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1

Forecasting electricity load demand: analysis of the 2001 rationing period  

E-Print Network (OSTI)

CEPEL e UENF. Abstract. This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.

Leonardo Rocha Souza; Lacir Jorge Soares; Leonardo Rocha Souza; Epge Fundação; Getúlio Vargas; Lacir Jorge Soares

2003-01-01T23:59:59.000Z

2

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

3

Neural networks based multiplex forecasting system of the end-point of copper blow period  

Science Conference Proceedings (OSTI)

The neural network and the experiential evaluation method are introduced into the industrial converting process forecast, and a multiplex forecast system is proposed at the end-point of copper blow period in a matte converting process. The fuzzy clustering ...

Lihua Xue; Hongzhong Huang; Yaohua Hu; Zhangming Shi

2005-05-01T23:59:59.000Z

4

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

5

Variable Selection and Inference for Multi-period Forecasting Problems  

E-Print Network (OSTI)

?t,x?t)?. Multi-period forecasts of yt can then be obtained iteratively using a conventional VAR of the form zt = µz + ( Ap(L) Bq(L) Cr(L) Ds(L) ) zt?1 + ?t, (10) where p and q are the lag order of yt and xt in the equation for yt and r and s is the lag order... , i.e. Cr(L) and Bq(L) in particular. To deal with this issue, a conditional factor-augmentation approach can be used. In this approach, the large-dimensional xt-vector is condensed into a subset of factors, fˆ t, of dimension m < M , used to summarize...

Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

6

Probabilities for a Period and Its Subperiods: Theoretical Relations for Forecasting  

Science Conference Proceedings (OSTI)

Consider an event definable in terms of two subevents as, for example, the occurrence of precipitation within a 24-h period is definable in terms of the occurrence of precipitation within each of the 12-h subperiods. A complete forecast must ...

Roman Krzysztofowicz

1999-02-01T23:59:59.000Z

7

forecasts  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 106. Average annual minemouth coal prices by region, 1990-2040 (2011 dollars per million Btu) Appalachia Interior West US Average

8

Evaluation of Atmospheric Fields from the ECMWF Seasonal Forecasts over a 15-Year Period  

Science Conference Proceedings (OSTI)

Since 1997, the European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the ...

Geert Jan van Oldenborgh; Magdalena A. Balmaseda; Laura Ferranti; Timothy N. Stockdale; David L. T. Anderson

2005-08-01T23:59:59.000Z

9

NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS  

E-Print Network (OSTI)

· NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Industry Insight: West Virginia Fiscal Forecast 34 CHAPTER 4: WEST ViRGiNiA'S 35 COUNTiES AND MSAs West Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

Mohaghegh, Shahab

10

Figure S.1  

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

2- Figures and Table 2.1 2- Figures and Table 2.1 Figure S.1 Figure 1.1 Figure 1.2 Figure 1.3 Figure 2.1 Figure 2.2 Figure 2.3 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 3.6 Figure 3.7 Figure 3.8 Figure 3.9 Figure 3.10 Figure 3.11 Figure 3.12 Figure 3.13 Figure 3.14 Figure 3.15 Figure 3.16 Figure 3.17 Figure 3.18 Figure 3.19 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.11 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Figure 4.16 Figure 4.17 Figure 4.18 Figure 4.19 J.1 Lewiston Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC FORMAT) J.2 Keswick Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC FORMAT) J.3 Natoma Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC

11

Forecast Technical Document Restocking in the Forecast  

E-Print Network (OSTI)

Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub

12

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Electricity Electricity Electricity consumption nearly doubles in the IEO2005 projection period. The emerging economies of Asia are expected to lead the increase in world electricity use. Figure 58. World Net Electricity Consumption, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 59. World Net Electricity Consumption by Region, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data The International Energy Outlook 2005 (IEO2005) reference case projects that world net electricity consumption will nearly double over the next two decades.10 Over the forecast period, world electricity demand is projected to grow at an average rate of 2.6 percent per year, from 14,275 billion

13

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting model (WRF) is used to downscale interim ECMWF Re-Analysis (ERA-Interim) data for the climate over Europe for the period 1990–95 with grid spacing of 0.44° for 12 combinations of physical parameterizations. Two ...

