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1

Short-Termed Integrated Forecasting System: 1993 Model documentation report  

Science Conference Proceedings (OSTI)

The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

Not Available

1993-05-01T23:59:59.000Z

2

ORNL integrated forecasting system  

SciTech Connect

This paper describes the integrated system for forecasting electric energy and load. In the system, service area models of electrical energy (kWh) and load distribution (minimum and maximum loads and load duration curve) are linked to a state-level model of electrical energy (kWh). Thus, the service area forecasts are conditional upon the state-level forecasts. Such a linkage reduces considerably the data requirements for modeling service area electricity demand.

Rizy, C.G.

1983-01-01T23:59:59.000Z

3

Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)  

DOE Green Energy (OSTI)

The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.

Not Available

1985-07-01T23:59:59.000Z

4

Annual Cycle Integration of the NMC Medium-Range Forecasting (MRF) Model  

Science Conference Proceedings (OSTI)

The NMC Global Spectral Model was integrated for one year. The model used is the same as the 1989 operational medium range forecast model except that the horizontal resolution was reduced from T80 to T40. Overall, the model was very successful in ...

M. Kanamitsu; K. C. Mo; E. Kalnay

1990-12-01T23:59:59.000Z

5

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network (OSTI)

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN; the former with primary contributions in the areas of climate and hydrologic forecasting and the latter Service (NWS) California Nevada River Forecast Center (CNRFC), the California Department of Water

6

Comparative analysis of models integrating synoptic forecast data into potato late blight risk estimate systems  

Science Conference Proceedings (OSTI)

Determinacy analysis, logistic regression, discriminant analysis and neural network models were compared for their accuracy in 5-day (120h) forecasts of daily potato late blight risk according to a modified-Wallin disease severity model. For 12 locations ... Keywords: Expert systems, Forecasting, Neural network models, Risk mitigation

Kathleen M. Baker; William W. Kirk

2007-05-01T23:59:59.000Z

7

HYBRID GREY RELATIONAL ARTIFICIAL NEURAL NETWORK AND AUTO REGRESSIVE INTEGRATED MOVING AVERAGE MODEL FOR FORECASTING TIME-SERIES DATA  

Science Conference Proceedings (OSTI)

The aim of this study is to develop a new hybrid model by combining a linear and nonlinear model for forecasting time-series data. The proposed model (GRANN_ARIMA) integrates nonlinear grey relational artificial neural network (GRANN) and a linear autoregressive ...

Roselina Sallehuddin; Siti Mariyam Hj. Shamsuddin

2009-05-01T23:59:59.000Z

8

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

Reports and Publications (EIA)

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

Information Center

1998-03-01T23:59:59.000Z

9

Toward an Integrated Seasonal Forecasting System for South America  

Science Conference Proceedings (OSTI)

This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: (i) an empirical model that uses Pacific and ...

C. A. S. Coelho; D. B. Stephenson; M. Balmaseda; F. J. Doblas-Reyes; G. J. van Oldenborgh

2006-08-01T23:59:59.000Z

10

Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system  

Science Conference Proceedings (OSTI)

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders

1989-09-01T23:59:59.000Z

11

Modeling and Forecasting Aurora  

Science Conference Proceedings (OSTI)

Modeling the physical processes needed for forecasting space-weather events requires multiscale modeling. This article discusses several modelsresearchers use to treat the various auroral processes that influence space weather.

Dirk Lummerzheim

2007-01-01T23:59:59.000Z

12

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

E-Print Network (OSTI)

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

Bush, Sarah, 1973-

2003-01-01T23:59:59.000Z

13

Consensus Forecasts of Modeled Wave Parameters  

Science Conference Proceedings (OSTI)

The use of numerical guidance has become integral to the process of modern weather forecasting. Using various techniques, postprocessing of numerical model output has been shown to mitigate some of the deficiencies of these models, producing more ...

Tom H. Durrant; Frank Woodcock; Diana J. M. Greenslade

2009-04-01T23:59:59.000Z

14

A new class of hybrid models for time series forecasting  

Science Conference Proceedings (OSTI)

Applying quantitative models for forecasting and assisting investment decision making has become more indispensable in business practices than ever before. Improving forecasting especially time series forecasting accuracy is an important yet often difficult ... Keywords: Artificial neural networks (ANNs), Auto-Regressive Integrated Moving Average (ARIMA), Hybrid models, Probabilistic neural networks (PNNs), Time series forecasting

Mehdi Khashei; Mehdi Bijari

2012-03-01T23:59:59.000Z

15

Why are survey forecasts superior to model forecasts?  

E-Print Network (OSTI)

We investigate two characteristics of survey forecasts that are shown to contribute to their superiority over purely model-based forecasts. These are that the consensus forecasts incorporate the effects of perceived changes in the long-run outlook, as well as embodying departures from the path toward the long-run expectation. Both characteristics on average tend to enhance forecast accuracy. At the level of the individual forecasts, there is scant evidence that the second characteristic enhances forecast accuracy, and the average accuracy of the individual forecasts can be improved by applying a mechanical correction.

Michael P. Clements; Michael P. Clements

2010-01-01T23:59:59.000Z

16

Dynamic filter weights neural network model integrated with differential evolution for day-ahead price forecasting in energy market  

Science Conference Proceedings (OSTI)

In this paper a new dynamic model for forecasting electricity prices from 1 to 24h in advance is proposed. The model is a dynamic filter weight Adaline using a sliding mode weight adaptation technique. The filter weights for this neuron constitute of ... Keywords: Differential evolution, Dynamic filter weights neuron, Energy market, Local linear wavelet neural network, Sliding mode control

S. Chakravarty; P. K. Dash

2011-09-01T23:59:59.000Z

17

Virtual Floe Ice Drift Forecast Model Intercomparison  

Science Conference Proceedings (OSTI)

Both sea ice forecast models and methods to measure their skill are needed for operational sea ice forecasting. Two simple sea ice models are described and tested here. Four different measures of skill are also tested. The forecasts from the ...

Robert W. Grumbine

1998-09-01T23:59:59.000Z

18

Ensemble Cloud Model Applications to Forecasting Thunderstorms  

Science Conference Proceedings (OSTI)

A cloud model ensemble forecasting approach is developed to create forecasts that describe the range and distribution of thunderstorm lifetimes that may be expected to occur on a particular day. Such forecasts are crucial for anticipating severe ...

Kimberly L. Elmore; David J. Stensrud; Kenneth C. Crawford

2002-04-01T23:59:59.000Z

19

Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness  

E-Print Network (OSTI)

In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms cannot distinguish between the ideal forecast and several competing forecasts. In this paper we show that their example has some unrealistic features from the perspective of the time-series forecasting literature, hence it is an insecure foundation for their argument that existing calibration procedures are inadequate in practice. We present an alternative, more realistic example in which relevant statistical methods, including information-based methods, provide the required discrimination between competing forecasts. We conclude that there is no need for a subsidiary criterion of sharpness.

James Mitchell; Kenneth F. Wallis

2008-01-01T23:59:59.000Z

20

Bayesian Model Verification of NWP Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Forecasts of convective precipitation have large uncertainties. To consider the forecast uncertainties of convection-permitting models, a convection-permitting ensemble prediction system (EPS) based on the Consortium for Small-scale Modeling (...

Andreas Röpnack; Andreas Hense; Christoph Gebhardt; Detlev Majewski

2013-01-01T23:59:59.000Z

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


21

A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System  

Science Conference Proceedings (OSTI)

The Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) is used operationally in the Integrated Forecast System (IFS) for describing the evolution of soil, vegetation, and snow over the continents at diverse spatial resolutions. A revised ...

Gianpaolo Balsamo; Anton Beljaars; Klaus Scipal; Pedro Viterbo; Bart van den Hurk; Martin Hirschi; Alan K. Betts

2009-06-01T23:59:59.000Z

22

Regional Climate–Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are ...

Xin-Zhong Liang; Min Xu; Xing Yuan; Tiejun Ling; Hyun I. Choi; Feng Zhang; Ligang Chen; Shuyan Liu; Shenjian Su; Fengxue Qiao; Yuxiang He; Julian X. L. Wang; Kenneth E. Kunkel; Wei Gao; Everette Joseph; Vernon Morris; Tsann-Wang Yu; Jimy Dudhia; John Michalakes

2012-09-01T23:59:59.000Z

23

The Use of Digital Warping of Microwave Integrated Water Vapor Imagery to Improve Forecasts of Marine Extratropical Cyclones  

Science Conference Proceedings (OSTI)

A technique is described in which forecasts of the locations of features associated with marine cyclones may be improved through the use of microwave integrated water vapor (IWV) imagery and image warping of forecast mesoscale model fields. Here, ...

G. David Alexander; James A. Weinman; J. L. Schols

1998-06-01T23:59:59.000Z

24

A novel hybridization of artificial neural networks and ARIMA models for time series forecasting  

Science Conference Proceedings (OSTI)

Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing decision makers in many areas. Both theoretical and empirical findings have indicated that integration of different models can be an effective ... Keywords: Artificial neural networks (ANNs), Auto-regressive integrated moving average (ARIMA), Hybrid models, Time series forecasting

Mehdi Khashei; Mehdi Bijari

2011-03-01T23:59:59.000Z

25

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

E-Print Network (OSTI)

This paper develops depositional sequences of the carbonate ramp and the carbonate shelf models for an idealized cycle and multiple cycles of depositions. Based on the developed depositional sequences, the integrated recovery efficiency forecast models of primary, initial waterflood and infill drilling are developed for the San Andres and Clearfork reservoirs in Central Basin Platform and the Northern Shelf, west Texas. The geological parameters and well spacing are considered major factors for controlling recovery efficiencies. The depositional environment and diagenesis are controlling geological factors affecting oil recovery efficiencies. The depositional sequences characterize the vertical and lateral variations of depositional-energy environments in development of the carbonate ramp and the carbonate shelf The depositional-energy environment controls the depositional rock's facies. The well-sorted and large-size grainstones are related to the higher depositional-energy environment. The poorly-sorted and small-size rocks are related to the lower depositional-energy environment. The depositions of the San Andres and Clearfork formation in the Central Basin Platform, separately, follow the prograding-ramp sequences of one major cycle with multiple subcycles. The lumping depositional energy increases from the inner platform to the platform boundary. Similarly, the depositions of San Andres and Clearfork formation in the Northern Shelf also follow one major prograding cycle with multiple subcycles, separately. However, the lumping depositional energy, decreases from the inner platform to the platform boundary. A normalized depositional energy index is defined based on the depositional sequences of the ramp and shelf models. Normalization is also used to define a porosity index and a well spacing index. Linear and exponential regressions on a database are conducted to develop recovery efficiency forecast models which include depositional energy, porosity and well spacing indices. Section 17, Dollarhide Clearfork Unit is used as an example to show the applications of the recovery efficiency forecast models.

Shao, Hongbin

1994-01-01T23:59:59.000Z

26

Integrated Forecasting and Inventory Control for Seasonal Demand ...  

E-Print Network (OSTI)

We present a data-driven forecasting technique with integrated inventory ... ponents of inventory management: the random demand is first estimated using ...

27

Integrated Forecasting and Inventory Control for Seasonal Demand  

E-Print Network (OSTI)

Mar 14, 2008 ... Abstract: We present a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional ...

28

Probabilistic Visibility Forecasting Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical postprocessing technique that has been used in probabilistic weather forecasting to calibrate forecast ensembles and generate predictive probability density functions (PDFs) for weather quantities. ...

Richard M. Chmielecki; Adrian E. Raftery

2011-05-01T23:59:59.000Z

29

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect

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

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

2009-03-01T23:59:59.000Z

30

A spatially distributed flash flood forecasting model  

Science Conference Proceedings (OSTI)

This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model ... Keywords: Distributed modelling, Dominant processes concept, Floods, Forecasting, Kalman Filter, Model accuracy, Parameter identification, Stream routing

Günter Blöschl; Christian Reszler; Jürgen Komma

2008-04-01T23:59:59.000Z

31

Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model  

E-Print Network (OSTI)

1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates

32

Ability to Forecast Regional Soil Moisture with a Distributed Hydrological Model Using ECMWF Rainfall Forecasts  

Science Conference Proceedings (OSTI)

This study mimics an online forecast system to provide nine day-ahead forecasts of regional soil moisture. It uses modified ensemble rainfall forecasts from the numerical weather prediction model of the European Centre for Medium-Range Weather ...

J. M. Schuurmans; M. F. P. Bierkens

2009-04-01T23:59:59.000Z

33

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B.B. Blevins Executive Director DISCLAIMER This report was prepared by a California has developed longterm forecasts of transportation energy demand as well as projected ranges

34

Operational forecasting based on a modified Weather Research and Forecasting model  

DOE Green Energy (OSTI)

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

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

35

Improving week two forecasts with multi-model re-forecast ensembles  

E-Print Network (OSTI)

Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr´ed´eric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill

Whitaker, Jeffrey S.

36

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network (OSTI)

1 Increasing NOAA's computational capacity to improve global forecast modeling A NOAA of the NWS's forecast products, even its regional forecast products, are constrained by the limitations of NOAA's global forecast model. Unfortunately, our global forecasts are less accurate than those from

Hamill, Tom

37

Dynamical Properties of Model Output Statistics Forecasts  

Science Conference Proceedings (OSTI)

The dynamical properties of forecasts corrected using model output statistics (MOS) schemes are explored, with emphasis on the respective role of model and initial condition uncertainties. Analytical and numerical investigations of low-order ...

S. Vannitsem; C. Nicolis

2008-02-01T23:59:59.000Z

38

Short-term load forecasting using lifting scheme and ARIMA models  

Science Conference Proceedings (OSTI)

Short-term load forecasting is achieved using a lifting scheme and autoregressive integrated moving average (ARIMA) models. The lifting scheme is a general and flexible approach for constructing bi-orthogonal wavelets that are usually in the spatial ... Keywords: Autoregressive integrated moving average model, Back propagation network, Lifting scheme, Multi-revolution analysis, Short-term load forecasting, Wavelet transform

Cheng-Ming Lee; Chia-Nan Ko

2011-05-01T23:59:59.000Z

39

Nambe Pueblo Water Budget and Forecasting model.  

SciTech Connect

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.

Brainard, James Robert

2009-10-01T23:59:59.000Z

40

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multi-model Ensemble Forecasts  

Science Conference Proceedings (OSTI)

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

Jianguo Liu; Zhenghui Xie

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


41

Evaluation of MJO Forecast Skill from Several Statistical and Dynamical Forecast Models  

Science Conference Proceedings (OSTI)

This work examines the performance of Madden–Julian oscillation (MJO) forecasts from NCEP’s coupled and uncoupled general circulation models (GCMs) and statistical models. The forecast skill from these methods is evaluated in near–real time. ...

Kyong-Hwan Seo; Wanqiu Wang; Jon Gottschalck; Qin Zhang; Jae-Kyung E. Schemm; Wayne R. Higgins; Arun Kumar

2009-05-01T23:59:59.000Z

42

Further Evaluation of the National Meterological Center's Medium-Range Forecast Model Precpitation Forecasts  

Science Conference Proceedings (OSTI)

Precipitation forecasts made by the National Meteorological Center's medium-range forecast (MRF) model are evaluated for the period, 1 March 1987 to 31 March 1989. As shown by Roads and Maisel, the MRF model wet bias was substantially alleviated ...

John O. Roads; T. Norman Maisal; Jordan Alpert

1991-12-01T23:59:59.000Z

43

Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint  

SciTech Connect

As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

2013-11-01T23:59:59.000Z

44

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

SciTech Connect

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

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

2013-12-18T23:59:59.000Z

45

Does increasing model stratospheric resolution improve extended range forecast skill?  

E-Print Network (OSTI)

Does increasing model stratospheric resolution improve extended range forecast skill? Greg Roff,1 forecast skill at high Southern latitudes is explored. Ensemble forecasts are made for two model configurations that differ only in vertical resolution above 100 hPa. An ensemble of twelve 30day forecasts

46

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

of future contributions from various emerging transportation fuels and technologies is unknown. PotentiallyCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

47

Improved Model Output Statistics Forecasts through Model Consensus  

Science Conference Proceedings (OSTI)

Consensus forecasts are computed by averaging model output statistics (MOS) forecasts based on the limited-area fine-mesh (LFM) model and the nested grid model (NGM) for the three-year period 1990–92. The test consists of four weather elements (...

Robert L. Vislocky; J. Michael Fritsch

1995-07-01T23:59:59.000Z

48

Time dependent Directional Profit Model for Financial Time Series Forecasting  

E-Print Network (OSTI)

Time dependent Directional Profit Model for Financial Time Series Forecasting Jingtao YAO Chew Lim@comp.nus.edu.sg Abstract Goodness­of­fit is the most popular criterion for neural network time series forecasting. In the context of financial time series forecasting, we are not only concerned at how good the forecasts fit

Yao, JingTao

49

Optimal statistical model for forecasting ozone  

Science Conference Proceedings (OSTI)

The objective of this paper is to apply time series analysis and multiple regression method to ozone data in order to obtain the optimal statistical model for forecasting next day ozone level. The best estimated model is then used to produce one-step ... Keywords: ARMA (p, q), Durbin-Watson Statistic, MAPE, R-square, multiple regression

M. Abdollahian; R. Foroughi; N. Debnath

2006-04-01T23:59:59.000Z

50

Forecasting Techniques The Use of Hourly Model-Generated Soundings to Forecast Mesoscale Phenomena. Part I: Initial Assessment in Forecasting Warm-Season Phenomena  

Science Conference Proceedings (OSTI)

Since late 1995, NCEP has made available to forecasters hourly model guidance at selected sites in the form of vertical profiles of various forecast fields. These profiles provide forecasters with increased temporal resolution and greater ...

Robert E. Hart; Gregory S. Forbes; Richard H. Grumm

1998-12-01T23:59:59.000Z

51

Model documentation: electricity market module. [15 year forecasts  

SciTech Connect

This report documents the electricity market model. This model is a component of the Intermediate Future Forecasting System (IFFS), the energy market model used to provide projections of energy markets up to 15 years into the future. The electricity market model was developed by the Supply Analysis and Integration Branch as part of building the larger system. This report is written for an audience consisting of mathematical economists, statisticians, operations research analysts, and utility planners. This report contains an overview and a mathematical specification of the electricity market module. It includes a description of the model logic and the individual subroutines in the computer code. A companion document Intermediate Future Forecasting System: Executive Summary (DOE/EIA-430) provides an overview of the components in IFFS and their linkages. 22 figures, 2 tables.

Sanders, R.C.; Murphy, F.H.

1984-12-01T23:59:59.000Z

52

Short-Term Forecast Validation of Six Models  

Science Conference Proceedings (OSTI)

The short-term forecast accuracy of six different forecast models over the western United States is described for January, February, and March 1996. Four of the models are operational products from the National Centers for Environmental ...

Bryan G. White; Jan Paegle; W. James Steenburgh; John D. Horel; Robert T. Swanson; Louis K. Cook; Daryl J. Onton; John G. Miles

1999-02-01T23:59:59.000Z

53

Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework  

E-Print Network (OSTI)

Calibrated probabilistic forecasting using ensemble modelSutcliffe (1970), River flow forecasting through conceptuala Distributed Flood Forecasting Model with Input Uncertainty

Li, M.

2013-01-01T23:59:59.000Z

54

New Concepts in Wind Power Forecasting Models  

E-Print Network (OSTI)

of the motivations behind the project led by ANL ­ Argonne National Laboratory, together with INESC Porto from a manageable procedure to compute the solution. IV. ENTROPY AND PARZEN WINDOW PDF ESTIMATION The most well into the substation connecting it to the electric power network. Other model's input variables include forecasts

Kemner, Ken

55

Forecasting Electricity Demand by Time Series Models  

Science Conference Proceedings (OSTI)

Electricity demand is one of the most important variables required for estimating the amount of additional capacity required to ensure a sufficient supply of energy. Demand and technological losses forecasts can be used to control the generation and distribution of electricity more efficiently. The aim of this paper is to utilize time series model

E. Stoimenova; K. Prodanova; R. Prodanova

2007-01-01T23:59:59.000Z

56

Possibility of Skill Forecast Based on the Finite-Time Dominant Linear Solutions for a Primitive Equation Regional Forecast Model  

Science Conference Proceedings (OSTI)

The possibility of using forecast errors originating from the finite-time dominant linear modes for the prediction of forecast skill for a primitive equation regional forecast model is studied. This is similar to the method for skill prediction ...

Tomislava Vuki?evi?

1993-06-01T23:59:59.000Z

57

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

Science Conference Proceedings (OSTI)

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

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

2013-07-25T23:59:59.000Z

58

A Nested Spectral Model for Hurricane Track Forecasting  

Science Conference Proceedings (OSTI)

A numerical method for analysing and forecasting a wide range of horizontal scales of motion is tested in a barotropic hurricane track forecast model. The numerical method uses cubic B-spline representations of variables on nested domains. The ...

Mark Demaria; Sim D. Aberson; Katsuyuki V. Ooyama; Stephen J. Lord

1992-08-01T23:59:59.000Z

59

Extended-Range Probability Forecasts Based on Dynamical Model Output  

Science Conference Proceedings (OSTI)

A probability forecast has advantages over a deterministic forecast as the former offers information about the probabilities of various possible future states of the atmosphere. As physics-based numerical models find their success in modern ...

Jianfu Pan; Huug van den Dool

1998-12-01T23:59:59.000Z

60

A Short-Range Objective Nocturnal Temperature Forecasting Model  

Science Conference Proceedings (OSTI)

A relatively simple, objective, nocturnal temperature forecasting model suitable for freezing and near-freezing conditions has been designed so that a user, presumably a weather forecaster, can put in standard meteorological data at a particular ...

Robert A. Sutherland

1980-03-01T23:59:59.000Z

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


61

The development of a statistical forecast model for Changma  

Science Conference Proceedings (OSTI)

Forecasting year-to-year variation in East Asian summer monsoon (EASM) precipitation is one of the most challenging tasks in climate prediction because predictors are not sufficiently well known and forecast skill by numerical models is poor. In ...

Seung-Eon Lee; Kyong-Hwan Seo

62

A Probability Model for Verifying Deterministic Forecasts of Extreme Events  

Science Conference Proceedings (OSTI)

This article proposes a method for verifying deterministic forecasts of rare, extreme events defined by exceedance above a high threshold. A probability model for the joint distribution of forecasts and observations, and based on extreme-value ...

Christopher A. T. Ferro

2007-10-01T23:59:59.000Z

63

How Essential is Hydrologic Model Calibration to Seasonal Streamflow Forecasting?  

Science Conference Proceedings (OSTI)

Hydrologic model calibration is usually a central element of streamflow forecasting based on the ensemble streamflow prediction (ESP) method. Evaluation measures of forecast errors such as root-mean-square error (RMSE) are heavily influenced by ...

Xiaogang Shi; Andrew W. Wood; Dennis P. Lettenmaier

2008-12-01T23:59:59.000Z

64

Forecast Combinations of Computational Intelligence and Linear Models for the  

E-Print Network (OSTI)

Forecast Combinations of Computational Intelligence and Linear Models for the NN5 Time Series Forecasting competition Robert R. Andrawis Dept Computer Engineering Cairo University, Giza, Egypt robertrezk@eg.ibm.com November 6, 2010 Abstract In this work we introduce a forecasting model with which we participated

Atiya, Amir

65

WRF-Fire: Coupled Weather–Wildland Fire Modeling with the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

A wildland fire-behavior module, named WRF-Fire, was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire-behavior model that is two-way coupled with the ...

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2013-01-01T23:59:59.000Z

66

A novel knowledge discovery model for fishery forecasting  

Science Conference Proceedings (OSTI)

In the area of ocean fisheries research, a new research interest is to use marine environment factors for fishery forecasting. This paper proposes a novel knowledge discovery model for fishery forecasting that uses the Indian Ocean big-eye tuna fishery ... Keywords: extension data mining, fishery forecasting, fuzzy rules, support vector machines

Hongchun Yuan; Ying Li; Ying Chen

2009-08-01T23:59:59.000Z

67

Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1  

E-Print Network (OSTI)

Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1 Adrian E. Raftery, Fadoua forecasting often exhibit a spread-skill relationship, but they tend to be underdispersive. This paper of PDFs centered around the individual (possibly bias-corrected) forecasts, where the weights are equal

Washington at Seattle, University of

68

SolarAnywhere forecast (Perez & Hoff) This chapter describes, and presents an evaluation of, the forecast models imbedded in the  

E-Print Network (OSTI)

SolarAnywhere forecast (Perez & Hoff) ABSTRACT This chapter describes, and presents an evaluation of, the forecast models imbedded in the SolarAnywhere platform. The models include satellite derived cloud motion based forecasts for the short to medium horizon (1 5 hours) and forecasts derived from NOAA

Perez, Richard R.

69

Getting the Most out of Ensemble Forecasts: A Valuation Model Based on User–Forecast Interactions  

Science Conference Proceedings (OSTI)

A flexible theoretical model of perceived forecast value is proposed that explicitly includes the effects of user and ensemble characteristics and their interactions. The model can be applied to arbitrary decision problems and is sensitive to a ...

Antony Millner

2008-10-01T23:59:59.000Z

70

Forecasting Natural Gas Prices Using Time Series Models .  

E-Print Network (OSTI)

??The objective of this thesis is to estimate the natural gas component of the All Urban Consumer Price Index (CP-U) using time series forecasting models.… (more)

Berg, Andrew

2006-01-01T23:59:59.000Z

71

Validation of Global Weather Forecast and Climate Models Over...  

NLE Websites -- All DOE Office Websites (Extended Search)

Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore...

72

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

DOE Green Energy (OSTI)

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

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

2009-10-09T23:59:59.000Z

73

An Integrated Approach to Mid- and Upper-Level Turbulence Forecasting  

Science Conference Proceedings (OSTI)

An automated procedure for forecasting mid- and upper-level turbulence that affects aircraft is described. This procedure, termed the Graphical Turbulence Guidance system, uses output from numerical weather prediction model forecasts to derive ...

R. Sharman; C. Tebaldi; G. Wiener; J. Wolff

2006-06-01T23:59:59.000Z

74

Modeling and Forecasting Electric Daily Peak Loads  

E-Print Network (OSTI)

Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity 29, 2012 Preliminary Results of the Electricity Price Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity market price forecast. A summary of the work

Abdel-Aal, Radwan E.

75

Merging Seasonal Rainfall Forecasts from Multiple Statistical Models through Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Merging forecasts from multiple models has the potential to combine the strengths of individual models and to better represent forecast uncertainty than the use of a single model. This study develops a Bayesian model averaging (BMA) method for ...

