se FAX:46-(0)46 104210 Introduction and abstract Weather forecasts

  13. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Company, AIKEN, SC (United States)

    1998-11-01

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally-released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND System, a system of computer models and monitors which collect data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space and time-dependent meteorological data for use in the WIND System dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications.

  14. A Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events

    E-Print Network [OSTI]

    Ding, Wei

    . Frequent pattern-based data representations have been used in various studies for abstracting climaticA Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events Dawei Wang, Wei@cs.umb.edu Abstract--Extreme weather events, like extreme rainfalls, are severe weather hazards and also the triggers

  15. Implementation and assessment of turbine wake models in the Weather Research and Forecasting model for both mesoscale and large-eddy simulation

    SciTech Connect (OSTI)

    Singer, M; Mirocha, J; Lundquist, J; Cleve, J

    2010-03-03

    Flow dynamics in large wind projects are influenced by the turbines located within. The turbine wakes, regions characterized by lower wind speeds and higher levels of turbulence than the surrounding free stream flow, can extend several rotor diameters downstream, and may meander and widen with increasing distance from the turbine. Turbine wakes can also reduce the power generated by downstream turbines and accelerate fatigue and damage to turbine components. An improved understanding of wake formation and transport within wind parks is essential for maximizing power output and increasing turbine lifespan. Moreover, the influence of wakes from large wind projects on neighboring wind farms, agricultural activities, and local climate are all areas of concern that can likewise be addressed by wake modeling. This work describes the formulation and application of an actuator disk model for studying flow dynamics of both individual turbines and arrays of turbines within wind projects. The actuator disk model is implemented in the Weather Research and Forecasting (WRF) model, which is an open-source atmospheric simulation code applicable to a wide range of scales, from mesoscale to large-eddy simulation. Preliminary results demonstrate the applicability of the actuator disk model within WRF to a moderately high-resolution large-eddy simulation study of a small array of turbines.

  16. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    user needs for convective weather forecasts," in AmericanJ. Andrews M. Weber, "Weather Information Requirements forInt. Conf. on Aviation Weather, Paris, France. [5] NASDAC. (

  17. Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

    SciTech Connect (OSTI)

    Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

    2011-09-29

    This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

  18. ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED BY THE NWS STORM PREDICTION CENTER

    E-Print Network [OSTI]

    effort to estimate potential severe weather societal impacts based on a combination of probabilistic forecasts and high resolution population data. For equal severe weather threat, events that occur over1 ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED

  19. Simulations of Clouds and Sensitivity Study by Weather Research and Forecast Model for Atmospheric Radiation Measurement Case 4

    SciTech Connect (OSTI)

    Wu, J.; Zhang, M.

    2005-03-18

    One of the large errors in general circulation models (GCMs) cloud simulations is from the mid-latitude, synoptic-scale frontal cloud systems. Now, with the availability of the cloud observations from Atmospheric Radiation Measurement (ARM) 2000 cloud Intensive Operational Period (IOP) and other observational datasets, the community is able to document the model biases in comparison with the observations and make progress in development of better cloud schemes in models. Xie et al. (2004) documented the errors in midlatitude frontal cloud simulations for ARM Case 4 by single-column models (SCMs) and cloud resolving models (CRMs). According to them, the errors in the model simulated cloud field might be caused by following reasons: (1) lacking of sub-grid scale variability; (2) lacking of organized mesoscale cyclonic advection of hydrometeors behind a moving cyclone which may play important role to generate the clouds there. Mesoscale model, however, can be used to better under stand these controls on the subgrid variability of clouds. Few studies have focused on applying mesoscale models to the forecasting of cloud properties. Weaver et al. (2004) used a mesoscale model RAMS to study the frontal clouds for ARM Case 4 and documented the dynamical controls on the sub-GCM-grid-scale cloud variability.

  20. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect (OSTI)

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  1. 1. Introduction Users of weather forecasts, particularly paying cus-

    E-Print Network [OSTI]

    1. Introduction Users of weather forecasts, particularly paying cus- tomers, are operating within Kingdom out of a total budget of approximately £140 million for winter road maintenance. It is difficult rely on a simple set of statistics provided by the weather service providers. The current guidance

  2. CloudCast: Cloud Computing for Short-term Mobile Weather Forecasts

    E-Print Network [OSTI]

    Shenoy, Prashant

    of Massachusetts Amherst Abstract--Since today's weather forecasts only cover large regions every few hours algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which One useful application is mobile weather forecasting, which provides hour-to-hour forecasts

  3. Impact of a Revised Convective Triggering Mechanism on CAM2 Model Simulations: Results from Short-Range Weather Forecasts

    SciTech Connect (OSTI)

    Xie, S; Boyle, J S; Cederwall, R T; Potter, G L; Zhang, M; Lin, W

    2004-02-19

    This study implements a revised convective triggering condition in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM2) model to reduce its excessive warm season daytime precipitation over land. The new triggering mechanism introduces a simple dynamic constraint on the initiation of convection that emulates the collective effects of lower level moistening and upward motion of the large-scale circulation. It requires a positive contribution from the large-scale advection of temperature and moisture to the existing positive Convective Available Potential Energy (CAPE) for model convection to start. In contrast, the original convection triggering function in CAM2 assumes that convection is triggered whenever there is positive CAPE, which results in too frequent warm season convection over land arising from strong diurnal variation of solar radiation. We examine the impact of the new trigger on CAM2 simulations by running the climate model in Numerical Weather Prediction (NWP) mode so that more available observations and high-frequency NWP analysis data can be used to evaluate model performance. We show that the modified triggering mechanism has led to considerable improvements in the simulation of precipitation, temperature, moisture, clouds, radiations, surface temperature, and surface sensible and latent heat fluxes when compared to the data collected from the Atmospheric Radiation Measurement (ARM) program at its South Great Plains (SGP) site. Similar improvements are also seen over other parts of the globe. In particular, the surface precipitation simulation has been significantly improved over both the continental United States and around the globe; the overestimation of high clouds in the equatorial tropics has been substantially reduced; and the temperature, moisture, and zonal wind are more realistically simulated. Results from this study also show that some systematic errors in the CAM2 climate simulations can be detected in the early stage of model integration. Examples are the extremely overestimated high clouds in the tropics in the vicinity of ITCZ and the spurious precipitation maximum in the east of the Rockies. This has important implications in studies of these model errors since running the climate model in NWP mode allows us to perform a more in-depth analysis during a short time period where more observations are available and different model errors from various processes have not compensated for the systematic errors.

  4. Weather Forecast Data an Important Input into Building Management Systems 

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01

    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 Input into Building..., Martin Fradette Environment Canada RPN ? Recherche en Pr?vision num?rique Dr. Wei Yu, Dr. Paul Vaillancourt, Dr. Sylvie Leroyer Natural Resources Canada ? Canmet Energy Dr. Jos? A. Candanedo Overview ? Building management and weather information...

  5. Exploiting weather forecast data for cloud detection 

    E-Print Network [OSTI]

    Mackie, Shona

    2009-01-01

    Accurate, fast detection of clouds in satellite imagery has many applications, for example Numerical Weather Prediction (NWP) and climate studies of both the atmosphere and of the Earth’s surface temperature. Most ...

  6. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

    GOES Aviation Products · The GOES aviation forecast products are based on energy measured in different characteristics #12;GOES Aviation Products Quiz · What is a geostationary satellite? · What generates energy received by the satellite in the visible band? · What generates energy received by the satellite

  7. Computational Models for Understanding Weather

    E-Print Network [OSTI]

    Muraki, David J.

    Computational Models for Understanding Weather Mathematics for Atmospheric Science http://weather-S migration Dutton Conway zonal jetstream in unstable weather 6 #12;Baroclinic Instability Vortices

  8. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

    E-Print Network [OSTI]

    Shenoy, Prashant

    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

  9. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

    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

  10. Reprinted from: Proceedings, International Workshop on Observations/Forecasting of Meso-scale Severe Weather and

    E-Print Network [OSTI]

    Doswell III, Charles A.

    -scale Severe Weather and Technology of Reduction of Relevant Disasters (Tokyo, Japan), 22-26 February 1993, 181 on the ingredients for particular severe weather events, a focus is provided for the forecasting process of forecasters is discussed also, as a necessary component in a balanced approach to weather forecasting

  11. Dynamic Algorithm for Space Weather Forecasting System 

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08

    .............................................................................................9 Task 1: Developing a database of solar weather data ...............................9 Task 2: Developing the ?dynamic analysis? process .............................. 10 Task 3: Developing a Java applet that presents real-time solar...-computing resources have been recently discovered. Software materials include the programming language ?Java?, the Graphical-User-Interface ?JCreator?, and Rapid Miner. We also make use of publicly available scientific databases that contain a vast plethora...

  12. Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization

    E-Print Network [OSTI]

    Nocedal, Jorge

    Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization M. Fisher J weather prediction centers to produce the initial conditions for 7- to 10-day weather fore- casts, with particular reference to the system in operation at the European Centre for Medium-Range Weather Forecasts. 1

  13. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist...

    E-Print Network [OSTI]

    Raftery, Adrian

    permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist... Yulia Gel; Adrian

  14. Results from the Second Forum on the Future Role of the Human in the Forecast Process. Part II: Cognitive Psychological Aspects of Expert Weather Forecasters

    E-Print Network [OSTI]

    Schultz, David

    : Cognitive Psychological Aspects of Expert Weather Forecasters NEIL A. STUART* NOAA/National Weather Service of Applied Research Associates, Fairborn, Ohio In Preparation for Submission to Forecasters Forum, Weather and Forecasting 30 June 2006 Corresponding author address: Neil A. Stuart, National Weather Service, 10009 General

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

    E-Print Network [OSTI]

    Marseille, Gert-Jan

    of forecast failures, in particular those with large socio economic impact. Forecast failures of high- impact on their ability to improve meteorological analyses and subsequently reduce the probability of forecast failures true atmospheric state. This was generated by the European Centre for Medium-Range Weather Forecasts

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    Numerical Weather Prediction (NWP), Solar Forecasting  1.   to more accurate prediction of solar  irradiance, given a to create daily solar electricity predictions accurate to 

  17. SYNTHESIZING WEATHER FORECASTS FROM FORMATFED DATA R.Kittredge and A.Polgu~re

    E-Print Network [OSTI]

    of several types of weather bulletin based on the same basic weather data, each type emphasizingSYNTHESIZING WEATHER FORECASTS FROM FORMATFED DATA R.Kittredge and A.Polgu~re D6partement de formatted weather data. Such synthesis appem~ feasible in certain natural sublanguages with stereo- typed

  18. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L.

    1999-01-26

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations.

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

    E-Print Network [OSTI]

    Raftery, Adrian

    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction LE proposes an effective bias correction technique for wind direction forecasts from numerical weather forecasts. These techniques are applied to 48-h forecasts of surface wind direction over the Pacific

  20. The new Athens Center applied to Space Weather Forecasting

    SciTech Connect (OSTI)

    Mavromichalaki, H.; Sarlanis, C.; Souvatzoglou, G.; Mariatos, G.; Gerontidou, M.; Plainaki, C.; Papaioannou, A.; Tatsis, S. [University of Athens, Physics Department, Section of Nuclear and Particle Physics, Zografos 15771 Athens (Greece); Belov, A.; Eroshenko, E.; Yanke, V. [IZMIRAN, Russian Academy of Science, 1420092 Moscow (Russian Federation)

    2006-08-25

    The Sun provides most of the initial energy driving space weather and modulates the energy input from sources outside the solar system, but this energy undergoes many transformations within the various components of the solar-terrestrial system, which is comprised of the solar wind, magnetosphere and radiation belts, the ionosphere, and the upper and lower atmospheres of Earth. This is the reason why an Earth's based neutron monitor network can be used in order to produce a real time forecasting of space weather phenomena.Since 2004 a fully functioned new data analysis Center in real-time is in operation in Neutron Monitor Station of Athens University (ANMODAP Center) suitable for research applications. It provides a multi sided use of twenty three neutron monitor stations distributing in all world and operating in real-time given crucial information on space weather phenomena. In particular, the ANMODAP Center can give a preliminary alert of ground level enhancements (GLEs) of solar cosmic rays which can be registered around 20 to 30 minutes before the main part of lower energy particles. Therefore these energetic solar cosmic rays provide the advantage of forth warning. Moreover, the monitoring of the precursors of cosmic rays gives a forehand estimate on that kind of events should be expected (geomagnetic storms and/or Forbush decreases)

  1. 6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO

    E-Print Network [OSTI]

    6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO Sarah J. Taylor* and Eric D. Howieson NOAA/National Weather Service Tulsa, Oklahoma 1. INTRODUCTION The modernization of the National then providesthemeteorologistanopportunitytoadjustmodel forecasts for local biases and terrain effects. The Tulsa, Oklahoma WFO has been a test office

  2. Neural network based short-term load forecasting using weather compensation

    SciTech Connect (OSTI)

    Chow, T.W.S.; Leung, C.T. [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering] [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering

    1996-11-01

    This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

  3. Information Preservation and Weather Forecasting for Black Holes

    E-Print Network [OSTI]

    S. W. Hawking

    2014-01-22

    It has been suggested [1] that the resolution of the information paradox for evaporating black holes is that the holes are surrounded by firewalls, bolts of outgoing radiation that would destroy any infalling observer. Such firewalls would break the CPT invariance of quantum gravity and seem to be ruled out on other grounds. A different resolution of the paradox is proposed, namely that gravitational collapse produces apparent horizons but no event horizons behind which information is lost. This proposal is supported by ADS-CFT and is the only resolution of the paradox compatible with CPT. The collapse to form a black hole will in general be chaotic and the dual CFT on the boundary of ADS will be turbulent. Thus, like weather forecasting on Earth, information will effectively be lost, although there would be no loss of unitarity.

  4. Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud Sadjadi, Shu-Ching Chen

    E-Print Network [OSTI]

    Chen, Shu-Ching

    Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud, Miami FL {ksale002, sadjadi,chens}@cs.fiu.edu ABSTRACT Current weather forecast and visualization systems lack the scalability to support numerous customized requests for weather research and forecasting

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    Evaluation of numerical weather prediction solar irradiancecycle: The RUC. Monthly Weather Review, 132 (2), 495-518.representations. Monthly Weather Review, 139 (6), 1972-1995.

  6. Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD

    E-Print Network [OSTI]

    Plale, Beth

    "mesoscale" weather events. In this paper we discuss an architectural framework that is forming our thinking "mesoscale" weather events. This is accomplished by middleware that facilitates adaptive uti- lization. The meteorology goal of the project is improved prediction of mesoscale weather phenomena; that is, regional scale

  7. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Ben C Allanach; Kyle Cranmer; Christopher G Lester; Arne M Weber

    2007-07-05

    Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan beta, while being constrained to postdict the central experimental value of MZ. We construct a different, new and more natural prior with a measure in mu and B (the more fundamental MSSM parameters from which tan beta and MZ are actually derived). We find that as a consequence this choice leads to a well defined fine-tuning measure in the parameter space. We investigate the effect of such on global CMSSM fits to indirect constraints, providing posterior probability distributions for Large Hadron Collider (LHC) sparticle production cross sections. The change in priors has a significant effect, strongly suppressing the pseudoscalar Higgs boson dark matter annihilation region, and diminishing the probable values of sparticle masses. We also show how to interpret fit information from a Markov Chain Monte Carlo in a frequentist fashion; namely by using the profile likelihood. Bayesian and frequentist interpretations of CMSSM fits are compared and contrasted.

  8. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    DB. Weather data for building performance simulation.forecast models, weather data, and building prototypes havethe TMY3 weather data in building simulations to evaluate

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    electric grid. Chapter 2 Marine Layer Meteorology 2.1 Marine Layer Stratocumulus Overview In coastal California, the dominant weather

  10. FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie

    E-Print Network [OSTI]

    FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Forecasting System (GLCFS) can be used to validate wind forecasts for the Great Lakes using observed weather prediction step-coordinate Eta Model are able to forecast winds for the Great Lakes region, using

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

    E-Print Network [OSTI]

    Sripada, Yaji

    turbines and neonatal intensive care unit (NICU). In the domain of gas turbines we are working on summarizing sensor data from an op- erational gas turbine (Yu et. al., 2003) for the maintenance engineersSUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud

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

    E-Print Network [OSTI]

    Reiter, Ehud

    turbines and neonatal intensive care unit (NICU). In the domain of gas turbines we are working on summarizing sensor data from an opera- tional gas turbine (Yu et. al., 2003) for the maintenance engineersSUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of Solar 2011, American Solar Energy Society, Raleigh, NC.Description and validation. Solar Energy, 73 (5), 307-317.forecast database. Solar Energy, Perez, R. , S. Kivalov, J.

  14. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

    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).

  15. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    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).

  16. Radiation fog forecasting using a 1-dimensional model 

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01

    weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray...

  17. Inclusion of biomass burning in WRF-Chem: Impact of wildfires on weather forecasts

    SciTech Connect (OSTI)

    Grell, G. A.; Freitas, Saulo; Stuefer, Martin; Fast, Jerome D.

    2011-06-06

    A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather forecasts using model resolutions of 10km and 2km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the final emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 hours of the integration, but significantly stronger storms during the afternoon hours.

  18. Where do Weather Forecasts and Climate Predictions Come From?

    E-Print Network [OSTI]

    Anderson, Charles W.

    on some aspect of the atmosphere. One sub-model is the solar flux model. Observations Prediction #12;3 The Solar Flux Model Public1.f Solar Flux Model The Public1.f Solar Flux Model is a Fortran program How do we get cloud properties from the spectrum BUT Cloud Observations #12;5 Inverting the Solar Flux

  19. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Company, AIKEN, SC (United States)

    1998-08-01

    This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space and time-dependent meteorological data for use in the WIND System dispersion models.

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

    E-Print Network [OSTI]

    Baran, Sándor

    2014-01-01

    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...

  1. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

    Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

  2. A Multi-period Equilibrium Pricing Model of Weather Derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01

    2002). On modelling and pricing weather derivatives. Applied2003). Arbitrage-fee pricing of weather derivatives based onfects and valuation of weather derivatives. The Financial

  3. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    SciTech Connect (OSTI)

    Chiswell, S.; Buckley, R.

    2009-01-15

    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.