P. A. Mooney; F. J. Mulligan; R. Fealy

2013-02-01T23:59:59.000Z

14

RBF Neural Networks Combined with Principal Component Analysis Applied to Quantitative Precipitation Forecast for a Reservoir Watershed during Typhoon Periods  

Science Conference Proceedings (OSTI)

The forecast of precipitations during typhoons has received much attention in recent years. It is important in meteorology and atmospheric sciences. Hence, the study on precipitation nowcast during typhoons is of great significance to operators of ...

Chih-Chiang Wei

2012-04-01T23:59:59.000Z

15

APPENDIX A: FIGURES  

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

APPENDIX A: FIGURES Project Name: Archbold Area Schools Wind Turbine Source Information: USGS, TRG Survey Figure Name: Turbine Location Notes: Turbine Location TRG Archbold...

16

APPENDIX A: FIGURES  

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

APPENDIX A: FIGURES Project Name: Pettisville Local Schools Wind Turbine Source Information: USGS, TRG Survey Figure Name: Turbine Location Notes: Turbine Location TRG...

17

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

18

Calibration of Probabilistic Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

From 1 August 1990 to 31 July 1995, the Weather Service Forecast Office in Pittsburgh prepared 6159 probabilistic quantitative precipitation forecasts. Forecasts were made twice a day for 24-h periods beginning at 0000 and 1200 UTC for two river ...

Roman Krzysztofowicz; Ashley A. Sigrest

1999-06-01T23:59:59.000Z

19

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

20

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 "forecast period figure" 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

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

22

Figure 6 - TMS  

Science Conference Proceedings (OSTI)

Figure 6. In wet stretching, (a) the fiber is allowed to contract unrestrained up to the supercontracted length; (b) it is stretched to the selected length and the ends

23

Forecasting of mine price for central Appalachian steam coal  

SciTech Connect

In reaction to Virginia's declining share of the steam coal market and the subsequent depression in southwest Virginia's economy, an optimization model of the central Appalachian steam coal market was developed. The input to the cost vector was the delivered cost of coal, which is comprised of the mine price (FOB) and transportation cost. One objective of the study was to develop a purchasing model that could be used to minimize the cost of coal procurement over a multi-period time span. The initial case study used a six-month period (7/86-12/86); this requires short-term, forecasts of the mine price of coal. Mine-cost equations and regression models were found to be inadequate for forecasting the mine price of coal. Instead forecasts were generated using modified time series models. This paper describes the application of classical time-series modeling to forecasting the mine price of coal in central Appalachia; in particular, the special modification to the classical methodology needed to generate short-term forecasts and their confidence limits and the need to take into account market-specific considerations such as the split between long-term contracts and the spot market. Special consideration is given to forecasting the spot market. 7 references, 4 figures, 3 tables.

Smith, M.L.

1988-01-01T23:59:59.000Z

24

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...

25

MECS Fuel Oil Figures  

U.S. Energy Information Administration (EIA) Indexed Site

: Percentage of Total Purchased Fuels by Type of Fuel : Percentage of Total Purchased Fuels by Type of Fuel Figure 1. Percent of Total Purchased Fuel Sources: Energy Information Administration. Office of Energy Markets and End Use, Manufacturing Energy Consumption Survey (MECS): Consumption of Energy; U.S. Department of Commerce, Bureau of the Census, Annual Survey of Manufactures (ASM): Statistics for Industry Groups and Industries: Statistical Abstract of the United States. Note: The years below the line on the "X" Axis are interpolated data--not directly from the Manufacturing Energy Consumption Survey or the Annual Survey of Manufactures. Figure 2: Changes in the Ratios of Distillate Fuel Oil to Natural Gas Figure 2. Changes in the Ratios of Distillate Fuel Oil to Natural Gas Sources: Energy Information Administration. Office of

26

Forecasting with Reference to a Specific Climatology  

Science Conference Proceedings (OSTI)

Seasonal forecasts are most commonly issued as anomalies with respect to some multiyear reference period. However, different seasonal forecasting centers use different reference periods. This paper shows that for near-surface temperature, ...