Q. J. Wang; Andrew Schepen; David E. Robertson

2012-08-01T23:59:59.000Z

76

Gulf Stream and Ring Feature Analyses for Forecast Model Validation*  

Science Conference Proceedings (OSTI)

A series of Gulf Stream forecast model test cases were developed for the Data Assimilation and Model Evaluation Experiment (DAMEE). The model initialization and verification procedure relies heavily on a series of accurate synoptic snapshots of ...

Scott M. Glenn; Michael F. Crowley

1997-12-01T23:59:59.000Z

77

Spectral Budget Analysis of the Short-Range Forecast Error of the NMC Medium-Range Forecast Model  

Science Conference Proceedings (OSTI)

The budget of the systematic component of the short-range forecast error in the National Meteorological Center's Medium-Range Forecast Model (NMC MRF) is examined. The budget is computed for the spectral coefficients and the variances of ...

Masao Kanamitsu; Suranjana Saha

1995-06-01T23:59:59.000Z

78

Improved Middle Atmosphere Climate and Forecasts in the ECMWF Model through a Nonorographic Gravity Wave Drag Parameterization  

Science Conference Proceedings (OSTI)

In model cycle 35r3 (Cy35r3) of the ECMWF Integrated Forecast System (IFS), the momentum deposition from small-scale nonorographic gravity waves is parameterized by the Scinocca scheme, which uses hydrostatic nonrotational wave dynamics to ...

Andrew Orr; Peter Bechtold; John Scinocca; Manfred Ern; Marta Janiskova

2010-11-01T23:59:59.000Z

79

Forecasting the Skill of a Regional Numerical Weather Prediction Model  

Science Conference Proceedings (OSTI)

It is demonstrated that the skill of short-term regional numerical forecasts can be predicted on a day-to-day basis. This was achieved by using a statistical regression scheme with the model forecast errors (MFE) as the predictands and the ...

L. M. Leslie; K. Fraedrich; T. J. Glowacki

1989-03-01T23:59:59.000Z

80

Chaotic time series forecasting using locally quadratic fuzzy neural models  

Science Conference Proceedings (OSTI)

Time series forecasting in highly nonlinear and chaotic systems is a challenging research area with a variety of applications in economics, environmental sciences and various fields of engineering. This paper presents a novel Locally Quadratic Fuzzy ... Keywords: chaotic time series, forecasting, locally quadratic neural fuzzy model

Mohammad J. Mahjoob; Majid Abdollahzade; Reza Zarringhalam; Ahmad Kalhor

2008-05-01T23:59:59.000Z

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


81

Integration of Variable Generation Forecasting into System Operations: Current Practices and Future Requirements  

Science Conference Proceedings (OSTI)

This project update provides the first output of the EPRI Bulk Renewable Integration Program Project P173-010, “Integration of Variable Generation Forecasts into System Operations.” This project, begun in 2013, aims to improve existing methods utilities/independent system operators (ISOs) use to integrate forecasts into system operations and develop new methods. This year’s goal was to identify current practices and future requirements. This was done by interacting with a wide ...

2013-12-11T23:59:59.000Z

82

A Preliminary Investigation of Temperature Errors in Operational Forecasting Models  

Science Conference Proceedings (OSTI)

Temperatures taken from model output (FOUS reports) routinely transmitted by the National Centers for Environmental Prediction are tabulated to determine errors during three months in the summer of 1996. These short-term model forecasts are ...

Frank P. Colby Jr.

1998-03-01T23:59:59.000Z

83

Forecasting electricity demand by hybrid machine learning model  

Science Conference Proceedings (OSTI)

This paper proposes a hybrid machine learning model for electricity demand forecasting, based on Bayesian Clustering by Dynamics (BCD) and Support Vector Machine (SVM). In the proposed model, a BCD classifier is firstly applied to cluster the input data ...

Shu Fan; Chengxiong Mao; Jiadong Zhang; Luonan Chen

2006-10-01T23:59:59.000Z

84

A Bayesian Forecast Model of Australian Region Tropical Cyclone Formation  

Science Conference Proceedings (OSTI)

A new and potentially skillful seasonal forecast model of tropical cyclone formation [tropical cyclogenesis (TCG)] is developed for the Australian region. The model is based on Poisson regression using the Bayesian approach. Predictor combinations ...

Angelika Werner; Neil J. Holbrook

2011-12-01T23:59:59.000Z

85

Impact of a New Radiation Package, McRad, in the ECMWF Integrated Forecasting System  

Science Conference Proceedings (OSTI)

A new radiation package, “McRad,” has become operational with cycle 32R2 of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). McRad includes an improved description of the land surface ...

J-J. Morcrette; H. W. Barker; J. N. S. Cole; M. J. Iacono; R. Pincus

2008-12-01T23:59:59.000Z

86

Snowfall Limit Forecasts and Hydrological Modeling  

Science Conference Proceedings (OSTI)

Hydrological flood forecasting in mountainous areas requires accurate partitioning between rain and snowfall to properly estimate the extent of runoff contributing areas. Here a method to make use of snowfall limit information—a standard output of ...

Cara Tobin; Andrea Rinaldo; Bettina Schaefli

2012-10-01T23:59:59.000Z

87

Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)  

SciTech Connect

Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

2009-11-01T23:59:59.000Z

88

Radiation fog forecasting using a 1-dimensional model  

E-Print Network (OSTI)

The importance of fog forecasting to the aviation community, to road transportation and to the public at large is irrefutable. The deadliest aviation accident in history was in fact partly a result of fog back on 27 March 1977. This has, along with numerous less dramatic examples, helped focus many meteorological efforts into trying to forecast this phenomenon as accurately as possible. Until recently, methods of fog forecasting have relied primarily on the forecaster's ability to recognize surface 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 with regards to the onset and dissipation of the phenomenon. Fortunately, now with computers becoming ever-increasingly powerful, numerical models have been utilized to attempt to more accurately deal with the fog forecasting problem. This study uses a 1 dimensional model called COBEL to simulate several past fog cases in the hopes of mimicking its actual occurrence and determining what weather parameters the fog is most sensitive to. The goal is to create a technique where the weather forecaster will be able to run several fog forecasts with the model each time with different initial conditions representing the uncertain weather conditions. In this way, the forecaster will be able to use his expertise to choose the most likely scenario. Results indicate that COBEL is able to simulate the fog cases quite well. Issues remain with the model's handling of the gravitational settling rate, the fact that it currently does not include any vegetation, and its coupling process with the soil model. Nevertheless, simulations and sensitivity tests indicate that soil temperature, soil moisture, low-level winds, initial relative humidity, dew deposition and surface emissivity are the weather parameters that affect fog the most. These parameters will be prime candidates for the 1 dimensional ensemble (ODEP) technique described above.

Peyraud, Lionel

2001-01-01T23:59:59.000Z

89

The Skill of Precipitation and Surface Temperature Forecasts by the NMC Global Model during DERF II  

Science Conference Proceedings (OSTI)

This study assesses the skill of forecasts of precipitation and surface temperature by the National Meteorological Center's (NMC) global model in the 108 consecutive 30-day forecasts [known as Dynamical Extended Range Forecast II (DERF II)] that ...

Glenn H. White; Eugenia Kalnay; Rodney Gardner; Masao Kanamitsu

1993-03-01T23:59:59.000Z

90

Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations  

Science Conference Proceedings (OSTI)

This study evaluates forecasts of thermodynamic variables from five convection-allowing configurations of the Weather Research and Forecasting Model (WRF) with the Advanced Research core (WRF-ARW). The forecasts vary only in their planetary ...

Michael C. Coniglio; James Correia Jr.; Patrick T. Marsh; Fanyou Kong

2013-06-01T23:59:59.000Z

91

Dynamical Downscaling of Austral Summer Climate Forecasts over Southern Africa Using a Regional Coupled Model  

Science Conference Proceedings (OSTI)

The prediction skill of dynamical downscaling is evaluated for climate forecasts over southern Africa using the Advanced Research Weather Research and Forecasting (WRF) model. As a case study, forecasts for the December–February (DJF) season of ...

J. V. Ratnam; S. K. Behera; S. B. Ratna; C. J. de W. Rautenbach; C. Lennard; J.-J. Luo; Y. Masumoto; K. Takahashi; T. Yamagata

2013-08-01T23:59:59.000Z

92

State-of-the art of freight forecast modeling: lessons learned and the road ahead  

E-Print Network (OSTI)

of-the art of freight forecast modeling: lessons learned andof goods as well as to forecast the expected future truckused for the short-term forecasts of freight volumes on

Chow, Joseph Y.; Yang, Choon Heon; Regan, Amelia C.

2010-01-01T23:59:59.000Z

93

A Lightning Data Assimilation Technique for Mesoscale Forecast Models  

Science Conference Proceedings (OSTI)

Lightning observations have been assimilated into a mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network (cloud-to-ground lightning detection) and a Lightning Mapping Array (...

Edward R. Mansell; Conrad L. Ziegler; Donald R. MacGorman

2007-05-01T23:59:59.000Z

94

Assimilation of Satellite Precipitable Water in a Meteorological Forecast Model  

Science Conference Proceedings (OSTI)

The lack of local humidity observations over a large portion of the globe hinders any improvement of humidity forecasting in meteorological models. However, satellite microwave radiometers routinely provide fields of precipitable water content ...

M. A. Filiberti; L. Eymard; B. Urban

1994-03-01T23:59:59.000Z

95

Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical way of postprocessing forecast ensembles to create predictive probability density functions (PDFs) for weather quantities. It represents the predictive PDF as a weighted average of PDFs centered on ...

J. Mc Lean Sloughter; Adrian E. Raftery; Tilmann Gneiting; Chris Fraley

2007-09-01T23:59:59.000Z

96

Using Bayesian Model Averaging to Calibrate Forecast Ensembles  

Science Conference Proceedings (OSTI)

Ensembles used for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive. This paper proposes a statistical method for postprocessing ensembles based on Bayesian model averaging (BMA), ...

Adrian E. Raftery; Tilmann Gneiting; Fadoua Balabdaoui; Michael Polakowski

2005-05-01T23:59:59.000Z

97

Volcanic Ash Forecast Transport And Dispersion (VAFTAD) Model  

Science Conference Proceedings (OSTI)

The National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory (ARL) has developed a Volcanic Ash Forecast Transport And Dispersion (VAFTAD) model for emergency response use focusing on hazards to aircraft flight operations. ...

Jerome L. Heffter; Barbara J. B. Stunder

1993-12-01T23:59:59.000Z

98

ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast...  

NLE Websites -- All DOE Office Websites (Extended Search)

ProductsCCPP-ARM Parameterization Testbed Model Forecast Data Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send PI Product :...

99

An Improved Modeling Scheme for Freezing Precipitation Forecasts  

Science Conference Proceedings (OSTI)

To improve forecasts of various weather elements (snow, rain, and freezing precipitation) in numerical weather prediction models, a new mixed-phase cloud scheme has been developed. The scheme is based on a single prognostic equation for total ...

André Tremblay; Anna Glazer

2000-05-01T23:59:59.000Z

100

A Multistep Automatic Calibration Scheme for River Forecasting Models  

Science Conference Proceedings (OSTI)

Operational flood forecasting models vary in complexity, but nearly all have parameters for which values must be estimated. The traditional and widespread manual calibration approach requires considerable training and experience and is typically ...

Terri S. Hogue; Soroosh Sorooshian; Hoshin Gupta; Andrea Holz; Dean Braatz

2000-12-01T23:59:59.000Z

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


101

THE PITTSBURGH REMI MODEL: LONG-TERM REMI MODEL FORECAST FOR  

E-Print Network (OSTI)

1 THE PITTSBURGH REMI MODEL: LONG-TERM REMI MODEL FORECAST FOR ALLEGHENY COUNTY AND THE PITTSBURGH made. REMI LONG-TERM FORECAST AND BEA PROJECTIONS This report includes UCSUR's 1998 economic and population projections for the Pittsburgh Region. The purpose of UCSUR's long-term regional forecasts

Sibille, Etienne

102

Electricity Price Curve Modeling and Forecasting by Manifold Learning  

E-Print Network (OSTI)

This paper proposes a novel nonparametric approach for the modeling and analysis of electricity price curves by applying the manifold learning methodology—locally linear embedding (LLE). The prediction method based on manifold learning and reconstruction is employed to make short-term and mediumterm price forecasts. Our method not only performs accurately in forecasting one-day-ahead prices, but also has a great advantage in predicting one-week-ahead and one-month-ahead prices over other methods. The forecast accuracy is demonstrated by numerical results using historical price data taken from the Eastern U.S. electric power markets.

Jie Chen; Shi-Jie Deng; Xiaoming Huo

2008-01-01T23:59:59.000Z

103

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

E-Print Network (OSTI)

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation technologies. This paper briefly discusses the observed patterns of the diffusion of new' technologies and the determinants (both sociological and economic) which have been proposed to explain the variation in the diffusion rates. Existing market penetration models are reviewed and their capability to forecast the use of conservation technologies is assessed using a set of criteria developed for this purpose. The reasoning behind the choice of criteria is discussed. The criteria includes the range of hypothesized influences to market penetration that are incorporated into the models and the applicability of the available parameter estimates. The attributes of our methodology and forecasting model choice (a behavioral lag equation developed by Mathtech, Inc.), are displayed using a list of the judgment criteria. This method was used to forecast the use of electricity conservation technologies in industries located in the Pacific Northwest for the Bonneville Power Administration.

Lang, K.

1982-01-01T23:59:59.000Z

104

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

SciTech Connect

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

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

1992-02-01T23:59:59.000Z

105

A.: Modeling and forecasting electricity loads: A comparison  

E-Print Network (OSTI)

In this paper we study two statistical approaches to load forecasting. Both of them model electricity load as a sum of two components – a deterministic (representing seasonalities) and a stochastic (representing noise). They differ in the choice of the seasonality reduction method. Model A utilizes differencing, while Model B uses a recently developed seasonal volatility technique. In both models the stochastic component is described by an ARMA time series. Models are tested on a time series of system-wide loads from the California power market and compared with the official forecast of the California System Operator (CAISO). 1.

Rafa? Weron

2004-01-01T23:59:59.000Z

106

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

SciTech Connect

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

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

1992-02-01T23:59:59.000Z

107

A PGAS Implementation by Co-design of the ECMWF Integrated Forecasting System (IFS)  

Science Conference Proceedings (OSTI)

Today the European Centre for Medium-Range Weather Forecasts (ECMWF) runs a 16 km global T1279 operational weather forecast model using 1,536 cores of an IBM Power7. Following the historical evolution in resolution upgrades, ECMWF could expect to be ... Keywords: PGAS, COARRAYS, FORTRAN2008, CRESTA,

George Mozdzynski, Mats Hamrud, Nils Wedi, Jens Doleschal, Harvey Richardson

2012-11-01T23:59:59.000Z

108

Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint  

DOE Green Energy (OSTI)

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

Hodge, B. M.; Lew, D.; Milligan, M.

2013-01-01T23:59:59.000Z

109

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

NLE Websites -- All DOE Office Websites (Extended Search)

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

110

RACORO Forecasting  

NLE Websites -- All DOE Office Websites (Extended Search)

Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated...

111

Forecasting volatility with the multifractal random walk model  

E-Print Network (OSTI)

We study the problem of forecasting volatility for the multifractal random walk model. In order to avoid the ill posed problem of estimating the correlation length T of the model, we introduce a limiting object defined in a quotient space; formally, this object is an infinite range logvolatility. For this object and the non limiting object, we obtain precise prediction formulas and we apply them to the problem of forecasting volatility and pricing options with the MRW model in the absence of a reliable estimate of the average volatility and T.

Duchon, Jean; Vargas, Vincent

2008-01-01T23:59:59.000Z

112

Evaluating a Hybrid Prognostic–Diagnostic Model That Improves Wind Forecast Resolution in Complex Coastal Topography  

Science Conference Proceedings (OSTI)

The results from a hybrid approach that combines the forecasts of a mesoscale model with a diagnostic wind model to produce high-resolution wind forecasts in complex coastal orography are evaluated. The simple diagnostic wind model [Winds on ...

Francis L. Ludwig; Douglas K. Miller; Shawn G. Gallaher

2006-01-01T23:59:59.000Z

113

Southern Hemisphere Medium-Range Forecast Skill and Predictability: A Comparison of Two Operational Models  

Science Conference Proceedings (OSTI)

The skill of two global numerical weather prediction models, the National Centers for Environmental Prediction (NCEP) medium-range forecast model and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model, has been ...

James A. Renwick; Craig S. Thompson

2001-09-01T23:59:59.000Z

114

An evaluation of tropical cyclone genesis forecasts from global numerical models  

Science Conference Proceedings (OSTI)

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

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

115

Solving the problem of inadequate scoring rules for assessing probabilistic football forecast models  

E-Print Network (OSTI)

Solving the problem of inadequate scoring rules for assessing probabilistic football forecast forecasting models, and the relative simplicity of the outcome of such forecasts (they require only three their forecast accuracy. Moreover, the various scoring rules used for validation in previous studies

Fenton, Norman

116

Retrospective ENSO Forecasts: Sensitivity to Atmospheric Model and Ocean Resolution  

Science Conference Proceedings (OSTI)

Results are described from a series of 40 retrospective forecasts of tropical Pacific SST, starting 1 January and 1 July 1980–99, performed with several coupled ocean–atmosphere general circulation models sharing the same ocean model—the Modular ...

Edwin K. Schneider; Ben P. Kirtman; David G. DeWitt; Anthony Rosati; Link Ji; Joseph J. Tribbia

2003-12-01T23:59:59.000Z

117

Monthly streamflow forecasting based on improved support vector machine model  

Science Conference Proceedings (OSTI)

To improve the performance of the support vector machine (SVM) model in predicting monthly streamflow, an improved SVM model with adaptive insensitive factor is proposed in this paper. Meanwhile, considering the influence of noise and the disadvantages ... Keywords: Adaptive insensitive factor, Artificial neural network, Chaos and phase-space reconstruction theory, Streamflow forecast, Support vector machine, Wavelet

Jun Guo; Jianzhong Zhou; Hui Qin; Qiang Zou; Qingqing Li

2011-09-01T23:59:59.000Z

118

Modelling and forecasting wind speed intensity for weather risk management  

Science Conference Proceedings (OSTI)

The main interest of the wind speed modelling is on the short-term forecast of wind speed intensity and direction. Recently, its relationship with electricity production by wind farms has been studied. In fact, electricity producers are interested in ... Keywords: ARFIMA-FIGARCH, Auto Regressive Gamma, Gamma Auto Regressive, Weather risk management, Wind speed modelling, Wind speed simulation

Massimiliano Caporin; Juliusz Pre

2012-11-01T23:59:59.000Z

119

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

Reports and Publications (EIA)

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.

Information Center

2010-06-01T23:59:59.000Z

120

Management of supply chain: an alternative modelling technique for forecasting  

E-Print Network (OSTI)

Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view

Datta, Shoumen

2007-05-23T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
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121

Forecast Skill of the Madden–Julian Oscillation in Two Canadian Atmospheric Models  

Science Conference Proceedings (OSTI)

The output of two global atmospheric models participating in the second phase of the Canadian Historical Forecasting Project (HFP2) is utilized to assess the forecast skill of the Madden–Julian oscillation (MJO). The two models are the third ...

Hai Lin; Gilbert Brunet; Jacques Derome

2008-11-01T23:59:59.000Z

122

Explicit Cloud-Scale Models for Operational Forecasts: A Note of Caution  

Science Conference Proceedings (OSTI)

As computational capacity has increased, cloud-scale numerical models are slowly being modified from pure research tools to forecast tools. Previous studies that used cloud-scale models as explicit forecast tools, in much the same way as a ...

Kimberly L. Elmore; David J. Stensrud; Kenneth C. Crawford

2002-08-01T23:59:59.000Z

123

A Stochastic-Dynamic Model for the Spatial Structure of Forecast Error Statistics  

Science Conference Proceedings (OSTI)

A simple model that yields the spatial correlation structure of global atmospheric mass-field forecast errors is derived. The model states that the relative potential vorticity of the forecast error is forced by spatially multi-dimensional white ...

R. Balgovind; A. Dalcher; M. Ghil; E. Kalnay

1983-04-01T23:59:59.000Z

124

Determination of Forecast Errors Arising from Different Components of Model Physics and Dynamics  

Science Conference Proceedings (OSTI)

This paper addresses a procedure to extract error estimates for the physical and dynamical components of a forecast model. This is a two-step process in which contributions to the forecast tendencies from individual terms of the model equations ...

T. N. Krishnamurti; J. Sanjay; A. K. Mitra; T. S. V. Vijaya Kumar

2004-11-01T23:59:59.000Z

125

The New NMC Mesoscale Eta Model: Description and Forecast Examples  

Science Conference Proceedings (OSTI)

In mid-1994 a new version of the Eta Model will begin producing operational forecast guidance down to mesoscale ranges. This version will have a horizontal resolution of approximately 30 km and about 50 layers in the vertical. A summary of the ...

Thomas L. Black

1994-06-01T23:59:59.000Z

126

Mesoscale Model Experimental Forecasts of the Haar of Northeast Scotland  

Science Conference Proceedings (OSTI)

A mesoscale model is used to simulate the diurnal evolution of sea fog off the northeast Scottish coast observed on 27 April 1984. It is shown that the accuracy of the early part of the forecast is very dependent on the specification of the ...

S. P. Ballard; B. W. Golding; R. N. B. Smith

1991-09-01T23:59:59.000Z

127

Statistical Characteristics of a Real-Time Precipitation Forecasting Model  

Science Conference Proceedings (OSTI)

At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate ...

Brian Gaudet; William R. Cotton

1998-12-01T23:59:59.000Z

128

Dynamical forecast experiments with a baroclinic quasigeostrophic open ocean model  

Science Conference Proceedings (OSTI)

We report here on a series of numerical forecast experiments using a baroclinic quasigeostropic open ocean model. A simulation has been carried out to produce a model data set consisting of values of streamfunction and potential vorticity in four dimensions. This data set exhibits quasiturbulent characteristics similar to those of the mesoscale eddy field in the North Western Atlantic. The simulation has been carried out for several model years over many independent synoptic realizations.

Robert N. Miller; Allan R. Robinson

1984-01-01T23:59:59.000Z

129

Crude Oil Price Forecasting: A Transfer Learning Based Analog Complexing Model  

Science Conference Proceedings (OSTI)

Most of the existing models for oil price forecasting only use the data in the forecasted time series itself. This study proposes a transfer learning based analog complexing model (TLAC). It first transfers some related time series in source domain to ... Keywords: transfer learning method, analog complexing model, genetic algorithm, crude oil price forecasting

Jin Xiao; Changzheng He; Shouyang Wang

2012-08-01T23:59:59.000Z

130

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

E-Print Network (OSTI)

USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING Roy MENDELSSOHN! ABSTRACT Box·Jenkins models are suggested as appropriate models for forecasting fishery dynamics in Hawaii. An actual 12-month forecast is shown to give a reasonable fit to the observed data. Most

131

Short-Term Ice Accretion Forecasts for Electric Utilities Using the Weather Research and Forecasting Model and a Modified Precipitation-Type Algorithm  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting model (WRF) is used to provide 6–12-h forecasts of the necessary input parameters to a separate algorithm that determines the most likely precipitation type at each model grid point. In instances where ...

Arthur T. DeGaetano; Brian N. Belcher; Pamela L. Spier

2008-10-01T23:59:59.000Z

132

Use of Multiple Verification Methods to Evaluate Forecasts of Convection from Hot- and Cold-Start Convection-Allowing Models  

Science Conference Proceedings (OSTI)

This study uses both traditional and newer verification methods to evaluate two 4-km grid-spacing Weather Research and Forecasting Model (WRF) forecasts: a “cold start” forecast that uses the 12-km North American Mesoscale Model (NAM) analysis and ...

Derek R. Stratman; Michael C. Coniglio; Steven E. Koch; Ming Xue

2013-02-01T23:59:59.000Z

133

Summer-Season Forecast Experiments with the NCEP Climate Forecast System Using Different Land Models and Different Initial Land States  

Science Conference Proceedings (OSTI)

To examine the impact from land model upgrades and different land initializations on the National Centers for Environmental Prediction (NCEP)’s Climate Forecast System (CFS), extensive T126 CFS experiments are carried out for 25 summers with 10 ...

Rongqian Yang; Kenneth Mitchell; Jesse Meng; Michael Ek

2011-05-01T23:59:59.000Z

134

Development of a Limited-Area Model for Operational Weather Forecasting around a Power Plant: The Need for Specialized Forecasts  

Science Conference Proceedings (OSTI)

A hydrostatic meteorological model, “PMETEO,” was developed for short-range forecasts for a high-resolution limited area located in the northwest region of Spain. Initial and lateral boundary conditions are externally provided by a coarse-mesh ...

C. F. Balseiro; M. J. Souto; E. Penabad; J. A. Souto; V. Pérez-Muñuzuri

2002-09-01T23:59:59.000Z

135

Probabilistic Forecast Guidance for Severe Thunderstorms Based on the Identification of Extreme Phenomena in Convection-Allowing Model Forecasts  

Science Conference Proceedings (OSTI)

With the advent of convection-allowing NWP models (CAMs) comes the potential for new forms of forecast guidance. While CAMs lack the required resolution to simulate many severe phenomena associated with convection (e.g., large hail, downburst ...

Ryan A. Sobash; John S. Kain; David R. Bright; Andrew R. Dean; Michael C. Coniglio; Steven J. Weiss

2011-10-01T23:59:59.000Z

136

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

DOE Green Energy (OSTI)

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

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

2011-03-28T23:59:59.000Z

137

Solar forecasting review  

E-Print Network (OSTI)

of Solar Forecasting . . . . . . . . . 2.4.1 Solarbudget at the foundation of satellite based forecastingWeather Research and Forecasting (WRF) Model 7.1 Global

Inman, Richard Headen

2012-01-01T23:59:59.000Z

138

An Operational Model for Forecasting Probability of Precipitation and Yes/No Forecast  

Science Conference Proceedings (OSTI)

An operational system for forecasting probability of precipitation (PoP) and yes/no forecast over 10 stations during monsoon season is developed. A perfect prog method (PPM) approach is followed for statistical interpretation of numerical weather ...

Ashok Kumar; Parvinder Maini; S. V. Singh

1999-02-01T23:59:59.000Z

139

The Behavior of Gravitational Modes in Numerical Forecasts with the NCAR Community Climate Model  

Science Conference Proceedings (OSTI)

Characteristics of gravitational-wave noise in noninitialized forecasts were investigated with the NCAR Community Climate Model. Forecasts were begun from FGGE analyses. The behavior of individual, gravitational normal modes was examined. In ...