  4. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

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

    2008-03-20

    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.

  5. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  6. Regional weather modeling on parallel computers.

    SciTech Connect (OSTI)

    Baillie, C.; Michalakes, J.; Skalin, R.; Mathematics and Computer Science; NOAA Forecast Systems Lab.; Norwegian Meteorological Inst.

    1997-01-01

    This special issue on 'regional weather models' complements the October 1995 special issue on 'climate and weather modeling', which focused on global models. In this introduction we review the similarities and differences between regional and global atmospheric models. Next, the structure of regional models is described and we consider how the basic algorithms applied in these models influence the parallelization strategy. Finally, we give a brief overview of the eight articles in this issue and discuss some remaining challenges in the area of adapting regional weather models to parallel computers.

  7. Extended Abstract, 20th Conf. Weather Analysis and Forecasting/ 16th Conf. Numerical Weather Prediction

    E-Print Network [OSTI]

    Droegemeier, Kelvin K.

    ) and of real radar data by Dowell et al. (2003). All three studies used the same anelastic cloud model of Sun

  8. Monthly Weather Review EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    Monthly Weather Review EARLY ONLINE RELEASE This is a preliminary PDF of the author into numerical weather4 prediction models can improve precipitation forecasts and extend prediction capabilities5 that assimilates precipitation-affected microwave radiances into the7 Weather Research and Forecasting (WRF) model

  9. Stochastic Parameterization: Towards a new view of Weather and Climate Models

    E-Print Network [OSTI]

    Berner, Judith; Batte, Lauriane; De La Camara, Alvaro; Crommelin, Daan; Christensen, Hannah; Colangeli, Matteo; Dolaptchiev, Stamen; Franzke, Christian L E; Friederichs, Petra; Imkeller, Peter; Jarvinen, Heikki; Juricke, Stephan; Kitsios, Vassili; Lott, Franois; Lucarini, Valerio; Mahajan, Salil; Palmer, Timothy N; Penland, Cecile; Von Storch, Jin-Song; Sakradzija, Mirjana; Weniger, Michael; Weisheimer, Antje; Williams, Paul D; Yano, Jun-Ichi

    2015-01-01

    The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides more skillful estimates of uncertainty, but is also extremely promising for reducing longstanding climate biases and relevant for determining the climate response to forcings such as e.g., an increase of CO2. This article highlights recent results from different research groups which show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface and cryosphere of comprehensive weather and climate models a) gives rise to more reliable probabilistic forecasts of weather and climate and b) reduces systematic model bias. We make a case that the use of mathematically ...

  10. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  11. ADAPTIVE GRIDS IN WEATHER AND CLIMATE MODELING

    E-Print Network [OSTI]

    Jablonowski, Christiane

    ADAPTIVE GRIDS IN WEATHER AND CLIMATE MODELING by Christiane Jablonowski A dissertation submitted adaptive grid library that he wrote for his Ph.D. thesis in the Electrical Engineering and Computer Science as a postdoctoral researcher. In addition, thanks to Detlev Majewski from the German Weather Service DWD

  12. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

    This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

  13. Funding Opportunity Announcement for Wind Forecasting Improvement...

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

    that take place in complex terrain, this funding opportunity will improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

  14. Upcoming Funding Opportunity for Wind Forecasting Improvement...

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

    processes that take place in complex terrain, this funding would improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

  15. Towards Ultra-High Resolution Models of Climate and Weather

    E-Print Network [OSTI]

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2008-01-01

    Models of Climate and Weather Michael Wehner, Leonid Oliker,modeling climate change and weather prediction is one of thedelity in both short term weather prediction and long term

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

  17. 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...

  18. COSPAR/ILWS roadmap on space weather research and forecasting: community input COSPAR and the International Living With a Star (ILWS) steering committee have commissioned a strategic

    E-Print Network [OSTI]

    Schrijver, Karel

    COSPAR/ILWS roadmap on space weather research and forecasting: community input commissioned a strategic planning activity (or roadmap) focusing on the ability access as supplemental information to the roadmap report. In order

  19. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN 2011, in final form 26 May 2012) ABSTRACT Probabilistic forecasts of wind vectors are becoming critical with univariate quantities, statistical approaches to wind vector forecasting must be based on bivariate

  20. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc in the context of wind power, where under- forecasting and overforecasting carry different financial penal- ties, calibrated and sharp probabilistic forecasts can help to make wind power a more financially competitive alter

  1. Journal of Atmospheric and Solar-Terrestrial Physics 66 (2004) 14911497 Sun-to-magnetosphere modeling: CISM forecast model

    E-Print Network [OSTI]

    2004-01-01

    -to-magnetosphere modeling: CISM forecast model development using linked empirical methods D.N. Bakera,Ã, R.S. Weigela , E Space Weather Modeling (CISM) is to provide linked end-to- end models of the connected Sun­Earth system. It is envisioned that the ultimate product of the CISM effort will be a single, physics-based (i.e., ``forward

  2. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    0400Z on the 18 th the wind is forecast at 15Knots blowingforecast for the day for the quarter-hour period , representing the windthe forecast is valid. The TAF predicts the wind speed, wind

  3. Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction

    E-Print Network [OSTI]

    McGovern, Amy

    Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1 dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun, current techniques for predicting severe weather are tied to specific characteristics of the radar systems

  4. CROPS AND SOILS RESEARCH PAPER Improved weather-based late blight risk management

    E-Print Network [OSTI]

    Douches, David S.

    CROPS AND SOILS RESEARCH PAPER Improved weather-based late blight risk management: comparing models of weather data. Although many new digital weather and forecast datasets are gridded data, the current improvements made to an artificial neuralnetwork for forecasting weather-based potato late blight (Phytophthora

  5. Published in proceedings of the 15 th IMACS'97 World Congress, August 1997, Berlin, Germany, Wissenshaft & Technik Verlag, Vol. 4, pp. 571--576. The CTADEL Application Driver for Numerical Weather Forecast Systems

    E-Print Network [OSTI]

    van Engelen, Robert A.

    , Wissenshaft & Technik Verlag, Vol. 4, pp. 571--576. The CTADEL Application Driver for Numerical Weather@cs.leidenuniv.nl Keywords: code generation; high performance computing; numerical weather forecasting ABSTRACT The CTADEL numerical weather forecast system. As such, the CTADEL system can be viewed as a problem­solving environment

  6. Adaptive Grids for Weather and Climate Models C. Jablonowski

    E-Print Network [OSTI]

    Stout, Quentin F.

    Adaptive Grids for Weather and Climate Models C. Jablonowski National Center for Atmospheric have been discussed in the literature. Nested-grid approaches are widely used at National Weather.: ADAPTIVE GRIDS FOR WEATHER AND CLIMATE MODELS two grids coincide. Other variable-resolution models

  7. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    for the same data. Two methods are described for forecasting daily peak loads up to one week ahead through, including generator unit commitment, hydro-thermal coordination, short-term maintenance, fuel allocation forecasting accuracies. STLF forecasting covers the daily peak load, total daily energy, and daily load curve

  8. Nimble@ITCEcnoGrid: A Grid in Research Domain for Weather Forecasting

    E-Print Network [OSTI]

    Dhir, Vijay; Dutta, Maitreyee; 10.5121/ijgca.2011.2404

    2012-01-01

    Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematical model to simulate salient features of Physical universe. These models can approximate reality at many levels of scale such as atomic nucleus, Earth's biosphere & weather/climate assessment. If the computer power is greater, the greater will be the accuracy in approximation i.e. close will be the approximation to the reality. The speed of the computer required for solution of such problems require computers with processing power of teraflops to Pets flops speed.. The way to speed up the computation is to "parallelize" it. One of the approach is to use multimillion dollar Supercomputer or use Computational Grid (which is also called poor man's supercomputer) having geographically distributed resources e.g. SETI@home (Used to detect radio waves emitted by intelligent civilizations outside earth) has 4.6 million participants computers. There are many alternatives tools available to achieve this goal like Glob...

  9. Environmental Physics Group Newsletter September 2013 Weather and Climate Modelling

    E-Print Network [OSTI]

    Williams, Paul

    Environmental Physics Group Newsletter September 2013 9 Weather and Climate Modelling Imperial and the Grantham Institute for Climate Change A half-day meeting on the topic of 'Should weather and climate increasingly common to represent subgrid-scale features in weather and climate models by including random noise

  10. Modeling Weather Impact on a Secondary Electrical Grid

    E-Print Network [OSTI]

    Wang, Dingquan

    Weather can cause problems for underground electrical grids by increasing the probability of serious “manhole events” such as fires and explosions. In this work, we compare a model that incorporates weather features ...

  11. Prediction Space Weather Using an Asymmetric Cone Model for Halo CMEs

    E-Print Network [OSTI]

    G. Michalek; N. Gopalswamy; S. Yashiro

    2007-10-24

    Halo coronal mass ejections (HCMEs) are responsible of the most severe geomagnetic storms. A prediction of their geoeffectiveness and travel time to Earth's vicinity is crucial to forecast space weather. Unfortunately coronagraphic observations are subjected to projection effects and do not provide true characteristics of CMEs. Recently, Michalek (2006, {\\it Solar Phys.}, {\\bf237}, 101) developed an asymmetric cone model to obtain the space speed, width and source location of HCMEs. We applied this technique to obtain the parameters of all front-sided HCMEs observed by the SOHO/LASCO experiment during a period from the beginning of 2001 until the end of 2002 (solar cycle 23). These parameters were applied for the space weather forecast. Our study determined that the space speeds are strongly correlated with the travel times of HCMEs within Earth's vicinity and with the magnitudes related to geomagnetic disturbances.

  12. EXTENSIONS OF GENERALIZED LINEAR MODELING APPROACH TO STOCHASTIC WEATHER GENERATORS

    E-Print Network [OSTI]

    Katz, Richard

    weather) -- Software R open source statistical programming language: Function glm "Family;(2) Generalized Linear Models Statistical Framework -- Multiple Regression Analysis (Linear model or LM) Response

  13. Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction

    SciTech Connect (OSTI)

    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

    2004-05-06

    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 that the GCM parameterizations of unresolved processes, in particular, 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, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a 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 tested in the same framework. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy 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.

  14. Error growth in poor ECMWF forecasts over the contiguous United States 

    E-Print Network [OSTI]

    Modlin, Norman Ray

    1993-01-01

    Successive improvements to the European Center for Medium-range Weather Forecasting model have resulted in improved forecast performance over the Contiguous United States (CONUS). While the overall performance of the model ...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    and validation.   Solar Energy.   73:5, 307? Perez, R. , irradiance forecasts for solar energy applications based on using satellite data.   Solar Energy 67:1?3, 139?150.  

  16. Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction

    E-Print Network [OSTI]

    Wirosoetisno, Djoko

    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 in weather dynamics, e.g., the asymptotic balance seen in high and low pressure systems. Aims of the project

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

    SciTech Connect (OSTI)

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

    2007-06-01

    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.

  18. Motivation Methods Model configuration Results Forecasting Summary & Outlook Retrieving direct and diffuse radiation with the

    E-Print Network [OSTI]

    Heinemann, Detlev

    Motivation Methods Model configuration Results Forecasting Summary & Outlook 1/ 14 Retrieving. 17, 2015 #12;Motivation Methods Model configuration Results Forecasting Summary & Outlook 2/ 14 Motivation Sky Imager based shortest-term solar irradiance forecasts for local solar energy applications

  19. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 – 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

  20. RECONSTRUCTING CORONAL MASS EJECTIONS WITH COORDINATED IMAGING AND IN SITU OBSERVATIONS: GLOBAL STRUCTURE, KINEMATICS, AND IMPLICATIONS FOR SPACE WEATHER FORECASTING

    SciTech Connect (OSTI)

    Liu Ying; Luhmann, Janet G.; Lin, Robert P.; Bale, Stuart D. [Space Sciences Laboratory, University of California, Berkeley, CA 94720 (United States); Thernisien, Arnaud [Universities of Space Research Association, Columbia, MD 21044 (United States); Vourlidas, Angelos [Space Science Division, Naval Research Laboratory, Washington, DC 20375 (United States); Davies, Jackie A., E-mail: liuxying@ssl.berkeley.ed [Space Science and Technology Department, Rutherford Appleton Laboratory, Didcot (United Kingdom)

    2010-10-20

    We reconstruct the global structure and kinematics of coronal mass ejections (CMEs) using coordinated imaging and in situ observations from multiple vantage points. A forward modeling technique, which assumes a rope-like morphology for CMEs, is used to determine the global structure (including orientation and propagation direction) from coronagraph observations. We reconstruct the corresponding structure from in situ measurements at 1 AU with the Grad-Shafranov method, which gives the flux-rope orientation, cross section, and a rough knowledge of the propagation direction. CME kinematics (propagation direction and radial distance) during the transit from the Sun to 1 AU are studied with a geometric triangulation technique, which provides an unambiguous association between solar observations and in situ signatures; a track fitting approach is invoked when data are available from only one spacecraft. We show how the results obtained from imaging and in situ data can be compared by applying these methods to the 2007 November 14-16 and 2008 December 12 CMEs. This merged imaging and in situ study shows important consequences and implications for CME research as well as space weather forecasting: (1) CME propagation directions can be determined to a relatively good precision as shown by the consistency between different methods; (2) the geometric triangulation technique shows a promising capability to link solar observations with corresponding in situ signatures at 1 AU and to predict CME arrival at the Earth; (3) the flux rope within CMEs, which has the most hazardous southward magnetic field, cannot be imaged at large distances due to expansion; (4) the flux-rope orientation derived from in situ measurements at 1 AU may have a large deviation from that determined by coronagraph image modeling; and (5) we find, for the first time, that CMEs undergo a westward migration with respect to the Sun-Earth line at their acceleration phase, which we suggest is a universal feature produced by the magnetic field connecting the Sun and ejecta. The importance of having dedicated spacecraft at L4 and L5, which are well situated for the triangulation concept, is also discussed based on the results.

  1. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    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.

  2. PI Research Organisation Project Title NE/J024678/1 Dr Christopher Davis University of Reading Driving space weather forecasts with real data

    E-Print Network [OSTI]

    /1 A modeling study of the impact of mesoscale air sea interactions over the Gulf Stream on weather and climate

  3. Astron. Nachr. / AN 328, No. 3/4, 329 338 (2007) / DOI 10.1002/asna.200610739 Towards using modern data assimilation and weather forecasting

    E-Print Network [OSTI]

    Brun, Allan Sacha

    2007-01-01

    solar wind and energetic plasma eruptions a direct impact on the Earth's magnetosphere and ionosphere modern data assimilation and weather forecasting methods in solar physics A.S. Brun DSM/DAPNIA/SAp, CEA words Sun: activity ­ Sun: magnetic fields ­ Sun: rotation ­ solar-terrestrial relation ­ methods

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

    SciTech Connect (OSTI)

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

    2014-06-01

    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.

  5. USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING

    E-Print Network [OSTI]

    ~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

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

    E-Print Network [OSTI]

    Hudlow, M.D.

    1967-01-01

    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...

  7. Influences of soil moisture and vegetation on convective precipitation forecasts

    E-Print Network [OSTI]

    Robock, Alan

    Influences of soil moisture and vegetation on convective precipitation forecasts over the United and vegetation on 30 h convective precipitation forecasts using the Weather Research and Forecasting model over, the complete removal of vegetation produced substantially less precipitation, while conversion to forest led

  8. Lateral boundary errors in regional numerical weather

    E-Print Network [OSTI]

    ?umer, Slobodan

    Lateral boundary errors in regional numerical weather prediction models Author: Ana Car Advisor, they describe evolution of atmospher - weather forecast. Every NWP model solves the same system of equations (1: assoc. prof. dr. Nedjeljka Zagar January 5, 2015 Abstract Regional models are used in many national

  9. GENERALIZED LINEAR MODELING APPROACH TO STOCHASTIC WEATHER GENERATORS

    E-Print Network [OSTI]

    Katz, Richard

    ) Multisites (Spatial dependence of daily weather) -- Software R open source statistical programming language (Capable of "reproducing" any desired statistic) -- Disadvantages Synthetic weather looks too much like") Not amenable to uncertainty analysis #12;#12;#12;(2) Generalized Linear Models · Statistical Framework

  10. Weather

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired SolarAbout /Two0Photos and Videos/01/2012 Page| National NuclearWeather

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

    E-Print Network [OSTI]

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations

  12. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    Reports and Publications (EIA)

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  13. 13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS FOR SEVERE CONVECTIVE WEATHER

    E-Print Network [OSTI]

    of computing power, innovative numerical systems, and assimilation of observations at high spatial and temporal system as a means by which model error and uncertainty can be quantified in the forecast. Employing13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS

  14. Interactive Weather Simulation and Visualization on a Display Wall

    E-Print Network [OSTI]

    Ha, Phuong H.

    Interactive Weather Simulation and Visualization on a Display Wall with Many-Core Compute Nodes B.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 forecasting are typically run at predetermined times at a predetermined resolution and a fixed

  15. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

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

    2014-10-27

    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.

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

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16

    . This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%....

  17. ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed

    E-Print Network [OSTI]

    Chapter 73 ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed Abstract The class of ARM (Autoregressive Modular) processes is a class of stochastic processes, defined by a non- linear autoregressive scheme with modulo-1 reduction and additional transformations. ARM processes

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    of variability for solar power plants.   While  NWP model operation of solar thermal power  plants, the management of 

  19. Assessing forecast uncertainties in a VECX model for Switzerland: an exercise in forecast combination across models and observation windows

    E-Print Network [OSTI]

    Assenmacher-Wesche, Katrin; Pesaran, M. Hashem

    horizons of up to eight quarters ahead since this is the rele- vant time horizon for central banks when setting interest rates. Table 6 shows the RMSFE, the bias and the hit rate of forecasts based on the VECX*(2,2) model for the longest estimation window...

  20. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect (OSTI)

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

    2011-03-28

    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.

  1. Evaluating climate models: Should we use weather or climate observations?

    SciTech Connect (OSTI)

    Oglesby, Robert J [ORNL; Erickson III, David J [ORNL

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their ability to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.