Emily Wallace; Alberto Arribas

2012-11-01T23:59:59.000Z

27

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

28

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

29

Limits to Flood Forecasting in the Colorado Front Range for Two Summer Convection Periods using Radar Nowcasting and a Distributed Hydrologic Model  

Science Conference Proceedings (OSTI)

Flood forecasting in mountain basins remains a challenge given the difficulty in accurately predicting rainfall and in representing hydrologic processes in complex terrain. This study identifies flood predictability patterns in mountain areas ...

Hernan A. Moreno; Enrique R. Vivoni; David J. Gochis

30

Limits to Flood Forecasting in the Colorado Front Range for Two Summer Convection Periods Using Radar Nowcasting and a Distributed Hydrologic Model  

Science Conference Proceedings (OSTI)

Flood forecasting in mountain basins remains a challenge given the difficulty in accurately predicting rainfall and in representing hydrologic processes in complex terrain. This study identifies flood predictability patterns in mountain areas ...

Hernan A. Moreno; Enrique R. Vivoni; David J. Gochis

2013-08-01T23:59:59.000Z

31

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

32

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

33

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2000 NEW JERSEY of growth will decelerate over the forecast period. The R/ECON TM forecast for New Jersey in 2000 looks to decelerate over the course of the forecast. These forces will combine to push the unemployment rate to more

34

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

35

R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 1999 NEW JERSEY the rate of inflation should remain under 3% a year. (See Table 1.) #12;Throughout the forecast period and wage growth slow later in the forecast period, income growth will average 4.8% a year between 2000

36

R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 2000 NEW JERSEY and 2002, with 84,800 jobs being added over the two-year period. The R/ECON TM forecast for New Jersey the rest of the forecast period as foreign immigration declines and the population ages. In the next 10

37

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Figure 9: Two Alternative Price Forecasts (denoted by openComparison of AEO 2007 Natural Gas Price Forecast toNYMEX Futures Prices Date: December 6, 2006 Introduction On

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

38

Management Earnings Forecasts and Value of Analyst Forecast Revisions  

E-Print Network (OSTI)

Prior studies evaluate the relative importance of the sources of value that financial analysts bring to the market based on the price impact of forecast revisions over the event time. We find that management earnings forecasts influence the timing and precision of analyst forecasts. More importantly, evidence suggests that prior studies ’ finding of weaker (stronger) stock-price responses to forecast revisions in the period immediately after (before) the prior-quarter earnings announcement is likely to be the artifact of a temporal pattern of management earnings forecasts over the event time. To the extent that management earnings forecasts are public disclosures, our results suggest that the relative importance of analysts ' information discovery role documented in prior studies is likely to be overstated.

Yongtae Kim; Minsup Song

2013-01-01T23:59:59.000Z

39

Silicon Nanoparticle Biocompatibility Figure 1  

Science Conference Proceedings (OSTI)

... Figure 2. Effect of SNs and SMs on cell survival percentage in RAW 264.7 cells based on trypan blue dye exclusion (A) and MTT (B) assay. ...

2012-10-01T23:59:59.000Z

40

Microsoft Word - Figure_15.docx  

U.S. Energy Information Administration (EIA) Indexed Site

Source: Energy Information Administration (EIA), Form EIA-191A, "Annual Underground Gas Storage Report." U.S. Energy Information Administration | Natural Gas Annual Figure 16....

Note: This page contains sample records for the topic "forecast period figure" 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

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

42

Evaluation of Probabilistic Medium-Range Temperature Forecasts from the North American Ensemble Forecast System  

Science Conference Proceedings (OSTI)

Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic ...

Doug McCollor; Roland Stull

2009-02-01T23:59:59.000Z

43

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

44

Three prominent figures (3PF)  

Science Conference Proceedings (OSTI)

Three Prominent Figures, a sub-group of the VOLT Collective (http://www.voltcollective.com) is a performance piece combining live DJ-ing, video art, and physical computing to explore non-invasive musical expression. Three Prominent Figures will be presented ...