R. M. Errico; D. L. Williamson

1988-09-01T23:59:59.000Z

140

Eta Model Precipitation Forecasts for a Period Including Tropical Storm Allison  

Science Conference Proceedings (OSTI)

A step-mountain (eta) coordinate limited-area model is being developed at the National Meteorological Center (NMC) to improve forecasts of severe weather and other mesoscale phenomena. Precipitation forecasts are reviewed for the 20-day period 16 ...

Fedor Mesinger; Thomas L. Black; David W. Plummer; John H. Ward

1990-09-01T23:59:59.000Z

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


141

Short-Range Forecasting and Nowcasting Using a Simple, Isentropic Prediction Model  

Science Conference Proceedings (OSTI)

The recent advancement of mini- and microcomputers into the local-work environment can provide local forecast offices with the capability to run simple numerical models for specific nowcasting and short-term forecast needs. While the capabilities ...

Ralph A. Petersen; Jeffrey H. Homan

1989-03-01T23:59:59.000Z

142

Using the WRF Model in an Operational Streamflow Forecast System for the Jordan River  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting (WRF) model was employed to provide precipitation forecasts during the 2008/09 and 2009/10 winters (wet season) for Israel and the surrounding region where complex terrain dominates. The WRF precipitation ...

Amir Givati; Barry Lynn; Yubao Liu; Alon Rimmer

2012-02-01T23:59:59.000Z

143

An Application of Model Output Statistics to the Development of a Local Wind Regime Forecast Procedure  

Science Conference Proceedings (OSTI)

The Model Output Statistics (MOS) approach is used to develop a procedure for forecasting the occurrence of a local wind regime at Rota, Spain known as the levante. Variables derived solely from surface pressure and 500 mb height forecast fields ...

Robert A. Godfrey

1982-12-01T23:59:59.000Z

144

A Single-Station Approach to Model Output Statistics Temperature Forecast Error Assessment  

Science Conference Proceedings (OSTI)

Error characteristics of model output statistics (MOS) temperature forecasts are calculated for over 200 locations around the continental United States. The forecasts are verified on a station-by-station basis for the year 2001. Error measures ...

Andrew A. Taylor; Lance M. Leslie

2005-12-01T23:59:59.000Z

145

Probabilistic Forecasts of Precipitation in Terms of Quantiles Using NWP Model Output  

Science Conference Proceedings (OSTI)

At sites with observations it is often possible to improve or enrich NWP model forecasts by means of statistical methods. Such forecasts are almost exclusively deterministic or probabilities of discrete events. In this paper a flexible approach ...

John Bjørnar Bremnes

2004-01-01T23:59:59.000Z

146

STORMTIPE: A Forecasting Experiment Using a Three-Dimensional Cloud Model  

Science Conference Proceedings (OSTI)

An experiment using a three-dimensional cloud-scale numerical model in an operational forecasting environment was carried out in the spring of 1991. It involved meteorologists generating forecast environmental conditions associated with ...

Harold E. Brooks; Charles A. Doswell III; Louis J. Wicker

1993-09-01T23:59:59.000Z

147

On the Impact of WRF Model Vertical Grid Resolution on Midwest Summer Rainfall Forecasts  

Science Conference Proceedings (OSTI)

Weather Research and Forecast (WRF) model exploratory sensitivity simulations were performed to determine the impact of vertical grid resolution (VGR) on the forecast skill of Midwest summer rainfall. Varying the VGR indicated that a refined VGR, ...

Eric A. Aligo; William A. Gallus Jr.; Moti Segal

2009-04-01T23:59:59.000Z

148

Mesoscale Forecasts Generated from Operational Numerical Weather-Prediction Model Output  

Science Conference Proceedings (OSTI)

A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale ...

John G. W. Kelley; Joseph M. Russo; Toby N. Carlson; J. Ronald Eyton

1988-01-01T23:59:59.000Z

149

Does increasing model stratospheric resolution improve5 extended-range forecast skill?6  

E-Print Network (OSTI)

1 1 2 3 4 Does increasing model stratospheric resolution improve5 extended-range forecast skill?6 7 The effect of stratospheric resolution on extended-range forecast skill at high latitudes2 in the Southern Hemisphere is explored. Ensemble forecasts are made for two model3 configurations that differ only

Birner, Thomas

150

Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model  

E-Print Network (OSTI)

Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model Neal Wagner programming (GP) to the task of forecasting with favorable results. However, these studies, like those "dynamic" GP model that is specifically tailored for forecasting in non-static environments. This Dynamic

Michalewicz, Zbigniew

151

Forecast Calls for Better Models: Examining the Core  

NLE Websites -- All DOE Office Websites (Extended Search)

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

152

RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN  

E-Print Network (OSTI)

or over predicting electricity demand due to poor weather forecasts is several hundred million dollars outages that many in the area experienced. Deep Thunder can also improve generation-side load forecasting by providing high-resolution weather forecast data for use in electricity demand forecast models. Integrating

Manry, Michael

153

Model Fidelity versus Skill in Seasonal Forecasting  

Science Conference Proceedings (OSTI)

The relation between skill and fidelity of seasonal mean hindcasts of surface temperature by seven coupled atmosphere–ocean models is investigated. By definition, fidelity measures the agreement between model and observational climatological ...

Timothy DelSole; Jagadish Shukla

2010-09-01T23:59:59.000Z

154

Forecast Combinations  

E-Print Network (OSTI)

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this chapter we analyze theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models’ forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where thenumbersofmodelsislargerelativetothe available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts. Key words: Forecast combinations; pooling and trimming; shrinkage methods; model misspecification, diversification gains

Allan Timmermann; Jel Codes C

2006-01-01T23:59:59.000Z

155

Value of Wind Power Forecasting  

DOE Green Energy (OSTI)

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.

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

2011-04-01T23:59:59.000Z

156

Use and Value of Multiple-Period Forecasts in a Dynamic Model of the Cost-Loss Ratio Situation  

Science Conference Proceedings (OSTI)

On most forecasting occasions forecasts are made for several successive periods, but decision-making models have traditionally neglected the impact of the potentially useful information contained in forecasts for periods beyond the initial ...

Edward S. Epstein; Allan H. Murphy

1988-03-01T23:59:59.000Z

157

A Comparison of the Noah and OSU Land Surface Models in the ECPC Seasonal Forecast Model  

Science Conference Proceedings (OSTI)

The Noah land surface model (LSM) has recently been implemented into the Experimental Climate Prediction Center’s (ECPC’s) global Seasonal Forecast Model (SFM). Its performance is compared to the older ECPC SFM with the Oregon State University (...

Laurel L. De Haan; Masao Kanamitsu; Cheng-Hsuan Lu; John O. Roads

2007-10-01T23:59:59.000Z

158

The Quality of Skill Forecasts for a Low-Order Spectral Model  

Science Conference Proceedings (OSTI)

A skill forecast gives the probability distribution for the error in the forecast. The purpose of this paper is to develop a skill-forecasting method. The method is applied to a spectral two-layer quasigeostrophic atmospheric model with a ...

P. L. Houtekamer

1992-12-01T23:59:59.000Z

159

Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks  

Science Conference Proceedings (OSTI)

Neural networks have been widely used for short-term, and to a lesser degree medium and long-term, demand forecasting. In the majority of cases for the latter two applications, multivariate modeling was adopted, where the demand time series is related ... Keywords: Abductive networks, Energy demand, Medium-term load forecasting, Neural networks, Time series forecasting, Univariate time series analysis

R. E. Abdel-Aal

2008-05-01T23:59:59.000Z

160

Update On The Wholesale Electricity Price Forecast & Modeling Results  

E-Print Network (OSTI)

Forecast Base Case includes § Medium Demand Forecast § Medium Natural Gas Price Forecast § Federal CO2 Rathdrum Power LLC-ID 4) CO2 Emissions - 2009 Selected Natural Gas Plants Plant level, emission percentage § Significantly lower electricity prices than 6th Plan Forecast, due to lower demand, lower gas prices, deferred

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


161

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-09-01T23:59:59.000Z

162

Response of the NMC MRF Model to Systematic-Error Correction within Integration  

Science Conference Proceedings (OSTI)

We describe an extensive nudging (within-integration correction) experiment with a large and sophisticated atmospheric model. The model is an R30 version of the National Meteorological Center (NMC) T80 operational global medium-range forecast ...

Suranjana Saha

1992-02-01T23:59:59.000Z

163

A Reduced Radiation Grid for the ECMWF Integrated Forecasting System  

Science Conference Proceedings (OSTI)

A specific interface between the radiation transfer calculations and the rest of the ECMWF model was introduced in 2003, potentially providing substantial economy in computer time by reducing the spatial resolution at which radiation transfer is ...

Jean-Jacques Morcrette; George Mozdzynski; Martin Leutbecher

2008-12-01T23:59:59.000Z

164

Locally Calibrated Probabilistic Temperature Forecasting Using Geostatistical Model Averaging and Local Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

The authors introduce two ways to produce locally calibrated grid-based probabilistic forecasts of temperature. Both start from the Global Bayesian model averaging (Global BMA) statistical postprocessing method, which has constant predictive bias ...

William Kleiber; Adrian E. Raftery; Jeffrey Baars; Tilmann Gneiting; Clifford F. Mass; Eric Grimit

2011-08-01T23:59:59.000Z

165

Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs)  

Science Conference Proceedings (OSTI)

Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. Auto-Regressive Integrated Moving Average (ARIMA) models are one of the most important time series models used in financial ... Keywords: Artificial Neural Networks (ANNs), Auto-Regressive Integrated Moving Average (ARIMA), Exchange rate, Financial markets, Fuzzy logic, Time series forecasting

Mehdi Khashei; Mehdi Bijari; Gholam Ali Raissi Ardali

2009-01-01T23:59:59.000Z

166

Statistical Wind Power Forecasting Models: Results for U.S. Wind Farms; Preprint  

DOE Green Energy (OSTI)

Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast makes it possible for grid operators to schedule the economically efficient generation to meet the demand of electrical customers. In the evolving markets, some form of auction is held for various forward markets, such as hour ahead or day ahead. This paper develops several statistical forecasting models that can be useful in hour-ahead markets that have a similar tariff. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets. We investigate the extent to which time-series analysis can improve on simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (ARMA) models to both wind speed and wind power output.

Milligan, M.; Schwartz, M.; Wan, Y.

2003-05-01T23:59:59.000Z

167

Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis.  

E-Print Network (OSTI)

??Stock price forecasting is a classic problem facing analysts. Forcasting models have been developed for predicting individual stocks and stock indices around the world and… (more)

Dravenstott, Ronald W.

2012-01-01T23:59:59.000Z

168

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

against the risk of energy price fluctuations. In theory,The poor track record of energy price forecasting models hasof information about future energy prices, including most

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

2005-01-01T23:59:59.000Z

169

The Performance of a Medium-Range Forecast Model in Winter–Impact of Physical Parameterizations  

Science Conference Proceedings (OSTI)

We present the results of a series of forecasts on seven weather situations from February 1976 using two models which differ only in their physical parameterizations.

A. Hollingsworth; K. Arpe; M. Tiedtke; M. Capaldo; H. Savijärvi

1980-11-01T23:59:59.000Z

170

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

E-Print Network (OSTI)

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

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

171

Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Probabilistic forecasts of wind vectors are becoming critical as interest grows in wind as a clean and renewable source of energy, in addition to a wide range of other uses, from aviation to recreational boating. Unlike other common forecasting ...

J. McLean Sloughter; Tilmann Gneiting; Adrian E. Raftery

2013-06-01T23:59:59.000Z

172

Comparative Forecast Evaluation: Graphical Gaussian Models and Sufficiency Relations  

Science Conference Proceedings (OSTI)

This paper deals with the comparative evaluation of categorical forecasts supposing that forecasts and observations are continuous variables and have a jointly normal distribution. An information content approach based on the well-established ...

Ulrich Callies

2000-06-01T23:59:59.000Z

173

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

174

Changes to the 1995 NCEP Operational Medium-Range Forecast Model Analysis–Forecast System  

Science Conference Proceedings (OSTI)

Recent changes in the operational National Centers for Environmental Prediction (formerly the National Meteorological Center) global analysis–forecast system are described. The most significant analysis change was the direct use of satellite-...

Peter Caplan; John Derber; William Gemmill; Song-You Hong; Hua-Lu Pan; David Parrish

1997-09-01T23:59:59.000Z

175

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

Science Conference Proceedings (OSTI)

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

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

2010-11-02T23:59:59.000Z

176

Performance evaluation of competing forecasting models: A multidimensional framework based on MCDA  

Science Conference Proceedings (OSTI)

So far, competing forecasting models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria - a situation where one cannot make an informed decision as to which model performs best ... Keywords: Crude oil prices, Forecasting models, Multi-Criteria Decision Analysis, Performance evaluation

Bing Xu; Jamal Ouenniche

2012-07-01T23:59:59.000Z

177

A Hybrid ARCH-M and BP Neural Network Model For GSCI Futures Price Forecasting  

Science Conference Proceedings (OSTI)

As a versatile investment tool in energy markets for speculators and hedgers, the Goldman Sachs Commodity Index (GSCI) futures are quite well known. Therefore, this paper proposes a hybrid model incorporating ARCH family models and ANN model to forecast ... Keywords: ANN, ARCH-M, Commodity Index, Forecasting, GSCI

Wen Bo; Wang Shouyang; K. K. Lai

2007-05-01T23:59:59.000Z

178

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

E-Print Network (OSTI)

) Controlling model error of underdamped forecast models in sparse observational networks using a variance@maths.usyd.edu.au The problem of controlling covariance overestimation due to underdamped forecast models and sparsity the initial conditions and forecast model and to combat the associated forecast error and flow

Gottwald, Georg A.

179

A comparison study between fuzzy time series model and ARIMA model for forecasting Taiwan export  

Science Conference Proceedings (OSTI)

This study compares the application of two forecasting methods on the amount of Taiwan export, the ARIMA time series method and the fuzzy time series method. Models discussed for the fuzzy time series method include the Factor models, the Heuristic models, ... Keywords: ARIMA model, Fuzzy time series, Taiwan export

Chi-Chen Wang

2011-08-01T23:59:59.000Z

180

Future world oil prices: modeling methodologies and summary of recent forecasts  

SciTech Connect

This paper has three main objectives. First, the various methodologies that have been developed to explain historical oil price changes and forecast future price trends are reviewed and summarized. Second, the paper summarizes recent world oil price forecasts, and, then possible, discusses the methodologies used in formulating those forecasts. Third, utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, oil price projections are given for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, at this point in time a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 69 references, 3 figures, 10 tables.

Curlee, T.R.

1985-04-01T23:59:59.000Z

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


181

Forecasting world oil prices: the evolution of modeling methodologies and summary of recent projections  

SciTech Connect

This paper has three main objectives: (1) to review and summarize the varios methodologies that have been developed to explain historical oil price changes and forecast future price trends, (2) to summarize recent world oil price forecasts, and, when possible, discuss the methodologies used in formulating those forecasts, and (3) utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, to give oil price projections for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 68 references, 1 figure, 6 tables.

Curlee, T.R.

1985-01-01T23:59:59.000Z

182

Integration of Climate and Weather Information for Improving 15-Day-Ahead Accumulated Precipitation Forecasts  

Science Conference Proceedings (OSTI)

Skillful medium-range weather forecasts are critical for water resources planning and management. This study aims to improve 15-day-ahead accumulated precipitation forecasts by combining biweekly weather and disaggregated climate forecasts. A ...

Hui Wang; A. Sankarasubramanian; Ranji S. Ranjithan

2013-02-01T23:59:59.000Z

183

FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2  

Science Conference Proceedings (OSTI)

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

Templeton, K.J.

1996-05-23T23:59:59.000Z

184

Does "model-free" forecasting really outperform the "true" model? A reply to Perretti et al  

E-Print Network (OSTI)

Estimating population models from uncertain observations is an important problem in ecology. Perretti et al. observed that standard Bayesian state-space solutions to this problem may provide biased parameter estimates when the underlying dynamics are chaotic. Consequently, forecasts based on these estimates showed poor predictive accuracy compared to simple "model-free" methods, which lead Perretti et al. to conclude that "Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data". However, a simple modification of the statistical methods also suffices to remove the bias and reverse their results.

Florian Hartig; Carsten F. Dormann

2013-05-15T23:59:59.000Z

185

Artificial Intelligence technique for modelling and forecasting of solar radiation data: a review  

Science Conference Proceedings (OSTI)

Artificial Intelligence (AI) has been used and applied in different sectors, such as engineering, economic, medicine, military, marine, etc. AI has also been applied for modelling, identification, optimisation, prediction, forecasting, and control ... Keywords: AI, FPGA, GAs, VHDL, artificial intelligence, fuzzy logic, genetic algorithms, hybrid systems, neural networks, photovoltaic systems, solar radiation forecasting, solar radiation modelling, solar radiation prediction

Adel Mellit

2008-11-01T23:59:59.000Z

186

Evaluation of a Simple Numerical Model as a Mesoscale Weather Forecasting Tool  

Science Conference Proceedings (OSTI)

During the America's Cup race series of 1986–1987, a numerical sea breeze model was used to assist offshore forecasts. The exercise has provided a detailed insight into the extent to which such a model may assist the forecasting process the ...

P. J. Rye

1989-12-01T23:59:59.000Z

187

Learning uncertainty models from weather forecast performance databases using quantile regression  

Science Conference Proceedings (OSTI)

Forecast uncertainty information is not available in the immediate output of Numerical weather prediction (NWP) models. Such important information is required for optimal decision making processes in many domains. Prediction intervals are a prominent ... Keywords: numerical weather forecast, prediction interval, quantile regression, uncertainty modeling

Ashkan Zarnani; Petr Musilek

2013-07-01T23:59:59.000Z

188

Numerical Extended-Range Prediction: Forecast Skill Using a Low-Resolution Climate Model  

Science Conference Proceedings (OSTI)

A pilot study that evaluates the potential forecast skill of winter 10–30-day time-mean flow from a low-resolution (R15) climate simulation model is presented. The hypothesis tested is that low-resolution climate model forecasts might be as ...

David P. Baumhefner

1996-09-01T23:59:59.000Z

189

Seasonal Forecasting in the Pacific Using the Coupled Model POAMA-2  

Science Conference Proceedings (OSTI)

The development of a dynamical model seasonal prediction service for island nations in the tropical South Pacific is described. The forecast model is the Australian Bureau of Meteorology's Predictive Ocean–Atmosphere Model for Australia (POAMA), a ...

Andrew Cottrill; Harry H. Hendon; Eun-Pa Lim; Sally Langford; Kay Shelton; Andrew Charles; David McClymont; David Jones; Yuriy Kuleshov

2013-06-01T23:59:59.000Z

190

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

Science Conference Proceedings (OSTI)

Forecasts of southeast Pacific stratocumulus at 20°S and 85°W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 are examined with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (...

Cécile Hannay; David L. Williamson; James J. Hack; Jeffrey T. Kiehl; Jerry G. Olson; Stephen A. Klein; Christopher S. Bretherton; Martin Köhler

2009-06-01T23:59:59.000Z

191

An Evaluation of Tropical Cyclone Genesis Forecasts from Global Numerical Models  

Science Conference Proceedings (OSTI)

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

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

2013-12-01T23:59:59.000Z

192

Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting  

SciTech Connect

Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework to incorporate the uncertainties associated with input, model structure, and parameter into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform the BNNs that only consider uncertainties associated with parameter and model structure. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters show that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of different uncertainty sources and including output error into the MCMC framework are expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting.

Zhang, Xuesong; Liang, Faming; Yu, Beibei; Zong, Ziliang

2011-11-09T23:59:59.000Z

193

An Analysis of the Accuracy of 120-h Predictions by the National Meteorological Center's Medium-Range Forecast Model  

Science Conference Proceedings (OSTI)

An assessment was made of the 120-h predictions by the medium range forecast (MRF) run of the National Meteorological Center's (NMC's) global spectral model. The ability of the model to forecast surface cyclones and anticyclones was evaluated and ...

Mary A. Bedrick; Anthony J. Cristaldi III; Stephen J. Colucci; Daniel S. Wilks

1994-03-01T23:59:59.000Z

194

Further Results on Forecasting and Model Selection Under Asymmetric Loss  

E-Print Network (OSTI)

: We make three related contributions. First, we propose a new technique for solving prediction problems under asymmetric loss using piecewise-linear approximations to the loss function, and we establish existence and uniqueness of the optimal predictor. Second, we provide a detailed application to optimal prediction of a conditionally heteroskedastic process under asymmetric loss, the insights gained from which are broadly applicable. Finally, we incorporate our results into a general framework for recursive prediction-based model selection under the relevant loss function. Acknowledgements: Helpful discussion was provided by Adolf Buse, Hashem Pesaran, Dale Poirrier, Enrique Sentana, Jim Stock, Ken Wallis, participants at meetings of the Econometric Society World Congress, the NBER/NSF Forecasting Seminar, the UCSD Conference on Multivariate Financial Econometrics, and numerous university seminars. All remaining inadequacies are ours alone. We thank the National Science Foundation, t...

Peter F. Christoffersen; Francis X. Diebold

1996-01-01T23:59:59.000Z

195

A Multigrid Wave Forecasting Model: A New Paradigm in Operational Wave Forecasting  

Science Conference Proceedings (OSTI)

A new operational wave forecasting system has been implemented at the National Centers for Environmental Prediction (NCEP) using the third public release of WAVEWATCH III. The new system uses a mosaic of grids with two-way nesting in a single ...

Arun Chawla; Hendrik L. Tolman; Vera Gerald; Deanna Spindler; Todd Spindler; Jose-Henrique G. M. Alves; Degui Cao; Jeffrey L. Hanson; Eve-Marie Devaliere

2013-08-01T23:59:59.000Z

196

A Real-Time Eulerian Photochemical Model Forecast System: Overview and Initial Ozone Forecast Performance in the Northeast U.S. Corridor  

Science Conference Proceedings (OSTI)

This article reports on the first implementation of a real-time Eulerian photochemical model forecast system in the United States. The forecast system consists of a tripartite set of one-way coupled models that run routinely on a parallel ...

John N. McHenry; William F. Ryan; Nelson L. Seaman; Carlie J. Coats Jr; Janusz Pudykiewicz; Sarav Arunachalam; Jeffery M. Vukovich

2004-04-01T23:59:59.000Z

197

Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models  

E-Print Network (OSTI)

In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX (”X” stands for exogenous/fundamental variable — system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to California Power Exchange (CalPX) system spot prices. We then use them for out-ofsample point and interval forecasting in normal and extremely volatile periods preceding the market crash in winter 2000/2001. We find evidence that (i) non-linear, threshold regime-switching (TAR/TARX) models outperform their linear counterparts, both in point and interval forecasting, and that (ii) an additional GARCH component generally decreases point forecasting efficiency. Interestingly, the former result challenges a number of previously published studies on the failure of non-linear regime-switching models in forecasting.

Adam Misiorek; Stefan Trueck; Rafal Weron

2006-01-01T23:59:59.000Z

198

On Modeling and Forecasting Time Series of Smooth Curves  

E-Print Network (OSTI)

/fertility rate curves (Hyndman and Ullah, 2007; Erbas et al., 2007). Other examples include electricity system the rates are unobservable; hence one needs to forecast future rate profiles based on historical call of telephone customer service centers, where forecasts of daily call arrival rate profiles are needed

Shen, Haipeng

199

Evaluation of the Weather Research and Forecasting model for two frost events  

Science Conference Proceedings (OSTI)

Meso-local-scale weather information could be used as a guideline for crop protection to effectively manage and mitigate the effects of frost damage. The main goal of this study was to evaluate the meso-local-scale weather forecasts from the state-of-the-art ... Keywords: Frost protection, Georgia Automated Environmental Monitoring Network, Temperature prediction, Weather Research and Forecasting model

Thara Prabha; Gerrit Hoogenboom

2008-12-01T23:59:59.000Z

200

A variable spread fuzzy linear regression model with higher explanatory power and forecasting accuracy  

Science Conference Proceedings (OSTI)

Fuzzy regression models have been applied to operational research (OR) applications such as forecasting. Some of previous studies on fuzzy regression analysis obtain crisp regression coefficients for eliminating the problem of increasing spreads for ... Keywords: Forecasting, Fuzzy inference, Fuzzy sets, Linear regression, Mathematical programming

Shih-Pin Chen; Jr-Fong Dang

2008-10-01T23:59:59.000Z

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


201

Experiences with 0–36-h Explicit Convective Forecasts with the WRF-ARW Model  

Science Conference Proceedings (OSTI)

Herein, a summary of the authors’ experiences with 36-h real-time explicit (4 km) convective forecasts with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) during the 2003–05 spring and summer seasons is presented. These ...

Morris L. Weisman; Christopher Davis; Wei Wang; Kevin W. Manning; Joseph B. Klemp

2008-06-01T23:59:59.000Z

202

The complex fuzzy system forecasting model based on triangular fuzzy robust wavelet ?-support vector machine  

Science Conference Proceedings (OSTI)

This paper presents a new version of fuzzy wavelet support vector regression machine to forecast the nonlinear fuzzy system with multi-dimensional input variables. The input and output variables of the proposed model are described as triangular fuzzy ... Keywords: Fuzzy ?-support vector machine, Fuzzy system forecasting, Particle swarm optimization, Wavelet kernel function

Qi Wu

2011-11-01T23:59:59.000Z

203

Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models  

Science Conference Proceedings (OSTI)

Forecasting airborne pollen concentrations is one of the most studied topics in aerobiology, due to its crucial application to allergology. The most used tools for this problem are single lineal regressions and autoregressive models (ARIMA). Notwithstanding, ... Keywords: Aerobiology, Airborne pollen, Forecasting, Neuro-fuzzy, Time series

José Luis Aznarte M.; José Manuel Benítez Sánchez; Diego Nieto Lugilde; Concepción de Linares Fernández; Consuelo Díaz de la Guardia; Francisca Alba Sánchez

2007-05-01T23:59:59.000Z

204

An Immersed Boundary Method for the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

This paper describes an immersed boundary method that facilitates the explicit resolution of complex terrain within the Weather Research and Forecasting (WRF) model. Mesoscale models, such as WRF, are increasingly used for high-resolution ...

Katherine A. Lundquist; Fotini Katopodes Chow; Julie K. Lundquist

2010-03-01T23:59:59.000Z

205

Quantitative Precipitation Forecasting for the Tennessee and Cumberland River Watersheds Using the NCEP Regional Spectral Model  

Science Conference Proceedings (OSTI)

A limited-area spectral model—the Regional Spectral Model—developed at the National Centers for Environmental Prediction is used to prepare daily quantitative precipitation forecasts out to 48 h for the Tennessee and Cumberland River basins in ...