  2. A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting

    E-Print Network [OSTI]

    Hsieh, William

    A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting Song Cai to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models forecasts for extreme events, namely poor air quality events defined as having ozone concentration 82 ppb

  3. THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF MODELS AND SUBSEQUENT

    E-Print Network [OSTI]

    Xue, Ming

    THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF NOAA's Hazardous Weather Testbed (HWT) is a joint facility managed by the National Severe Storms Laboratory (NSSL), the Storm Prediction Center (SPC), and the NWS Oklahoma City/Norman Weather Forecast

  4. A multi-period equilibrium pricing model of weather derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2010-01-01

    Y. : Valuation and hedging of weather derivatives on monthlyJ. Risk 31. Yoo, S. : Weather derivatives and seasonaleffects and valuation of weather derivatives. Financ. Rev.

  5. 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]

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet

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

    SciTech Connect (OSTI)

    Chiswell, S

    2009-01-11

    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.

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

    E-Print Network [OSTI]

    Irwin, Mark E.

    2005-01-01

    conditional on observed (or forecasted) meteorology including temperature, humidity, pressure, and wind speed, defining the spatial­temporal extent of episodes of dangerous air quality, forecasting urban and areaAtmospheric Environment 39 (2005) 1373­1382 A hierarchical Bayesian model to estimate and forecast

  8. Atmospheric Test Models and Numerical Experiments for the Simulation of the Global Distributions of Weather Data Transponders III. Horizontal Distributions

    SciTech Connect (OSTI)

    Molenkamp, C.R.; Grossman, A.

    1999-12-20

    A network of small balloon-borne transponders which gather very high resolution wind and temperature data for use by modern numerical weather predication models has been proposed to improve the reliability of long-range weather forecasts. The global distribution of an array of such transponders is simulated using LLNL's atmospheric parcel transport model (GRANTOUR) with winds supplied by two different general circulation models. An initial study used winds from CCM3 with a horizontal resolution of about 3 degrees in latitude and longitude, and a second study used winds from NOGAPS with a 0.75 degree horizontal resolution. Results from both simulations show that reasonable global coverage can be attained by releasing balloons from an appropriate set of launch sites.

  9. 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)

    Finley, Cathy

    2014-04-30

    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.

  10. Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western United States based on Weather Research and Forecasting chemistry and regional climate simulations

    SciTech Connect (OSTI)

    Qian, Yun; Gustafson, William I.; Leung, Lai-Yung R.; Ghan, Steven J.

    2009-02-14

    Radiative forcing induced by soot on snow is a major anthropogenic forcing affecting the global climate. However, it is uncertain how the soot-induced snow albedo perturbation affects regional snowpack and the hydrological cycle. In this study we simulated the deposition of soot aerosol on snow and investigated the resulting impact on snowpack and the surface water budget in the western United States. A yearlong simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine an annual budget of soot deposition, followed by two regional climate simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the net solar radiation flux at the surface during late winter to early spring, increase the surface air temperature, reduce snow water equivalent amount, and lead to reduced snow accumulation and less spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow covered regions. Our simulations indicate that the change of maximum snow albedo induced by soot on snow contributes to 60% of the net albedo reduction over the central Rockies. Snowpack reduction accounts for the additional 40%.

  11. Coupled Weather and Wildfire Behavior Modeling at Los Alamos: An Overview

    SciTech Connect (OSTI)

    Bossert, James E.; Harlow, Francis H.; Linn, Rodman R.; Reisner, Jon M.; White, Andrew B.; Winterkamp, Judith L.

    1997-12-31

    Over the past two years, researchers at Los Alamos National Laboratory (LANL) have been engaged in coupled weather/wildfire modeling as part of a broader initiative to predict the unfolding of crisis events. Wildfire prediction was chosen for the following reasons: (1) few physics-based wild-fire prediction models presently exist; (2) LANL has expertise in the fields required to develop such a capability; and (3) the development of this predictive capability would be enhanced by LANL`s strength in high performance computing. Wildfire behavior models have historically been used to predict fire spread and heat release for a prescribed set of fuel, slope, and wind conditions (Andrews 1986). In the vicinity of a fire, however, atmospheric conditions are constantly changing due to non-local weather influences and the intense heat of the fire itself. This non- linear process underscores the need for physics-based models that treat the atmosphere-fire feedback. Actual wildfire prediction with full-physics models is both time-critical and computationally demanding, since it must include regional- to local-scale weather forecasting together with the capability to accurately simulate both intense gradients across a fireline, and atmosphere/fire/fuel interactions. Los Alamos has recently (January 1997) acquired a number of SGI/Cray Origin 2000 machines, each presently having 32 to 64 processors. These high performance computing systems are part of the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). While offering impressive performance now, upgrades to the system promise to deliver over 1 Teraflop (10(12) floating point operations per second) at peak performance before the turn of the century.

  12. Traffic congestion forecasting model for the INFORM System. Final report

    SciTech Connect (OSTI)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  13. Resolution dependence in modeling extreme weather events.

    SciTech Connect (OSTI)

    Taylor, J.; Larson, J.

    2001-04-13

    At Argonne National Laboratory we have developed a high performance regional climate modeling simulation capability based on the NCAR MM5v3.4. The regional climate simulation system at Argonne currently includes a Java-based interface to allow rapid selection and generation of initial and boundary conditions, a high-performance version of MM5v3.4 modified for long climate simulations on our 512-processor Beowulf cluster (Chiba City), an interactive Web-based analysis tool to facilitate analysis and collaboration via the Web, and an enhanced version of the CAVE5d software capable of working with large climate data sets. In this paper we describe the application of this modeling system to investigate the role of model resolution in predicting extreme events such as the ''Hurricane Huron'' event of 11-15 September 1996. We have performed a series of ''Hurricane Huron'' experiments at 80, 40, 20, and 10 km grid resolution over an identical spatiotemporal domain. We conclude that increasing model resolution leads to dramatic changes in the vertical structure of the simulated atmosphere producing significantly different representations of rainfall and other parameters critical to the assessment of impacts of climate change.

  14. Hydrological Forecasting Improvements Primary Investigator: Thomas Croley -NOAA GLERL (Emeritus)

    E-Print Network [OSTI]

    multiple data streams in a near-real-time manner and incorporate them into the AHPS data base, run for matching weather forecasts with historical data, and prepare extensive forecasts of hydrology probabilities maximum use of all available information and be based on efficient and true hydrological process models

  15. USE OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION

    E-Print Network [OSTI]

    USE OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION by ADAM N OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION written by Adam N. Hobson has and Architectural Engineering) Use of a Stochastic Weather Generator in a Watershed Model for Streamflow Simulation

  16. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

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

    2013-03-19

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (‘stochastic’) model with the weather forecast model (‘deterministic’) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

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

    E-Print Network [OSTI]

    Sitnov, Mikhail I.

    Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting issue. This paper presents a data-derived model of the solar wind-magnetosphere coupling that combines of solar wind-magnetosphere coupling: From modeling to forecasting, Geophys. Res. Lett., 31, L08802, doi:10

  18. The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models

    E-Print Network [OSTI]

    Zhou, Shujia

    2009-01-01

    Acceleration of Numerical Weather Prediction,” ProceedingsComputer Systems for Climate and Weather Models Shujia Zhouprocesses in climate and weather models demands a continual

  19. Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic st

    E-Print Network [OSTI]

    Post, David M.

    Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic steps to be better informed about and prepared for Hurricanes

  20. Combining Weather Data for a Dataset Sufficient for Generating High-Resolution Weather Prediction Models

    SciTech Connect (OSTI)

    Fox, Jared B.; Ghan, Steven J.

    2004-03-01

    Assessments of the effects of climate change typically require information at scales of 10 km or less. In regions with complex terrain, much of the spatial variability in climate (temperature, precipitation, and snow water) occurs on scales below 10 km. Since the typical global climate model simulations grid size is more than 200 km, it is necessary to develop models with much higher resolution. Unfortunately, no datasets currently produced are both highly accurate and provide data at a sufficiently high resolution. As a result, current global climate models are forced to ignore the important climate variations that occur below the 200 km scale. This predicament prompted the creation of a global hybrid dataset with information for precipitation, temperature, and relative humidity. The resulting dataset illustrated the importance of having high-resolution datasets and gives clear proof that regions with complex terrain require a fine resolution grid to give an accurate represent at ion of their climatology. For example, the Andes Mountains in Chile cause a temperature shift of more than 25C within the same area as a single 2.5 grid cell from the NCEP dataset. Fortunately the CRU, U.D., GPCP, and NCEP datasets, when hybridized, are able to provide both precision and satisfactory resolution with global coverage. This composite will enable the development of both high-resolution models and quality empirical downscaling methods--both of which are necessary for scientists to more accurately predict the effects of global climate change. Without accurate long-term forecasts, climatologists and policy makers will not have the tools they need to effectively reduce the negative effects human activity have on the earth.

  1. A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities

    E-Print Network [OSTI]

    A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities Ke Xu of the technique and its potential for nowcasting weather radar reflectivities. Key Words: Bayesian, dilation to nowcasting weather radar reflectivities into two general categories. The first is the use of simple

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

    E-Print Network [OSTI]

    Xue, Ming

    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

  3. Atmospheric test models and numerical experiments for the simulation of the global distribution of weather data transponders

    SciTech Connect (OSTI)

    Grossman, A; Molenkamp, C R

    1999-08-25

    A proposal has been made to establish a high density global network of atmospheric micro transponders to record time, temperature, and wind data with time resolution of {le} 1 minute, temperature accuracy of {+-} 1 K, spatial resolution no poorer than {approx}3km horizontally and {approx}0.1km vertically, and 2-D speed accuracy of {le} 1m/s. This data will be used in conjunction with advanced numerical weather prediction models to provide increases in the reliability of long range weather forecasts. Major advances in data collection technology will be required to provide the proposed high-resolution data collection network. Systems studies must be undertaken to determine insertion requirements, spacing, and evolution of the transponder ensemble, which will be used to collect the data. Numerical models which provide realistic global weather pattern simulations must be utilized in order to perform these studies. A global circulation model with a 3{sup o} horizontal resolution has been used for initial simulations of the generation and evolution of transponder distributions. These studies indicate that reasonable global coverage of transponders can be achieved by a launch scenario consisting of the sequential launch of transponders at specified heights from a globally distributed set of launch sites.

  4. Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid dynamicalstatistical model

    E-Print Network [OSTI]

    Webster, Peter J.

    Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid 20 September 2010; published 9 November 2010. [1] A hybrid forecast model for seasonal hurricane between the number of seasonal hurricane and the large scale variables from ECMWF hindcasts. The increase

  5. FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO-MEMBER ENSEMBLE

    E-Print Network [OSTI]

    Schubert, Wayne H.

    system using an efficient multigrid barotropic vorticity equation model (MBAR). Five perturbation classes Advisor Department Head ii #12;ABSTRACT OF THESIS FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO forecasts. These increases have been largely driven by improved numerical weather prediction models

  6. A, Science Service Feature ? WHY TRE WEATHER ?

    E-Print Network [OSTI]

    No. 228 May 80 A, Science Service Feature ? WHY TRE WEATHER ? Dr, Charles E', Brooks of C 1ark% carefully follow the Weather Bureau's forecast. Tho khserver at the central office c)f ,the Weather Bureau unnecessarily, neither does he get wet. Though the weather rilanls wife scoffs at his forecasts, she always asks

  7. Green Bank Weather Dana S. Balser

    E-Print Network [OSTI]

    Balser, Dana S.

    Green Bank Weather Dana S. Balser #12;Weather Resources 1. Weather Stations 2. Weather Forecasts (NOAA/Maddalena) 3. Pyrgeometer 4. 86 GHz Tipping Radiometer 5. 12 GHz Interferometer #12;Weather Parameters 1 May 2004 to 1 March 2007 speedwindousInstantaneV :Hz)(12StationWeather e

  8. Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model

    E-Print Network [OSTI]

    Surussavadee, Chinnawat

    2007-01-01

    This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for ...

  9. Multidimensional approaches to performance evaluation of competing forecasting models 

    E-Print Network [OSTI]

    Xu, Bing

    2009-01-01

    The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions ...

  10. NOAA's National Weather Service Building a Weather-Ready Nation

    E-Print Network [OSTI]

    NOAA's National Weather Service Building a Weather-Ready Nation For more information, please visit: www.noaa.gov and www.nws.noaa.gov NOAA's National Weather Service (NWS) is the Nation's official source for weather and water data, forecasts, and warnings. From information accessed on your smartphone

  11. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology

    Broader source: Energy.gov [DOE]

    As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an...

  12. Reverse supply chain forecasting and decision modeling for improved inventory management

    E-Print Network [OSTI]

    Petersen, Brian J. (Brian Jude)

    2013-01-01

    This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of ...

  13. Comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate. 

    E-Print Network [OSTI]

    Balaban, Ercan

    2002-01-01

    The relative out-of-sample forecasting quality of symmetric and asymmetric conditional volatility models of an exchange rate differs according to the symmetric and asymmetric evaluation criteria as well as a regression-based ...

  14. Using multi-layer models to forecast gas flow rates in tight gas reservoirs 

    E-Print Network [OSTI]

    Jerez Vera, Sergio Armando

    2007-04-25

    USING MULTI-LAYER MODELS TO FORECAST GAS FLOW RATES IN TIGHT GAS RESERVOIRS A Thesis by SERGIO ARMANDO JEREZ VERA Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE December 2006 Major Subject: Petroleum Engineering USING MULTI-LAYER MODELS TO FORECAST GAS FLOW RATES IN TIGHT GAS RESERVOIRS A Thesis by SERGIO ARMANDO JEREZ VERA Submitted...

  15. A baseline model for utility bill analysis using both weather and non-weather-related variables

    SciTech Connect (OSTI)

    Sonderegger, R.C. [SRC Systems, Inc., Berkeley, CA (United States)

    1998-12-31

    Many utility bill analyses in the literature rely only on weather-based correlations. While often the dominant cause of seasonal variations in utility consumption, weather variables are far from the only determinant factors. Vacation shutdowns, plug creep, changes in building operation and square footage, and plain poor correlation are all too familiar to the practicing performance contractor. This paper presents a generalized baseline equation, consistent with prior results by others but extended to include other, non-weather-related independent variables. Its compatibility with extensive prior research by others is shown, as well as its application to several types of facilities. The baseline equation, as presented, can accommodate up to five simultaneous independent variables for a maximum of eight free parameters. The use of two additional, empirical degree-day threshold parameters is also discussed. The baseline equation presented here is at the base of a commercial utility accounting software program. All case studies presented to illustrate the development of the baseline equation for each facility are drawn from real-life studies performed by users of this program.

  16. Intercomparison of mesoscale meteorological models for precipitation forecasting Hydrology and Earth System Sciences, 7(6), 799811 (2003) EGU

    E-Print Network [OSTI]

    Boyer, Edmond

    2003-01-01

    Intercomparison of mesoscale meteorological models for precipitation forecasting 799 Hydrology and Earth System Sciences, 7(6), 799811 (2003) © EGU Intercomparison of mesoscale meteorological models

  17. Severe Weather on the Web: Computer Lab for WEST Severe Weather Module

    E-Print Network [OSTI]

    Jiang, Haiyan

    Severe Weather on the Web: Computer Lab for WEST Severe Weather Module Summary: Students Weather Service-- National Weather Hazards Website: http://www.weather.gov/view/largemap.php --This termforecasts in the lower 48 USstates. Definitions Forecast--The prediction of what the weather

  18. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect (OSTI)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  19. Disaggregation of spatial rainfall fields for hydroloigcal modelling Hydrology and Earth System Sciences, 5(2), 165173 (2001) EGS

    E-Print Network [OSTI]

    Boyer, Edmond

    2001-01-01

    to investigate the evolution of the climate (DOE, 1996) while at the regional scale, mesoscale models are weather. In the case of rainfall forecasting, some combination of the mesoscale forecast and a finer scale advection

  20. A global aerosol model forecast for the ACE-Asia field experiment Mian Chin,1,2

    E-Print Network [OSTI]

    Chin, Mian

    layer. We attribute this ``missing'' dust source to desertification regions in the Inner Mongolia forecasting. After incorporating the desertification sources, the model is able to reproduce the observed

  1. BRIDGING WEATHER AND CLIMATE IN RESEARCH AND

    E-Print Network [OSTI]

    Johnson, Richard H.

    BRIDGING WEATHER AND CLIMATE IN RESEARCH AND FORECASTS OF THE GLOBAL MONSOON SYSTEM by Chih and forecast issues ranging from mesoscale weather to climate change in various monsoon regions of the globe organized under the new World Weather Research Programme (WWRP). The previous emphasis of this workshop

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

    SciTech Connect (OSTI)

    Auffhammer, Maximilian; Hsiang, Solomon M.; Schlenker, Wolfram; Sobel, Adam H.

    2013-06-28

    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.

  3. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  4. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  5. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens to the Klim wind farm using three WPPT forecasts based on different weather forecasting systems. It is shown of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  6. An Investigation of the Limitations in Plume Rise Models used in Air Quality Forecast Systems

    E-Print Network [OSTI]

    Collins, Gary S.

    are important for predicting pollutants regulated by National Ambient Air Quality Standards (NAAQS). NAAQS pollutants, include CO, NO2, PM2.5, PM10, O3, and SO2, are considered deleterious to public health and airAn Investigation of the Limitations in Plume Rise Models used in Air Quality Forecast Systems 1

  7. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect (OSTI)

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  8. Discussion of long-range weather prediction

    SciTech Connect (OSTI)

    Canavan, G.H.

    1998-09-10

    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.

  9. The widely used Weather Research and Forecasting (WRF) model provides a few land surface schemes

    E-Print Network [OSTI]

    Menut, Laurent

    is com- puted from the surface energy balance using a force- restore algorithm for heat exchange within linearised surface energy balance equation representing the combined ground-vegetation sur- face. Soil (USA) and widely used in the World meteorolo- gical and air quality communities. WRF provides a choice

  10. Space Weather Forecasting Identifying periodic block-structured models to predict

    E-Print Network [OSTI]

    lines, which can overwhelm and destroy transform- ers and electrical networks [2]. Figure 7 shows damage in the ionosphere. To predict these large ejections of magnetic and plasma energy, satellites monitor the solar past the Earth and the other planets in the form of the solar wind. The Sun's magnetic field, which

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII JumpQuarterly Smart GridNorth Carolina: Energy ResourcesLLC JumpMILAGRO

  12. Validation of Global Weather Forecast and Climate Models Over the North

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentric viewingValidating extended MHDCERES/SARB DataSlope of

  13. Social Science in NOAA Weather John Gaynor

    E-Print Network [OSTI]

    Social Science in NOAA Weather Research John Gaynor Director Office of Weather and Air Quality NOAA Impacts Program #12;Vision a society that maximizes the net social benefit of weather information Mission improve the societal benefits of weather forecasting Goal national and international focal point of social

  14. -A Science Service Feature ? WHY THE WEATHER ?