Roberto Osorio-Goenaga; Gregory Boland; Nathaniel Weiner

2007-06-01T23:59:59.000Z

45

Forecast of auroral activity  

Science Conference Proceedings (OSTI)

A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting

A. T. Y. Lui

2004-01-01T23:59:59.000Z

46

Microsoft Word - figure_03.doc  

U.S. Energy Information Administration (EIA) Indexed Site

0 U.S. Energy Information Administration | Natural Gas Annual Figure 3. Marketed production of natural gas in the United States and the Gulf of Mexico, 2011 (million cubic feet)...

47

Microsoft Word - figure_24.doc  

U.S. Energy Information Administration (EIA) Indexed Site

1 Figure 25. Average price of natural gas delivered to U.S. onsystem industrial consumers, 2011 (dollars per thousand cubic feet) U.S. Energy Information Administration | Natural...

48

Microsoft Word - figure_99.doc  

U.S. Energy Information Administration (EIA) Indexed Site

6 U.S. Energy Information Administration | Natural Gas Annual Figure 6. Natural gas processing in the United States and the Gulf of Mexico, 2011 (million cubic feet) None 1-15,000...

49

R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1999 NEW and wage growth slow later in the forecast, income growth will average 5% a year between 2000 and 2004. Over the forecast period, population growth will average 0.5% a year. The population will rise from 8

50

R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2001 NEW JERSEY each year. The R/ECONTM forecast for New Jersey looks for growth in real output of 2.6 percent years. Over the forecast period, both the construction and manufacturing sectors will lose jobs

51

R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2001 NEW JERSEY and 2005, and by an average of 43,000 thereafter (from 2005 to 2020). The R/ECONTM forecast for New Jersey.6 percent a year over the rest of the forecast period. Personal income will rise 5.6 percent this year, down

52

R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1998 NEW 1997 will continue-- though at a reduced rate--through the forecast period that ends in 2001. New inflation of about 1.5%. In 1998, R/ECONTM forecasts that employment will rise by 76,000 jobs, or 2

53

R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 1999 NEW JERSEY forecast for New Jersey is for a continuation of the current expansion but at a somewhat slower pace in employment through the forecast period will be in services and trade. We also expect considerable growth

54

R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 1999 NEW JERSEY forecast for New Jersey is for a continuing but slowing expansion. (See Table 1.) In 1998, employment rose increased by 0.7% in 1998. It will slow a bit over the forecast period as foreign immigration declines. #12

55

R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2000 NEW JERSEY to more inflation and higher interest rates. The R/ECON TM forecast for New Jersey looks for employment.6% a year over the forecast period. The services and trade sectors will provide 90% of the net increase

56

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

57

NFI Forecasts Methodology NFI Forecasts Methodology  

E-Print Network (OSTI)

NFI Forecasts Methodology NFI Forecasts Methodology Overview Issued by: National Forest Inventory.brewer@forestry.gsi.gov.uk Website: www.forestry.gov.uk/inventory 1 NFI Softwood Forecasts Methodology Overview #12;NFI Forecasts ........................................................................................................4 Rationale behind the new approach to the GB Private sector production forecast ........4 Volume

58

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS  

E-Print Network (OSTI)

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia. From October 2013 new and improved 7 day forecasts will be introduced for Brisbane, Gold Coast

Greenslade, Diana

59

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Natural Gas Natural gas is the fastest growing primary energy source in the IEO2005 forecast. Consumption of natural gas is projected to increase by nearly 70 percent between 2002 and 2025, with the most robust growth in demand expected among the emerging economies. Figure 34. World Natural Gas Consumption, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center on 202-586-8800. Figure Data Figure 35. Natural Gas Consumption by Region, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 36. Increase in Natural Gas Consumption by Region and Country, 2002-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data

60

Another Approach to Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

The skill of a medium-range numerical forecast can fluctuate widely from day to day. Providing an a priori estimate of the skill of the forecast is therefore important. Existing approaches include Monte Carlo Forecasting and Lagged Average ...

W. Y. Chen

1989-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Threshold Relative Humidity Duration Forecasts for Plant Disease Prediction  

Science Conference Proceedings (OSTI)

Duration of high relative humidity periods is an important component of many plant disease development models. Performance of forecasts of this quantity, based on the model output statistics 3-h temperature and dewpoint forecasts produced by the ...