Qi Mao; Stephen F. Mueller; Hann-Ming Henry Juang

2000-02-01T23:59:59.000Z

206

A More Extensive Investigation of the Use of Ensemble Forecasts for Dispersion Model Evaluation  

Science Conference Proceedings (OSTI)

An ensemble forecast is used as input to a Lagrangian particle dispersion model to study the effect that analysis errors in the numerical weather prediction assimilation cycle have on dispersion modeling. The wind and temperature fields from a ...

Anne Grete Straume

2001-03-01T23:59:59.000Z

207

Can a Regional Climate Model Improve the Ability to Forecast the North American Monsoon?  

Science Conference Proceedings (OSTI)

Global climate models are challenged to represent the North American monsoon, in terms of its climatology and interannual variability. To investigate whether a regional atmospheric model can improve warm season forecasts in North America, a ...

Christopher L. Castro; Hsin-I Chang; Francina Dominguez; Carlos Carrillo; Jae-Kyung Schemm; Hann-Ming Henry Juang

2012-12-01T23:59:59.000Z

208

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

Science Conference Proceedings (OSTI)

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

John M. Lanicci

2012-05-01T23:59:59.000Z

209

Properties of the Convection Scheme in NCEP's Eta Model that Affect Forecast Sounding Interpretation  

Science Conference Proceedings (OSTI)

The impact of parameterized convection on Eta Model forecast soundings is examined. The Betts–Miller–Janji? parameterization used in the National Centers for Environmental Prediction Eta Model introduces characteristic profiles of temperature and ...

Michael E. Baldwin; John S. Kain; Michael P. Kay

2002-10-01T23:59:59.000Z

210

A Real-Time Hurricane Surface Wind Forecasting Model: Formulation and Verification  

Science Conference Proceedings (OSTI)

A real-time hurricane wind forecast model is developed by 1) incorporating an asymmetric effect into the Holland hurricane wind model; 2) using the National Oceanic and Atmospheric Administration (NOAA)/National Hurricane Center’s (NHC) hurricane ...

Lian Xie; Shaowu Bao; Leonard J. Pietrafesa; Kristen Foley; Montserrat Fuentes

2006-05-01T23:59:59.000Z

211

METRo: A New Model for Road-Condition Forecasting in Canada  

Science Conference Proceedings (OSTI)

A numerical model to forecast road conditions, Model of the Environment and Temperature of Roads (METRo), has been developed to run at Canadian weather centers. METRo uses roadside observations from road weather information systems stations as ...

Louis-Philippe Crevier; Yves Delage

2001-11-01T23:59:59.000Z

212

An Examination of Model Track Forecast Errors for Hurricane Ike (2008) in the Gulf of Mexico  

Science Conference Proceedings (OSTI)

Sources of dynamical model track error for Hurricane Ike (2008) in the Gulf of Mexico are examined. Deterministic and ensemble model output are compared against National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ...

Michael J. Brennan; Sharanya J. Majumdar

2011-12-01T23:59:59.000Z

213

Field Significance Revisited: Spatial Bias Errors in Forecasts as Applied to the Eta Model  

Science Conference Proceedings (OSTI)

The spatial structure of bias errors in numerical model output is valuable to both model developers and operational forecasters, especially if the field containing the structure itself has statistical significance in the face of naturally ...

Kimberly L. Elmore; Michael E. Baldwin; David M. Schultz

2006-02-01T23:59:59.000Z

214

A new hybrid for improvement of auto-regressive integrated moving average models applying particle swarm optimization  

Science Conference Proceedings (OSTI)

A time series forecasting is an active research applied significantly in a variety of economics areas. Over the past three decades an auto-regressive integrated moving average (ARIMA) model, as one of the most important time series models, has been applied ... Keywords: ARIMA, Forecasting, PSOARIMA

Shahrokh Asadi; Akbar Tavakoli; Seyed Reza Hejazi

2012-04-01T23:59:59.000Z

215

Implementation of a Corporate Energy Accounting and Forecasting Model  

E-Print Network (OSTI)

The development and implementation of a Frito-Lay computer based energy consumption reporting and modeling program is discussed. The system has been designed to relate actual plant energy consumption to a standard consumption which incorporates the effects of weather, product mix, specific equipment types, and other plant factors. The model also provides energy consumption forecasts based on projected production, equipment improvements, and fuels mix. Development of the model began in August 1979 and was preceded by two years of complete auditing of all areas in two manufacturing plants plus specific processing lines in other plants to determine typical energy usage. Extensive analyses of the data resulted in the formulation of standards for the various pieces of equipment which are used as energy performance 'yardsticks'. Monthly reports permit equitable comparisons of plant energy consumption and isolation of those plants with the lowest efficiencies. The financial impact of increasing energy consumption, of the projected energy use for new plants or plant expansions, and of the effect of process changes on overall energy consumption can be also evaluated.

Kympton, H. W.; Bowman, B. M.

1981-01-01T23:59:59.000Z

216

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

E-Print Network (OSTI)

The Zimbabwean government utilizes the corn supply forecasts to establish producer prices for the following growing season, estimate corn storage and handling costs, project corn import needs and associated costs, and to assess the Grain Marketing 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. The objectives of the study are: (a) determine how changes in the government-established producer price affects the quantity of corn supplied to the Grain Marketing Board by the large-scale corn-producing sector and (b) whether including rainfall or rainfall probabilities into econometric models would result in an improvement of corn supply forecasts compared to current forecasts by the government. In order to accomplish the first objective a supply elasticity model was specified and estimated using ordinary least squares. This model is intended to provide 'de insight to the government regarding the influence of the government-established corn price and other related variables on corn supplied to the Grain Marketing Board by the large-scale producers. Thus, the estimated model would be useful to the government when establishing corn prices in March/April for production in the following growing season (October - February). To achieve the second objective, preliminary analysis was carried out to verify whether there is statistical evidence to support the hypothesis that rainfall cause" corn production and supply, and also corn prices and sales. Specifically the preliminary analysis involved using the Granger causality tests, stationarity tests and innovation accounting (impulse responses and forecast error decomposition). Having verified and quantified the causal effects of rainfall on corn production and supply, the next task was to investigate whether including rainfall and/or drought probabilities into forecasting econometric models would help provide improved out-of-sample forecasts compared to the government's forecasts. The forecasting accuracy of the models (short-run) was evaluated using standard statistical measures such as, the mean square error (MSE), mean absolute percentage error (MAPEI), improved mean absolute percentage error (IMAPE) and Theil's U-statistic, and thereupon select the best model. The results indicated that by incorporating rainfall and/or rainfall probabilities into econometric forecasting models, there was substantial improvement in corn supply forecasts. It follows that the the government would likely find it beneficial to incorporate the rainfall variable into their forecasting effort.

Makaudze, Ephias

1993-01-01T23:59:59.000Z

217

Comparison of Model Forecast Skill of Sea Level Pressure along the East and West Coasts of the United States  

Science Conference Proceedings (OSTI)

Despite recent advances in numerical weather prediction, major errors in short-range forecasts still occur. To gain insight into the origin and nature of model forecast errors, error frequencies and magnitudes need to be documented for different ...

Garrett B. Wedam; Lynn A. McMurdie; Clifford F. Mass

2009-06-01T23:59:59.000Z

218

Value of Real-Time Vegetation Fraction to Forecasts of Severe Convection in High-Resolution Models  

Science Conference Proceedings (OSTI)

Near-real-time values of vegetation fraction are incorporated into a 2-km nested version of the Advanced Research Weather Research and Forecasting (ARW) model and compared to forecasts from a control run that uses climatological values of ...

Kenneth A. James; David J. Stensrud; Nusrat Yussouf

2009-02-01T23:59:59.000Z

219

An Evaluation of Precipitation Forecasts from Operational Models and Reanalyses Including Precipitation Variations Associated with MJO Activity  

Science Conference Proceedings (OSTI)

In this paper, the results of an examination of precipitation forecasts for 1–30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ...

John E. Janowiak; Peter Bauer; Wanqiu Wang; Phillip A. Arkin; Jon Gottschalck

2010-12-01T23:59:59.000Z

220

Urban traffic flow forecasting using Gauss-SVR with cat mapping, cloud model and PSO hybrid algorithm  

Science Conference Proceedings (OSTI)

In order to improve forecasting accuracy of urban traffic flow, this paper applies support vector regression (SVR) model with Gauss loss function (namely Gauss-SVR) to forecast urban traffic flow. By using the input historical flow data as the validation ... Keywords: Cat mapping, Chaos theory, Cloud model, Particle Swarm Optimization, Support vector regression, Traffic flow forecasting

Ming-Wei Li; Wei-Chiang Hong; Hai-Gui Kang

2013-01-01T23:59:59.000Z

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


221

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

Open Energy Info (EERE)

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

222

Integrated Assessment Modeling  

Science Conference Proceedings (OSTI)

This paper discusses the role of Integrated Assessment models (IAMs) in climate change research. IAMs are an interdisciplinary research platform, which constitutes a consistent scientific framework in which the large-scale interactions between human and natural Earth systems can be examined. In so doing, IAMs provide insights that would otherwise be unavailable from traditional single-discipline research. By providing a broader view of the issue, IAMs constitute an important tool for decision support. IAMs are also a home of human Earth system research and provide natural Earth system scientists information about the nature of human intervention in global biogeophysical and geochemical processes.

Edmonds, James A.; Calvin, Katherine V.; Clarke, Leon E.; Janetos, Anthony C.; Kim, Son H.; Wise, Marshall A.; McJeon, Haewon C.

2012-10-31T23:59:59.000Z

223

Statistical Forecasts Based on the National Meteorological Center's Numerical Weather Prediction System  

Science Conference Proceedings (OSTI)

The production of interpretive weather element forecasts from dynamical model output variables is now an integral part of the centralized guidance systems of weather services throughout the world. The statistical forecasting system in the United ...

Gary M. Carter; J. Paul Dallavalle; Harry R. Glahn

1989-09-01T23:59:59.000Z

224

A statistical model for risk management of electric outage forecasts  

Science Conference Proceedings (OSTI)

Risk management of power outages caused by severe weather events, such as hurricanes, tornadoes, and thunderstorms, plays an important role in electric utility distribution operations. Damage prediction based on weather forecasts on an appropriate spatial ...

H. Li; L. A. Treinish; J. R. M. Hosking

2010-05-01T23:59:59.000Z

225

Successful Hydrologic Forecasting for California Using an Information Theoretic Model  

Science Conference Proceedings (OSTI)

The Entropy Minimax technique from information theory has been applied to long-range, hydrologic forecasting in California. Based on 1852–1977 records, the technique exhibits a limited, but statistically significant, success for predictions one ...

R. A. Christensen; R. F. Eilbert; O. H. Lindgren; L. L. Rans

1981-06-01T23:59:59.000Z

226

Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels?  

Science Conference Proceedings (OSTI)

Multimodel ensemble combination (MMEC) has become an accepted technique to improve probabilistic forecasts from short- to long-range time scales. MMEC techniques typically widen ensemble spread, thus improving the dispersion characteristics and ...

Andreas P. Weigel; Mark A. Liniger; Christof Appenzeller

2009-04-01T23:59:59.000Z

227

Cross-Validation in Statistical Climate Forecast Models  

Science Conference Proceedings (OSTI)

Cross-validation is a statistical procedure that produces an estimate of forecast skill which is less biased than the usual hindcast skill estimates. The cross-validation method systematically deletes one or more cases in a dataset, derives a ...

Joel Michaelsen

1987-11-01T23:59:59.000Z

228

Probabilistic Seasonal Forecasting of African Drought by Dynamical Models  

Science Conference Proceedings (OSTI)

As a natural phenomenon, drought can have devastating impacts on local populations through food insecurity and famine in the developing world such as Africa. In this study, we have established a seasonal hydrologic forecasting system over Africa. ...

Xing Yuan; Eric F. Wood; Nathaniel W. Chaney; Justin Sheffield; Jonghun Kam; Miaoling Liang; Kaiyu Guan

229

Regional load-curve models: scenario and forecast using the DRI model. Final report. [Forecasts of electric power loads in 32 US regions  

SciTech Connect

Regional load curve models were constructed for 32 regions that have been created by aggregating hourly load data from 146 electric utilities. These utilities supply approximately 95% of the electricity consumed in the continental US. The 32 models forecast electricity demands by hour, 8784 regional load forecasts per year. Because projections are made for each hour in the year, contemporaneous forecasts are available for peak demands, megawatt hour demands, load factors, load duration curves, and typical load shapes. The forecast scenario is described and documented in this volume and the forecast resulting from the use of this scenario is presented. The highlights of this forecast are two observations: (1) peak demands will once again become winter phenomena. By the year 2000, 18 of the 32 regions peak in a winter month as compared with the 8 winter peaking regions in 1977. In the heating season, the model is responsive to the number of heating degree-hours, the penetration rate of electric heating equipment, and the rate at which this space conditioning equipment is utilized, which itself is functionally dependent on the level of real electricity prices and real incomes. Thus, as the penetration rate of electric heating equipment increases, winter season demands grow more rapidly than demands in other seasons and peaks begin to appear in winter months; and (2) load factors begin to increase in the forecast, reversing the trend which began in the early 1960s. Nationally, load factors do not leap upwards, instead they increase gradually from .609 in 1977 to .629 in the year 2000. The improvement is more consequential in some regions, with load factors increasing, at times, by .10 or more. In some regions, load factors continue to decline.

Platt, H.D.

1981-08-01T23:59:59.000Z

230

Forecasting Financial Time-Series using Artificial Market Models  

E-Print Network (OSTI)

We discuss the theoretical machinery involved in predicting financial market movements using an artificial market model which has been trained on real financial data. This approach to market prediction - in particular, forecasting financial time-series by training a third-party or 'black box' game on the financial data itself -- was discussed by Johnson et al. in cond-mat/0105303 and cond-mat/0105258 and was based on some encouraging preliminary investigations of the dollar-yen exchange rate, various individual stocks, and stock market indices. However, the initial attempts lacked a clear formal methodology. Here we present a detailed methodology, using optimization techniques to build an estimate of the strategy distribution across the multi-trader population. In contrast to earlier attempts, we are able to present a systematic method for identifying 'pockets of predictability' in real-world markets. We find that as each pocket closes up, the black-box system needs to be 'reset' - which is equivalent to sayi...

Gupta, N; Johnson, N F; Gupta, Nachi; Hauser, Raphael; Johnson, Neil F.

2005-01-01T23:59:59.000Z

231

Development of the Upgraded Tangent Linear and Adjoint of the Weather Research and Forecasting (WRF) Model  

Science Conference Proceedings (OSTI)

The authors propose a new technique for parallelizations of tangent linear and adjoint codes, which were applied in the redevelopment for the Weather Research and Forecasting (WRF) model with its Advanced Research WRF dynamic core using the ...

Xin Zhang; Xiang-Yu Huang; Ning Pan

2013-06-01T23:59:59.000Z

232

Calibrating Multimodel Forecast Ensembles with Exchangeable and Missing Members Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical postprocessing technique that generates calibrated and sharp predictive probability density functions (PDFs) from forecast ensembles. It represents the predictive PDF as a weighted average of PDFs ...

Chris Fraley; Adrian E. Raftery; Tilmann Gneiting

2010-01-01T23:59:59.000Z

233

A Reduced Spectral Transform for the NCEP Seasonal Forecast Global Spectral Atmospheric Model  

Science Conference Proceedings (OSTI)

A reduced spectral transformation is applied to the NCEP atmospheric global spectral model for operational seasonal forecasts. The magnitude of the associated Legendre coefficient provides a basis for this new transformation, which is a simple ...

Hann-Ming Henry Juang

2004-04-01T23:59:59.000Z

234

Impacts of Soil Heating Condition on Precipitation Simulations in the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This ...

Xingang Fan

2009-07-01T23:59:59.000Z

235

On the Use of Mesoscale and Cloud-Scale Models in Operational Forecasting  

Science Conference Proceedings (OSTI)

In the near future, the technological capability will be available to use mesoscale and cloud-scale numerical models for forecasting convective weather in operational meteorology. We address some of the issues concerning effective utilization of ...

Harold E. Brooks; Charles A. Doswell III; Robert A. Maddox

1992-03-01T23:59:59.000Z

236

Use of Medium-Range Numerical Weather Prediction Model Output to Produce Forecasts of Streamflow  

Science Conference Proceedings (OSTI)

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output ...

Martyn P. Clark; Lauren E. Hay

2004-02-01T23:59:59.000Z

237

Predicting Cloud-to-Ground and Intracloud Lightning in Weather Forecast Models  

Science Conference Proceedings (OSTI)

A new prognostic, spatially and temporally dependent variable is introduced to the Weather Research and Forecasting Model (WRF). This variable is called the potential electrical energy (Ep). It was used to predict the dynamic contribution of the ...

Barry H. Lynn; Yoav Yair; Colin Price; Guy Kelman; Adam J. Clark

2012-12-01T23:59:59.000Z

238

Diagnostic and Forecast Graphics Products at NMC Using High Frequency Model Output  

Science Conference Proceedings (OSTI)

Archived hourly output from the National Meteorological Center (NMC) prediction models has provided the basis for advanced graphic diagnostic and forecast tools. The high-frequency data are available on a regional selected station network. Each ...

David W. Plummer

1989-03-01T23:59:59.000Z

239

Modeling the Distribution of Precipitation Forecasts from the Canadian Ensemble Prediction System Using Kernel Density Estimation  

Science Conference Proceedings (OSTI)

Kernel density estimation is employed to fit smooth probabilistic models to precipitation forecasts of the Canadian ensemble prediction system. An intuitive nonparametric technique, kernel density estimation has become a powerful tool widely used ...

Syd Peel; Laurence J. Wilson

2008-08-01T23:59:59.000Z

240

Model Bias in a Continuously Cycled Assimilation System and Its Influence on Convection-Permitting Forecasts  

Science Conference Proceedings (OSTI)

During the spring 2011 season, a real-time continuously cycled ensemble data assimilation system using the Advanced Research version of the Weather Research and Forecasting Model (WRF) coupled with the Data Assimilation Research Testbed toolkit ...

Glen S. Romine; Craig S. Schwartz; Chris Snyder; Jeff L. Anderson; Morris L. Weisman

2013-04-01T23:59:59.000Z

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


241

The Effect of Horizontal Resolution on Systematic Errors of the GLA Forecast Model  

Science Conference Proceedings (OSTI)

Systematic prediction errors of the Goddard Laboratory for Atmospheres (GLA) forecast system are reduced when the higher-resolution (2° × 2.5°) model version is used. Based on a budget analysis of the 200-mb eddy streamfunction, the improvement ...

Tsing-Chang Chen; Jau-Ming Chen; James Pfaendtner

1990-06-01T23:59:59.000Z

242

Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms  

Science Conference Proceedings (OSTI)

Accurate cloud-ceiling-height forecasts derived from numerical weather prediction (NWP) model data are useful for aviation and other interests where low cloud ceilings have an impact on operations. A demonstration of the usefulness of data-mining ...

Richard L. Bankert; Michael Hadjimichael

2007-10-01T23:59:59.000Z

243

Calibrated Surface Temperature Forecasts from the Canadian Ensemble Prediction System Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) has recently been proposed as a way of correcting underdispersion in ensemble forecasts. BMA is a standard statistical procedure for combining predictive distributions from different sources. The output of BMA is a ...

Laurence J. Wilson; Stephane Beauregard; Adrian E. Raftery; Richard Verret

2007-04-01T23:59:59.000Z

244

Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation  

Science Conference Proceedings (OSTI)

Ensemble prediction systems typically show positive spread-error correlation, but they are subject to forecast bias and dispersion errors, and are therefore uncalibrated. This work proposes the use of ensemble model output statistics (EMOS), an ...

Tilmann Gneiting; Adrian E. Raftery; Anton H. Westveld III; Tom Goldman

2005-05-01T23:59:59.000Z

245

Model Output Statistics Forecasts: Three Years of Operational Experience in the Netherlands  

Science Conference Proceedings (OSTI)

In the Netherlands, one to five day Model Output Statistics (MOS) forecasts have been used operationally since November 1983. The weather elements predicted are the probability of precipitation, the conditional probability of frozen precipitation,...

C. Lemcke; S. Kruizinga

1988-05-01T23:59:59.000Z

246

Statistical Recalibration of GCM Forecasts over Southern Africa Using Model Output Statistics  

Science Conference Proceedings (OSTI)

A technique for producing regional rainfall forecasts for southern Africa is developed that statistically maps or “recalibrates” large-scale circulation features produced by the ECHAM3.6 general circulation model (GCM) to observed regional ...

Willem A. Landman; Lisa Goddard

2002-08-01T23:59:59.000Z

247

Australian Experimental Model Output Statistics Forecasts of Daily Maximum and Minimum Temperature  

Science Conference Proceedings (OSTI)

Model output statistics (MOS) forecasts of daily temperature maxima and minima are developed for seven Australian cities. The developmental data and method of derivation of the MOS equations are described and the equations briefly compared to ...

F. Woodcock

1984-10-01T23:59:59.000Z

248

A Verification of Numerical Model Forecasts for Sounding-Derived Indices above Udine, Northeast Italy  

Science Conference Proceedings (OSTI)

In this work, 40 different indices derived from real soundings and the corresponding ECMWF model forecasts for the same location (near Udine, northeast Italy) are compared. This comparison is repeated for more than 500 days, from June 2004 to ...

Agostino Manzato

2008-06-01T23:59:59.000Z

249

Uncertainty Propagation of Regional Climate Model Precipitation Forecasts to Hydrologic Impact Assessment  

Science Conference Proceedings (OSTI)

A Monte Carlo framework is adopted for propagating uncertainty in dynamically downscaled seasonal forecasts of area-averaged daily precipitation to associated streamflow response calculations. Daily precipitation is modeled as a mixture of two ...

Phaedon C. Kyriakidis; Norman L. Miller; Jinwon Kim

2001-04-01T23:59:59.000Z

250

Impact of Domain Size on Modeled Ozone Forecast for the Northeastern United States  

Science Conference Proceedings (OSTI)

This study investigates the impact of model domain extent and the specification of lateral boundary conditions on the forecast quality of air pollution constituents in a specific region of interest. A developmental version of the national Air ...

Pius Lee; Daiwen Kang; Jeff McQueen; Marina Tsidulko; Mary Hart; Geoff DiMego; Nelson Seaman; Paula Davidson

2008-02-01T23:59:59.000Z

251

Numerical Prediction of an Antarctic Severe Wind Event with the Weather Research and Forecasting (WRF) Model  

Science Conference Proceedings (OSTI)

This study initiates the application of the maturing Weather Research and Forecasting (WRF) model to the polar regions in the context of the real-time Antarctic Mesoscale Prediction System (AMPS). The behavior of the Advanced Research WRF (ARW) ...

Jordan G. Powers

2007-09-01T23:59:59.000Z

252

Reverse supply chain forecasting and decision modeling for improved inventory management  

E-Print Network (OSTI)

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 ...

Petersen, Brian J. (Brian Jude)

2013-01-01T23:59:59.000Z

253

Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting  

Science Conference Proceedings (OSTI)

Accurate, real-time forecasting of coastal inundation due to hurricanes and tropical storms is a challenging computational problem requiring high-fidelity forward models of currents and water levels driven by hurricane-force winds. Despite best ...

T. Butler; M. U. Altaf; C. Dawson; I. Hoteit; X. Luo; T. Mayo

2012-07-01T23:59:59.000Z

254

Crude Oil Price Forecasting with an Improved Model Based on Wavelet Transform and RBF Neural Network  

Science Conference Proceedings (OSTI)

The fluctuation of oil price decides the security of energy and economics. So the crude oil price forecasting performs importantly. In the paper, we apply the improved model based on Wavelet Transform and Radial Basis Function (RBF) neural network to ...

Wu Qunli; Hao Ge; Cheng Xiaodong

2009-05-01T23:59:59.000Z

255

Experiments in probability of Precipitation Amount Forecasting Using Model Output Statistics  

Science Conference Proceedings (OSTI)

Modifications to current model output statistics procedures for quantitative precipitation forecasting were explored. Probability of precipitation amount equations were developed for warm and cool seasons in a region in the eastern United States. ...

Raymond W. Arritt; William M. Frank

1985-11-01T23:59:59.000Z

256

About the Reliability of Manual Model PV Corrections to Improve Forecasts  

Science Conference Proceedings (OSTI)

The National Weather Forecast Centre of Météo-France has developed a tool that corrects the state of the atmosphere within the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) operational global model by adjusting the potential vorticity ...

Philippe Arbogast; Karine Maynard; Catherine Piriou

2012-12-01T23:59:59.000Z

257

Accounting for Model Error in Ensemble-Based State Estimation and Forecasting  

Science Conference Proceedings (OSTI)

Accurate forecasts require accurate initial conditions. For systems of interest, even given a perfect model and an infinitely long time series of observations, it is impossible to determine a system's exact initial state. This motivates a ...

James A. Hansen

2002-10-01T23:59:59.000Z

258

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

Science Conference Proceedings (OSTI)

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

Emma B. Suckling; Leonard A. Smith

2013-12-01T23:59:59.000Z

259

Diabatic Forcing and Initialization with Assimilation of Cloud Water and Rainwater in a Forecast Model  

Science Conference Proceedings (OSTI)

In this study, diabatic initialization, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. ...

William H. Raymond; William S. Olson; Geary Callan

1995-02-01T23:59:59.000Z

260

An evaluation of decadal probability forecasts from state-of-the-art climate models  

Science Conference Proceedings (OSTI)

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

Emma B. Suckling; Leonard A. Smith

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


261

Hindcasting and Forecasting of the POLYMODE Data Set with the Harvard Open–Ocean Model  

Science Conference Proceedings (OSTI)

A regional quasi-geostrophic model has been used to hindcast and forecast the POLYMODE data set. After briefly discussing hindcast methodology, the hindcast fields are compared with the analyzed data set Periods of significant difference of ...