    E-Print Network [OSTI]

    No. 772 Oct. 31 -A Science Service Feature ? WHY THE WEATHER ? By Dr. Charles B. Brooks of Clark University. FORECASTING WEATHER FOR BEES Many people consult the Weather Bureau before planning a picnic o r the service. In the f a l l of 1923 the Weather Bureau started a Special service In theregion north

  15. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  16. Why Models Don%3CU%2B2019%3Et Forecast.

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

  17. Modeling Field-level Irrigation Demands with Changing Weather and Crop Choices

    E-Print Network [OSTI]

    MardanDoost, Babak

    2015-05-31

    . The presented water budget model is capable of estimate daily water demand over space and time under predicted climate and land-use change. The model-predicted irrigation demand was developed based on crop-specific evapotranspiration, weather data, and with 2007...

  18. Air pollution forecasting by coupled atmosphere-fire model WRF and SFIRE with WRF-Chem

    E-Print Network [OSTI]

    Kochanski, Adam K; Mandel, Jan; Clements, Craig B

    2013-01-01

    Atmospheric pollution regulations have emerged as a dominant obstacle to prescribed burns. Thus, forecasting the pollution caused by wildland fires has acquired high importance. WRF and SFIRE model wildland fire spread in a two-way interaction with the atmosphere. The surface heat flux from the fire causes strong updrafts, which in turn change the winds and affect the fire spread. Fire emissions, estimated from the burning organic matter, are inserted in every time step into WRF-Chem tracers at the lowest atmospheric layer. The buoyancy caused by the fire then naturally simulates plume dynamics, and the chemical transport in WRF-Chem provides a forecast of the pollution spread. We discuss the choice of wood burning models and compatible chemical transport models in WRF-Chem, and demonstrate the results on case studies.

  19. Severe Weather Update: JLab Remains in HPC-2 for Nor'easter ...

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

    Severe Weather Update: JLab Remains in HPC-2 for Nor'easter & Hurricane Jefferson Lab's Emergency Management Severe Weather Team continues monitoring the forecasts and conditions...

  20. Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

    SciTech Connect (OSTI)

    Done, James; Holland, Greg; Bruyere, Cindy; Leung, Lai-Yung R.; Suzuki-Parker, Asuka

    2012-06-01

    Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are presented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices. Capsule: "Combining dynamical modeling of high-impact weather using traditional regional climate models with statistical techniques allows for comprehensive sampling of the full distribution, uncertainty estimation, direct assessment of impacts, and increased confidence in future changes."

  1. Regional forecasting with global atmospheric models; Third year report

    SciTech Connect (OSTI)

    Crowley, T.J.; North, G.R.; Smith, N.R.

    1994-05-01

    This report was prepared by the Applied Research Corporation (ARC), College Station, Texas, under subcontract to Pacific Northwest Laboratory (PNL) as part of a global climate studies task. The task supports site characterization work required for the selection of a potential high-level nuclear waste repository and is part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work is under the overall direction of the Office of Civilian Radioactive Waste Management (OCRWM), US Department of Energy Headquarters, Washington, DC. The scope of the report is to present the results of the third year`s work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain several studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals.

  2. MODELLING SURFACE HOAR FORMATION AND EVOLUTION ON MOUNTAIN SLOPES Simon Horton1

    E-Print Network [OSTI]

    Jamieson, Bruce

    evaluates surface hoar size predictions made with empirical weather based models and discusses how buried. Weather station data and forecasted data from the GEM15 numerical weather prediction model were used. The surface energy balance model made good predictions of crystal size with real station data (r2 = 0

  3. NOAA's Proposed Climate Service Background updated 7/13/11 NOAA's shortterm weather forecasts of conditions out to about twoweeks are critical to saving lives and

    E-Print Network [OSTI]

    forecasts of conditions out to about twoweeks are critical to saving lives and property. Similarly, NOAA to saving lives and property. For example: o firefighters in Texas, New Mexico and Arizona used industry estimates it saved $300 million per year in construction costs alone by using temperature trends

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

    E-Print Network [OSTI]

    Kulkarni, Siddhivinayak

    2009-01-01

    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...

  5. Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING ZHANG

    E-Print Network [OSTI]

    Baer, Ferdinand

    Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING scenarios for many time scales, more computer power than is currently available will be needed. One and sometimes with a biosphere included, are very complex and require so much computing power on available

  6. Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model

    E-Print Network [OSTI]

    Marsham, John

    1 Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model Céline;2 Summary Aerosols are known to significantly affect cloud and precipitation patterns and intensity. The impact of changing cloud droplet number concentration (CDNC), on cloud and precipitation evolution can

  7. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  8. Continuous Model Updating and Forecasting for a Naturally Fractured Reservoir 

    E-Print Network [OSTI]

    Almohammadi, Hisham

    2013-07-26

    . Such capabilities allow for a paradigm change in which reservoir management can be looked at as a strategy that enables a semi-continuous process of model updates and decision optimizations instead of being periodic or reactive. This is referred to as closed...

  9. Sun-to-thermosphere simulation of the 28--30 October 2003 storm with the Space Weather Modeling Framework

    E-Print Network [OSTI]

    De Zeeuw, Darren L.

    pipelines, and the electric power grid have all become facts of life; however, they all rely on technologiesSun-to-thermosphere simulation of the 28--30 October 2003 storm with the Space Weather Modeling was carried out with the newly developed Space Weather Modeling Framework (SWMF, see http

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

    SciTech Connect (OSTI)

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

    2008-11-15

    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)

  11. ECMWF analyses and forecasts of 500 mb synoptic-scale activity during wintertime blocking 

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

    An observational study of 500 mb atmospheric blocking is conducted based on an European Centre for Medium-Range Weather Forecasts (ECMWF) wintertime analysis and forecast dataset during dynamic extended range forecasting ...

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

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

    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.

  13. A New Forecasting Model for USD/CNY Exchange Rate

    E-Print Network [OSTI]

    Cai, Zongwu; Chen, Linna; Fang, Ying

    2012-09-18

    hypothesis and using GARCH type models or their variants, most studies found evidence of nonlinearity in volatilities of exchange rates; see, for example, Bollerslev (1990), Brock, Hsieh and Lebaron (1991), Engle, Ito and Lin (1990), West and Cho (1995.... Alternatively, one might consider other smoothing variables used in the literature, such as the moving average technique trading rule (MATTR) Ut,MATTR = Yt?1 ?L j=1 Yt?j/L ? 1 for certain L (say, L = 21), as in Brock, Lakonishock and Lebaron (1992) and Hong...

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

    Reports and Publications (EIA)

    1998-01-01

    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.

  15. Online short-term solar power forecasting

    SciTech Connect (OSTI)

    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)

    2009-10-15

    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)

  16. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    Wind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number weather forecasts and do not take any possible correlation into ac- count. Since wind and wave forecasts

  17. Coupling the high-complexity land surface model ACASA to the mesoscale model WRF

    E-Print Network [OSTI]

    Pyles, R. D.

    In this study, the Weather Research and Forecasting (WRF) model 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 ...

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

    E-Print Network [OSTI]

    Xu, L.

    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 ...

  19. Towards Ultra-High Resolution Models of Climate and Weather

    SciTech Connect (OSTI)

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2007-01-01

    We present a speculative extrapolation of the performance aspects of an atmospheric general circulation model to ultra-high resolution and describe alternative technological paths to realize integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by stability criterion, the solution of the equations of motion dominate the calculation at ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require at least a sustained ten petaflop computer to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of petaflop scale systems. Embedded processor technology could be exploited to tailor a custom machine designed to ultra-high climate model specifications at relatively affordable cost and power considerations. The major conceptual changes required by a kilometer scale climate model are certain to be difficult to implement. Although the hardware, software, and algorithms are all equally critical in conducting ultra-high climate resolution studies, it is likely that the necessary petaflop computing technology will be available in advance of a credible kilometer scale climate model.

  20. Understanding space weather to shield society

    E-Print Network [OSTI]

    Schrijver, Karel

    Understanding space weather to shield society Improving understanding and forecasts of space weather requires addressing scientific challenges within the network of physical processes that connect the Sun to society. The roadmap team identified the highest-priority areas within the Sun-Earth space-weather

  1. Model predicts space weather and protects satellite hardware

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete7 AssessmentBusinessAlternativeModel Verification

  2. Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

    SciTech Connect (OSTI)

    Done, James; Holland, Greg; Bruyere, Cindy; Leung, Lai-Yung R.; Suzuki-Parker, Asuka

    2013-10-19

    Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.

  3. An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01

    e?ects and valuation of weather derivatives. The FinancialWei, J. (1999). Pricing weather derivative: an equilibrium2005). An introduction to cme weather products. www.cme.com/

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

    E-Print Network [OSTI]

    Bush, Sarah, 1973-

    2003-01-01

    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+ ...

  5. Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models

    E-Print Network [OSTI]

    Arumugam, Sankar

    Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater

  6. A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis 

    E-Print Network [OSTI]

    Makaudze, Ephias

    1993-01-01

    Board's financial resource needs. Thus, the corn supply forecasts are important information used by the government for contingency planning, decision-making, policy-formulation and implementation. As such, the need for accurate forecasts is obvious...

  7. MET 416: TROPICAL ANALYSIS AND FORECASTING Spring Semester 2013

    E-Print Network [OSTI]

    current (nowcasting) and expected weather, using all available real-time operational weather data Exam 4/9 Summer trade-wind weather based on HaRP 4/11-16 Large-scale influences, Diurnal cycle to the development of tropical storm systems and mesoscale weather. Lectures will include a forecasting perspective

  8. HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

    SciTech Connect (OSTI)

    Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; Pereira, Jose M.; Hurtt, George C.

    2015-01-01

    Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spread over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.

  9. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    forecast of 4) Calculate Hourly Load Allocation Factor s for each day for 2019 For use in RA analysis as a function ofthe load for electricity in the region as a function of cyclical, weather and economic variables

  10. Data Network Weather Service Reporting - Final Report

    SciTech Connect (OSTI)

    Michael Frey

    2012-08-30

    A final report is made of a three-year effort to develop a new forecasting paradigm for computer network performance. This effort was made in co-ordination with Fermi Lab's construction of e-Weather Center.

  11. Very short-term wind speed forecasting with Bayesian structural break model , Zhe Song a,*, Andrew Kusiak b

    E-Print Network [OSTI]

    Kusiak, Andrew

    of the wind industry, such as wind turbine predictive control [2,3], wind power grid integration and economic July 2012 Available online Keywords: Time series Forecasting Wind power Wind speed Bayesian structural applications, such as wind turbine predictive control, wind power scheduling. The proposed model is tested

  12. Forecast of surface layer meteorological parameters at Cerro Paranal with a mesoscale atmospherical model

    E-Print Network [OSTI]

    Lascaux, Franck; Fini, Luca

    2015-01-01

    This article aims at proving the feasibility of the forecast of all the most relevant classical atmospherical parameters for astronomical applications (wind speed and direction, temperature) above the ESO ground-base site of Cerro Paranal with a mesoscale atmospherical model called Meso-Nh. In a precedent paper we have preliminarily treated the model performances obtained in reconstructing some key atmospherical parameters in the surface layer 0-30~m studying the bias and the RMSE on a statistical sample of 20 nights. Results were very encouraging and it appeared therefore mandatory to confirm such a good result on a much richer statistical sample. In this paper, the study was extended to a total sample of 129 nights between 2007 and 2011 distributed in different parts of the solar year. This large sample made our analysis more robust and definitive in terms of the model performances and permitted us to confirm the excellent performances of the model. Besides, we present an independent analysis of the model p...

  13. HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

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

    Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; Pereira, Jose M.; Hurtt, George C.

    2015-02-13

    Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore »over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

  14. Accuracy of near real time updates in wind power forecasting

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy 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 #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

  15. A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.

    E-Print Network [OSTI]

    McCalley, James D.

    University, Ames, Iowa (Manuscript received 2 October 2011, in final form 15 May 2013) ABSTRACT The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements.S. Department of Energy goal of having 20% of the nation's electrical energy from wind by 2030 will require

  16. Exploring the sensitivity of precipitation behavior using a single-column model

    E-Print Network [OSTI]

    Clark, Kathryn

    2013-05-31

    Relationships between land-surface conditions, boundary layer (PBL) growth, atmospheric stability, and convective precipitation behavior are explored using the Weather Research and Forecasting Model (ARW WRF) in single ...

  17. The Potential for Integrating GIS in Activity-Based Forecasting Models

    E-Print Network [OSTI]

    McNally, Michael G.

    1997-01-01

    3" (ENTERTAINMENT) Figure 4. A GIS-based Microsimulation ofDestinations Figure 5. A GIS-based Microsimulation ofPotential for Integrating GIS in Activity Based Forecasting

  18. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

    Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

    2005-01-01

    index.html. Appendix A.1 Natural Gas Price Data for FuturesError STEO Error A.1 Natural Gas Price Data for Futuresof forecasts for natural gas prices as reported by the

  19. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  20. 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]

    Shao, Hongbin

    1994-01-01

    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...

  1. The Role of "Citizen Science" in Weather and Climate Research

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    stations to help document Climate resources of the country And provide science-based weather forecasts by volunteers to see their data put to use. #12;Weather reports began on Pikes Peak in 1873 Credit: NOAA Photo weather and climate data were simple ­ Determining the "climate resource" of our country -- specifically

  2. ForPeerReview Verification of Mountain Weather Information Service

    E-Print Network [OSTI]

    Birch, Cathryn

    ForPeerReview Verification of Mountain Weather Information Service forecasts for three upland areas in the UK Journal: Weather Manuscript ID: WEA-13-0098.R1 Wiley - Manuscript type: Research Article Date and Environment Birch, Cathryn; University of Leeds, School of Earth and Environment Monk, Geoffrey; The Weather

  3. Similarity-based semi-local estimation of EMOS models

    E-Print Network [OSTI]

    Lerch, Sebastian

    2015-01-01

    Weather forecasts are typically given in the form of forecast ensembles obtained from multiple runs of numerical weather prediction models with varying initial conditions and physics parameterizations. Such ensemble predictions tend to be biased and underdispersive and thus require statistical postprocessing. In the ensemble model output statistics (EMOS) approach, a probabilistic forecast is given by a single parametric distribution with parameters depending on the ensemble members. This article proposes two semi-local methods for estimating the EMOS coefficients where the training data for a specific observation station are augmented with corresponding forecast cases from stations with similar characteristics. Similarities between stations are determined using either distance functions or clustering based on various features of the climatology, forecast errors, ensemble predictions and locations of the observation stations. In a case study on wind speed over Europe with forecasts from the Grand Limited Area...

  4. An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting

    E-Print Network [OSTI]

    Oren, Shmuel S.

    -day ice storm in February 2003 electricity prices spiked to $990/MWh causing a retail energy provider, representing some three trillion dollars annually, bears some degree of weather and climate risk. Energy be affected by weather. For example, the profit function of energy distribution companies, which are obligated

  5. NOAA National Weather Service I'm a weather forecaster.

    E-Print Network [OSTI]

    , it goes a long way But if he hits it from the top of a hill, it goes even farther. So, if my dad had super will need is an instrument to tell whether it's hot or cold down below. Good! In your kitchen, place a tray of ice near a bowl of hot tap water. Move your hand over the ice, then over the hot water. Do you feel

  6. Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)

    SciTech Connect (OSTI)

    Churchfield, M. J.; Michalakes, J.; Vanderwende, B.; Lee, S.; Sprague, M. A.; Lundquist, J. K.; Moriarty, P. J.

    2013-10-01

    Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in wind plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.

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

    SciTech Connect (OSTI)

    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

    2003-11-21

    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.

  8. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  9. A resampling procedure for generating conditioned daily weather Martyn P. Clark,1

    E-Print Network [OSTI]

    Balaji, Rajagopalan

    A resampling procedure for generating conditioned daily weather sequences Martyn P. Clark,1 the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied weather sequence. The weather generator model is extended to produce sequences of weather

  10. Sensitivity analysis of the MM5 weather model using automatic differentiation

    SciTech Connect (OSTI)

    Bischof, C.H. [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)] [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States); Pusch, G.D. [Physics Department, Michigan State University, East Lansing, Michigan 48842 (United States)] [Physics Department, Michigan State University, East Lansing, Michigan 48842 (United States); Knoesel, R. [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)] [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)

    1996-11-01

    We present a general method for using automatic differentiation to facilitate model sensitivity analysis. Automatic differentiation techniques augment, in a completely mechanical fashion, an existing code such that it also simultaneously and efficiently computes derivatives. Our method allows the sensitivities of the code{close_quote}s outputs to its parameters and inputs to be determined with minimal human effort by exploiting the relationship between differentiation and formal perturbation theory. Employing this methodology, we performed a sensitivity study of the MM5 code, a mesoscale weather model jointly developed by Penn State University and the National Center for Atmospheric Research, that is composed of roughly 40,000 lines of Fortran 77 code. Our results show that automatic differentiation-computed sensitivities exhibit superior accuracy compared to divided difference approximations computed from finite-amplitude perturbations. We also comment on a numerically induced precursor wave that would almost certainly have been undetectable if one used a divided difference method. {copyright} {ital 1996 American Institute of Physics.}

  11. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

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

    E-Print Network [OSTI]

    Martin, Randall

    ) and sea level pressure (SLP) readings to anticipate water-stress six months prior to harvest-economic variability. Explored within is a new approach to seasonal crop forecasting, one derived from crop water, and other climatic factors over the period 1961-1994 are compared with calculated available water from

  13. Modeling, History Matching, Forecasting and Analysis of Shale Reservoirs Performance Using Artificial Intelligence

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    matching, forecasting and analyzing oil and gas production in shale reservoirs. In this new approach and analysis of oil and gas production from shale formations. Examples of three case studies in Lower Huron and New Albany shale formations (gas producing) and Bakken Shale (oil producing) is presented

  14. Improving Tropical Cyclogenesis Statistical Model Forecasts through the Application of a Neural Network Classifier

    E-Print Network [OSTI]

    Marzban, Caren

    /National Hurricane Center 11691 SW 17th Street Miami, FL 33165 Email: Christopher.Hennon@noaa.gov #12;2 ABSTRACT networks are able to detect nonlinear patterns in data and can be a very powerful tool for forecasting applications if they are designed and used properly. Although they are a more recent innovation than

  15. A Better Way to ID Extreme Weather Events in Climate Models

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

    developing techniques to do just that. "We're using state-of-the-art methods in data mining and high performance computing to locate and quantify extreme weather phenomena in the...