Daniel S. Wilks; Karin W. Shen

1991-04-01T23:59:59.000Z

62

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

63

EIS-0268-Figures-1997.pdf  

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

DOFJ'EIS-0268 DOFJ'EIS-0268 - PKw.2F Figure 4-L L-Lake and environs. 4-3 -- =----- 90 --m--- -m- EAST o (C.nti""ed O"figure 4.4b) AA 320 1 300 1 Fourmile Indian Grave Upland Pen Branch Brench Formation Branch 280 ~ 280 240 : E -220 ~ L 200 180 I 160 140 1 I I 1 2 3 4 5 Miles Legend: _ _ Inferredcontact Note:TO converito kilometersmultiply by 1.609 to convetito metersmultiply by0.304e Figure 4-4a. Generalized geologic cross section from Fourmile Branch to L DO~IS-0268 I t" 1 I I t 4-8 DOE/EIS-0268 I 4-60 I t t i I I DOE/EIS-0268 ,. ,. 4-61 DOE/EIS-0268 ,. ,,.':, .. ,.. , 4-62 I 1 I I I DOE/EIS-0268 4-63 DOEI'EIS-0268 ., . . 4-64 I I 1 B I I I m 1 I I I I 1 I I I m I DOE~IS-0268 4-65 DO~IS-0268 Radon in homes: 200 millirem per year Notes me major contributor to the annual average individual dose in the United StaIeS, [ncluti"g residents of the Central Savannah River Area, is naturally occuning radiation

64

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

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

65

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

66

Forecast of geothermal-drilling activity  

DOE Green Energy (OSTI)

The number of geothermal wells that will be drilled to support electric power production in the United States through 2000 A.D. are forecasted. Results of the forecast are presented by 5-year periods for the five most significant geothermal resources.

Mansure, A.J.; Brown, G.L.

1982-07-01T23:59:59.000Z

67

Forecasting in Meteorology  

Science Conference Proceedings (OSTI)

Public weather forecasting heralded the beginning of modern meteorology less than 150 years ago. Since then, meteorology has been largely a forecasting discipline. Thus, forecasting could have easily been used to test and develop hypotheses, ...

C. S. Ramage

1993-10-01T23:59:59.000Z

68

The Hanford Site New Production Reactor (NPR) economic and demographic baseline forecasts  

SciTech Connect

The objective of this is to present baseline employment and population forecasts for Benton, Franklin, and Yakima Counties. These forecasts will be used in the socioeconomic analysis portion of the New Production Reactor Environmental Impact Statement. Aggregate population figures for the three counties in the study area were developed for high- and low-growth scenarios for the study period 1990 through 2040. Age-sex distributions for the three counties during the study period are also presented. The high and low scenarios were developed using high and low employment projections for the Hanford site. Hanford site employment figures were used as input for the HARC-REMI Economic and Demographic (HED) model to produced baseline employment forecasts for the three counties. These results, in turn, provided input to an integrated three-county demographic model. This model, a fairly standard cohort-component model, formalizes the relationship between employment and migration by using migration to equilibrate differences in labor supply and demand. In the resulting population estimates, age-sex distributions for 1981 show the relatively large work force age groups in Benton County while Yakima County reflects higher proportions of the population in the retirement ages. The 2040 forecasts for all three counties reflect the age effects of relatively constant and low fertility increased longevity, as well as the cumulative effects of the migration assumptions in the model. By 2040 the baby boom population will be 75 years and older, contributing to the higher proportion of population in the upper end age group. The low scenario age composition effects are similar. 13 refs., 5 figs., 9 tabs.

Cluett, C.; Clark, D.C. (Battelle Human Affairs Research Center, Seattle, WA (USA)); Pittenger, D.B. (Demographics Lab., Olympia, WA (USA))

1990-08-01T23:59:59.000Z

69

Evaluating the Cloud Cover Forecast of NCEP Global Forecast System with Satellite Observation  

E-Print Network (OSTI)

To assess the quality of daily cloud cover forecast generated by the operational global numeric model, the NCEP Global Forecast System (GFS), we compose a large sample with outputs from GFS model and satellite observations from the International Satellite Cloud Climatology Project (ISCCP) in the period of July 2004 to June 2008, to conduct a quantitative and systematic assessment of the performance of a cloud model that covers a relatively long range of time, basic cloud types, and in a global view. The evaluation has revealed the goodness of the model forecast, which further illustrates our completeness on understanding cloud generation mechanism. To quantity the result, we found a remarkably high correlation between the model forecasts and the satellite observations over the entire globe, with mean forecast error less than 15% in most areas. Considering a forecast within 30% difference to the observation to be a "good" one, we find that the probability for the GFS model to make good forecasts varies between...