Leonard J. Walstad; Allan R. Robinson

1990-11-01T23:59:59.000Z

262

Hybridization of autoregressive integrated moving average (ARIMA) with probabilistic neural networks (PNNs)  

Science Conference Proceedings (OSTI)

Autoregressive integrated moving average (ARIMA) models are one of the most important time series models applied in financial market forecasting over the past three decades. Improving forecasting especially time series forecasting accuracy is an important ... Keywords: Autoregressive integrated moving average (ARIMA), Hybrid models, Probabilistic neural networks (PNNs), Time series forecasting

Mehdi Khashei; Mehdi Bijari; Gholam Ali Raissi Ardali

2012-08-01T23:59:59.000Z

263

Information and Inference in Econometrics: Estimation, Testing and Forecasting  

E-Print Network (OSTI)

Application: Forecasting Equity Premium . . . . . . . . . .2.6.1 Forecasting4 Forecasting Using Supervised Factor Models 4.1

Tu, Yundong

2012-01-01T23:59:59.000Z

264

Using Bayesian Model Averaging to Calibrate Forecast Ensembles ADRIAN E. RAFTERY, TILMANN GNEITING, FADOUA BALABDAOUI, AND MICHAEL POLAKOWSKI  

E-Print Network (OSTI)

Using Bayesian Model Averaging to Calibrate Forecast Ensembles ADRIAN E. RAFTERY, TILMANN GNEITING for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive centered on the individual bias-corrected forecasts, where the weights are equal to posterior probabilities

Raftery, Adrian

265

Comparison of Model Forecast Skill of Sea-Level Pressure Along the East and West Coasts of the United States  

E-Print Network (OSTI)

1 Comparison of Model Forecast Skill of Sea-Level Pressure Along the East and West Coasts, University of Washington, Seattle, Washington Submitted to: Weather and Forecasting May 2008 Revised recent advances in numerical weather prediction, major errors in short-range forecasts still occur

Mass, Clifford F.

266

Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System  

Science Conference Proceedings (OSTI)

NOAA and the U.S. Environmental Protection Agency (EPA) have developed a national air quality forecasting (AQF) system that is based on numerical models for meteorology, emissions, and chemistry. The AQF system generates gridded model forecasts ...

Tanya L. Otte; George Pouliot; Jonathan E. Pleim; Jeffrey O. Young; Kenneth L. Schere; David C. Wong; Pius C. S. Lee; Marina Tsidulko; Jeffery T. McQueen; Paula Davidson; Rohit Mathur; Hui-Ya Chuang; Geoff DiMego; Nelson L. Seaman

2005-06-01T23:59:59.000Z

267

The ENIAC Forecasts: A Re-creation  

Science Conference Proceedings (OSTI)

The numerical forecasts made in 1950 using the Electronic Numerical Integrator and Computer (ENIAC) paved the way for the remarkable advances that have been made over the past half-century in weather prediction and climate modeling. We review the ...

Peter Lynch

2008-01-01T23:59:59.000Z

268

Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting (WRF) model is evaluated by conducting various sensitivity experiments over central California including the San Francisco Bay Area (SFBA), with the goal of establishing a WRF model configuration to be used by ...

Raphael E. Rogers; Aijun Deng; David R. Stauffer; Brian J. Gaudet; Yiqin Jia; Su-Tzai Soong; Saffet Tanrikulu

2013-09-01T23:59:59.000Z

269

Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting (WRF) model is evaluated by conducting various sensitivity experiments over central California (CA) including the San Francisco Bay Area (SFBA), with the goal of establishing a WRF model configuration to be ...

Raphael E. Rogers; Aijun Deng; David R. Stauffer; Brian J. Gaudet; Yiqin Jia; Su-Tzai Soong; Saffet Tanrikulu

270

The Forecast Gap: Linking Forwards and Forecasts  

Science Conference Proceedings (OSTI)

This report addresses a common problem in price forecasting: What to do when confronted with a persistent gap between results obtained from a structural forecast model and actual forward or spot prices? The report examines examples taken from natural gas and electric power forecasts and presents a novel approach to closing this “forecast gap.” Inspection reveals that the ratio of actual prices to forecast prices often exhibits stochastic movements that resemble those of commodity price movements. By usin...

2008-12-15T23:59:59.000Z

271

DND: a model for forecasting electrical energy usage by water-resource subregion  

SciTech Connect

A forecast methodology was derived from principles of econometrics using exogenous variables, i.e., cost of electricity, consumer income, and price elasticity as indicators of growth for each consuming sector: residential, commercial, and industrial. The model was calibrated using forecast data submitted to the Department of Energy (DOE) by the nine Regional Electric Reliability Councils. Estimates on electrical energy usage by specific water-resource subregion were obtained by normalizing forecasted total electrical energy usage by state into per capita usage. The usage factor and data on forecasted population were applied for each water resource subregion. The results derived using the model are self-consistent and in good agreement with DOE Energy Information Administration projections. The differences that exist are largely the result of assumptions regarding specific aggregations and assignment of regional-system reliability and load factors. 8 references, 2 figures, 13 tables.

Sonnichsen, J.C. Jr.

1980-02-01T23:59:59.000Z

272

Forecasting Lightning Threat Using Cloud-Resolving Model Simulations  

Science Conference Proceedings (OSTI)

Two new approaches are proposed and developed for making time- and space-dependent, quantitative short-term forecasts of lightning threats, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are ...

Eugene W. McCaul Jr.; Steven J. Goodman; Katherine M. LaCasse; Daniel J. Cecil

2009-06-01T23:59:59.000Z

273

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

274

Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation  

Science Conference Proceedings (OSTI)

Tourism is one of the key service industries in Thailand, with a 5.27% share of Gross Domestic Product in 2003. Since 2000, international tourist arrivals, particularly those from East Asia, to Thailand have been on a continuous upward trend. Tourism ... Keywords: Autoregressive integrated moving average, Forecast, Spatial aggregation, Tourism

Chia-Lin Chang; Songsak Sriboonchitta; Aree Wiboonpongse

2009-01-01T23:59:59.000Z

275

Probabilistic Performance Forecasting for Unconventional Reservoirs With Stretched-Exponential Model  

E-Print Network (OSTI)

Reserves estimation in an unconventional-reservoir setting is a daunting task because of geologic uncertainty and complex flow patterns evolving in a long-stimulated horizontal well, among other variables. To tackle this complex problem, we present a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow has two different applications: forecasting probabilistic future performance of wells that have production history; and forecasting production from new wells without production data. For the new field case, numerical model runs are made in accord with the statistical design of experiments for a range of design variables pertinent to the field of interest. In contrast, for the producing wells the early-time data often need adjustments owing to restimulation, installation of artificial-lift, etc. to focus on the decline trend. Thereafter, production data of either new or existing wells are grouped in accord with initial rates to obtain common SEPD parameters for similar wells. After determining the distribution of model parameters using well grouping, the methodology establishes a probabilistic forecast for individual wells. We present a probabilistic performance forecasting methodology in unconventional reservoirs for wells with and without production history. Unlike other probabilistic forecasting tools, grouping wells with similar production character allows estimation of self-consistent SEPD parameters and alleviates the burden of having to define uncertainties associated with reservoir and well-completion parameters.

Can, Bunyamin

2011-05-01T23:59:59.000Z

276

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

Open Energy Info (EERE)

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

277

CFT, Integrable Models Liouville Gravity  

E-Print Network (OSTI)

CFT, Integrable Models And Liouville Gravity Chernogolovka 2009 Sunday June 28, 2009. Conference as one of components of their L, A pairs. #12;CFT, Integrable Models And Liouville Gravity Chernogolovka Gravity Chernogolovka, 2009 Tuesday June 30, 2009. CONFERENCE HALL 09:30­10:10 Herman Boos (Wuppertal

Fominov, Yakov

278

Model Transformations And Tool Integration  

E-Print Network (OSTI)

Model transformations are increasingly recognised as being of significant importance to many areas of software development and integration. Recent attention on model transformations has particularly focused on the OMG's Queries / Views / Transformations (QVT) Request for Proposals (RFP). In this paper I motivate the need for dedicated approaches to model transformations, particularly for the data involved in tool integration, outline the challenges involved, and then present a number of technologies and techniques which allow the construction of flexible, powerful and practical model transformations.

Laurence Tratt

2004-01-01T23:59:59.000Z

279

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

Science Conference Proceedings (OSTI)

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.

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

2013-03-19T23:59:59.000Z

280

Numerical Forecasting of Radiation Fog. Part I: Numerical Model and Sensitivity Tests  

Science Conference Proceedings (OSTI)

To improve the forecast of dense radiative fogs, a method has been developed using a one-dimensional model of the nocturnal boundary layer forced by the mesoscale fields provided by a 3D limited-area operational model. The 1D model involves a ...

Thierry Bergot; Daniel Guedalia

1994-06-01T23:59:59.000Z

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


281

Development of Wind Speed Forecasting Model Based on the Weibull Probability Distribution  

Science Conference Proceedings (OSTI)

Wind is a variable energy source. The power output of a wind turbine generator (WTG) unit, therefore, fluctuates with wind speed variations. Accurate models reflecting the variability of wind speed is hence required in both reliability evaluation of ... Keywords: Wind Energy, Wind Speed Forecasting Model, Weibull Distribution, Maximum Likelihood Method, Time Series Model

Ruigang Wang; Wenyi Li; B. Bagen

2011-02-01T23:59:59.000Z

282

Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions  

Science Conference Proceedings (OSTI)

A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high-resolution NWP model. Results by the Weather Research and Forecasting model (WRF) and the High-Resolution Limited-Area Model (...

I. R. van der Velde; G. J. Steeneveld; B. G. J. Wichers Schreur; A. A. M. Holtslag

2010-11-01T23:59:59.000Z

283

Regional load curve models: specification and estimation of the DRI Model. Final report. [Forecasts of electric loads in 32 US regions  

SciTech Connect

The DRI Model of hourly load curves is developed in this report. The model is capable of producing long-term forecasts for 32 US regions. These regions were created by aggregating hourly system load data from 146 electric utilities. These utilities supply approximately 95% of all electricity consumed in the continental US. The model forecasts electricity demands for each hour of the year for each of the 32 regions. Model output includes forecasts of peak demands, megawatt hour demands, load factors, and load duration curves. The DRI Model is estimated in two stages. In the first stage, for each region and month, hourly electricity demands are parameterized into load components representing the effects of lifestyles and weather on regional loads through a time-series model. In the second stage, the variation in these parameterized load components across months and regions is modeled econometrically in terms of energy prices, income levels, appliance saturation rates, and other variables. The second-stage models are essentially models of electricity demand which are estimated using estimated first-stage parameters as dependent variables, instead of observed demands. Regional price and income demand elasticities are implied by the second-stage models. Moreover, since the dependent variables refer to particular hours of the day, these estimated elasticities are hour-specific. (Since prices did not vary over the day in years when hourly load data were available, hour-to-hour, cross-price elasticities were not estimated.) Integrated system hourly load forecasts are obtained combining the influences of individual customer classes. Finally, approximate customer class hourly load shapes can be produced for each region, though these series may be useful only in research endeavors since they lack the precision available through survey methods.

Platt, H.D.; Einhorn, M.A.; Ignelzi, P.C.; Poirier, D.J.

1981-01-01T23:59:59.000Z

284

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

285

Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow  

E-Print Network (OSTI)

econ. WEATHER AND FORECASTING Environmental decisions (1993seasonal, and WEATHER AND FORECASTING V OLUME 19 spatialfor details. WEATHER AND FORECASTING V OLUME 19 T ABLE 2.

Simpson, James J; Dettinger, M D; Gehrke, F; McIntire, T J; Hufford, G L

2004-01-01T23:59:59.000Z

286

European Union Wind Energy Forecasting Model Development and Testing: U.S. Department of Energy -- EPRI Wind Turbine Verification Pr ogram  

Science Conference Proceedings (OSTI)

Wind forecasting can increase the strategic and market values of wind power from large wind facilities. This report summarizes the results of the European Union (EU) wind energy forecasting project and performance testing of the EU wind forecasting model. The testing compared forecast and observed wind speed and generation data from U.S. wind facilities.

1999-12-15T23:59:59.000Z

287

Performance of the Weather Research and Forecasting Model for Month-Long Pan-Arctic Simulations  

Science Conference Proceedings (OSTI)

The performance of the Weather Research and Forecasting (WRF) model was evaluated for month-long simulations over a large pan-Arctic model domain. The evaluation of seven different WRF (version 3.1) configurations for four months (January, April, ...

John J. Cassano; Matthew E. Higgins; Mark W. Seefeldt

2011-11-01T23:59:59.000Z

288

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

Science Conference Proceedings (OSTI)

This paper explores the degree to which short-term forecasts with global models might be improved if clouds were fully included in a data assimilation system, so that observations of clouds affected all parts of the model state and cloud ...

Robert Pincus; Robert J. Patrick Hofmann; Jeffrey L. Anderson; Kevin Raeder; Nancy Collins; Jeffrey S. Whitaker

2011-03-01T23:59:59.000Z

289

Deterministic regression model and visual basic code for optimal forecasting of financial time series  

Science Conference Proceedings (OSTI)

A new, non-statistical method is presented for analysis of the past history and current evolution of economic and financial processes. The method is based on the sliding model approach using linear differential or difference equations applied to discrete ... Keywords: Optimal forecasting in finance, Sliding deterministic regression models

Alejandro Balbás; Beatriz Balbás; Inna Galperin; Efim Galperin

2008-11-01T23:59:59.000Z

290

Relative Merit of Model Improvement versus Availability of Retrospective Forecasts: The Case of Climate Forecast System MJO Prediction  

Science Conference Proceedings (OSTI)

Retrospective forecasts of the new NCEP Climate Forecast System (CFS) have been analyzed out to 45 days from 1999 to 2009 with four members (0000, 0600, 1200, and 1800 UTC) each day. The new version of CFS [CFS, version 2 (CFSv2)] shows ...

Qin Zhang; Huug van den Dool

2012-08-01T23:59:59.000Z

291

ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL  

E-Print Network (OSTI)

5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended

Hamill, Tom

292

The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part III: Forecasting with Secondary-Applications Models  

Science Conference Proceedings (OSTI)

Output from the Army Test and Evaluation Command’s Four-Dimensional Weather System’s mesoscale model is used to drive secondary-applications models to produce forecasts of quantities of importance for daily decision making at U.S. Army test ...

Robert D. Sharman; Yubao Liu; Rong-Shyang Sheu; Thomas T. Warner; Daran L. Rife; James F. Bowers; Charles A. Clough; Edward E. Ellison

2008-04-01T23:59:59.000Z

293

Statistical Analysis of Forecasting Models across the North Slope of Alaska during the Mixed-Phase Arctic Clouds Experiment  

Science Conference Proceedings (OSTI)

The National Centers for Environmental Prediction’s (NCEP) Eta Model, the models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration’s (NASA) Global Modeling and Assimilation ...

Victor T. Yannuzzi; Eugene E. Clothiaux; Jerry Y. Harrington; Johannes Verlinde

2009-12-01T23:59:59.000Z

294

Global and Local Skill Forecasts  

Science Conference Proceedings (OSTI)

A skill forecast gives the probability distribution for the error in a forecast. Statistically, Well-founded skill forecasting methods have so far only been applied within the context of simple models. In this paper, the growth of analysis errors ...

P. L. Houtekamer

1993-06-01T23:59:59.000Z

295

Weather Forecasts by the WRF-ARW Model with the GSI Data Assimilation System in the Complex Terrain Areas of Southwest Asia  

Science Conference Proceedings (OSTI)

This paper will first describe the forecasting errors encountered from running the National Center for Atmospheric Research (NCAR) mesoscale model (the Advanced Research Weather Research and Forecasting model; ARW) in the complex terrain of ...

J. Xu; S. Rugg; L. Byerle; Z. Liu

2009-08-01T23:59:59.000Z

296

Comparison of 10-m Wind Forecasts from a Regional Area Model and QuikSCAT Scatterometer Wind Observations over the Mediterranean Sea  

Science Conference Proceedings (OSTI)

Surface wind forecasts from a limited-area model [the Quadrics Bologna Limited-Area Model (QBOLAM)] covering the entire Mediterranean area at 0.1° grid spacing are verified against Quick Scatterometer (QuikSCAT) wind observations. Only forecasts ...

Christophe Accadia; Stefano Zecchetto; Alfredo Lavagnini; Antonio Speranza

2007-05-01T23:59:59.000Z

297

Experiments in Shower-Top Forecasting Using an Interactive One-Dimensional Cloud Model  

Science Conference Proceedings (OSTI)

Experiments were made in prediction of the elevation of warm season shower-tops, both prevailing and highest, using a one-dimensional cloud model run on a real-time minicomputer system. A forecaster inter-actively altered the initial temperatures ...

Timothy D. Crum; John J. Cahir

1983-04-01T23:59:59.000Z

298

A strategy for verifying near-convection-resolving model forecasts at observing sites  

Science Conference Proceedings (OSTI)

Routine verification of deterministic Numerical Weather Prediction (NWP) forecasts from the convection-permitting 4 km (UK4) and near-convection-resolving 1.5 km (UKV) configurations of the Met Office Unified Model (MetUM) has shown that it is ...

Marion P. Mittermaier

299

Improving High-Resolution Model Forecasts of Downslope Winds in the Las Vegas Valley  

Science Conference Proceedings (OSTI)

Numerical simulations for severe downslope winds as well as trapped lee waves in Nevada’s Las Vegas Valley were performed in this study. The goal of this study was to improve model forecasts of downslope-wind-event intensities. This was measured ...

Andre K. Pattantyus; Sen Chiao; Stanley Czyzyk

2011-06-01T23:59:59.000Z

300

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

Science Conference Proceedings (OSTI)

Seasonal maize water-stress forecasts were derived for area averages of the primary maize-growing regions of South Africa and Zimbabwe. An agroclimatological model was used to create a historical record of maize water stress as a function of ...

Randall V. Martin; Richard Washington; Thomas E. Downing

2000-09-01T23:59:59.000Z

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


301

Error Climatology of the 80-Wave Medium-Range Forecast Model  

Science Conference Proceedings (OSTI)

A climatology of the once-daily (0000 UTC) 1000-hPa error fields of the National Meteorological Center's 80-wave Medium-Range Forecast (MRF) model is studied. An analysis of the error field has been conducted over the contiguous United States and ...

David R. Walker; Robert E. Davis

1995-09-01T23:59:59.000Z

302

The Integrated Environmental Control Model (IECM)  

NLE Websites -- All DOE Office Websites (Extended Search)

Innovations for Existing Plants The Integrated Environmental Control Model (IECM) The Integrated Environmental Control Model (IECM) was developed for the National Energy Technology...

303

Separations and safeguards model integration.  

Science Conference Proceedings (OSTI)

Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.

Cipiti, Benjamin B.; Zinaman, Owen

2010-09-01T23:59:59.000Z

304

Wind Speed Forecasting for Power System Operation  

E-Print Network (OSTI)

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system operation in terms of the efficiency of the system. The goal of this dissertation is to develop advanced statistical wind speed predictive models to reduce the uncertainties in wind, especially the short-term future wind speed. Moreover, a criterion is proposed to evaluate the performance of models. Cost reduction in power system operation, as proposed, is more realistic than prevalent criteria, such as, root mean square error (RMSE) and absolute mean error (MAE). Two advanced space-time statistical models are introduced for short-term wind speed forecasting. One is a modified regime-switching, space-time wind speed fore- casting model, which allows the forecast regimes to vary according to the dominant wind direction and seasons. Thus, it avoids a subjective choice of regimes. The other one is a novel model that incorporates a new variable, geostrophic wind, which has strong influence on the surface wind, into one of the advanced space-time statistical forecasting models. This model is motivated by the lack of improvement in forecast accuracy when using air pressure and temperature directly. Using geostrophic wind in the model is not only critical, it also has a meaningful geophysical interpretation. The importance of model evaluation is emphasized in the dissertation as well. Rather than using RMSE or MAE, the performance of both wind forecasting models mentioned above are assessed by economic benefits with real wind farm data from Pacific Northwest of the U.S and West Texas. Wind forecasts are incorporated into power system economic dispatch models, and the power system operation cost is used as a loss measure for the performance of the forecasting models. From another perspective, the new criterion leads to cost-effective scheduling of system-wide wind generation with potential economic benefits arising from the system-wide generation of cost savings and ancillary services cost savings. As an illustration, the integrated forecasts and economic dispatch framework are applied to the Electric Reliability Council of Texas (ERCOT) equivalent 24- bus system. Compared with persistence and autoregressive models, the first model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars. For the second model, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model.

Zhu, Xinxin

2013-08-01T23:59:59.000Z

305

Similarity retrieval from time-series tropical cyclone observations using a neural weighting generator for forecasting modeling  

Science Conference Proceedings (OSTI)

Building a forecasting model for time-series data is a tough but very valuable research topic in recent years. High variation of time-series features must be considered appropriately for an accurate prediction. For weather forecasting, which is continuous, ...

Bo Feng; James N. K. Liu

2005-09-01T23:59:59.000Z

306

Seasonal Precipitation Forecasting with a 6–7 Month Lead Time in the Pacific Northwest Using an Information Theoretic Model  

Science Conference Proceedings (OSTI)

An entropy minimax analysis for the forecast of seasonal precipitation with a 6–7 month lead time was performed for two regions in the Pacific Northwest. A model for the forecast of winter precipitation in the Willamette Valley, Oregon was ...

R. A. Christensen; R. F. Eilbert

1985-04-01T23:59:59.000Z

307

Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework  

E-Print Network (OSTI)

An integrated hydrologic Bayesian multimodel combinationon "An integrated hydrologic Bayesian multimodel combinationand Z. S. Hou (2007), A Bayesian model for gas saturation

Li, M.

2013-01-01T23:59:59.000Z

308

Characteristics of High-Resolution Versions of the Met Office Unified Model for Forecasting Convection over the United Kingdom  

Science Conference Proceedings (OSTI)

With many operational centers moving toward order 1-km-gridlength models for routine weather forecasting, this paper presents a systematic investigation of the properties of high-resolution versions of the Met Office Unified Model for short-range ...

Humphrey W. Lean; Peter A. Clark; Mark Dixon; Nigel M. Roberts; Anna Fitch; Richard Forbes; Carol Halliwell

2008-09-01T23:59:59.000Z

309

Extracting Unique Information from High-Resolution Forecast Models: Monitoring Selected Fields and Phenomena Every Time Step  

Science Conference Proceedings (OSTI)

A new strategy for generating and presenting model diagnostic fields from convection-allowing forecast models is introduced. The fields are produced by computing temporal-maximum values for selected diagnostics at each horizontal grid point ...

John S. Kain; Scott R. Dembek; Steven J. Weiss; Jonathan L. Case; Jason J. Levit; Ryan A. Sobash

2010-10-01T23:59:59.000Z

310

Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere–Ocean Coupled Models. Part I: Climatology  

Science Conference Proceedings (OSTI)

The goal of this study is to utilize several recent developments on rainfall data collection, downscaling of available climate models, training and forecasts from such models within the framework of a multimodel superensemble, and first a detailed ...

Vinay Kumar; T. N. Krishnamurti

2012-01-01T23:59:59.000Z

311

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

SciTech Connect

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

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

2008-01-24T23:59:59.000Z

312

A new modeling approach of STLF with integrated dynamics mechanism and based on the fusion of dynamic optimal neighbor phase points and ICNN  

Science Conference Proceedings (OSTI)

Based on the time evolution similarity principle of the topological neighbor phase points in the Phase Space Reconstruction (PSR), a new modeling approach of Short-Term Load Forecasting (STLF) with integrated dynamics mechanism and based on the fusion ...

Zhisheng Zhang; Yaming Sun; Shiying Zhang

2006-05-01T23:59:59.000Z

313

Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis  

E-Print Network (OSTI)

Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .

Zhao, Feng

2013-01-01T23:59:59.000Z

314

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

Science Conference Proceedings (OSTI)

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.

McNamara, Laura A.

2010-08-01T23:59:59.000Z

315

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-01-01T23:59:59.000Z

316

Forecast cloudy; The limits of global warming models  

SciTech Connect

This paper reports on climate models used to study global warming. It discusses factors which must be included in climate models, shortcomings of existing climate models, and scenarios for global warming.

Stone, P.H.

1992-02-01T23:59:59.000Z

317

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

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

318

Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Science Conference Proceedings (OSTI)

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

2010-04-20T23:59:59.000Z

319

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

E-Print Network (OSTI)

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.

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

2013-01-01T23:59:59.000Z

320

HEURISTIC APPROACH FOR OPTIMAL PARAMETER ESTIMATION OF ELECTRIC LOAD FORECAST MODEL  

Science Conference Proceedings (OSTI)

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

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

2009-01-01T23:59:59.000Z

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


321

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

SciTech Connect

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.

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

2007-12-01T23:59:59.000Z

322

Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements  

Science Conference Proceedings (OSTI)

Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the ...

Anne Grete Straume; Ernest N’Dri Koffi; Katrin Nodop

1998-11-01T23:59:59.000Z

323

Fitting a Linear Autoregressive Model for Long-Range Forecasting  

Science Conference Proceedings (OSTI)

Methods of fitting a linear autoregressive model to a stationary time series are summarized. Parameters of the linear autoregressive model were estimated by the Durbin stepwise procedure and the order of this model was chosen by means of a t-test ...

C. S. Yao

1983-04-01T23:59:59.000Z

324

Real &me numerical forecast of global epidemic spreading using large-scale computa&onal models  

E-Print Network (OSTI)

Real &me numerical forecast of global epidemic spreading using large conditions). Forecast = best prediction given the present knowledge on the system. Projection = attempt functionalities) #12;Real time forecast for the H1N1pdm (2009) Key parameters

Cattuto, Ciro

325

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Market and STEO Error Forecast Error from 1998 to 2003 (2 Futures Market and STEO Error Forecast Error from 1998to 2003 (Months 13- Forecast from 1998 to 2003 (Months 1-12)

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

2005-01-01T23:59:59.000Z

326

NIST Modeled integrated scattering tool (MIST)  

Science Conference Proceedings (OSTI)

... been developed to provide users with a general application to model an integrated scattering system. The program performs an integration of the ...

2012-08-07T23:59:59.000Z

327

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

the forecast. In 1978 the Natural Gas Policy Act was passedof Other Natural Gas Price Forecasts Researchers and policyresearchers and policy makers who utilize natural gas prices

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

2005-01-01T23:59:59.000Z

328

Regional forecasting with global atmospheric models; Third year report  

SciTech Connect

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.