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

    E-Print Network [OSTI]

    Juarez Torres, Miriam 77-

    2012-08-31

    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...

  17. Real-time, rapidly updating severe weather products for virtual globes Travis M. Smitha

    E-Print Network [OSTI]

    Lakshmanan, Valliappa

    Real-time, rapidly updating severe weather products for virtual globes Travis M. Smitha It is critical that weather forecasters are able to put severe weather information from a variety audience. In this paper, we describe the data and methods for enabling severe weather threat analysis

  18. Commercial Weatherization

    Broader source: Energy.gov [DOE]

    Commercial buildings consume 19 percent of the energy used in the U.S. Learn how the Energy Department is supporting research and deployment on commercial weatherization.

  19. 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]

    Bronson, J. D.

    1992-01-01

    that extract hourly end-use energy consumption and weather data from DOE-2's hourly output reports and process the data into three-dimensional plots and temperature-specific humidity carpet plots....

  20. Cointegration of the Daily Electric Power System Load and the Weather

    E-Print Network [OSTI]

    Stefanov, Stefan Z

    2007-01-01

    The paper examines the cointegration of the daily electric power system load and the weather by a field intelligent system. The daily load has been modelled by dynamic regressions. A "Daily Artificial Dispather" thermal intelligent system has been costructed. Time and energy tests have been obtained for this intelligent system. The improvement in the daily load forecast, achieved by this intelligent system, has been obtained. The predicted daily electricity price has been found.

  1. Mesoscale predictability and background error convariance estimation through ensemble forecasting 

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties ...

  2. PV powering a weather station for severe weather

    SciTech Connect (OSTI)

    Young, W. Jr. [Florida Solar Energy Center, Cocoa, FL (United States); Schmidt, J. [Joe Schmidt, Inc., Miami, FL (United States)

    1997-12-31

    A natural disaster, such as Hurricane Andrew, destroys thousands of homes and businesses. The destruction from this storm left thousands of people without communications, potable water, and electrical power. This prompted the Florida Solar Energy Center to study the application of solar electric power for use in disasters. During this same period, volunteers at the Tropical Prediction Center at the National Hurricane Center (NHC), Miami, Florida and the Miami Office of the National Weather Service (NWS) were working to increase the quantity and quality of observations received from home weather stations. Forecasters at NHC have found surface reports from home weather stations a valuable tool in determining the size, strength and course of hurricanes. Home weather stations appear able to record the required information with an adequate level of accuracy. Amateur radio, utilizing the Automatic Packet Report System, (APRS) can be used to transmit this data to weather service offices in virtually real time. Many weather data collecting stations are at remote sites which are not readily serviced by dependable commercial power. Photovoltaic (solar electric) modules generate electricity and when connected to a battery can operate as a stand alone power system. The integration of these components provides an inexpensive standalone system. The system is easy to install, operates automatically and has good communication capabilities. This paper discusses the design criteria, operation, construction and deployment of a prototype solar powered weather station.

  3. Two way coupling RAM-SCB to the space weather modeling framework

    SciTech Connect (OSTI)

    Welling, Daniel T [Los Alamos National Laboratory; Jordanova, Vania K [Los Alamos National Laboratory; Zaharia, Sorin G [Los Alamos National Laboratory; Toth, Gabor [UNIV OF MICHIGAN

    2010-12-03

    The Ring current Atmosphere interaction Model with Self-Consistently calculated 3D Magnetic field (RAM-SCB) has been used to successfully study inner magnetosphere dynamics during different solar wind and magnetosphere conditions. Recently, one way coupling of RAM-SCB with the Space Weather Modeling Framework (SWMF) has been achieved to replace all data or empirical inputs with those obtained through first-principles-based codes: magnetic field and plasma flux outer boundary conditions are provided by the Block Adaptive Tree Solar wind Roe-type Upwind Scheme (BATS-R-US) MHO code, convection electric field is provided by the Ridley Ionosphere Model (RIM), and ion composition is provided by the Polar Wind Outflow Model (PWOM) combined with a multi-species MHO approach. These advances, though creating a powerful inner magnetosphere virtual laboratory, neglect the important mechanisms through which the ring current feeds back into the whole system, primarily the stretching of the magnetic field lines and shielding of the convection electric field through strong region two Field Aligned Currents (FACs). In turn, changing the magnetosphere in this way changes the evolution of the ring current. To address this shortcoming, the coupling has been expanded to include feedback from RAM-SCB to the other coupled codes: region two FACs are returned to the RIM while total plasma pressure is used to nudge the MHO solution towards the RAMSCB values. The impacts of the two way coupling are evaluated on three levels: the global magnetospheric level, focusing on the impact on the ionosphere and the shape of the magnetosphere, the regional level, examining the impact on the development of the ring current in terms of energy density, anisotropy, and plasma distribution, and the local level to compare the new results to in-situ measurements of magnetic and electric field and plasma. The results will also be compared to past simulations using the one way coupling and no coupling whatsoever. This work is the first to fully couple an anisotropic kinetic ring current code with a selfconsistently calculated magnetic field to a set of global models.

  4. Weatherization Roundup

    Broader source: Energy.gov [DOE]

    More than 750 thousand homes were weatherized by the Department’s Weatherization Assistance Program in the past three years. Secretary Chu spoke with governors and members of Congress around the country to celebrate this huge accomplishment -- which was finished ahead of schedule and is saving the average household $400 annually on their heating and cooling bills.

  5. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  6. Identification of Robust Terminal-Area Routes in Convective Weather

    E-Print Network [OSTI]

    Balakrishnan, Hamsa

    Convective weather is responsible for large delays and widespread disruptions in the U.S. National Airspace System, especially during summer. Traffic flow management algorithms require reliable forecasts of route blockage ...

  7. The Regional Atmospheric Modeling System (RAMS): Development for Parallel Processing Computer

    E-Print Network [OSTI]

    Cirne, Walfredo

    on the mesoscale (horizontal scales from 2 km to 2000 km) for purposes ranging from operational weather forecasting and simulating convective clouds, mesoscale convective systems, cirrus clouds, and precipitating weather systems models that had a great deal of overlap, the CSU cloud/mesoscale mode (Tripoli and Cotton, 1982

  8. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

    Airplanes Aloft as a Sensor Network for Wind Forecasting Ashish Kapoor, Zachary Horvitz, Spencer for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor

  9. Value of global weather sensors

    SciTech Connect (OSTI)

    Canavan, G.H.

    1998-12-23

    Long-range weather predictions have great scientific and economic potential, but require precise global observations. Small balloon transponders could serve as lagrangian trace particles to measure the vector wind, which is the primary input to long-range numerical forecasts. The wind field is difficult to measure; it is at present poorly sampled globally. Distance measuring equipment (DME) triangulation of signals from roughly a million transponders could sample it with sufficient accuracy to support {approximately} two week forecasts. Such forecasts would have great scientific and economic potential which is estimated below. DME uses small, low-power transmitters on each transponder to broadcast short, low-power messages that are detected by several small receivers and forwarded to the ground station for processing of position, velocity, and state information. Thus, the transponder is little more than a balloon with a small radio, which should only weigh a few grams and cost a few dollars.

  10. 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]

    Hogan, Robin

    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

  11. HELIOPHYSICS V. SPACE WEATHER AND SOCIETY

    E-Print Network [OSTI]

    Schrijver, Karel

    on the electric power grid 74 David Boteler 4.1 Introduction 74 4.2 Cause of power system problems 75 4.3 Magnetic on transformers 87 4.7 System impacts 88 4.8 Hazard assessment 91 4.9 Space weather forecasting for power grids 93HELIOPHYSICS V. SPACE WEATHER AND SOCIETY Early chapter collection v. January 5, 2015 http

  12. Weatherizing America

    ScienceCinema (OSTI)

    Stewart, Zachary; Bergeron, T.J.; Barth, Dale; Qualis, Xavier; Sewall, Travis; Fransen, Richard; Gill, Tony;

    2013-05-29

    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 again, but also to find a calling.

  13. 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...

  14. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvén waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

  15. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

    solar forecasting system based on numerical weather prediction plus satellite and ground-based data.1 Photovoltaic Systems: Report 3 Development of data base allowing managed access to statewide PV and insolation Based Data 13 Summary 14 References 14 #12;List of Figures Figure Number and Title Page # 1. Topography

  16. Understanding space weather to shield society: A global road map for 2015-2025 commissioned by COSPAR and ILWS

    E-Print Network [OSTI]

    Schrijver, Carolus J; Aylward, Alan D; Denardini, Clezio M; Gibson, Sarah E; Glover, Alexi; Gopalswamy, Nat; Grande, Manuel; Hapgood, Mike; Heynderickx, Daniel; Jakowski, Norbert; Kalegaev, Vladimir V; Lapenta, Giovanni; Linker, Jon A; Liu, Siqing; Mandrini, Cristina H; Mann, Ian R; Nagatsuma, Tsutomu; Nandi, Dibyendu; Obara, Takahiro; O'Brien, T Paul; Onsager, Terrance; Opgenoorth, Hermann J; Terkildsen, Michael; Valladares, Cesar E; Vilmer, Nicole

    2015-01-01

    There is a growing appreciation that the environmental conditions that we call space weather impact the technological infrastructure that powers the coupled economies around the world. With that comes the need to better shield society against space weather by improving forecasts, environmental specifications, and infrastructure design. [...] advanced understanding of space weather requires a coordinated international approach to effectively provide awareness of the processes within the Sun-Earth system through observation-driven models. This roadmap prioritizes the scientific focus areas and research infrastructure that are needed to significantly advance our understanding of space weather of all intensities and of its implications for society. Advancement of the existing system observatory through the addition of small to moderate state-of-the-art capabilities designed to fill observational gaps will enable significant advances. Such a strategy requires urgent action: key instrumentation needs to be sustaine...

  17. A Chapter In Space Weather: Physics and Effects

    E-Print Network [OSTI]

    Vassiliadis, Dimitrios

    costs. A smaller number of assets is on Earth's surface (electric power grids, pipeline systems- 1 - A Chapter In Space Weather: Physics and Effects by V. Bothmer and I.A. Daglis (editors) Springer Praxis September 2005 Draft date: March 9, 2007 Forecasting Space Weather Dimitris Vassiliadis ST

  18. Evidences for and the models of self-similar skeletal structures in fusion devices, severe weather phenomena and space

    E-Print Network [OSTI]

    Kukushkin, A B

    2005-01-01

    The paper briefly reviews (i) the evidences for self-similar structures of a skeletal form (namely, tubules and cartwheels, and their simplest combinations), called the Universal Skeletal Structures (USS), observed in the range 10-5 cm - 1023 cm. in the high-current electric discharges in various fusion devices, severe weather phenomena, and space, (ii) the models for interpreting the phenomenon of skeletal structures, including the hypothesis for a fractal condensed matter (FCM), assembled from nanotubular dust, and (iii) probable role of FCM, which might be responsible for the USS phenomenon, in tornado, ball lightning, and waterspout.

  19. A SOLAR WARMING MODEL (SWarm) TO ESTIMATE DIURNAL CHANGES IN NEAR-SURFACE SNOWPACK TEMPERATURES FOR BACK-COUNTRY AVALANCHE FORECASTING

    E-Print Network [OSTI]

    Jamieson, Bruce

    be used to measure incoming solar radiation, but they are not common due to cost and maintenance issuesA SOLAR WARMING MODEL (SWarm) TO ESTIMATE DIURNAL CHANGES IN NEAR-SURFACE SNOWPACK TEMPERATURES. To facilitate use in large forecast areas where representative meteorological data are typically scarce

  20. Long Range Evolution-based Path Planning for UAVs through Realistic Weather Environments

    E-Print Network [OSTI]

    Long Range Evolution-based Path Planning for UAVs through Realistic Weather Environments Juan Planning for UAVs through Realistic Weather Environments Juan Carlos Rubio Torroella Co range flights is pre- sented. The planner makes use of wind information from actual weather forecast

  1. Synoptic Code Symbols with Range of Values BBXX Ship Weather Report Indicator BBXX

    E-Print Network [OSTI]

    Weather data indicator 1, 3 h Cloud base height 0-9, / VV Visibility 90-99 N Cloud cover 0-9, / dd Wind Administration National Weather Service National Data Buoy Center Building 1007 Stennis Space Center, MS 39529 be vast marine areas without data, making weather forecasting nearly impossible for these areas

  2. Feedback Control of the National Airspace System to Mitigate Weather Disruptions

    E-Print Network [OSTI]

    Le Ny, Jerome

    Feedback Control of the National Airspace System to Mitigate Weather Disruptions Jerome Le Ny during a weather event, given a probabilistic forecast of capacities. We also address the management to weather disruptions. I. INTRODUCTION The frequent occurrence of air traffic delays in the Na- tional

  3. he Cooperative Observer Program is a unique partnership between the National Weather Service

    E-Print Network [OSTI]

    T he Cooperative Observer Program is a unique partnership between the National Weather Service the nation with a cost-effective way to collect weather data for immediate forecasting needs and longer with Congressional passage of the National Weather Service Organic Act, which set up a system to recruit and train

  4. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    and forecasting of solar radiation data: a review,”forecasting of solar- radiation data,” Solar Energy, vol.sequences of global solar radiation data for isolated sites:

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

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    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.

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

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

    Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

    2009-10-27

    In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s 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 ensemblemore »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.« less

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

    SciTech Connect (OSTI)

    Deremble, Bruno [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); D'Andrea, Fabio [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); Ghil, Michael [Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Inst. of Geophysics and Planetary Physics

    2009-10-27

    In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s 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.

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

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

    Deremble, Bruno [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); D'Andrea, Fabio [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); Ghil, Michael [Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Inst. of Geophysics and Planetary Physics

    2009-01-01

    In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s 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.

  9. Hawaii demand-side management resource assessment. Final report, Reference Volume 5: The DOETRAN user`s manual; The DOE-2/DBEDT DSM forecasting model interface

    SciTech Connect (OSTI)

    1995-04-01

    The DOETRAN model is a DSM database manager, developed to act as an intermediary between the whole building energy simulation model, DOE-2, and the DBEDT DSM Forecasting Model. DOETRAN accepts output data from DOE-2 and TRANslates that into the format required by the forecasting model. DOETRAN operates in the Windows environment and was developed using the relational database management software, Paradox 5.0 for Windows. It is not necessary to have any knowledge of Paradox to use DOETRAN. DOETRAN utilizes the powerful database manager capabilities of Paradox through a series of customized user-friendly windows displaying buttons and menus with simple and clear functions. The DOETRAN model performs three basic functions, with an optional fourth. The first function is to configure the user`s computer for DOETRAN. The second function is to import DOE-2 files with energy and loadshape data for each building type. The third main function is to then process the data into the forecasting model format. As DOETRAN processes the DOE-2 data, graphs of the total electric monthly impacts for each DSM measure appear, providing the user with a visual means of inspecting DOE-2 data, as well as following program execution. DOETRAN provides three tables for each building type for the forecasting model, one for electric measures, gas measures, and basecases. The optional fourth function provided by DOETRAN is to view graphs of total electric annual impacts by measure. This last option allows a comparative view of how one measure rates against another. A section in this manual is devoted to each of the four functions mentioned above, as well as computer requirements and exiting DOETRAN.

  10. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

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

    2013-10-01

    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.

  11. Assessment and added value estimation of an ensemble approach with a focus on global radiation forecasts

    E-Print Network [OSTI]

    Bouallegue, Zied Ben

    2015-01-01

    The assessment of the high-resolution ensemble weather prediction system COSMO-DE-EPS is achieved with the perspective of using it for renewable energy applications. The performance of the ensemble forecast is explored focusing on global radiation, the main weather variable affecting solar power production, and on quantile forecasts, key probabilistic products for the energy sector. First, the ability of the ensemble system to capture and resolve the observation variability is assessed. Secondly, the potential benefit of the ensemble forecasting strategy compared to a single forecast approach is quantitatively estimated. A new metric called ensemble added value is proposed, aiming at a fair comparison of an ensemble forecast with a single forecast, when optimized to the users' needs. Hourly mean forecasts are verified against pyranometer measurements over verification periods covering 2013. The results show in particular that the added value of the ensemble approach is season-dependent and increases with the ...

  12. o help guard against the ravages of severe weather, NOAA's National Weather Service designed

    E-Print Network [OSTI]

    redundant methods to receive severe weather forecasts/warnings and alert the public, · Create a system and flood operations. Tsunami tragedies over the past decade have reminded the world of the socioeconomic impacts this hazard can inflict. Major tsunami events include: the Indian Ocean in December 2004, Samoa

  13. "The Voice of NOAA's National Weather Service" Supporting NOAA's Weather Ready Nation Initiative

    E-Print Network [OSTI]

    . Warnings are broadcast for both natural (such as tsunamis and volcanoes) and man-made (such as Amber Alerts federally operated system broadcasting weather and emergency warnings to the public. Reception of NWR) warnings, watches, forecasts and other emergency information from nearby NWS offices 24 hours a day. Known

  14. Orphan drugs : future viability of current forecasting models, in light of impending changes to influential market factors

    E-Print Network [OSTI]

    Gottlieb, Joshua

    2011-01-01

    Interviews were conducted to establish a baseline for how orphan drug forecasting is currently undertaken by financial market and industry analysts with the intention of understanding the variables typically accounted for ...

  15. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

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

    SciTech Connect (OSTI)

    Morrison, PI Hugh

    2012-09-21

    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).