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

1994-05-01T23:59:59.000Z

329

Regional forecasting with global atmospheric models; Final report  

SciTech Connect

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

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

1994-05-01T23:59:59.000Z

330

FY 1996 solid waste integrated life-cycle forecast volume summary - Volume 1 and Volume 2  

Science Conference Proceedings (OSTI)

Solid waste forecast volumes to be generated or received ;at Westinghouse Hanford Company`s Solid Waste program over the life cycle of the site are described in this report. Previous forecast summary reports have covered only a 30-year period; however, the life-cycle approach was adopted for this FY 1996 report to ensure consistency with waste volumes reported in the 1996 Multi-Year Program Plans (MYPP). The volume data were collected on a life-cycle basis from onsite and offsite waste generators who currently ship or plan to ship solid waste to the Solid Waste program. The volumes described in detail are low-level mixed waste (LLMW) and transuranic/transuranic-mixed (TRU(M)) waste. The volumes reported in this document represent the external volume of the containers selected to ship the waste. Summary level information pertaining to low-level waste (LLW) is described in Appendix B. Hazardous waste volumes are also provided in Appendices E and F but are not described in detail since they will be managed by a commercial facility. Emphasis is placed on LLMW and TRU(M) waste because it will require processing and storage at Hanford Solid Waste`s Central Waste Complex (CORK) prior to final disposal. The LLW will generally be sent directly to disposal. The total baselines volume of LLMW and TRU(M) waste forecast to be received by the Solid Waste program (until 2070) is approximately 100,900 cubic meters. This total waste volume is composed of the following waste categories: 077,080 cubic meters of LLMW; 23,180 cubic meters of TRU(M); 640 cubic meters of greater-than-class III LLMW. This total is about 40% of the total volume reported last year (FY 1995).

Valero, O.J.

1996-02-22T23:59:59.000Z

331

Long Lead Time Drought Forecasting Using a Wavelet and Fuzzy Logic Combination Model: A Case Study in Texas  

Science Conference Proceedings (OSTI)

Drought forecasting is important for drought risk management. Considering the El Niño–Southern Oscillation (ENSO) variability and persistence in drought characteristics, this study developed a wavelet and fuzzy logic (WFL) combination model for ...

Mehmet Özger; Ashok K. Mishra; Vijay P. Singh

2012-02-01T23:59:59.000Z

332

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

Science Conference Proceedings (OSTI)

Standard indices used in the National Fire Danger Rating System (NFDRS) and Fosberg fire-weather indices are calculated from Weather Research and Forecasting (WRF) model simulations and observations in interior Alaska for June 2005. Evaluation ...

Nicole Mölders

2008-10-01T23:59:59.000Z

333

Improved Seasonal Climate Forecasts of the South Asian Summer Monsoon Using a Suite of 13 Coupled Ocean–Atmosphere Models  

Science Conference Proceedings (OSTI)

Several modeling studies have shown that the south Asian monsoon region has the lowest skill for seasonal forecasts compared with many other domains of the world. This paper demonstrates that a multimodel synthetic superensemble approach, when ...

Arindam Chakraborty; T. N. Krishnamurti

2006-06-01T23:59:59.000Z

334

High-Order Numerics in an Unstaggered Three-Dimensional Time-Split Semi-Lagrangian Forecast Model  

Science Conference Proceedings (OSTI)

Traditional finite-difference numerical forecast models usually employ relatively low-order approximations on grids staggered in both the horizontal and the vertical. In a previous study, Purser and Leslie (1988) demonstrated that high-order ...

L. M. Leslie; R. J. Purser

1991-07-01T23:59:59.000Z

335

Sensitivity of 0–12-h Warm-Season Precipitation Forecasts over the Central United States to Model Initialization  

Science Conference Proceedings (OSTI)

Sensitivity of 0–12-h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and ...

Juanzhen Sun; Stanley B. Trier; Qingnong Xiao; Morris L. Weisman; Hongli Wang; Zhuming Ying; Mei Xu; Ying Zhang

2012-08-01T23:59:59.000Z

336

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

Science Conference Proceedings (OSTI)

Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs ...

Dev Niyogi; Kiran Alapaty; Sethu Raman; Fei Chen

2009-02-01T23:59:59.000Z

337

Improving Global Model Precipitation Forecasts over India Using Downscaling and the FSU Superensemble. Part II: Seasonal Climate  

Science Conference Proceedings (OSTI)

This study addresses seasonal forecasts of rains over India using the following components: high-resolution rain gauge–based rainfall data covering the years 1987–2001, rain-rate initialization, four global atmosphere–ocean coupled models, a ...

Arindam Chakraborty; T. N. Krishnamurti

2009-09-01T23:59:59.000Z

338

Resolved turbulence characteristics in large-eddy simulations nested within mesoscale simulations using the Weather Research and Forecasting model  

Science Conference Proceedings (OSTI)

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

Jeff Mirocha; Branko Kosovi?; Gokhan Kirkil

339

Evaluating Weather Research and Forecasting (WRF) Model Predictions of Turbulent Flow Parameters in a Dry Convective Boundary Layer  

Science Conference Proceedings (OSTI)

Weather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry ...

Jeremy A. Gibbs; Evgeni Fedorovich; Alexander M. J. van Eijk

2011-12-01T23:59:59.000Z

340

An Objective Comparison of Model Output Statistics and “Perfect Prog” Systems in Producing Numerical Weather Element Forecasts  

Science Conference Proceedings (OSTI)

The “perfect prog” (PP) and model output statistics (MOS) approaches were used to develop multiple linear regression equations to forecast probabilities of more than a trace of precipitation over 6-h periods, probabilities of precipitation ...

N. Brunet; R. Verret; N. Yacowar

1988-12-01T23:59:59.000Z

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


341

NAM Model Forecasts of Warm-Season Quasi-Stationary Frontal Environments in the Central United States  

Science Conference Proceedings (OSTI)

Using a composite procedure, North American Mesoscale Model (NAM) forecast and observed environments associated with zonally oriented, quasi-stationary surface fronts for 64 cases during July–August 2006–08 were examined for a large region ...

Shih-Yu Wang; Adam J. Clark

2010-08-01T23:59:59.000Z

342

Analysis of Idealized Tropical Cyclone Simulations Using the Weather Research and Forecasting Model: Sensitivity to Turbulence Parameterization and Grid Spacing  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting Advanced Research Model (WRF-ARW) was used to perform idealized tropical cyclone (TC) simulations, with domains of 36-, 12-, and 4-km horizontal grid spacing. Tests were conducted to determine the sensitivity ...

Kevin A. Hill; Gary M. Lackmann

2009-02-01T23:59:59.000Z

343

Operational Implementation of the ISBA Land Surface Scheme in the Canadian Regional Weather Forecast Model. Part I: Warm Season Results  

Science Conference Proceedings (OSTI)

The summertime improvement resulting from the operational implementation of a new surface modeling and assimilation strategy into the Canadian regional weather forecasting system is described in this study. The surface processes over land are ...

Stéphane Bélair; Louis-Philippe Crevier; Jocelyn Mailhot; Bernard Bilodeau; Yves Delage

2003-04-01T23:59:59.000Z

344

Evaluation of WRF Model Output for Severe Weather Forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment  

Science Conference Proceedings (OSTI)

This study assesses forecasts of the preconvective and near-storm environments from the convection-allowing models run for the 2008 National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) spring experiment. ...

Michael C. Coniglio; Kimberly L. Elmore; John S. Kain; Steven J. Weiss; Ming Xue; Morris L. Weisman

2010-04-01T23:59:59.000Z

345

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

E-Print Network (OSTI)

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

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

346

Forecast Technical Document Forecast Types  

E-Print Network (OSTI)

Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Forecast Types Background Different `types' of forecast are possible for a specified area

347

Mesoscale Modeling for Mountain Weather Forecasting Over the Himalayas  

Science Conference Proceedings (OSTI)

Severe weather has a more calamitous effect in the mountainous region-because the terrain is complex and the economy is poorly developed and fragile. Such weather systems occurring on a small spatiotemporal scale invite application of models with ...

Someshwar Das; S. V. Singh; E. N. Rajagopal; Robert Gall

2003-09-01T23:59:59.000Z

348

Dynamical Forecast Experiments with a Barotropic Open Ocean Model  

Science Conference Proceedings (OSTI)

The initial/boundary value problem for the barotropic version of a quasi-geostrophic open ocean model which requires normal flow everywhere on the boundary and vorticity on the inflow is studied. Parameter dependencies and sensitivities are ...

A. R. Robinson; D. B. Haidvogel

1980-12-01T23:59:59.000Z

349

Forecasting Pacific SSTs: Linear Inverse Model Predictions of the PDO  

Science Conference Proceedings (OSTI)

A linear inverse model (LIM) is used to predict Pacific (30°S–60°N) sea surface temperature anomalies (SSTAs), including the Pacific decadal oscillation (PDO). The LIM is derived from the observed simultaneous and lagged covariance statistics of ...

Michael A. Alexander; Ludmila Matrosova; Cécile Penland; James D. Scott; Ping Chang

2008-01-01T23:59:59.000Z

350

A Linear Markov Model for East Asian Monsoon Seasonal Forecast  

Science Conference Proceedings (OSTI)

A linear Markov model has been developed to predict the short-term climate variability of the East Asian monsoon system, with emphasis on precipitation variability. Precipitation, sea level pressure, zonal and meridional winds at 850 mb, along ...

Qiaoyan Wu; Ying Yan; Dake Chen

2013-07-01T23:59:59.000Z

351

Fog Forecasting for the Southern Region: A Conceptual Model Approach  

Science Conference Proceedings (OSTI)

The prediction of fog occurrence, extent, duration, and intensity remains difficult despite improvements in numerical guidance and modeling of the fog phenomenon. This is because of the dependency of fog on microphysical and mesoscale processes ...

Paul J. Croft; Russell L. Pfost; Jeffrey M. Medlin; G. Alan Johnson

1997-09-01T23:59:59.000Z

352

Cloud Predictions Diagnosed from Global Weather Model Forecasts  

Science Conference Proceedings (OSTI)

The U.S. Air Force has a long history of investment in cloud analysis and prediction operations. Their need for accurate cloud cover information has resulted in routine production of global cloud analyses (from their RTNEPH analysis model) and ...

Donald C. Norquist

2000-10-01T23:59:59.000Z

353

A forecasting model of tourist arrivals from major markets to Thailand  

E-Print Network (OSTI)

International tourism is a rapidly growing phenomenon hics. worldwide. However, the East Asia and Pacific Region is expected to be the focus of the worldwide tourism industry in the new millennium because tourist arrivals and receipts registered a growth about twice the rates of industrialized countries in the last decade. The tourism industry has become a powerful engine for economic development and a major foreign exchange generator. With such growth and increased competition, it is vitally important to forecast tourism demand in the region and understand the factors affecting demand. Considering the national importance of tourism, Thailand was chosen as the destination country with nine major markets as the countries of origin. A model was developed for each country to forecast tourism demand from that market. Multiple regression analysis was applied over time series data. The empirical results suggest that independent variables, such as income level in the country of origin, prices of tourism goods in the destination country, currency exchange rate between the origin and destination country, and rooms supply in destination, do affect tourism demand. Qualitative factors, represented by dummy variables, namely special promotional program and political unrest, show slight impact on demand. The study reveals that there are differences in the relative impacts of variables among the tourist generating countries. Thus, country-specific forecasting models and strategies must be formulated to reflect the uniqueness of each country of origin. Furthermore, forecasting techniques should include more qualitative factors to better asses their impacts on tourism demand. For future research, it is suggested that the models developed be updated regularly to reflect changes in the selected independent variables. Surveys and studies dealing with consumer motivation should be carried out to understand more about the tourists themselves and how they select particular destinations and types of tourism. Finally, in order to take advantage of modern technologies, the Internet is suggested as a tool to promote tourism.

Hao, Ching

1998-01-01T23:59:59.000Z

354

APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY  

E-Print Network (OSTI)

1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic

Katz, Richard

355

On model selection forecasting, Dark Energy and modified gravity  

E-Print Network (OSTI)

The Fisher matrix approach (Fisher 1935) allows one to calculate in advance how well a given experiment will be able to estimate model parameters, and has been an invaluable tool in experimental design. In the same spirit, we present here a method to predict how well a given experiment can distinguish between different models, regardless of their parameters. From a Bayesian viewpoint, this involves computation of the Bayesian evidence. In this paper, we generalise the Fisher matrix approach from the context of parameter fitting to that of model testing, and show how the expected evidence can be computed under the same simplifying assumption of a gaussian likelihood as the Fisher matrix approach for parameter estimation. With this `Laplace approximation' all that is needed to compute the expected evidence is the Fisher matrix itself. We illustrate the method with a study of how well upcoming and planned experiments should perform at distinguishing between Dark Energy models and modified gravity theories. In particular we consider the combination of 3D weak lensing, for which planned and proposed wide-field multi-band imaging surveys will provide suitable data, and probes of the expansion history of the Universe, such as proposed supernova and baryonic acoustic oscillations surveys. We find that proposed large-scale weak lensing surveys from space should be able readily to distinguish General Relativity from modified gravity models.

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

2007-03-08T23:59:59.000Z

356

Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint  

DOE Green Energy (OSTI)

Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

2013-10-01T23:59:59.000Z

357

Growth Diagnostics for Dark Energy models and EUCLID forecast  

E-Print Network (OSTI)

In this work we introduce a new set of parameters $(r_{g}, s_{g})$ involving the linear growth of matter perturbation that can distinguish and constrain different dark energy models very efficiently. Interestingly, for $\\Lambda$CDM model these parameters take exact value $(1,1)$ at all red shifts whereas for models different from $\\Lambda$CDM, they follow different trajectories in the $(r_{g}, s_{g})$ phase plane. By considering the parametrization for the dark energy equation of state ($w$) and for the linear growth rate ($f_{g}$), we show that different dark energy behaviours with similar evolution of the linear density contrast, can produce distinguishable trajectories in the $(r_{g}, s_{g})$ phase plane. Moreover, one can put stringent constraint on these phase plane using future measurements like EUCLID ruling out some of the dark energy behaviours.

Sampurnanand; Anjan A. Sen

2013-01-06T23:59:59.000Z

358

Web based integrated models for participatory planning  

Science Conference Proceedings (OSTI)

The present paper focuses on the development of an integrated assessment model that embeds the web dimension and aims at increasing awareness in society, especially on environmental issues. The model incorporates features that make it capable of promoting ... Keywords: greenhouse gas emissions, increasing awareness, integrated assessment models, web based participatory integrated assessment models

Grammatikogiannis Elias; Maria Giaoutzi

2011-06-01T23:59:59.000Z

359

A Markov Model for Seasonal Forecast of Antarctic Sea Ice  

Science Conference Proceedings (OSTI)

A linear Markov model has been developed to simulated and predict the short-term climate change in the Antarctic, with particular emphasis on sea ice variability. Seven atmospheric variables along with sea ice were chosen to define the state of ...

Dake Chen; Xiaojun Yuan

2004-08-01T23:59:59.000Z

360

Operational Ensemble Cloud Model Forecasts: Some Preliminary Results  

Science Conference Proceedings (OSTI)

From 15 July through 30 September of 2001, an ensemble cloud-scale model was run for the Storm Prediction Center on a daily basis. Each ensemble run consisted of 78 members whose initial conditions were derived from the 20-km Rapid Update Cycle ...

Kimberly L. Elmore; Steven J. Weiss; Peter C. Banacos

2003-10-01T23:59:59.000Z

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


361

Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation: Preprint  

DOE Green Energy (OSTI)

Over the past several years, there has been considerable development and application of wind forecasting models. The main purpose of these models is to provide grid operators with the best information available so that conventional power generators can be scheduled as efficiently and as cost-effectively as possible. One of the important ancillary services is reserves, which involves scheduling additional capacity to guard against shortfalls. In a recent paper, Strbac and Kirschen[1] proposed a method to allocate the reserve burden to generators. Although Milligan adapted this technique to wind plants[2], neither of these papers accounts for the wind forecast in the reliability calculation. That omission is rectified here. For the system studied in this paper, we found that a reserve allocation scheme using 1-hour forecasts results in a small allocation of system reserve relative to the rated capacity of the wind power plant. This reserve allocation is even smaller when geographically dispersed wind sites are used instead of a large single site.

Milligan, M. R.

2002-05-01T23:59:59.000Z

362

www.inescc.pt 1 Short Term Load Forecasting Using Gaussian Process Models  

E-Print Network (OSTI)

Abstract — The electrical deregulated market increases the need for short-term load forecast algorithms in order to assist electrical utilities in activities such as planning, operating and controlling electric energy systems. Methodologies based on regression methods have been widely used with satisfactory results. However, this type of approach has some shortcomings. This paper proposes a short-term load forecast methodology applied to distribution systems, based on Gaussian Process models. This methodology establishes an interesting and valuable approach to short-term forecasting applied to the electrical sector. The results obtained are in accordance with the best values of expected errors for these types of methodologies. A careful study of the input variables (regressors) was made, from the point of view of contiguous values, in order to include the strictly necessary instances of endogenous variables. Regressors representing the trend of consumption, at homologous time intervals in the past, were also included in the input vector. The proposed approach was tested on real-load from three medium-sized supply electrical distribution substations located in the center of Portugal. To test the performance of the model in different load situations, the case study includes three different electrical distribution substations representative of typical load consuming patterns,

Inesc Coimbra; João Lourenço; Paulo Santos; Lourenço J. M; Santos P. J

2010-01-01T23:59:59.000Z

363

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

SciTech Connect

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

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

2008-01-01T23:59:59.000Z

364

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

choice model for forecasting demand for alternative-fuel7511, Urban Travel Demand Forecasting Project, Institute of89 (1999) 109—129 Forecasting new product penetration with ?

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

365

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

7511, Urban Travel Demand Forecasting Project, Institute ofchoice model for forecasting demand for alternative-fuel89 (1999) 109—129 Forecasting new product penetration with

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

366

Earthquake Forecasting in Diverse Tectonic Zones of the Globe  

E-Print Network (OSTI)

Long-term probabilistic forecasting of earthquakes, J.2000), Probabilistic forecasting of earthquakes, Geophys. J.F.F. (2006), The EEPAS forecasting model and the probability

Kagan, Y. Y.; Jackson, D. D.

2010-01-01T23:59:59.000Z

367

Ensemble-based methods for forecasting census in hospital units  

E-Print Network (OSTI)

P, Fitzgerald G: Regression forecasting of patient admissionapproach to modeling and forecasting demand in the emergencySJ, Haug PJ, Snow GL: Forecasting daily patient volumes in

Koestler, Devin C; Ombao, Hernando; Bender, Jesse

2013-01-01T23:59:59.000Z

368

LOAD FORECASTING Eugene A. Feinberg  

E-Print Network (OSTI)

's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts

Feinberg, Eugene A.

369

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

370

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

371

Quantifying the Predictive Skill in Long-Range Forecasting. Part II: Model Error in Coarse-Grained Markov Models with Application to Ocean-Circulation Regimes  

Science Conference Proceedings (OSTI)

An information-theoretic framework is developed to assess the predictive skill and model error in imperfect climate models for long-range forecasting. Here, of key importance is a climate equilibrium consistency test for detecting false predictive ...

Dimitrios Giannakis; Andrew J. Majda

2012-03-01T23:59:59.000Z

372

Transition of the Coastal and Estuarine Storm Tide Model to an Operational Storm Surge Forecast Model: A Case Study of the Florida Coast  

Science Conference Proceedings (OSTI)

The operational forecast demands and constraints of the National Hurricane Center require that a storm surge model in research mode be tested against a benchmark model such as Sea, Lake, and Overland Surges from Hurricanes (SLOSH) for accuracy, ...

Keqi Zhang; Yuepeng Li; Huiqing Liu; Jamie Rhome; Cristina Forbes

2013-08-01T23:59:59.000Z

373

Coupling the ISBA Land Surface Model and the TOPMODEL Hydrological Model for Mediterranean Flash-Flood Forecasting: Description, Calibration, and Validation  

Science Conference Proceedings (OSTI)

Innovative coupling between the soil–vegetation–atmosphere transfer (SVAT) model Interactions between Soil, Biosphere, and Atmosphere (ISBA) and the hydrological model TOPMODEL has been specifically designed for flash-flood forecasting in the ...

Ludovic Bouilloud; Katia Chancibault; Béatrice Vincendon; Véronique Ducrocq; Florence Habets; Georges-Marie Saulnier; Sandrine Anquetin; Eric Martin; Joel Noilhan

2010-04-01T23:59:59.000Z

374

An Integrated Computational Model for Additive Manufacturing ...  

Science Conference Proceedings (OSTI)

As part of this integrated model, this paper describes a macroscopic thermo- mechanical modeling approach to simulate the layer-by-layer AM process to build ...

375

Adaptive Urban Dispersion Integrated Model  

DOE Green Energy (OSTI)

Numerical simulations represent a unique predictive tool for understanding the three-dimensional flow fields and associated concentration distributions from contaminant releases in complex urban settings (Britter and Hanna 2003). Utilization of the most accurate urban models, based on fully three-dimensional computational fluid dynamics (CFD) that solve the Navier-Stokes equations with incorporated turbulence models, presents many challenges. We address two in this work; first, a fast but accurate way to incorporate the complex urban terrain, buildings, and other structures to enforce proper boundary conditions in the flow solution; second, ways to achieve a level of computational efficiency that allows the models to be run in an automated fashion such that they may be used for emergency response and event reconstruction applications. We have developed a new integrated urban dispersion modeling capability based on FEM3MP (Gresho and Chan 1998, Chan and Stevens 2000), a CFD model from Lawrence Livermore National Lab. The integrated capability incorporates fast embedded boundary mesh generation for geometrically complex problems and full three-dimensional Cartesian adaptive mesh refinement (AMR). Parallel AMR and embedded boundary gridding support are provided through the SAMRAI library (Wissink et al. 2001, Hornung and Kohn 2002). Embedded boundary mesh generation has been demonstrated to be an automatic, fast, and efficient approach for problem setup. It has been used for a variety of geometrically complex applications, including urban applications (Pullen et al. 2005). The key technology we introduce in this work is the application of AMR, which allows the application of high-resolution modeling to certain important features, such as individual buildings and high-resolution terrain (including important vegetative and land-use features). It also allows the urban scale model to be readily interfaced with coarser resolution meso or regional scale models. This talk will discuss details of the approach and present results for some example calculations performed in Manhattan in support of the DHS Urban Dispersion Program (UDP) using some of the tools developed as part of this new capability.

Wissink, A; Chand, K; Kosovic, B; Chan, S; Berger, M; Chow, F K

2005-11-03T23:59:59.000Z

376

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

E-Print Network (OSTI)

The petroleum industry commonly uses single-layer models to characterize and forecast long-term production in tight gas reservoir systems. However, most tight gas reservoirs are layered systems where the permeability and porosity of each layer can vary significantly, often over several orders of magnitude. In addition, the drainage areas of each of the layers can be substantially different. Due to the complexity of such reservoirs, the analysis of pressure and production history using single-layer analyses techniques provide incorrect estimates of permeability, fracture conductivity, drainage area, and fracture half-length. These erroneous values of reservoir properties also provide the reservoir engineer with misleading values of forecasted gas recovery. The main objectives of this research project are: (1) to demonstrate the typical errors that can occur in reservoir properties when single-layer modeling methods are used to history match production data from typical layered tight gas reservoirs, and (2) to use the single-layer match to demonstrate the error that can occur when forecasting long-term gas production for such complex gas reservoirs. A finite-difference reservoir simulator was used to simulate gas production from various layered tight gas reservoirs. These synthetic production data were analyzed using single-layer models to determine reservoir properties. The estimated reservoir properties obtained from the history matches were then used to forecast ten years of cumulative gas production and to find the accuracy of gas reserves estimated for tight gas reservoirs when a single-layer model is used for the analysis. Based on the results obtained in this work, I conclude that the accuracy in reservoir properties and future gas flow rates in layered tight gas reservoirs when analyzed using a single-layer model is a function of the degree of variability in permeability within the layers and the availability of production data to be analyzed. In cases where there is an idea that the reservoir presents a large variability in ��k�, using a multi-layer model to analyze the production data will provide the reservoir engineer with more accurate estimates of long-term production recovery and reservoir properties.

Jerez Vera, Sergio Armando

2006-12-01T23:59:59.000Z

377

Business forecasting methods  

E-Print Network (OSTI)

Forecasting is a common statistical task in business, where it helps inform decisions about scheduling of production, transportation and personnel, and provides a guide to long-term strategic planning. However, business forecasting is often done poorly and is frequently confused with planning and goals. They are three different things. Forecasting is about predicting the future as accurately as possible, given all the information available including historical data and knowledge of any future events that might impact the forecasts. Goals are what you would like to happen. Goals should be linked to forecasts and plans, but this does not always occur. Too often, goals are set without any plan for how to achieve them, and no forecasts for whether they are realistic. Planning is a response to forecasts and goals. Planning involves determining the appropriate actions that are required to make your forecasts match your goals. Forecasting should be an integral part of the decision-making activities of management, as it can play an important role in many areas of a company. Modern organizations require short-, medium- and long-term forecasts, depending on the specific application.

Rob J Hyndman

2009-01-01T23:59:59.000Z

378

Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration  

SciTech Connect

The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

1992-09-01T23:59:59.000Z

379

Forecasters ’ Objectives and Strategies ?  

E-Print Network (OSTI)

This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive literature on analysts, we review the empirical evidence on strategic forecasting and illustrate how our model can be structurally estimated.

Iván Marinovic; Marco Ottaviani; Peter Norman Sørensen

2011-01-01T23:59:59.000Z

380

Numerical Forecasting of Radiation Fog. Part II: A Comparison of Model Simulation with Several Observed Fog Events  

Science Conference Proceedings (OSTI)

A 1D model adapted for forecasting the formation and development of fog, and forced with mesoscale parameters derived from a 3D limited-area model, was used to simulate three fog event observations made during the Lille 88 campaign. The model ...

Daniel Guedalia; Thierry Bergot

1994-06-01T23:59:59.000Z

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


381

Integrated Hydrogen Storage System Model  

NLE Websites -- All DOE Office Websites (Extended Search)

WSRC-TR-2007-00440, REVISION 0 WSRC-TR-2007-00440, REVISION 0 Keywords: Hydrogen Kinetics, Hydrogen Storage Vessel Metal Hydride Retention: Permanent Integrated Hydrogen Storage System Model Bruce J. Hardy November 16, 2007 Washington Savannah River Company Savannah River Site Aiken, SC 29808 Prepared for the U.S. Department of Energy Under Contract Number DEAC09-96-SR18500 DISCLAIMER This report was prepared for the United States Department of Energy under Contract No. DE-AC09-96SR18500 and is an account of work performed under that contract. Neither the United States Department of Energy, nor WSRC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for accuracy, completeness, or usefulness, of any information,

382

Objective Debiasing for Improved Forecasting of Tropical Cyclone Intensity with a Global Circulation Model  

Science Conference Proceedings (OSTI)

The damage potential of a tropical cyclone is proportional to a power (generally greater than one) of intensity, which demands high accuracy in forecasting intensity for managing this natural disaster. However, the current skill in forecasting ...

P. Goswami; S. Mallick; K. C. Gouda

2011-08-01T23:59:59.000Z

383

Spatial Forecasts of Maximum Hail Size Using Prognostic Model Soundings and HAILCAST  

Science Conference Proceedings (OSTI)

Forecasting the occurrence of hail and the maximum hail size is a challenging problem. This paper investigates the feasibility of producing maps of the forecast maximum hail size over the Canadian prairies using 12-h prognostic soundings from an ...

Julian C. Brimelow; Gerhard W. Reuter; Ron Goodson; Terrence W. Krauss

2006-04-01T23:59:59.000Z

384

Combined hydraulic and black-box models for flood forecasting in urban drainage systems  

E-Print Network (OSTI)

Abstract: Rapid urbanization and its implications for both water quality issues and floods have increased the need for modeling of urban drainage systems. Many operational models are based on deterministic solutions of hydraulic equations. Improving such models by adding a “black-box ” component to deal with any systematic structure in the residuals is proposed. In this study, a conventional deterministic stormwater drainage network model is first developed for a rapidly developing catchment using the HYDROWORKS ?now called Infoworks ? package, from Wallingford Software in the United Kingdom. However, despite the generally satisfactory results, the HYDROWORKS model tended to underestimate the flow volume. In this paper, a black-box or “systems ” model is fitted to the hydraulic urban drainage model in order to improve its overall efficiency. A study was conducted of suitable black-box models, which included the nonlinear artificial neural network model ?ANN?, and the linear time series models of Box and Jenkins in 1976. They were added to either the output ?in simulation mode ? or, in updating mode, to the residuals ?i.e., difference between modeled and measured output ? of the deterministic hydraulic model. The updating procedure provided a considerable improvement in the overall model efficiency for different lead-time forecasting. In simulation mode, however, only the nonlinear ANN model gave better performance in calibration, and a slight improvement in validation.

Michael Bruen; M. Asce; Jianqing Yang

2006-01-01T23:59:59.000Z

385

What Is the True Value of Forecasts?  

Science Conference Proceedings (OSTI)

Understanding the economic value of weather and climate forecasts is of tremendous practical importance. Traditional models that have attempted to gauge forecast value have focused on a best-case scenario, in which forecast users are assumed to ...

Antony Millner

2009-10-01T23:59:59.000Z

386

Whither the Weather Analysis and Forecasting Process?  

Science Conference Proceedings (OSTI)

An argument is made that if human forecasters are to continue to maintain a skill advantage over steadily improving model and guidance forecasts, then ways have to be found to prevent the deterioration of forecaster skills through disuse. The ...

Lance F. Bosart

2003-06-01T23:59:59.000Z

387

Calibration of Probabilistic Forecasts of Binary Events  

Science Conference Proceedings (OSTI)

Probabilistic forecasts of atmospheric variables are often given as relative frequencies obtained from ensembles of deterministic forecasts. The detrimental effects of imperfect models and initial conditions on the quality of such forecasts can ...

Cristina Primo; Christopher A. T. Ferro; Ian T. Jolliffe; David B. Stephenson

2009-03-01T23:59:59.000Z

388

Forecasting women's apparel sales using mathematical  

E-Print Network (OSTI)

Forecasting women's apparel sales using mathematical modeling Celia Frank and Ashish Garg, USA Les Sztandera Philadelphia University, Philadelphia, PA, USA Keywords Apparel, Forecasting average (MA), auto- regression (AR), or combinations of them are used for forecasting sales. Since

Raheja, Amar

389

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Conference Proceedings (OSTI)

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

Thomas J. Galarneau Jr.; Christopher A. Davis

2013-02-01T23:59:59.000Z

390

A Comparative Verification of Localized Aviation Model Output Statistics Program (LAMP) and Numerical Weather Prediction (NWP) Model Forecasts of Ceiling Height and Visibility  

Science Conference Proceedings (OSTI)

In an effort to support aviation forecasting, the National Weather Service’s Meteorological Development Laboratory (MDL) has recently redeveloped the Localized Aviation Model Output Statistics (MOS) Program (LAMP) system. LAMP is designed to run ...

David E. Rudack; Judy E. Ghirardelli

2010-08-01T23:59:59.000Z

391

An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting  

Science Conference Proceedings (OSTI)

Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the ... Keywords: Bayesian model selection, Bayesian neural networks, Input selection, Load forecasting

Henrique S. Hippert; James W. Taylor

2010-04-01T23:59:59.000Z

392

INTEGRATED HYDROGEN STORAGE SYSTEM MODEL  

DOE Green Energy (OSTI)

Hydrogen storage is recognized as a key technical hurdle that must be overcome for the realization of hydrogen powered vehicles. Metal hydrides and their doped variants have shown great promise as a storage material and significant advances have been made with this technology. In any practical storage system the rate of H2 uptake will be governed by all processes that affect the rate of mass transport through the bed and into the particles. These coupled processes include heat and mass transfer as well as chemical kinetics and equilibrium. However, with few exceptions, studies of metal hydrides have focused primarily on fundamental properties associated with hydrogen storage capacity and kinetics. A full understanding of the complex interplay of physical processes that occur during the charging and discharging of a practical storage system requires models that integrate the salient phenomena. For example, in the case of sodium alanate, the size of NaAlH4 crystals is on the order of 300nm and the size of polycrystalline particles may be approximately 10 times larger ({approx}3,000nm). For the bed volume to be as small as possible, it is necessary to densely pack the hydride particles. Even so, in packed beds composed of NaAlH{sub 4} particles alone, it has been observed that the void fraction is still approximately 50-60%. Because of the large void fraction and particle to particle thermal contact resistance, the thermal conductivity of the hydride is very low, on the order of 0.2 W/m-{sup o}C, Gross, Majzoub, Thomas and Sandrock [2002]. The chemical reaction for hydrogen loading is exothermic. Based on the data in Gross [2003], on the order of 10{sup 8}J of heat of is released for the uptake of 5 kg of H{sub 2}2 and complete conversion of NaH to NaAlH{sub 4}. Since the hydride reaction transitions from hydrogen loading to discharge at elevated temperatures, it is essential to control the temperature of the bed. However, the low thermal conductivity of the hydride makes it difficult to remove the heat of reaction, especially in the relatively short target refueling times, see Attachment 3. This document describes a detailed numerical model for general metal hydride beds that couples reaction kinetics with heat and mass transfer, for both hydriding and dehydriding of the bed. The detailed model is part of a comprehensive methodology for the design, evaluation and modification of hydrogen storage systems. In Hardy [2007], scoping models for reaction kinetics, bed geometry and heat removal parameters are discussed. The scoping models are used to perform a quick assessment of storage systems and identify those which have the potential to meet DOE performance targets. The operational characteristics of successful candidate systems are then evaluated with the more detailed models discussed in this document. The detailed analysis for hydrogen storage systems is modeled in either 2 or 3-dimensions, via the general purpose finite element solver COMSOL Multiphysics{reg_sign}. The two-dimensional model serves to provide rapid evaluation of bed configurations and physical processes, while the three-dimensional model, which requires a much longer run time, is used to investigate detailed effects that do not readily lend themselves to two-dimensional representations. The model is general and can be adapted to any geometry or storage media. In this document, the model is applied to a modified cylindrical shell and tube geometry with radial fins perpendicular to the axis, see Figures 4.1-1 and 4.1-2. Sodium alanate, NaAlH{sub 4}, is used as the hydrogen storage medium. The model can be run on any DOS, LINUX or Unix based system.

Hardy, B

2007-11-16T23:59:59.000Z

393

Precipitation Forecasting Using Doppler Radar Data, a Cloud Model with Adjoint, and the Weather Research and Forecasting Model: Real Case Studies during SoWMEX in Taiwan  

Science Conference Proceedings (OSTI)

The quantitative precipitation forecast (QPF) capability of the Variational Doppler Radar Analysis System (VDRAS) is investigated in the Taiwan area, where the complex topography and surrounding oceans pose great challenges to accurate rainfall ...

Sheng-Lun Tai; Yu-Chieng Liou; Juanzhen Sun; Shao-Fan Chang; Min-Chao Kuo

2011-12-01T23:59:59.000Z

394

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

Science Conference Proceedings (OSTI)

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.

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.

2012-06-01T23:59:59.000Z

395

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

Science Conference Proceedings (OSTI)

This study examines 2–3-day solar irradiance forecasts with respect to their application in solar energy industries, such as yield prediction for the integration of the strongly fluctuating solar energy into the electricity grid. During cloud-...

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

2009-09-01T23:59:59.000Z

396

NREL: Technology Deployment - Integrated Deployment Model  

NLE Websites -- All DOE Office Websites (Extended Search)

Integrated Deployment Model Integrated Deployment Model NREL's integrated deployment model provides a framework to focus on the national goal of accelerating market adoption of clean energy technologies through local efforts. With support from the U.S. Department of Energy (DOE), NREL developed and applies the integrated deployment model to select projects including disaster recovery, statewide activities, federal agency support, island activities, and community renewable energy deployment. How the Model Works To address the complex challenges of multi-technology, multi-stakeholder, and multi-fuel deployment, NREL created the integrated deployment model to support each technology area separately but also consider the integration points between the technologies. NREL also identifies the cross-cutting

397

Verification of Precipitation Forecasts from NCEP’s Short-Range Ensemble Forecast (SREF) System with Reference to Ensemble Streamflow Prediction Using Lumped Hydrologic Models  

Science Conference Proceedings (OSTI)

Precipitation forecasts from the Short-Range Ensemble Forecast (SREF) system of the National Centers for Environmental Prediction (NCEP) are verified for the period April 2006–August 2010. Verification is conducted for 10–20 hydrologic basins in ...

James D. Brown; Dong-Jun Seo; Jun Du

2012-06-01T23:59:59.000Z

398

The role of ICTs in downscaling and up-scaling integrated weather forecasts for farmers in sub-Saharan Africa  

Science Conference Proceedings (OSTI)

Despite global advancements in technology and inter-trade volumes, Sub-Saharan Africa is the only Region where cases of hunger have increased since 1990. Rampant and frequent droughts are one of the major causes of this. Monumental and mostly donor-funded ... Keywords: Nganyi clan of western Kenya, indigenous knowledge weather forecasts, seasonal climate forecasts, sub-Saharan Africa, wireless sensor networks

Muthoni Masinde; Antoine Bagula; Nzioka J. Muthama

2012-03-01T23:59:59.000Z

399

Innovative approaches to integrated global change modelling  

Science Conference Proceedings (OSTI)

Integrated models are important tools to investigate the interactions between planetary processes and the growing impacts of human populations - in short: global change. Current models still have significant shortcomings, notably in their representation ... Keywords: Global change, Innovative approaches, Integrated assessment, Modelling, Research priorities

Carlo Giupponi, Mark E. Borsuk, Bert J. M. De Vries, Klaus Hasselmann

2013-06-01T23:59:59.000Z

400

Implementation of the Semi-Lagrangian Method in a High-Resolution Version of the ECMWF Forecast Model  

Science Conference Proceedings (OSTI)

In this article the implementation of the semi-Lagrangian method in a high-resolution version of the ECMWF forecast model is examined. Novel aspects include the application of the semi-Lagrangian scheme to a global model using the ECMWF hybrid ...

Harold Ritchie; Clive Temperton; Adrian Simmons; Mariano Hortal; Terry Davies; David Dent; Mats Hamrud

1995-02-01T23:59:59.000Z

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


401

A review of agent-based models for forecasting the deployment of distributed generation in energy systems  

Science Conference Proceedings (OSTI)

Agent-based models are seeing increasing use in the study of distributed generation (DG) deployment. Researchers and decision makers involved in the implementation of DG have been lacking a concise overview of why they should consider using agent-based ... Keywords: agent-based modeling, consumer behavior, distributed generation, energy forecasting, product deployment

Jason G. Veneman; M. A. Oey; L. J. Kortmann; F. M. Brazier; L. J. de Vries

2011-06-01T23:59:59.000Z

402

Integrated Chemical, Thermal, Mechanical and Hydrological Modeling...  

Open Energy Info (EERE)

489,476 1,602,500 Retrieved from "http:en.openei.orgwindex.php?titleIntegratedChemical,Thermal,MechanicalandHydrologicalModeling&oldid313283" Category:...

403

Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

We have shown that it is possible to predict the skill of numerical weather forecasts—a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average ...

Eugenia Kalnay; Amnon Dalcher

1987-02-01T23:59:59.000Z

404

Space, time and nesting Integrated Assessment Models  

Science Conference Proceedings (OSTI)

Integrated Assessment Modelling in the field of air pollution has advanced greatly since the 1985 Helsinki Protocol on the reduction of Sulphur emissions and their transboundary fluxes. With subsequent protocols and increased understanding of the inter-relationships ... Keywords: CLRTAP, Integrated Assessment Modelling, Scale, Science-policy interaction, Space, Time

T. Oxley; H. M. ApSimon

2007-12-01T23:59:59.000Z

405

Characterization of Weekly Cumulative Rainfall Forecasts over Meteorological Subdivisions of India Using a GCM  

Science Conference Proceedings (OSTI)

Weekly cumulative rainfall forecasts were made for the meteorologically homogeneous areas of the Indian subcontinent, divided into meteorological subdivisions, by performing 7-day integrations of the operational Indian T80 Global Spectral Model ...

S. A. Saseendran; S. V. Singh; L. S. Rathore; Someshwar Das

2002-08-01T23:59:59.000Z

406

The Impact of El Niño on an Ensemble of Extended-Range Forecasts  

Science Conference Proceedings (OSTI)

Two ensembles of 90-day forecasts for 1982–83 have been made with the UK Meteorological Office 11-layer atmospheric general circulation model. Each ensemble comprised three integrations initialized one day apart, using analyses from December ...

J. A. Owen; T. N. Palmer

1987-09-01T23:59:59.000Z

407

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

SciTech Connect

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

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

2008-04-01T23:59:59.000Z

408

Repetitive Decision Making and the Value of Forecasts in the Cost?Loss Ratio Situation: A Dynamic Model  

Science Conference Proceedings (OSTI)

The purposes of this paper are to describe a dynamic model for repetitive decision?making in the cost–loss ratio situation and to present some theoretical and numerical results related to the optimal use and economic value of weather forecasts ...

Allan H. Murphy; Richard W. Katz; Robert L. Winkler; Wu-Ron Hsu

1985-05-01T23:59:59.000Z

409

Quantifying the Predictive Skill in Long-Range Forecasting. Part I: Coarse-Grained Predictions in a Simple Ocean Model  

Science Conference Proceedings (OSTI)

An information-theoretic framework is developed to assess the long-range coarse-grained predictive skill in a perfect-model environment. Central to the scheme is the notion that long-range forecasting involves regimes; specifically, that the ...

Dimitrios Giannakis; Andrew J. Majda

2012-03-01T23:59:59.000Z

410

INTEGRATED FISCHER TROPSCH MODULAR PROCESS MODEL  

Science Conference Proceedings (OSTI)

With declining petroleum reserves, increased world demand, and unstable politics in some of the world’s richest oil producing regions, the capability for the U.S. to produce synthetic liquid fuels from domestic resources is critical to national security and economic stability. Coal, biomass and other carbonaceous materials can be converted to liquid fuels using several conversion processes. The leading candidate for large-scale conversion of coal to liquid fuels is the Fischer Tropsch (FT) process. Process configuration, component selection, and performance are interrelated and dependent on feed characteristics. This paper outlines a flexible modular approach to model an integrated FT process that utilizes a library of key component models, supporting kinetic data and materials and transport properties allowing rapid development of custom integrated plant models. The modular construction will permit rapid assessment of alternative designs and feed stocks. The modeling approach consists of three thrust areas, or “strands” – model/module development, integration of the model elements into an end to end integrated system model, and utilization of the model for plant design. Strand 1, model/module development, entails identifying, developing, and assembling a library of codes, user blocks, and data for FT process unit operations for a custom feedstock and plant description. Strand 2, integration development, provides the framework for linking these component and subsystem models to form an integrated FT plant simulation. Strand 3, plant design, includes testing and validation of the comprehensive model and performing design evaluation analyses.

Donna Post Guillen; Richard Boardman; Anastasia M. Gribik; Rick A. Wood; Robert A. Carrington

2007-12-01T23:59:59.000Z

411

How Do You Like Your Weather?: Using Weather Forecast Data to Improve Short-Term Load Forecasts  

Science Conference Proceedings (OSTI)

This document provides a quick overview of weather forecasts as a data issue in the development of electricity demand forecasts. These are three sections in this Brief: o reasons behind the rise in interest in using weather forecasts in electricity forecasting models, o an overview of what some utilities are doing to evaluate weather forecasts, and o a resource list of weather forecast providers.

2001-09-28T23:59:59.000Z

412

NREL: Vehicle Ancillary Loads Reduction - Integrated Modeling  

NLE Websites -- All DOE Office Websites (Extended Search)

Integrated Modeling Integrated Modeling NREL's Vehicle Ancillary Loads Reduction (VALR) team predicts the impact of advanced vehicle cooling technologies before testing by using an integrated modeling process. Evaluating the heat load on a vehicle under real world conditions is a difficult task. An accepted method to evaluate passenger compartment airflow and heat transfer is computational fluid dynamics. (CFD). Combining analytical models with CFD provides a powerful tool to assist industry both on current vehicles and on future design studies. Flow chart showing the vehicle integrated modeling process which considers solar radiation, air conditioning, and vehicles with CAD, glazing, cabin thermal/fluid, and thermal comfort modeling tools. Results are provided for fuel economy, tailpipe emissions and occupant thermal comfort.

413

Legacy model integration with repast simphony.  

SciTech Connect

Repast is a widely used, free, and open-source, agent-based modeling and simulation toolkit. Three Repast version 3 platforms are currently available, each of which has the same core features but with differing environments for these features. Repast Simphony (Repast S) extends the Repast 3 portfolio by offering a new approach to simulation development and execution. Repast S's new simulation development capabilities include direct support for integrating existing (i.e., legacy) file-based models into agent-based simulations. This paper reviews related work on model integration and data exchange; introduces the Repast S's legacy model integration system; and discusses how the new system can be used to integrate existing file-based models, either agent-based or nonagent-based, into agent models.

North, M. J.; Sydelko, P. J.; Vos, J. R.; Howe, T. R.; Collier, N. T.; Decision and Information Sciences; Univ. of Chicago; Univ. of Illinois; PantaRei Corp.

2006-01-01T23:59:59.000Z

414

A comparison of cloud microphysical quantities with forecasts from cloud prediction models  

SciTech Connect

Numerical weather prediction models (ECMWF, NCEP) are evaluated using ARM observational data collected at the Southern Great Plains (SGP) site. Cloud forecasts generated by the models are compared with cloud microphysical quantities, retrieved using a variety of parameterizations. Information gained from this comparison will be utilized during the FASTER project, as models are evaluated for their ability to reproduce fast physical processes detected in the observations. Here the model performance is quantified against the observations through a statistical analysis. Observations from remote sensing instruments (radar, lidar, radiometer and radiosonde) are used to derive the cloud microphysical quantities: ice water content, liquid water content, ice effective radius and liquid effective radius. Unfortunately, discrepancies in the derived quantities arise when different retrieval schemes are applied to the observations. The uncertainty inherent in retrieving the microphysical quantities using various retrievals is estimated from the range of output microphysical values. ARM microphysical retrieval schemes (Microbase, Mace) are examined along with the CloudNet retrieval processing of data from the ARM sites for this purpose. Through the interfacing of CloudNet and “ARM” processing schemes an ARMNET product is produced and employed as accepted observations in the assessment of cloud model predictions.

Dunn, M.; Jensen, M.; Hogan, R.; O’Connor, E.; Huang, D.

2010-03-15T23:59:59.000Z

415

Forecasting overview  

E-Print Network (OSTI)

Forecasting is required in many situations: deciding whether to build another power generation plant in the next five years requires forecasts of future demand; scheduling staff in a call centre next week requires forecasts of call volume; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. Some things are easier to forecast than others. The time of the sunrise tomorrow morning can be forecast very precisely. On the other hand, currency exchange rates are very difficult to forecast with any accuracy. The predictability of an event or a quantity depends on how well we understand the factors that contribute to it, and how much unexplained variability is involved. Forecasting situations vary widely in their time horizons, factors determining actual outcomes, types of data patterns, and many other aspects. Forecasting methods can be very simple such as using the most recent observation as a forecast (which is called the “naïve method”), or highly complex such as neural nets and econometric systems of simultaneous equations. The

Rob J Hyndman

2009-01-01T23:59:59.000Z

416

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

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

2005-07-01T23:59:59.000Z

417

Conceptual Modeling for Data Integration  

Science Conference Proceedings (OSTI)

The goal of data integration is to provide a uniform access to a set of heterogeneous data sources, freeing the user from the knowledge about where the data are, how they are stored, and how they can be accessed. One of the outcomes of the research work ...

Diego Calvanese; Giuseppe Giacomo; Domenico Lembo; Maurizio Lenzerini; Riccardo Rosati

2009-07-01T23:59:59.000Z

418

Short-term wind speed forecasting based on a hybrid model  

Science Conference Proceedings (OSTI)

Wind power is currently one of the types of renewable energy with a large generation capacity. However, operation of wind power generation is very challenging because of the intermittent and stochastic nature of the wind speed. Wind speed forecasting ... Keywords: Forecasting, RBF neural networks, Seasonal adjustment, Wavelet transform, Wind speed

Wenyu Zhang, Jujie Wang, Jianzhou Wang, Zengbao Zhao, Meng Tian

2013-07-01T23:59:59.000Z

419

Context-aware parameter estimation for forecast models in the energy domain  

Science Conference Proceedings (OSTI)

Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability and efficiency of energy grids. This balancing task requires accurate forecasts of future electricity consumption and production at any point in time. For ... Keywords: energy, forecasting, maintenance, parameter estimation

Lars Dannecker; Robert Schulze; Matthias Böhm; Wolfgang Lehner; Gregor Hackenbroich

2011-07-01T23:59:59.000Z

420

Revenue forecasting using a least-squares support vector regression model in a fuzzy environment  

Science Conference Proceedings (OSTI)

Revenue forecasting is difficult but essential for companies that want to create high-quality revenue budgets, especially in an uncertain economic environment with changing government policies. Under these conditions, the subjective judgment of decision ... Keywords: Genetic algorithms, Least-squares support vector regression, Membership function, Revenue forecasting

Kuo-Ping Lin; Ping-Feng Pai; Yu-Ming Lu; Ping-Teng Chang

2013-01-01T23:59:59.000Z

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


421

Time Series Models Adoptable for Forecasting Nile Floods and Ethiopian Rainfalls  

Science Conference Proceedings (OSTI)

Long-term rainfall forecasting is used in making economic and agricultural decisions in many countries. It may also be a tool in minimizing the devastation resulting from recurrent droughts. To be able to forecast the total annual rainfall or the ...

M. G. El-Fandy; S. M. M. Taiel; Z. H. Ashour

1994-01-01T23:59:59.000Z

422

ANN-based residential water end-use demand forecasting model  

Science Conference Proceedings (OSTI)

Bottom-up urban water demand forecasting based on empirical data for individual water end uses or micro-components (e.g., toilet, shower, etc.) for different households of varying characteristics is undoubtedly superior to top-down estimates originating ... Keywords: Artificial neural network, Residential water demand forecasting, Water demand management, Water end use, Water micro-component

Christopher Bennett; Rodney A. Stewart; Cara D. Beal

2013-03-01T23:59:59.000Z

423

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

424

Perspectives of Integrated Modeling at NERSC  

NLE Websites -- All DOE Office Websites (Extended Search)

on Integrated Whole-Device Modeling on Integrated Whole-Device Modeling at NERSC Alexei Y. Pankin 1 , Arnold H. Kritz 2 , and Tariq Rafiq 2 1 Tech-X Corporation, Boulder, CO 2 Lehigh University, Bethlehem, PA Integrated Whole-Device Modeling of Tokamak Plasmas Studies in isolation of elements that describe plasma behavior (plasma heating, MHD equilibria, large scale instabilities, core and edge transport ...) * Do not capture interactive nature of physics described in whole-device integrated modeling simulations  It is important that we understand effects that result from interactions between various physical processes in tokamak plasmas Predictive whole-device modeling helps avoid costly design mistakes * Facilitates the optimization and control of experimental scenarios in order to make the most effective use of expensive experiments

425

Testing the Effects of a New Land Surface Scheme and of Initial Soil Moisture Conditions in the Canadian Global Forecast Model  

Science Conference Proceedings (OSTI)

A new land surface scheme developed for the Canadian general circulation model has been introduced into the Canadian global forecast model and tested for a summer case. It features three soil layers, a snow layer, and a vegetation layer; its ...

Yves Delage; Diana Verseghy

1995-11-01T23:59:59.000Z

426

Integrated Computational Modeling of Welding – Development to ...  

Science Conference Proceedings (OSTI)

Integrated computational modeling is considered as a viable pathway to ... lack of a standard verification and validation (V&V) documents to build a technical case. ... Evolution with the Impact of Anisotropic Grain Boundary Energy and Mobility.

427

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human-environment interactions: A drought example in Central Pennsylvania, USA  

Science Conference Proceedings (OSTI)

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through ... Keywords: Decision support, Drought, GeoAgent, Geographic information systems (GIS), Hazard management, Knowledge representation, Modeling

Chaoqing Yu; Alan M. MacEachren; Donna J. Peuquet; Brent Yarnal

2009-12-01T23:59:59.000Z

428

Integration of EBS Models with Generic Disposal System Models | Department  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal system model (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

429

Integration of EBS Models with Generic Disposal System Models | Department  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal system model (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

430

Integrated Modeling of Microbial Ecology  

NLE Websites -- All DOE Office Websites (Extended Search)

Modeling of Microbial Ecology in Subsurface Environments Speaker: Dr. Krishna Mahadevan Department of Chemical Engineering and Applied Chemistry University of Toronto Date:...

431

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

432

Implementing Innovation in Planning Practice: The Case of Travel Demand Forecasting  

E-Print Network (OSTI)

Urban Travel Demand Forecasting Project. Institute ofTRB. Metropolitan Travel Forecasting: Current Practice andPurvis. Regional Travel Forecasting Model System for the San

Newmark, Gregory Louis

2011-01-01T23:59:59.000Z

433

Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets  

SciTech Connect

The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

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

2005-06-30T23:59:59.000Z

434

Downscaling Extended Weather Forecasts for Hydrologic Prediction  

SciTech Connect

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.