  17. Social Media: Space Weather #SpaceWeather

    E-Print Network [OSTI]

    ://www.swpc.noaa.gov/impacts/spaceweatherandgpssystems #SpaceWeather #12;Space Weather Impacts on the Power Grid Facebook The electric power grid. To learn about space weather and impacts to the electric grid visit http on the Power Grid Space Weather and the Aurora Borealis What are Solar Flares? What are Coronal Mass

  18. Understanding space weather to shield society

    E-Print Network [OSTI]

    Schrijver, Karel

    Understanding space weather to shield society An international, interdisciplinary roadmap to advance the scientific understanding of the Sun-Earth connections leading to space weather, on behalf observatory along with models and innovative approaches to data incorporation;! b) Understand space weather

  19. SPACE WEATHER RISKS FROM AN INSURANCE PERSPECTIVE

    E-Print Network [OSTI]

    Schrijver, Karel

    SPACE WEATHER RISKS FROM AN INSURANCE PERSPECTIVE 26.04.2011 Jan Eichner ­ Geo Risks Research #12, including geophysical hazards, weather-related hazards and potential consequences of climate change weather). · Linking geo-scientific research with business expertise in risk assessment, risk modeling

  20. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

    Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

    2005-01-01

    Update on Petroleum, Natural Gas, Heating Oil and Gasoline.of the Market for Natural Gas Futures. Energy Journal 16 (Modeling Forum. 2003. Natural Gas, Fuel Diversity and North

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

    E-Print Network [OSTI]

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

    2003-01-01

    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 ...

  2. Efficient market model: within-sample fit versus out-of-sample forecasts 

    E-Print Network [OSTI]

    Cheng, Chi

    1993-01-01

    In this paper, we study whether the pricing of index futures and the underlying cash prices are efficient. Price efficiency per se is not testable. It must be tested jointly with a maintained model. The topic of time ...

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

    E-Print Network [OSTI]

    Liu, Chang

    2009-05-15

    better estimate. The PUNQ-S3 reservoir model is used to test two methods in this thesis. The methods are: STATIC (traditional) SIMULATION PROCESS and CONTINUOUS SIMULATION PROCESS. The continuous process provides continuously updated probabilistic...

  4. Can Fully Accounting for Clouds in Data Assimilation Improve Short-Term Forecasts by Global Models?

    E-Print Network [OSTI]

    Robert, Pincus

    ? ROBERT PINCUS AND ROBERT J. PATRICK HOFMANN University of Colorado and NOAA/Earth System Research for Atmospheric Research, Boulder, Colorado JEFFREY S. WHITAKER NOAA/Earth Systems Research Laboratory using a single ensemble data assimilation system coupled to two present-generation climate models

  5. ReseaRch at the University of Maryland The Chesapeake Bay Forecast Modeling System

    E-Print Network [OSTI]

    Hill, Wendell T.

    . The impact of industry, fishing, agriculture, development, and climate change raise significant devastate fragile fish stocks. Rita Colwell uses bioinformatics methods to model the emergence of pathogens color to detect the presence of fish species and to estimate their numbers. This information is useful

  6. Building a Weather-Ready Nation Winter Weather Safety

    E-Print Network [OSTI]

    Building a Weather-Ready Nation Winter Weather Safety NOAA/NWS Winter Weather Safety Seasonal Campaign www.weather.gov #12;Building a Weather-Ready Nation Winter Weather Hazards Winter Weather Safety www.weather.gov · Snow/Ice · Blizzards · Flooding · Cold Temperatures #12;Building a Weather

  7. System implementation for US Air Force Global Theater Weather Analysis and Prediction System (GTWAPS)

    SciTech Connect (OSTI)

    Simunich, K.L.; Pinkerton, S.C.; Michalakes, J.G.; Christiansen, J.H.

    1997-03-01

    The Global Theater Weather Analysis and Prediction System (GTWAPS) is intended to provide war fighters and decision makers with timely, accurate, and tailored meteorological and oceanographic (METOC) information to enhance effective employment of battlefield forces. Of critical importance to providing METOC theater information is the generation of meteorological parameters produced by numerical prediction models and application software at the Air Force Global Weather Central (AFGWC), Offutt Air Force Base, Nebraska. Ultimately, application-derived data will be produced by the regional Joint METOC Forecast Units and by the deployed teams within a theater. The USAF Air Staff contracted with Argonne National Laboratory (ANL) for assistance in defining a hardware and software solution using off-the-shelf technology that would give the USAF the flexibility of testing various meteorological models and the ability to use the system within their daily operational constraints.

  8. web page: http://w3.pppl.gov/~ zakharov On Real Time Forecasts (RTF) of Tokamak Discharges1

    E-Print Network [OSTI]

    Zakharov, Leonid E.

    structure (Data Base) . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.3 Communication control of code to "yesterday" weather analysis) or predictive codes ("next month" weather predictions), RTF targets a forecast of the plasma regime, e.g., in 0.1 e (like the "next hour" weather predictions). Three components, crucial

  9. web page: http://w3.pppl.gov/~ zakharov On Real Time Forecasts (RTF) of Tokamak Discharges 1

    E-Print Network [OSTI]

    Zakharov, Leonid E.

    structure (Data Base) . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.3 Communication control of code to "yesterday" weather analysis) or predictive codes ("next month" weather predictions), RTF targets a forecast of the plasma regime, e.g., in 0.1 # e (like the "next hour" weather predictions). Three components, crucial

  10. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    vs. synthesized energy modeling weather files. Journal ofHong TZ, Jiang Y. Stochastic weather model for building HVAC1. [9] Crawley DB. Which weather data should you use for

  11. s the nation's weather and oceans agency, NOAA plays a major role before, during and after a

    E-Print Network [OSTI]

    real-time data from NOAA's polar orbiting and geostationary weather satellites, ocean and coastal observing systems, and land-based radars. NOAA's local National Weather Service forecast offices incorporate for inland high winds, flooding and severe weather -- including tornadoes. Data from the atmosphere are also

  12. Weatherization Training for South Carolina's Muggy Weather

    Broader source: Energy.gov [DOE]

    Why it makes sense for one technical college in Charleston, South Carolina is adding weatherization programs to their curriculum.

  13. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  14. Essays on Forecasting and Hedging Models in the Oil Market and Causality Analysis in the Korean Stock Market 

    E-Print Network [OSTI]

    Choi, Hankyeung

    2012-10-19

    , the nature of forecasting crude oil prices based on financial data for the oil and oil product market is examined. As crack spread and oil-related Exchange-Traded Funds (ETFs) have enabled more consumers and investors to gain access to the crude oil...

  15. Cathy Zoi on Weatherization

    ScienceCinema (OSTI)

    Zoi, Cath

    2013-05-29

    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.

  16. Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2

    E-Print Network [OSTI]

    Dasso, Sergio

    Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2 , N. Gopalswamy1 and A. Lara of the major requirements to forecast the space weather conditions in the terrestrial envi- ronment. Several properties, such as the background solar wind speed, and the density of the ejecta. However, only a few

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

    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

  18. Early View (EV): 1-EV Nice weather for bettongs: using weather events, not climate

    E-Print Network [OSTI]

    Turner, Monica G.

    distribution using temporally matched observations of the species with weather data (includ- ing extremeEarly View (EV): 1-EV Nice weather for bettongs: using weather events, not climate means applications of species distribution models (SDM) are typically static, in that they are based on correlations

  19. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    , regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting to make important decisions including decisions on pur- chasing and generating electric power, load for different operations within a utility company. The natures 269 #12;270 APPLIED MATHEMATICS FOR POWER SYSTEMS

  20. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

    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.

  1. A Fourier series model to predict hourly heating and cooling energy use in commercial buildings with outdoor temperature as the only weather variable

    SciTech Connect (OSTI)

    Dhar, A. [Enron Corp., Houston, TX (United States); Reddy, T.A. [Drexel Univ., Philadelphia, PA (United States). Civil and Architectural Engineering Dept.; Claridge, D.E. [Texas A and M Univ., College Station, TX (United States). Energy Systems Lab.

    1999-02-01

    Accurate modeling of hourly heating and cooling energy use in commercial buildings can be achieved by a Generalized Fourier Series (GFS) approach involving weather variables such as dry-bulb temperature, specific humidity and horizontal solar flux. However, there are situations when only temperature data is available. The objective of this paper is to (i) describe development of a variant of the GFS approach which allows modeling both heating and cooling hourly energy use in commercial buildings with outdoor temperature as the only weather variable and (ii) illustrate its application with monitored hourly data from several buildings in Texas. It is found that the new Temperature based Fourier Series (TFS) approach (1) provides better approximation to heating energy use than the existing GFS approach, (ii) can indirectly account for humidity and solar effects in the cooling energy use, (iii) offers physical insight into the operating pattern of a building HVAC system and (iv) can be used for diagnostic purposes.

  2. Simulation of a Polar Low Case in the North Atlantic with different regional numerical models

    E-Print Network [OSTI]

    Zahn, Matthias

    by the DWD (German Weather Service) by means of their forecast model HRM (High Resolution Model) and another University Press, Cambridge. (a) CLM (b) REMO (c) HRM, DWD (d) BWK Figure 1: 1(a)- 1(c)10m wind velocity pressure from CLM and REMO simulations and HRM analysis, DWD, respectively, at 15/10/93, 6:00, 1(d) surface

  3. Weather Photos - Hanford Site

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

    weather Mammatus clouds Mammatus clouds Mammatus Clouds Mammatus Clouds Mammatus clouds Mammatus clouds Downburst Downburst...

  4. MOSE: a feasibility study for optical turbulence forecasts with the Meso-Nh mesoscale model to support AO facilities at ESO sites (Paranal and Armazones)

    E-Print Network [OSTI]

    Masciadri, E; 10.1117/12.925924

    2012-01-01

    We present very encouraging preliminary results obtained in the context of the MOSE project, an on-going study aiming at investigating the feasibility of the forecast of the optical turbulence and meteorological parameters (in the free atmosphere as well as in the boundary and surface layer) at Cerro Paranal (site of the Very Large Telescope - VLT) and Cerro Armazones (site of the European Extremely Large Telescope - E-ELT), both in Chile. The study employs the Meso-Nh atmospheric mesoscale model and aims at supplying a tool for optical turbulence forecasts to support the scheduling of the scientific programs and the use of AO facilities at the VLT and the E-ELT. In this study we take advantage of the huge amount of measurements performed so far at Paranal and Armazones by ESO and the TMT consortium in the context of the site selection for the E-ELT and the TMT to constraint/validate the model. A detailed analysis of the model performances in reproducing the atmospheric parameters (T, V, p, H, ...) near the g...

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

    SciTech Connect (OSTI)

    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.

    2011-11-01

    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.

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

    SciTech Connect (OSTI)

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

    2010-01-01

    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.

  7. This study considered the impact of grid resolution on wind velocity simulated by Weather Research and Forecasting (WRF) model. The period simulated spanned November 2009 through January

    E-Print Network [OSTI]

    the entire domains and the wind velocity observed solely over offshore locations. Wind velocity was observed locations for wind farms. The results go further to suggest the ideal location for these potential wind farms will be at offshore locations. Mechanical Engineering Master's Defense Impact of Grid Resolution

  8. Solar thematic maps for space weather operations E. Joshua Rigler,1,2

    E-Print Network [OSTI]

    , it presents results from validation experiments designed to ascertain the robustness of the technique Weather, 10, S08009, doi:10.1029/2012SW000780. 1. Introduction [2] Forecasters at the NOAA Space Weather algorithms on powerful computers. Sometimes first-principle physics are used to convert raw measurements

  9. Building a Weather-Ready Nation Fall Weather Safety

    E-Print Network [OSTI]

    Building a Weather-Ready Nation Fall Weather Safety www.weather.gov/safety Wildfire ­ Drought ­ Hurricanes ­ Wind ­ Early Season Winter ­ Flood #12;Building a Weather-Ready Nation Wildfire Safety smoking materials. weather.gov/wildfire www.weather.gov/safety #12;Building a Weather-Ready Nation

  10. A Science Service -Feature*.-..-7 WHY THE WEATHER '1

    E-Print Network [OSTI]

    the data on solar radiation, :Dr. C, G, Abbot, who collected these data, then discusses the analysis, and night, occupied with a symposium on solar radiation and the weather, probably the mcbt This morning, finally, 3. Helm Clayton, who has used the data f o r forecasting, discusses t o what extent solar heat

  11. Estimating the likelihood of weather criteria exceedance during marine operations

    SciTech Connect (OSTI)

    Brabazon, P.G. [Four Elements Ltd., London (United Kingdom); Gudmestad, O.T. [Statoil, Stavanger (Norway); Hopkins, J.S.

    1996-12-31

    This paper describes an approach to estimating the probability of marine operations being exposed to unsafe weather conditions. Marine operations, both inshore and offshore, are normally sensitive to environmental conditions. For the majority of operations threshold weather criteria will be predefined. An estimate of the likelihood of the operation experiencing bad weather, taking into account the uncertainties in weather forecasting, is of great value. The method is intended to be used as part of a risk assessment of marine operations, enabling the impact of design and scheduling decisions to be assessed in a structured and systematic way. The method has two components. Firstly, the time to complete an operation is defined in the form of a probability/time distribution. This is done by analyzing the duration of the tasks within the operation and identifying possible causes of delays. The likelihood and duration of each delay is estimated. Secondly, a probability/time curve is defined for the weather conditions exceeding the predefined threshold. The curve is determined by reference to the location of the marine operation, the time of year of the operation, the initial weather conditions and the accuracy of weather forecasting. Using the two probability/time curves, the likelihood of exposure is calculated.

  12. 4Science,Service F s a t w e ? WHY THE WEATHER ?

    E-Print Network [OSTI]

    No. 33 June 19 4Science,Service F s a t w e ? WHY THE WEATHER ? Dr. Charles F. Brooks, Secretary calm time i n the l i f e of the Weather forecaster, y e t it is not without its t h r i l l, There a r e no general Storms, galeo* A p r i l showers have dried up; the cool fair weather of llay has

  13. Wind Power Forecasting Data

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

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  14. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  15. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National...

  16. Social Media: Space Weather #SpaceWeather

    E-Print Network [OSTI]

    causing blackouts in rare cases. To learn about space weather and impacts to the electric grid visit on the Power Grid Space Weather and the Aurora Borealis What are Solar Flares? What are Coronal Mass we do. Satellite communications, GPS applications, and the electric power grid provide the backbone

  17. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

    Levin, Mark Sh; Kistler, Rolf; Klapproth, Alexander

    2012-01-01

    The article addresses combinatorial evolution and forecasting of communication protocol for wireless sensor networks (ZigBee). Morphological tree structure (a version of and-or tree) is used as a hierarchical model for the protocol. Three generations of ZigBee protocol are examined. A set of protocol change operations is generated and described. The change operations are used as items for forecasting based on combinatorial problems (e.g., clustering, knapsack problem, multiple choice knapsack problem). Two kinds of preliminary forecasts for the examined communication protocol are considered: (i) direct expert (expert judgment) based forecast, (ii) computation of the forecast(s) (usage of multicriteria decision making and combinatorial optimization problems). Finally, aggregation of the obtained preliminary forecasts is considered (two aggregation strategies are used).

  18. Weatherization Assistance Program

    Broader source: Energy.gov [DOE]

    This fact sheet provides an overview of the U.S. Department of Energys Weatherization Assistance Program.

  19. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  20. Impact of vegetation properties on U.S. summer weather prediction

    E-Print Network [OSTI]

    Xue, Y; Fennessy, M; Sellers, P

    1996-01-01

    Meteorological Center, Mon. Weather Rev. , 108, 1279-1292,VEGETATION IN U.S. SUMMER WEATHER model (SIB) for use withinConference on Numerical Weather Prediction, pp. 726 -733,

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

    E-Print Network [OSTI]

    Kwak, Do Young

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

  2. Weather Effects on European Agricultural Output 1850-1913

    E-Print Network [OSTI]

    Solomou, Solomos; Wu, Weike

    2004-06-16

    This paper compares the effects of weather shocks on agricultural production in Britain, France and Germany during the late nineteenth century. Using semi- parametric models to estimate the non-linear agro-weather relationship, we find...

  3. Weather Data Gamification 

    E-Print Network [OSTI]

    Gargate, Rohit

    2013-07-25

    . 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...

  4. Paintball Summer Weather

    E-Print Network [OSTI]

    Sin, Peter

    Highlights · Paintball · Summer Weather · Birthdays · Manners TheELIWeekly Paintball! Come out Turkey United States Venezuela Summer Weather Safety We've come to realize in the past that not all of our students are aware of our unique weather problems in Central Florida. One hazard that you should

  5. WEATHER HAZARDS Basic Climatology

    E-Print Network [OSTI]

    WEATHER HAZARDS Basic Climatology Colorado Climate Center Funding provided by NOAA Sectoral) Wildfires (Jun 02) Recent Declared Disasters in Colorado No Map from FEMA provided #12;National Weather and Warnings Outlook Indicates that hazardous weather may develop ­ useful to those who need considerable

  6. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

    and encouragement. I am very grateful to Lucille and Michael Hobbs for their friendship, understanding and financial support. Finally, thank you to Tom Decker, Pat Jackson and Brian Zellar for all their contributions and hard work on this project... below: 1. Na?ve 2. Linear Regression 3. Moving Average 4. Exponential 5. Double exponential The na?ve forecasting method assumes that more recent data values are the best predictors of future values. The model is ? t+1 = Y t . Where ? t...

  7. Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

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

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; Hailegiorgis, Atesmachew; Dahari, Harel; Major, Marian E.; Kaderali, Lars

    2015-09-30

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID tomore »build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.« less

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

    E-Print Network [OSTI]

    Simunic, Tajana

    , forecasting the weather accurately gained even more importance. Even now, a group of Smart Grid control Diego Email: {bakyurek,jkleissl}@ucsd.edu Electrical and Computer Engineering University of California- ergy resources within the Smart Grid, solar forecasting has become an important problem for hour

  9. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS 

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    2000-01-01

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  10. Exploiting weather forecasts for sizing photovoltaic energy bids

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    penalties for generation shortfall and surplus. The optimal bidding strategy depends on the statistics of the PV power generation and on the monetary penalties applied. We show how to tune the bidding strategy the risk associated with the intermittent nature of PV generation and maximize the expected profit

  11. Predicting Solar Generation from Weather Forecasts Using Machine Learning

    E-Print Network [OSTI]

    Shenoy, Prashant

    of smart grid initiatives is significantly increasing the fraction of grid energy contributed by renewables increase the penetration of environmentally-friendly renewable energy sources, such as solar and wind. For example, the Renewables Portfolio Standard targets up to 25% of energy generation from intermittent

  12. Roel Neggers European Centre for Medium-range Weather Forecasts

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust, High-Throughput Analysis of Protein Structures Print ScientistsRodney Ellis About

  13. The addition of a US Rare Earth Element (REE) supply-demand model improves the characterization and scope of the United States Department of Energy's effort to forecast US REE Supply and Demand

    E-Print Network [OSTI]

    Mancco, Richard

    2012-01-01

    This paper presents the development of a new US Rare Earth Element (REE) Supply-Demand Model for the explicit forecast of US REE supply and demand in the 2010 to 2025 time period. In the 2010 Department of Energy (DOE) ...