Leung, Lai-Yung R.; Qian, Yun

2005-03-01T23:59:59.000Z

435

General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products  

Science Conference Proceedings (OSTI)

General Electric (GE) Energy's nascent solar business has revenues of over $100 million, expects those revenues to grow to over $1 billion in the next three years, and has plans to rapidly grow the business beyond this period. GE Global Research (GEGR), ... Keywords: capital budgeting, cost analysis, facilities planning, forecasting, mathematical programming, risk

Bex George Thomas; Srinivas Bollapragada

2010-09-01T23:59:59.000Z

436

Chapter 11 Forecasting breaks and forecasting during breaks  

E-Print Network (OSTI)

Success in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break. To clarify the roles of these six necessary conditions, we distinguish between the information set for ‘normal forces ’ and the one for ‘break drivers’, then outline sources of potential information. Relevant non-linear, dynamic models facing multiple breaks can have more candidate variables than observations, so we discuss automatic model selection. As a failure to accurately forecast breaks remains likely, we augment our strategy by modelling breaks during their progress, and consider robust forecasting devices.

Jennifer L. Castle; Nicholas W. P. Fawcett; David F. Hendry

2011-01-01T23:59:59.000Z

437

The Description of the Navy Operational Global Atmospheric Prediction System's Spectral Forecast Model  

Science Conference Proceedings (OSTI)

We present a description of the development of the spectral forecast components of the Navy Operational Global Atmospheric Prediction System (NOGAPS). The original system, called 3.0, was introduced in January 1988. New versions were introduced ...

Timothy F. Hogan; Thomas E. Rosmond

1991-08-01T23:59:59.000Z

438

Incorporating Hurricane Forecast Uncertainty into a Decision Support Application for Power Outage Modeling  

Science Conference Proceedings (OSTI)

A variety of decision-support systems, such as those employed by energy and utility companies, use the National Hurricane Center (NHC) forecasts of track and intensity to inform operational decision-making as a hurricane approaches. Track and intensity ...

Steven M. Quiring; Andrea B. Schumacher; Seth D. Guikema

439

Ensemble Forecasting of Tropical Cyclone Motion Using a Barotropic Model. Part II: Perturbations of the Vortex  

Science Conference Proceedings (OSTI)

In Part I of this study, the technique of ensemble forecasting is applied to the problem of tropical cyclone motion prediction by perturbing the environmental flow. In this part, the focus is shifted to perturbation of the vortex structure. The ...

Kevin K. W. Cheung; Johnny C. L. Chan

1999-11-01T23:59:59.000Z

440

Real-Time Forecasting of the Western Australian Summertime Trough: Evaluation of a New Regional Model  

Science Conference Proceedings (OSTI)

The real-time prediction of the location, strength, and structure of the summertime heat trough is a major forecasting problem over Western Australia. Maximum temperatures, wind strength and direction along the west coast, low-level coastal cloud,...

Lance M. Leslie; Terry C. L. Skinner

1994-09-01T23:59:59.000Z

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


441

Historical Developments Leading to Current Forecast Models of Annual Atlantic Hurricane Activity  

Science Conference Proceedings (OSTI)

There is considerable interest in forecasting interannual hurricane activity for the Atlantic basin. Various predictors representing different components of the tropical Atlantic climate have been suggested. The choice of predictors is based on ...

J. C. Hess; J. B. Elsner

1994-09-01T23:59:59.000Z

442

An Analysis of NCEP Tropical Cyclone Vitals and Potential Effects on Forecasting Models  

Science Conference Proceedings (OSTI)

This study analyzes the Tropical Cyclone Vitals Database (TCVitals), which contains cyclone location, intensity, and structure information, generated in real time by forecasters. These data are used to initialize cyclones in several NCEP ...

Sam Trahan; Lynn Sparling

2012-06-01T23:59:59.000Z

443

Lower-Tropospheric Enhancement of Gravity Wave Drag in a Global Spectral Atmospheric Forecast Model  

Science Conference Proceedings (OSTI)

The impacts of enhanced lower-tropospheric gravity wave drag induced by subgrid-scale orography on short- and medium-range forecasts as well as seasonal simulations are examined. This study reports on the enhanced performance of the scheme ...

Song-You Hong; Jung Choi; Eun-Chul Chang; Hoon Park; Young-Joon Kim

2008-06-01T23:59:59.000Z

444

Distributed Quantitative Precipitation Forecasting Using Information from Radar and Numerical Weather Prediction Models  

Science Conference Proceedings (OSTI)

The benefits of short-term (1–6 h), distributed quantitative precipitation forecasts (DQPFs) are well known. However, this area is acknowledged to be one of the most challenging in hydrometeorology. Previous studies suggest that the “state of the ...

Auroop R. Ganguly; Rafael L. Bras

2003-12-01T23:59:59.000Z

445

Generalized Linear Models for Site-Specific Density Forecasting of U.K. Daily Rainfall  

Science Conference Proceedings (OSTI)

Site-specific probability density rainfall forecasts are needed to price insurance premiums, contracts, and other financial products based on precipitation. The spatiotemporal correlations in U.K. daily rainfall amounts over the Thames Valley are ...

Max A. Little; Patrick E. McSharry; James W. Taylor

2009-03-01T23:59:59.000Z

446

Fuzzy-neural model with hybrid market indicators for stock forecasting  

Science Conference Proceedings (OSTI)

A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market ...

A. A. Adebiyi; C. K. Ayo; S. O. Otokiti

2011-07-01T23:59:59.000Z

447

Development of a Statistical Model for Forecasting Episodes of Visibility Degradation in the Denver Metropolitan Area  

Science Conference Proceedings (OSTI)

In 1990, the State of Colorado implemented a visibility standard of 0.076 km?1 of beta extinction for the Denver metropolitan area. Meteorologists with Colorado's Air Pollution Control Division forecast high pollution days associated with ...

P. J. Reddy; D. E. Barbarick; R. D. Osterburg

1995-03-01T23:59:59.000Z

448

Statistical Model for Forecasting Monthly Large Wildfire Events in Western United States  

Science Conference Proceedings (OSTI)

The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes ...

Haiganoush K. Preisler; Anthony L. Westerling

2007-07-01T23:59:59.000Z

449

Improvement of Long-Range Forecasting by EEOF Extrapolation Using an AR-MEM Model  

Science Conference Proceedings (OSTI)

This paper presents an optimum combination of two robust statistical techniques that can be used to improve the skill of long-range weather forecasts. The first method uses decomposition and analysis based on extended empirical orthogonal ...

C. Mares and Ileana Mares

2003-04-01T23:59:59.000Z

450

NeuroInflow: The New Model to Forecast Average Monthly Inflow  

Science Conference Proceedings (OSTI)

In utilities using a mixture of hydroelectric and non-hydroelectricpower, the economics of the hydroelectricplants depend upon the reservoir height and the inflowinto the reservoir for several months into the future.Accurate forecasts of reservoir inflow ...

Mêuser Valença; Teresa Ludermir

2002-11-01T23:59:59.000Z

451

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

452

Representing Serial Correlation of Meteorological Events and Forecasts in Dynamic Decision–Analytic Models  

Science Conference Proceedings (OSTI)

A recursive solution for optimal sequences of decisions given uncertainty in future weather events, and forecasts of those events, is presented. The formulation incorporates a representation of the autocorrelation that is typically exhibited. The ...

Daniel S. Wilks

1991-07-01T23:59:59.000Z

453

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

Science Conference Proceedings (OSTI)

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

Samuel Rémy; Thierry Bergot

2010-05-01T23:59:59.000Z

454

Potential Impacts of the Saharan Air Layer on Numerical Model Forecasts of North Atlantic Tropical Cyclogenesis  

Science Conference Proceedings (OSTI)

Tropical cyclones have devastating impacts on countries across large parts of the globe, including the Atlantic basin. Thus, forecasting of the genesis of Atlantic tropical cyclones is important, but this problem remains a challenge for ...

Aaron S. Pratt; Jenni L. Evans

2009-04-01T23:59:59.000Z

455

Forecasting during the Lake-ICE/SNOWBANDS Field Experiments  

Science Conference Proceedings (OSTI)

Despite improvements in numerical weather prediction models, statistical models, forecast decision trees, and forecasting rules of thumb, human interpretation of meteorological information for a particular forecast situation can still yield a ...

Peter J. Sousounis; Greg E. Mann; George S. Young; Richard B. Wagenmaker; Bradley D. Hoggatt; William J. Badini

1999-12-01T23:59:59.000Z

456

Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint  

DOE Green Energy (OSTI)

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.

Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

2012-09-01T23:59:59.000Z

457

Cash Flow Forecasting Model for General Contractors Using Moving Weights of Cost Categories  

E-Print Network (OSTI)

. Navon's model 1995, 1997 automatically in- tegrates the bill of quantity BOQ , cost estimate. Moreover, the main obstacle to automating the integration process is compatibility between cost items, and equipment which are specified as percentages of total cost. This approach is very realistic because

Sheridan, Jennifer

458

Transition and Equilibration of Neutral Atmospheric Boundary Layer Flow in One-Way Nested Large-Eddy Simulations Using the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting Model permits finescale large-eddy simulations (LES) to be nested within coarser simulations, an approach that can generate more accurate turbulence statistics and improve other aspects of simulated flows. ...

Jeff Mirocha; Gokhan Kirkil; Elie Bou-Zeid; Fotini Katopodes Chow; Branko Kosovi?

2013-03-01T23:59:59.000Z

459

Diagnosing the Relative Impact of “Sneaks,” “Phantoms,” and Volatility in Sequences of Lagged Ensemble Probability Forecasts with a Simple Dynamic Decision Model  

Science Conference Proceedings (OSTI)

Monte Carlo simulation of sequences of lagged ensemble probability forecasts is undertaken using Markov transition law estimated from a reforecast ensemble. A simple three-state, three-action dynamic decision model is then applied to the Monte ...

Justin G. McLay

2011-02-01T23:59:59.000Z

460

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

SciTech Connect

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

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

2008-01-01T23:59:59.000Z

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


461

Modeling for System Integration Studies (Presentation)  

SciTech Connect

This presentation describes some the data requirements needed for grid integration modeling and provides real-world examples of such data and its format. Renewable energy integration studies evaluate the operational impacts of variable generation. Transmission planning studies investigate where new transmission is needed to transfer energy from generation sources to load centers. Both use time-synchronized wind and solar energy production and load as inputs. Both examine high renewable energy penetration scenarios in the future.

Orwig, K. D.

2012-05-01T23:59:59.000Z

462

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

463

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

E-Print Network (OSTI)

Currently, effective reservoir management systems play a very important part in exploiting reservoirs. Fully exploiting all the possible events for a petroleum reservoir is a challenge because of the infinite combinations of reservoir parameters. There is much unknown about the underlying reservoir model, which has many uncertain parameters. MCMC (Markov Chain Monte Carlo) is a more statistically rigorous sampling method, with a stronger theoretical base than other methods. The performance of the MCMC method on a high dimensional problem is a timely topic in the statistics field. This thesis suggests a way to quantify uncertainty for high dimensional problems by using the MCMC sampling process under the Bayesian frame. Based on the improved method, this thesis reports a new approach in the use of the continuous MCMC method for automatic history matching. The assimilation of the data in a continuous process is done sequentially rather than simultaneously. In addition, by doing a continuous process, the MCMC method becomes more applicable for the industry. Long periods of time to run just one realization will no longer be a big problem during the sampling process. In addition, newly observed data will be considered once it is available, leading to a 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 forecasts of well and reservoir performance, accessible at any time. It can be used to optimize long-term reservoir performance at field scale.

Liu, Chang

2008-12-01T23:59:59.000Z

464

Assimilation of Screen-Level Variables in ECMWF’s Integrated Forecast System: A Study on the Impact on the Forecast Quality and Analyzed Soil Moisture  

Science Conference Proceedings (OSTI)

In many operational numerical weather prediction applications, the soil moisture analysis is based on the modeled first-guess and screen-level variables; that is, 2-m temperature and 2-m relative humidity. A set of two global 61-day analysis/...

Matthias Drusch; Pedro Viterbo

2007-02-01T23:59:59.000Z

465

The Influence of Variations in Surface Treatment on 24-Hour Forecasts with a Limited Area Model, Including a Comparison of Modeled and Satellite-Measured Surface Temperatures  

Science Conference Proceedings (OSTI)

The effect of variations in surface parameters on 24-hour limited area forecasts has been examined on a day in July 1981. The vehicle for the study is a ten-level primitive equation model covering most of the continental United States. Variations ...

George Diak; Stacey Heikkinen; John Rates

1986-01-01T23:59:59.000Z

466

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

467

FROM ANALYSTS ' EARNINGS FORECASTS  

E-Print Network (OSTI)

We examine the accuracy and bias of intrinsic equity prices estimated from three accounting-based valuation models using analyst’s earnings forecasts over a four-year horizon. The models are: (a) the earnings capitalization model, (b) the residual income model without a terminal value, and (c) the residual income model with a terminal value that assumes residual income will grow beyond the horizon at a constant rate determined from the expected residual income growth rate over the forecast horizon. Our analysis is based on valuation errors that are calculated by comparing estimated prices to actual prices. We contribute to the literature by examining whether: (i) the analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book value and dividends, (ii) the use of firm specific growth rates in terminal value calculations results in more unbiased and accurate valuations than the use of constant growth rates, and (iii) different models perform better under different ex-ante conditions. We find that analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Each of the models that we used has valuation errors that decline monotonically as the horizon increases implying that earnings forecasts at each horizon convey new value relevant information. We cannot find a clear advantage to using firm specific growth rates instead of a constant rate of 4 % across all sample

Theodore Sougiannis; Takashi Yaekura

2000-01-01T23:59:59.000Z

468

Load forecast and treatment of conservation  

E-Print Network (OSTI)

Load forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservation in the short-term model Our short-term model is an econometric model which can not explicitly forecast

469

5, 183218, 2008 A rainfall forecast  

E-Print Network (OSTI)

HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N

Paris-Sud XI, Université de

470

Forecasting Skill Limits of Nested, Limited-Area Models: A Perfect-Model Approach  

Science Conference Proceedings (OSTI)

The fundamental hypothesis underlying the use of limited-area models (LAMs) is their ability to generate meaningful small-scale features from low-resolution information, provided as initial conditions and at their lateral boundaries by a model or ...

Ramón de Ela; René Laprise; Bertrand Denis

2002-08-01T23:59:59.000Z

471

Need for an Integrated Risk Model  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Need for An Integrated Risk Need for An Integrated Risk Model Michael Salmon, LANL Voice: 505-665-7244 Fax: 505-665-2897 salmon@lanl.gov 10/22/2008 p. 2, LA-UR 11-06023 Purpose * To highlight some observations on safety strategy when concerned with NPH * To encourage discussion and collaboration on the use of an integrated risk model at sites * To propose a test case for use of a sample case 10/22/2008 p. 3, LA-UR 11-06023 Observations * SAFER Comments of Peer Reviewers - There is a need to consider operator interaction - What about fire following earthquake? - What about flood following earthquake? - lessons from kashiwazake * Sites do not consider common cause initiating events * Investment decisions are not based on quantitative estimates of risk reduction 10/22/2008 p. 4, LA-UR 11-06023

472

Modeling hydro power plants in deregulated electricity markets : integration and application of EMCAS and VALORAGUA.  

Science Conference Proceedings (OSTI)

In this paper, we present details of integrating an agent-based model, Electricity Market Complex Adaptive System (EMCAS) with a hydro-thermal coordination model, VALORAGUA. EMCAS provides a framework for simulating deregulated markets with flexible regulatory structure along with bidding strategies for supply offers and demand bids. VALORAGUA provides longer-term operation plans by optimizing hydro and thermal power plant operation for the entire year. In addition, EMCAS uses the price forecasts and weekly hydro schedules from VALORAGUA to provide intra-week hydro plant optimization for hourly supply offers. The integrated model is then applied to the Iberian electricity market which includes about 111 thermal plants and 38 hydro power plants. We then analyze the impact of hydro plant supply offers on the market prices and ways to minimize the Gencospsila exposure to price risk.

Thimmapuram, P.; Veselka, T.; Koritarov, V.; Vilela, S.; Pereira, R.; Silva, R. (Decision and Information Sciences); (Rede Electrica Nacional, S.A.); (Energias de Portugal)

2008-01-01T23:59:59.000Z

473

Regional load-curve models: QUERI's model long-run forecasts and sensitivity analysis. Volume 4. Final report. [Hourly demand in 32 US regions  

SciTech Connect

This report presents detailed forecasts of the hourly demand for electricity in 32 regions of the US through the year 2000. The forecasts are generated by a load curve model estimated by QUERI and described in Volume II of this report. Two primary sets of input assumptions for this model are utilized: one based on DRI's macro, regional and sectoral models is called the Baseline Scenario while the other, which is a projection of historical trends, is the Extrapolation Scenario. Under both assumptions, the growth rates of electricity are forecast to slow from historical levels. Load factors are generally projected to continue to decline; most regions are forecast to remain Summer peaking but this is rather sensitive to the choice of scenario. By considering other scenarios which are small perturbations of the Baseline assumptions, elasticities of average, peak and hourly loads are calculated. Different weather assumptions are also examined for the sensitivity of the load shapes to changes in the weather.

Engle, R.F.; Granger, C.W.J.; Ramanathan, R.

1981-09-01T23:59:59.000Z

474

A Probabilistic Forecast Approach for Daily Precipitation Totals  

Science Conference Proceedings (OSTI)

Commonly, postprocessing techniques are employed to calibrate a model forecast. Here, a probabilistic postprocessor is presented that provides calibrated probability and quantile forecasts of precipitation on the local scale. The forecasts are ...

Petra Friederichs; Andreas Hense

2008-08-01T23:59:59.000Z

475

Prediction of Consensus Tropical Cyclone Track Forecast Error  

Science Conference Proceedings (OSTI)

The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, ...

James S. Goerss

2007-05-01T23:59:59.000Z

476

An Alternative Tropical Cyclone Intensity Forecast Verification Technique  

Science Conference Proceedings (OSTI)

The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a ...

Sim D. Aberson

2008-12-01T23:59:59.000Z

477

NREL: Transmission Grid Integration - FESTIV Model  

NLE Websites -- All DOE Office Websites (Extended Search)

FESTIV Model FESTIV Model The Flexible Energy Scheduling Tool for Integration of Variable Generation (FESTIV) is a model that simulates the behavior of the electric power system to help researchers understand the impacts of variability and uncertainty on operating reserves requirements. FESTIV includes security-constrained unit commitment, security-constrained economic dispatch, and automatic generation control sub-models. Electric power system operators use a variety of scheduling techniques to match electricity generation and demand. When the total supply of energy is different from the total demand, system operators must deploy operating reserves (including regulating, following, contingency, and ramping reserves) to correct the energy imbalance. The way they do this and,

478

Issues in midterm analysis and forecasting 1998  

SciTech Connect

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.

NONE

1998-07-01T23:59:59.000Z

479

Operational pollution forecast for the region of Bulgaria  

Science Conference Proceedings (OSTI)

An operational prototype of the Integrated Bulgarian Chemical Weather Forecasting and Information System is presented. This version of the system is limited to relatively low resolution (10 km) but covers all Bulgaria. It is based on the US EPA Models-3 System (MM5

D. Syrakov; I. Etropolska; M. Prodanova; K. Ganev; N. Miloshev; K. Slavov

2012-01-01T23:59:59.000Z

480

Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets  

E-Print Network (OSTI)

the accuracy of two methods to forecast natural gas prices:forecasting models along with the AEO forecast. Appendix ATable 1. Forecast Year AEO Predicted Price from 1996-2003

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

2005-01-01T23:59:59.000Z

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


481

Short-term streamflow forecasting: ARIMA vs neural networks  

Science Conference Proceedings (OSTI)

Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of ... Keywords: artificial neural networks, auto regressive integrated moving average, forecasting, streamflow

Juan Frausto-Solis; Esmeralda Pita; Javier Lagunas

2008-03-01T23:59:59.000Z

482

VBR MPEG Video Traffic Dynamic Prediction Based on the Modeling and Forecast of Time Series  

Science Conference Proceedings (OSTI)

The variable-bit-rate traffic characteristic brings a large complication to the utilization of network resources, especially bandwidth. To solve this problem, this paper proposes a dynamic prediction scheme of MPEG video traffic. We first advance an ... Keywords: MPEG, video trace, forecast, time series, ARMA

Jun Dai; Jun Li

2009-08-01T23:59:59.000Z

483

An Analysis of NMC's Nested Grid Model Forecasts of Alberta Clippers  

Science Conference Proceedings (OSTI)

Forecasts of Alberta Clipper–type cyclones defined as cyclones that move southeastward from regions of western Canada into south-central Canada or the north-central United States before moving eastward to the coast of North America, were studied ...

Todd A. Hutchinson

1995-09-01T23:59:59.000Z

484

A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting  

Science Conference Proceedings (OSTI)

Stock market forecasting is important and interesting, because the successful prediction of stock prices may promise attractive benefits. The economy of Taiwan relies on international trade deeply, and the fluctuations of international stock markets ... Keywords: ANFIS, Genetic algorithm, Neural network, Weighted rule

Liang-Ying Wei

2013-02-01T23:59:59.000Z

485

Forecasting of Chaotic Cloud Absorption Time Series for Meteorological and Plume Dispersion Modeling  

Science Conference Proceedings (OSTI)

A nonlinear forecasting method based on the reconstruction of a chaotic strange attractor from about 1.5 years of cloud absorption data obtained from half-hourly Meteosat infrared images was used to predict the behavior of the time series 24 h in ...

V. Pérez-Muñuzuri

1998-11-01T23:59:59.000Z

486

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

E-Print Network (OSTI)

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

Mohaghegh, Shahab

487

Verification of the NOAA Smoke Forecasting System: Model Sensitivity to the Injection Height  

Science Conference Proceedings (OSTI)

A detailed evaluation of NOAA’s Smoke Forecasting System (SFS) is a fundamental part of its development and further refinement. In this work, particulate matter with a diameter less than or equal to 2.5-?m (PM2.5) concentration levels, simulated ...

Ariel F. Stein; Glenn D. Rolph; Roland R. Draxler; Barbara Stunder; Mark Ruminski

2009-04-01T23:59:59.000Z

488

Integrable Models and the Toda Lattice Hierarchy  

E-Print Network (OSTI)

A pedagogical presentation of integrable models with special reference to the Toda lattice hierarchy has been attempted. The example of the KdV equation has been studied in detail, beginning with the infinite conserved quantities and going on to the Lax formalism for the same. We then go on to symplectic manifolds for which we construct the Lax operator. This formalism is applied to Toda Lattice systems. The Zakharov Shabat formalism aimed at encompassing all integrable models is also covered after which the zero curvature condition and its fallout are discussed. We then take up Toda Field Theories and their connection to W algebras via the Hamiltonian reduction of the WZNW model. Finally, we dwell on the connection between four dimensional Yang Mills theories and the KdV equation along with a generalization to supersymmetry.

Södermark, B M

2000-01-01T23:59:59.000Z

489

Integrable Models and the Toda Lattice Hierarchy  

E-Print Network (OSTI)

A pedagogical presentation of integrable models with special reference to the Toda lattice hierarchy has been attempted. The example of the KdV equation has been studied in detail, beginning with the infinite conserved quantities and going on to the Lax formalism for the same. We then go on to symplectic manifolds for which we construct the Lax operator. This formalism is applied to Toda Lattice systems. The Zakharov Shabat formalism aimed at encompassing all integrable models is also covered after which the zero curvature condition and its fallout are discussed. We then take up Toda Field Theories and their connection to W algebras via the Hamiltonian reduction of the WZNW model. Finally, we dwell on the connection between four dimensional Yang Mills theories and the KdV equation along with a generalization to supersymmetry.

Bani Mitra Sodermark

1999-06-21T23:59:59.000Z

490

Fuzzy forecasting with DNA computing  

Science Conference Proceedings (OSTI)

There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard ...

Don Jyh-Fu Jeng; Junzo Watada; Berlin Wu; Jui-Yu Wu

2006-06-01T23:59:59.000Z

491

SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2  

Science Conference Proceedings (OSTI)

This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

BARCOT, R.A.

2005-08-17T23:59:59.000Z

492

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

SciTech Connect

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

Chiswell, S

2009-01-11T23:59:59.000Z

493

Improving Ocean Model Initialization for Coupled Tropical Cyclone Forecast Models Using GODAE Nowcasts  

Science Conference Proceedings (OSTI)

To simulate tropical cyclone (TC) intensification, coupled ocean–atmosphere prediction models must realistically reproduce the magnitude and pattern of storm-forced sea surface temperature (SST) cooling. The potential for the ocean to support ...

G. R. Halliwell Jr.; L. K. Shay; S. D. Jacob; O. M. Smedstad; E. W. Uhlhorn

2008-07-01T23:59:59.000Z

494

Airmass Modification over the Gulf of Mexico: Mesoscale Model and Airmass Transformation Model Forecasts  

Science Conference Proceedings (OSTI)

Several numerical models are used to examine strong air-sea fluxes and resultant airmass modification following a cold-frontal passage over the Gulf of Mexico. Data from the Gulf of Mexico Experiment (GUFMEX), which was conducted in February-...

Stephen D. Burk; William T. Thompson

1992-08-01T23:59:59.000Z

495

SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2  

Science Conference Proceedings (OSTI)

This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

BARCOT, R.A.

2003-12-01T23:59:59.000Z

496

Performance of Recent Multimodel ENSO Forecasts  

Science Conference Proceedings (OSTI)

The performance of the International Research Institute for Climate and Society “ENSO forecast plume” during the 2002–11 period is evaluated using deterministic and probabilistic verification measures. The plume includes multiple model forecasts ...

Michael K. Tippett; Anthony G. Barnston; Shuhua Li

2012-03-01T23:59:59.000Z

497

Intercomparison of Spatial Forecast Verification Methods  

Science Conference Proceedings (OSTI)

Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because ...

Eric Gilleland; David Ahijevych; Barbara G. Brown; Barbara Casati; Elizabeth E. Ebert

2009-10-01T23:59:59.000Z

498

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...

Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister

2001-01-01T23:59:59.000Z

499

Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts  

Science Conference Proceedings (OSTI)

This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-...

William A. Gallus Jr.; Michael E. Baldwin; Kimberly L. Elmore

2007-02-01T23:59:59.000Z

500

Aviation forecasting and systems analyses  

SciTech Connect

The 9 papers in this report deal with the following areas: method of allocating airport runway slots; method for forecasting general aviation activity; air traffic control network-planning model based on second-order Markov chains; analyzing ticket-choice decisions of air travelers; assessing the safety and risk of air traffic control systems: risk estimation from rare events; forecasts of aviation fuel consumption in Virginia; estimating the market share of international air carriers; forecasts of passenger and air-cargo activity at Logan International Airport; and forecasting method for general aviation aircraft and their activity.

Geisinger, K.E.; Brander, J.R.G.; Wilson, F.R.; Kohn, H.M.; Polhemus, N.W.

1980-01-01T23:59:59.000Z