  14. Comment on `Testing earthquake prediction methods: "The West Pacific short-term forecast of earthquakes with magnitude MwHRV >= 5.8"' by V. G. Kossobokov

    E-Print Network [OSTI]

    Kagan, Yan Y; Jackson, David D

    2006-01-01

    tensor solutions for 1087 earthquakes, Phys. Earth Planet.and time-independent earthquake forecast models for southernKagan, 1999. Testable earthquake forecasts for 1999, Seism.

  15. Inclusion of In-Situ Velocity Measurements into the UCSD Time-Dependent Tomography to Constrain and Better-Forecast Remote-Sensing Observations

    E-Print Network [OSTI]

    Jackson, B. V.; Hick, P. P.; Bisi, M. M.; Clover, J. M.; Buffington, A.

    2010-01-01

    time”. The solar-wind velocity forecast 24 hours ahead of72-hour forecast volume using the extant solar-wind model.forecast. In-situ data have been the primary measurements available for study of solar-wind

  16. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

    . In addressing this problem, we have built a model to estimate the occupancy behavior of humans based enhancement in the accuracy of trajectory forecasting by incorporating the occupancy behavior model. Keywords Trajectory forecasting, human occupancy behavior, 3D ge- ometric context 1. INTRODUCTION Given a human

  17. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    . Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data Office. Andrea Gough ran the summary energy model and supervised data preparation. Glen Sharp prepared models. Both the staff revised energy consumption and peak forecasts are slightly higher than

  18. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    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

  19. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

  20. HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

    SciTech Connect (OSTI)

    Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

    2011-05-10

    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.

  1. Impact of fair-weather cumulus clouds and the Chesapeake Bay breeze on pollutant transport and transformation

    E-Print Network [OSTI]

    Dickerson, Russell R.

    evolve in the atmosphere, to forecast air quality and climate impacts of pollutants, and to help evaluate air pollution and climate change mitigation plans. Fine scale weather structures, such as fairImpact of fair-weather cumulus clouds and the Chesapeake Bay breeze on pollutant transport

  2. Impact of fair-weather cumulus clouds and the Chesapeake Bay breeze on pollutant transport and transformation

    E-Print Network [OSTI]

    Zhang, Da-Lin

    to investigate how pollutants evolve in the atmosphere, to forecast air quality and climate impacts of pollutants, and to help evaluate air pollution and climate change mitigation plans. Fine scale weather structuresImpact of fair-weather cumulus clouds and the Chesapeake Bay breeze on pollutant transport

  3. Nonlinear dynamics of the magnetosphere and space weather

    SciTech Connect (OSTI)

    Sharma, A.S. [Univ. of Maryland, College Park, MD (United States). Dept. of Astronomy

    1996-12-31

    The solar wind-magnetosphere-ionosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity in the dynamics. The observational time series data have been used extensively to analyze the magnetospheric dynamics by using the techniques of phase space reconstruction. Analyses of the solar wind and auroral electrojet and Dst indices have shown low dimensionality of the dynamics and accurate prediction can be made with an input-output model. The predictability of the magnetosphere in spite of the apparent complexity arises form its being synchronized, in the dynamical sense, to the solar wind. The AE and Dst data are used to analyze the storm-substorm relationship based on the input-output model. This shows differences between the storm-time and non-storm substorms, and is interpreted in terms of loading-unloading and directly driven processes. The strong electrodynamic coupling between the different regions of the magnetosphere yields its coherent and thus low dimensional behavior. The data from multiple satellites and ground stations are used to develop a spatio-temporal model that identifies the coupling between the different regions. These nonlinear dynamical models provide forecasting tools for space weather.

  4. Is Weather Chaotic?

    E-Print Network [OSTI]

    Ales Raidl

    1998-10-13

    The correlation dimension and K2-entropy are estimated from meteorological time- series. The results lead us to claim that seasonal variability of weather is under influence of low dimensional dynamics, whereas changes of weather from day to day are governed by high dimensional system(s). Error-doubling time of this system is less than 3 days. We suggest that the outstanding feature of the weather dynamics is deterministic chaos.

  5. Weather Charts - Hanford Site

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

    Meteorological Station > Met and Climate Data Summary Products > Historical Weather Charts Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS...

  6. The Weatherization Training program at Pennsylvania College

    ScienceCinema (OSTI)

    Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia;

    2013-05-29

    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.

  7. The Weatherization Training program at Pennsylvania College

    SciTech Connect (OSTI)

    Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia

    2010-01-01

    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.

  8. The Weatherization Training program at Pennsylvania College

    Broader source: Energy.gov [DOE]

    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...

  9. Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data

    E-Print Network [OSTI]

    Kurapov, Alexander

    Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data Based on comparisons with infrared (GOES) and microwave (AMSE-R) satellite data, our coastal ocean forecast model set circulation model and satellite data helps to improve forecasting of ocean conditions (esp. currents and SST

  10. Management of Weather and Climate Disputes

    E-Print Network [OSTI]

    Weiss, Edith Brown

    1983-01-01

    who may suffer harm from weather modification, efforts mustmitigating disputes over weather and cli- mate changes.Legal Implications of Weather Modification, in WEATHER

  11. Home Weatherization Visit

    ScienceCinema (OSTI)

    Chu, Steven

    2013-05-29

    Secretary Steven Chu visits a home that is in the process of being weatherized in Columbus, OH, along with Ohio Governor Ted Strickland and Columbus Mayor Michael Coleman. They discuss the benefits of weatherization and how funding from the recovery act is having a direct impact in communities across America.

  12. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    markets could aid in the design of appropriate price forecasting tools for such markets. Scenario1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou, restructured wholesale power markets, scenario generation, ARMA model, moment-matching method I. INTRODUCTION

  13. THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD

    E-Print Network [OSTI]

    THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc of Research Project: The Desire to Acquire: Forecasting the Evolution of Household Energy Services Report No, and gasoline. A fixed effects panel model was used to examine the relationship of demand for energy

  14. Today's Space Weather Space Weather Case Studies

    E-Print Network [OSTI]

    ], and grounding is difficult Hydro-Quebec's power grid is, within 90-sec of storm onset interference was thought to be due to Russian radio jamming ! GOES weather satellites, knocked out Power outage lasted 9-hours #12;What We Focus on Regarding This Storm: Power Grids

  15. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

    Improvement in sales forecasting allows firms not only to respond quickly to customers' needs but also to reduce inventory costs, ultimately increasing their profits. Sales forecasts have been studied extensively to improve ...

  16. Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  17. Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment of the requirements for

    E-Print Network [OSTI]

    Instituto de Sistemas e Robotica

    Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment;iii Abstract Electricity generated from wind power is both variable and uncertain. Wind forecasts prices. Wind power forecast errors for aggregated wind farms are often modeled with Gaussian

  18. Ozone ensemble forecast with machine learning Vivien Mallet,1,2

    E-Print Network [OSTI]

    Mallet, Vivien

    Ozone ensemble forecast with machine learning algorithms Vivien Mallet,1,2 Gilles Stoltz,3; published 13 March 2009. [1] We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system

  19. Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud

    E-Print Network [OSTI]

    Lavaei, Javad

    Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud May 11, 2014 Abstract This paper presents a survey of electricity price forecasting for the Nordic region, and performs that time series models more appropriate for forecasting electricity prices, compared to machine learning

  20. Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts Ronald H. Brown1 that allows long-term natural gas demand signals to be used effect- ively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent

  1. Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

    SciTech Connect (OSTI)

    Xiao, Heng; Mechoso, C. R.; Sun, Rui; Han, J.; Pan, H. L.; Park, S.; Hannay, Cecile; Bretherton, Christopher S.; Teixeira, J.

    2014-07-25

    We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is ³delayed² and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

  2. Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar

    E-Print Network [OSTI]

    radar data. 1 Introduction The National Weather Service operates the WSR-88D (Weather Surveillance Radar, weather, and even airborne dust. Consequently, data must be interpreted manually by a highly information collected by Doppler radar. Our model is based on wind profiling algorithms from the weather

  3. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  4. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

  5. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    System (REEPS 2.1) , developed by the Electric Power Research Institute (EPRI), is a forecasting model

  6. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01

    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.

  7. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  8. Weatherizing Wilkes-Barre

    Broader source: Energy.gov [DOE]

    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.

  9. Neighborhood Weatherization, Houston 

    E-Print Network [OSTI]

    Fowler, M.

    2011-01-01

    . 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 reserved. CATEE...

  10. Home Weatherization Visit

    Broader source: Energy.gov [DOE]

    Secretary Steven Chu visits a home that is in the process of being weatherized in Columbus, OH, along with Ohio Governor Ted Strickland and Columbus Mayor Michael Coleman. They discuss the benefits...

  11. Weatherizing Wilkes-Barre

    ScienceCinema (OSTI)

    Calore, Joe

    2013-05-29

    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.

  12. The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models

    SciTech Connect (OSTI)

    Zhou, Shujia; Duffy, Daniel; Clune, Thomas; Suarez, Max; Williams, Samuel; Halem, Milton

    2009-01-10

    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.

  13. Enduse Global Emissions Mitigation Scenarios (EGEMS): A New Generation of Energy Efficiency Policy Planning Models

    E-Print Network [OSTI]

    McNeil, Michael A.

    2010-01-01

    driver for the energy demand forecast. The basic assumptionglobal bottom-up energy demand forecasts, and a frameworkin modelling energy demand is to forecast activity. Activity

  14. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  15. A New Scheme for Predicting Fair-Weather Cumulus

    SciTech Connect (OSTI)

    Berg, Larry K.; Stull, Roland B.

    2007-04-01

    A new parameterization for boundary layer cumulus clouds, called the cumulus potential (CuP) scheme, is introduced. Unlike many other parameterizations, the CuP scheme explicitly links the fair-weather clouds to the boundary-layer turbulence and accounts for the non-local nature of the turbulence. This scheme uses joint probability density functions (JPDFs) of virtual potential temperature and water-vapor mixing ratio, as well as the mean vertical profiles of virtual potential temperature, to predict the amount and size distribution of boundary layer cloud cover. This model considers the diversity of air parcels over a heterogeneous surface, and recognizes that some parcels rise above their lifting condensation level to become cumulus, while other parcels might rise as clear updrafts. This model has several unique features: 1) surface heterogeneity and boundary-layer turbulence is represented using the boundary layer JPDF of virtual potential temperature versus water-vapor mixing ratio, 2) clear and cloudy thermals are allowed to coexist at the same altitude, and 3) a range of cloud-base heights, cloud-top heights, and cloud thicknesses are predicted within any one cloud field, as observed. Using data from Boundary Layer Experiment 1996 and a model intercomparsion study using large eddy simulation (LES) based on the Barbados Oceanographic and Meteorological Experiment (BOMEX), the CuP scheme is compared to three other cumulus parameterizations: one based on relative humidity, a statistical scheme based on the saturation deficit, and a slab model. It is shown that the CuP model does a better job predicting the cloud-base height and the cloud-top height than three other parameterizations. The model also shows promise in predicting cloud cover, and is found to give better cloud-cover estimates than the three other cumulus parameterizations. In ongoing work supported by the US Department of Energy¹s Atmospheric Radiation Measurement Program, the CuP scheme is being implemented in the Weather Research and Forecasting (WRF) model, in which it replaces the ad-hoc trigger function in an existing cumulus parameterization.

  16. DEVELOPMENT OF ADVANCED ALGORITHMS TO DETECT, CHARACTERIZE AND FORECAST SOLAR ACTIVITIES

    E-Print Network [OSTI]

    . This is critical for determining the non-potentiality of active regions. Solar flares are generated by the sudden earth space environment (so called space weather). In this dissertation, an automated solar flare machine) to forecast the occurrences of solar flares based on photospheric magnetic features. Logistic

  17. EUROBRISA: A EURO-BRazilian Initiative for improving South American seasonal forecasts

    E-Print Network [OSTI]

    Estudos Climáticos (CPTEC/INPE), Brazil, 2. Universidade de São Paulo (USP), Brazil 3.Universidade Federal do Paraná (UFPR), Brazil, 4. Instituto Nacional de Meteorologia (INMET), Brazil, 5. European Centre for Medium-Range and Weather Forecasts (ECMWF), 6. United Kingdom Met Office (UKMO), UK, 7. University

  18. Forecasting Spatiotemporal Impact of Traffic Incidents on Road Networks Bei Pan, Ugur Demiryurek, Cyrus Shahabi

    E-Print Network [OSTI]

    Shahabi, Cyrus

    Forecasting Spatiotemporal Impact of Traffic Incidents on Road Networks Bei Pan, Ugur Demiryurek and quantifying the impact of traffic incidents. Traffic incidents include any non-recurring events on road networks, including accidents, weather hazard, road construction or work zone closures. By analyzing

  19. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect (OSTI)

    Gonzalez, Frank

    2009-04-06

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  20. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  1. Improvements of the shock arrival times at the Earth model STOA

    E-Print Network [OSTI]

    Liu, H -L

    2015-01-01

    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.

  2. Sept. 18, 2012 Kahua A`o, A Learning Foundation Weather Maps and Hazardous Storms of Hawai`i Hurricane `Iniki making landfall over Kaua`i,

    E-Print Network [OSTI]

    Businger, Steven

    geological forces can help forecast the locations and likelihoods of future events (ibid). Hawai`i Standard 8's surface. SC.ES.8.7 Describe climate and weather patterns associated with certain geographic locations how we choose to dress, to what activities we do, and the plants we choose to grow. Hawai`i's weather

  3. Forecasting Stock Market Volatility: Evidence from Fourteen Countries. 

    E-Print Network [OSTI]

    Balaban, Ercan; Bayar, Asli; Faff, Robert

    2002-01-01

    This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously ...

  4. 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

  5. VALUE OF A WEATHER-READY NATION LAST REVISED 9/13/2011

    E-Print Network [OSTI]

    . The renewable energy industry is one such sector. Renewable energy firms use NOAA weather and climate forecasts of renewable energy. To meet the growing demand for information and to improve the timeliness and accuracy the agency, we have begun collecting data on the economic importance of the sectors we support, the costs

  6. WORKSHOP ON RADIATION BELTS: MODELS & STANDARDS, BRUSSELS, 17{20 OCT., 1995 Los Alamos Geosynchronous Space Weather Data For

    E-Print Network [OSTI]

    Reeves, Geoffrey D.

    WORKSHOP ON RADIATION BELTS: MODELS & STANDARDS, BRUSSELS, 17{20 OCT., 1995 Los Alamos. Henderson, R. A. Christensen, P. S. McLachlan, and J. C. Ingraham Los Alamos National Laboratory, Mail Stop D436, Los Alamos, NM 87545, USA, reeves@lanl.gov Abstract. This paper presents an overview

  7. Long-range weather prediction and prevention of climate catastrophes: a status report

    SciTech Connect (OSTI)

    Caldeira, K; Caravan, G; Govindasamy, B; Grossman, A; Hyde, R; Ishikawa, M; Ledebuhr, A; Leith, C; Molenkamp, C; Teller, E; Wood, L

    1999-08-18

    As the human population of Earth continues to expand and to demand an ever-higher quality-of-life, requirements for ever-greater knowledge--and then control--of the future of the state of the terrestrial biosphere grow apace. Convenience of living--and, indeed, reliability of life itself--become ever more highly ''tuned'' to the future physical condition of the biosphere being knowable and not markedly different than the present one, Two years ago, we reported at a quantitative albeit conceptual level on technical ways-and-means of forestalling large-scale changes in the present climate, employing practical means of modulating insolation and/or the Earth's mean albedo. Last year, we reported on early work aimed at developing means for creating detailed, high-fidelity, all-Earth weather forecasts of two weeks duration, exploiting recent and anticipated advances in extremely high-performance digital computing and in atmosphere-observing Earth satellites bearing high-technology instrumentation. This year, we report on recent progress in both of these areas of endeavor. Preventing the commencement of large-scale changes in the current climate presently appears to be a considerably more interesting prospect than initially realized, as modest insolation reductions are model-predicted to offset the anticipated impacts of ''global warming'' surprisingly precisely, in both space and time. Also, continued study has not revealed any fundamental difficulties in any of the means proposed for insolation modulation and, indeed, applicability of some of these techniques to other planets in the inner Solar system seems promising. Implementation of the high-fidelity, long-range weather-forecasting capability presently appears substantially easier with respect to required populations of Earth satellites and atmospheric transponders and data-processing systems, and more complicated with respect to transponder lifetimes in the actual atmosphere; overall, the enterprise seems more technically feasible than originally anticipated.

  8. Low-dimensional Models in Spatio-Temporal Wind Speed Forecasting Borhan M. Sanandaji, Akin Tascikaraoglu, , , Kameshwar Poolla, and Pravin Varaiya

    E-Print Network [OSTI]

    Sanandaji, Borhan M.

    Tascikaraoglu, , , Kameshwar Poolla, and Pravin Varaiya Abstract-- Integrating wind power into the grid to achieve the power balance needed for its integration into the grid [3], [4]. The use of ancillary services of wind power. The paper presents a spatio-temporal wind speed forecasting algorithm that incorporates

  9. Setups for Weathering Tests 

    E-Print Network [OSTI]

    Unknown

    2011-08-17

    cotton. This Web-based decision support system, the Crop Weather Program for South Texas (CWP), is stationed out of the Texas AgriLife Research and Extension Center at Corpus Christi. The program provides easy access to his- torical and current... weather data as well as cal- culators and other tools that generate useful field-specific information about the crop and its environment, said Dr. Carlos J. Fern?ndez, associate professor and the Plant Physiology and Cropping Systems Program?s leader...

  10. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

    S. Robbins; C. J. Henney; J. W. Harvey

    2007-01-09

    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.

  11. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

    Bin Wang; Ya-Zheng Chen; Xue-Qian Li

    2011-03-29

    We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

  12. Intelligent weather agent for aircraft severe weather avoidance 

    E-Print Network [OSTI]

    Bokadia, Sangeeta

    2002-01-01

    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...

  13. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  14. Weather regime prediction using statistical learning

    E-Print Network [OSTI]

    Deloncle, A.; Berk, Richard; D’Andrea, F.; Ghil, M.

    2005-01-01

    and B. Legras, 1995: Weather regimes: Recurrence and quasi10952. Molteni, F. , 2002: Weather regimes and multipleK. Ide, and M. Ghil, 2004: Weather regimes and preferred

  15. Infiltration as Ventilation: Weather-Induced Dilution

    E-Print Network [OSTI]

    Sherman, Max H.

    2014-01-01

    LOGICS. 1999. Canadian Weather for Energy Calculations, In:natural ventilation rate with weather conditions, Renewablefor ASHRAE 136 [1/h] WSF Weather and Shielding Factor [1/h

  16. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

    Deloncle, A.; Berk, Richard A.; D'Andrea, F.; Ghil, M.

    2005-01-01

    and B. Legras, 1995: Weather regimes: Recurrence and quasi10952. Molteni, F. , 2002: Weather regimes and multipleK. Ide, and M. Ghil, 2004: Weather regimes and preferred

  17. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

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

    2011-01-01

    and B. Legras, 1995: Weather regimes: Recurrence and quasi10952. Molteni, F. , 2002: Weather regimes and multipleK. Ide, and M. Ghil, 2004: Weather regimes and preferred

  18. Wind Power Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  19. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1£~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  20. Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary

    SciTech Connect (OSTI)

    Hollander, A.

    2014-09-01

    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.

  1. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  2. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  3. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  4. Global disease monitoring and forecasting with Wikipedia

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

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore »logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

  5. THE WEATHER VISUALIZER, JAVATM , HABANEROTM

    E-Print Network [OSTI]

    Wilhelmson, Robert

    13.19 THE WEATHER VISUALIZER, JAVATM , HABANEROTM , AND THE FUTURE Joel Plutchak* , Robert B Urbana-Champaign has developed a web-based visualization tool known as The Weather Visualizer (DAS, 1997 and images.__ Since its debut in 1995, the goals of the various versions of the Weather Visualizer have

  6. Summer Weather TheELIWeekly

    E-Print Network [OSTI]

    Sin, Peter

    Highlights · Midterms · Summer Weather · Manners · Grammar TheELIWeekly Midterms Good luck on your will be closed for the Independence Day Holiday. th th Summer Weather Safety We've come to realize in the past that not all of our students are aware of our unique weather problems in Central Florida. One hazard that you

  7. Useful Weather Links Nolan Doesken

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    Useful Weather Links Nolan Doesken Odie Bliss Colorado Climate Center Presented at ProfessionalAgMet (Colorado Agricultural Meteorological Network) · http://www.coagmet.com Weather data for agriculture #12://www.hprcc.unl.edu/index.php #12;BLM / Forest Service Remote Automated Weather Stations ­ RAWS · http://www.fs.fed.us/raws/ #12

  8. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

    of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach...

  9. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

    Economy, 95(5), 1062—1088. MULTIVARIATE FORECASTS Chaudhuri,Notion of Quantiles for Multivariate Data,” Journal of thePress, United Kingdom. MULTIVARIATE FORECASTS Kirchgässner,

  10. Weather Ready Nation: A Vital Conversation on

    E-Print Network [OSTI]

    Weather Ready Nation: A Vital Conversation on Tornadoes and Severe Weather A Community Report March;WeatherReady Nation: A Vital Conversation on Tornadoes and Severe Weather Report from the December 2011

  11. 7.5 Influence of Chemical Weathering on Hillslope Forms SM Mudd, University of Edinburgh, Edinburgh, UK

    E-Print Network [OSTI]

    Mudd, Simon Marius

    frequently, soil production is cast as a function of soil thickness. Abstract Chemical weathering affects7.5 Influence of Chemical Weathering on Hillslope Forms SM Mudd, University of Edinburgh, Edinburgh Model of Hillslope Evolution Including Chemical Weathering 56 7.5.2.1 The Chemical Weathering Mass

  12. Leveraging Resources for Weatherization Innovation Pilot Projects...

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

    Weatherization Innovation Pilot Projects (WIPP) Presentation Leveraging Resources for Weatherization Innovation Pilot Projects (WIPP) Presentation As a WIPP agency, reporting...

  13. Weatherize | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data CenterFinancialInvestingRenewableTeachDevelopmentWaterAt-A-GlanceWeatherize

  14. Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments

    SciTech Connect (OSTI)

    Robert Pincus

    2011-05-17

    This project focused on the variability of clouds that is present across a wide range of scales ranging from the synoptic to the millimeter. In particular, there is substantial variability in cloud properties at scales smaller than the grid spacing of models used to make climate projections (GCMs) and weather forecasts. These models represent clouds and other small-scale processes with parameterizations that describe how those processes respond to and feed back on the largescale state of the atmosphere.

  15. A Framework of Short-Term Activity-Aware Load Forecasting Yong Ding, Martin Neumann and Michael Beigl

    E-Print Network [OSTI]

    Beigl, Michael

    the best use of electric energy and relieve the conflict between supply and demand [Niu et al., 2010]. However, inaccurate load forecasts will lead to not only monetary losses but also grid security losses), such as weather factors, climatic conditions, social activi- ties, and seasonal factors, past usage patterns

  16. Virginie GUEMAS, Lead researcher for Polar Climate Prediction in the Climate Forecasting Unit (CFU) at IC3

    E-Print Network [OSTI]

    Virginie GUEMAS, Lead researcher for Polar Climate Prediction in the Climate Forecasting Unit (CFU in exchange for a commitment to do a PhD. INVITED STAYS · ECMWF (European Center for Medium Range Weather, Reading, England).in December 2008: invitation by Rowan Sutton for a one-week stay #12;PEER REVIEWED

  17. Shedding Light on the Weather Srinivasa G. Narasimhan and Shree K. Nayar

    E-Print Network [OSTI]

    Nayar, Shree K.

    Shedding Light on the Weather Srinivasa G. Narasimhan and Shree K. Nayar Computer Science Dept in image processing and computer vision, for removing weather effects from images, as- sume single in bad weather. Modeling multiple scattering is critical to un- derstanding the complex effects

  18. "WEATHER IN A TANK" exploiting Laboratory experiments in the Teaching of

    E-Print Network [OSTI]

    Lee, Sukyoung

    "WEATHER IN A TANK" exploiting Laboratory experiments in the Teaching of meteorology, oceanography revealing midlatitude weather systems (the North Pole is in the middle) "stirring" properties between that govern atmospheric synoptic-scale weather systems. The laboratory model is a simplified system

  19. Quadratic hedging of weather and catastrophe risk by using short term climate predictions

    E-Print Network [OSTI]

    Imkeller, Peter

    Quadratic hedging of weather and catastrophe risk by using short term climate predictions Stefan 10099 Berlin Germany February 12, 2008 Abstract The extent to which catastrophic weather events occur into account in any reasonable management of weather related risk. In this paper we first set up a risk model

  20. Winter Weather Outlook

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubictheThe U.S. Department ofWinners0 Winter Weather

  1. Winter Weather Outlook

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubictheThe U.S. Department ofWinners0 Winter Weather1

  2. Forecasting the 2013–2014 influenza season using Wikipedia

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

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore »to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  3. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  4. Bishop Paiute Weatherization Training Program

    SciTech Connect (OSTI)

    Carlos Hernandez

    2010-01-28

    The DOE Weatherization Training Grant assisted Native American trainees in developing weatherization competencies, creating employment opportunities for Bishop Paiute tribal members in a growing field. The trainees completed all the necessary training and certification requirements and delivered high-quality weatherization services on the Bishop Paiute Reservation. Six tribal members received all three certifications for weatherization; four of the trainees are currently employed. The public benefit includes (1) development of marketable skills by low-income Native individuals, (2) employment for low-income Native individuals in a growing industry, and (3) economic development opportunities that were previously not available to these individuals or the Tribe.

  5. Weatherization Apprenticeship Program

    SciTech Connect (OSTI)

    Watson, Eric J

    2012-12-18

    Weatherization improvement services will be provided to Native people by Native people. The proposed project will recruit, train and hire two full-time weatherization technicians who will improve the energy efficiency of homes of Alaska Natives/American Indians residing in the Indian areas, within the Cook Inlet Region of Alaska. The Region includes Anchorage as well as 8 small tribal villages: The Native Villages of Eklutna, Knik, Chickaloon, Seldovia, Ninilchik, Kenaitze, Salamatof, and Tyonek. This project will be a partnership between three entities, with Cook Inlet Tribal Council (CITC) as the lead agency: CITCA's Employment and Training Services Department, Cook Inlet Housing Authority and Alaska Works Partnership. Additionally, six of the eight tribal villages within the Cook Inlet Region of Alaska have agreed to work with the project in order to improve the energy efficiency of their tribally owned buildings and homes. The remaining three villages will be invited to participate in the establishment of an intertribal consortium through this project. Tribal homes and buildings within Anchorage fall under Cook Inlet Region, Inc. (CIRI) tribal authority.

  6. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  7. Wind Forecast Improvement Project Southern Study Area Final Report...

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

    Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study...

  8. Reducing Extreme Weather Impacts: Building a Weather-Ready Nation For more than 140 years, the National Weather Service (NWS) has provided weather, water, and climate

    E-Print Network [OSTI]

    Reducing Extreme Weather Impacts: Building a Weather-Ready Nation For more than 140 years, the National Weather Service (NWS) has provided weather, water, and climate information to protect lives also been a year of extreme weather events. The impact of these events, both on lives and the economy

  9. QUANTIFICATION OF WEATHERING Robert Hack

    E-Print Network [OSTI]

    Hack, Robert

    : Weathering and especially future weathering after construction of a slope is a main cause for failure Proc. Engineering geology and the environment. Athens. Eds. Marinos et al.. 1997. Publ. Balkema 40 60 80 H slate medium H slate v.thin H slate tick lam. Tg21 thick Tg21 medium Tg21 thin Tg21 v

  10. MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler

    E-Print Network [OSTI]

    Stuefer, Martin

    MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler Geophysical Institute, University of Alaska, Fairbanks 1. Abstract Fifth-generation mesoscale model (MM5) is being used air. Algorithm input data are MM5 forecasted temperature and humidity values at defined pressure

  11. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching

    E-Print Network [OSTI]

    Genton, Marc G.

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

  12. Ensemble-based air quality forecasts: A multimodel approach applied to ozone

    E-Print Network [OSTI]

    Mallet, Vivien

    Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1 21 September 2006. [1] The potential of ensemble techniques to improve ozone forecasts ozone-monitoring networks. We found that several linear combinations of models have the potential

  13. Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts

    E-Print Network [OSTI]

    Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts Electricity prices in the Council's Power Plan are forecast using the AURORATM Electricity Market Model of the entire prices at several pricing points in the West, four of which are in the Pacific Northwest. The one most

  14. Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Department of Computer Science

    E-Print Network [OSTI]

    Hwang, Kai

    peak demand periods using pricing incentives. Reliable building energy forecast models can help predictImproving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Saima Aman prasanna@usc.edu Abstract--The rising global demand for energy is best addressed by adopting and promoting

  15. TMY2 Weather Data | Department of Energy

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

    TMY2 Weather Data TMY2 Weather Data TMY2 weather data that were used to generate the reference buildings refbldgs-v1.35.0-weatherfilestmy2.zip More Documents & Publications TMY2...

  16. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    and operation of solar power plants and the model- ing offor application to solar ther- mal power plants energy

  17. Weatherization Formula Grants - American Recovery and Reinvestment...

    Energy Savers [EERE]

    Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) U.S. Department of...

  18. Incorporating Weather Data into Energy Savings Calculations ...

    Energy Savers [EERE]

    Incorporating Weather Data into Energy Savings Calculations Incorporating Weather Data into Energy Savings Calculations Better Buildings Residential Network Peer Exchange Call...

  19. WEATHER MODIFICATION BY AIRCRAFT CLOUD SEEDING

    E-Print Network [OSTI]

    Vali, Gabor

    WEATHER MODIFICATION BY AIRCRAFT CLOUD SEEDING BERYULEV G.P. Head, Department of Cloud Physics and Weather Modification Central Aerological Observatory Rosgidromet, Russian Federation #12

  20. New York: Weatherizing Westbeth Reduces Energy Consumption |...

    Office of Environmental Management (EM)

    York: Weatherizing Westbeth Reduces Energy Consumption New York: Weatherizing Westbeth Reduces Energy Consumption August 21, 2013 - 12:00am Addthis The New York State Homes and...

  1. Los Alamos Space Weather Summer School

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

    Non-U.S Citizens Mentors, Projects Papers, Reports Photos NSEC IGPPS Space Weather Summer School Los Alamos Space Weather Summer School June 1 - July 24, 2015 Contacts...

  2. Connecticut's Health Impact Study Rapidly Increasing Weatherization...

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

    Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts June 18, 2014 - 10:49am...

  3. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  4. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  5. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

    Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

  6. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

  7. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    income 7 Figure 1.14: United States inflation Rate 8 Figure 1.15: Select United States interest Rates 8 2014 TABLE OF CONTENTS EXECUTiVE SUMMARY 1 CHAPTER 1: THE UNiTED STATES ECONOMY 3 Recent Trends Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

  8. The Role of Multimodel Climate Forecasts in Improving Water and Energy Management over the Tana River Basin, Kenya

    E-Print Network [OSTI]

    Arumugam, Sankar

    - logical ensembles are used in a reservoir model to allocate water for power generation by ensuring clima. Retrospective reservoir analysis shows that inflow forecasts developed from single GCM and multiple GCMs perform the single- model inflow forecasts by reducing uncertainty and the overconfidence of individual model

  9. Survey and Analysis of Weather Data for Building Energy Simulations

    SciTech Connect (OSTI)

    Bhandari, Mahabir S [ORNL; Shrestha, Som S [ORNL; New, Joshua Ryan [ORNL

    2012-01-01

    In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data plays an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data for 20-35 km2 grid across the globe. Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct, diffuse and horizontal solar radiation; and wind speed are statistically compared. Moreover, we ascertain the relative contributions of each weather variable and its impact on building loads. Annual simulations are calculated for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by 7% while monthly building loads can vary by 40% as a function of the provided location s weather data.

  10. WeatherMaker: Weather file conversion and evaluation

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1999-07-01

    WeatherMaker is a weather-data utility for use with the ENERGY-10 design-tool computer program. The three main features are: Convert--Weather files can be converted from one format to another. For example, a TMY2 format file can be converted to an ENERGY-10 binary file that can be used in a simulation. This binary file can then be converted to a text format that allows it to be read and/or manipulated in WordPad or Excel. Evaluate--ENERGY-10 weather files can be studied in great detail. There are 8 graphical displays of the data that provide insight into the data, and a summary tables that presents results calculated from the hourly data. Adjust--Hourly temperature data can be adjusted starting with hourly data from a nearby TMY2 site. Dry-bulb and wet-bulb temperatures are adjusted up or down as required to match given monthly statistics. This feature can be used to generate weather files for any of 3,958 sites in the US where such monthly statistics are tabulated. The paper shows a variety of results, explains the methods used, and discusses the rationale for making the adjustments. It is anticipated that WeatherMaker will be released by the time of the ASES Solar 99 conference.

  11. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

  12. Volterra network modeling of the nonlinear finite-impulse reponse of the radiation belt flux

    SciTech Connect (OSTI)

    Taylor, M.; Daglis, I. A.; Anastasiadis, A. [Institute for Space Applications and Remote Sensing(ISARS), National Observatory of Athens (NOA), Metaxa and Vasillis Pavlou Street, Penteli, Athens 15236 (Greece); Vassiliadis, D. [Department of Physics, Hodges Hall, PO Box 6315, West Virginia University, Morgantown, WV 26506-6315 (United States)

    2011-01-04

    We show how a general class of spatio-temporal nonlinear impulse-response forecast networks (Volterra networks) can be constructed from a taxonomy of nonlinear autoregressive integrated moving average with exogenous inputs (NAR-MAX) input-output equations, and used to model the evolution of energetic particle f uxes in the Van Allen radiation belts. We present initial results for the nonlinear response of the radiation belts to conditions a month earlier. The essential features of spatio-temporal observations are recovered with the model echoing the results of state space models and linear f nite impulse-response models whereby the strongest coupling peak occurs in the preceding 1-2 days. It appears that such networks hold promise for the development of accurate and fully data-driven space weather modelling, monitoring and forecast tools.

  13. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

    Forecasting phenology under global warming Ine´s Iba´n~ez1,*, Richard B. Primack2, Abraham J in phenology. Keywords: climate change; East Asia, global warming; growing season, hierarchical Bayes; plant is shifting, and these shifts have been linked to recent global warming (Parmesan & Yohe 2003; Root et al

  14. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

  15. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore »larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  16. 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 Southern Study Area, Final Report

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  17. Weather vs. Climate What is the difference between

    E-Print Network [OSTI]

    Johnson, Cari

    Consul7ng #12;Weather Consul6ng Using Climate Data · A weather consultant helps people or businesses make decisions based on knowledge of weather or climateWeather vs. Climate #12;What is the difference between weather and climate

  18. Low-Income Weatherization: The Human Dimension

    Broader source: Energy.gov [DOE]

    This presentation focuses on how the human dimension saves energy within low-income weatherization programs.

  19. Arizona Foundation Expands Weatherization Training Center

    Broader source: Energy.gov [DOE]

    Read about one weatherization training center that's looking forward to an onslaught of new trainees.

  20. Monthly Weather Review EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Monthly Weather Review EARLY ONLINE RELEASE This is a preliminary PDF of the author, Colorado5 December 20126 (submitted to Monthly Weather Review)7 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt AFB, NE, 68113