Ye, Quanzhi

2011-01-01T23:59:59.000Z

70

Microsoft Word - figure_18.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 0 2 4 6 8 10 12 14 2001 2002 2003 2004 2005 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 360 400 440 Dollars per Thousand Cubic Meters Residential Commercial Industrial Electric Power Vehicle Fuel Figure 18. Average Price of Natural Gas Delivered to Consumers in the United States, 2001-2005 Note: Coverage for prices varies by consumer sector. See Appendix A for further discussion on consumer prices. Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to Consumers"; Federal Energy Regulatory Commission (FERC), Form FERC-423, "Monthly Report of Cost and Quality of Fuels for

71

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2007 (Million Cubic Feet) Nigeria Algeria 37,483 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Algeria Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and the Office of Fossil Energy, Natural Gas Imports and Exports.

72

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 0 2 4 6 8 10 2003 2004 2005 2006 2007 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-906, "Power Plant Report"; Form EIA-920, "Combined Heat and Power Plant Report"; and Form EIA-923, "Power Plant Operations Report." Figure 15. Natural Gas Delivered to Consumers in the United States, 2003-2007 Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2003 through 2007.

73

PHOBOS Experiment: Figures and Data  

DOE Data Explorer (OSTI)

PHOBOS consists of many silicon detectors surrounding the interaction region. With these detectors physicists can count the total number of produced particles and study the angular distributions of all the products. Physicists know from other branches of physics that a characteristic of phase transitions are fluctuations in physical observables. With the PHOBOS array they look for unusual events or fluctuations in the number of particles and angular distribution. The articles that have appeared in refereed science journals are listed here with separate links to the supporting data plots, figures, and tables of numeric data.  See also supporting data for articles in technical journals at http://www.phobos.bnl.gov/Publications/Technical/phobos_technical_publications.htm and from conference proceedings at http://www.phobos.bnl.gov/Publications/Proceedings/phobos_proceedings_publications.htm

The PHOBOS Collaboration

74

Microsoft Word - figure_20.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 0 2 4 6 8 10 12 14 16 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2005 dollars using the chain-type price indexes for Gross Domestic Product (2005 = 1.0) as published by the U.S. Department of Commerce, Bureau of Economic Analysis. dollars per thousand cubic feet base year Figure 21. Average price of natural gas delivered to residential consumers, 1980-2011 nominal dollars

75

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

38 38 0 2 4 6 8 10 2002 2003 2004 2005 2006 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-906, "Power Plant Report." Figure 15. Natural Gas Delivered to Consumers in the United States, 2002-2006 Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2002 through 2006. EIA collects information on the number of residential and commercial consumers through a survey of companies that deliver gas

76

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

38 38 0 2 4 6 8 10 2001 2002 2003 2004 2005 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Figure 15. Natural Gas Delivered to Consumers in the United States, 2001-2005 Sources: Energy Information Administration (EIA), Form EIA -176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-906, "Power Plant Report." Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2001 through 2005. EIA collects information on the number of residential and commercial consumers through a survey of companies that deliver gas

77

RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 1998  

E-Print Network (OSTI)

RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 1998 NEW JERSEY: EXPANSION CONTINUES/ECONTM forecast for New Jersey is for a continuation of the current expansion but at a much reduced rate. In 1998 and throughout the forecast period will be in various service sectors and in retail trade. Health services

78

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta*  

E-Print Network (OSTI)

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta* Department of Economics Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition-sample period and January 1990 to March 2009 as the out-of- sample horizon, we compare the forecast performance

Ahmad, Sajjad

79

Mid-range energy-forecasting system: structure, forecasts, and critique  

SciTech Connect

The Mid-Range Energy Forecasting System (MEFS) is a large-scale, interdisciplinary model of the US energy system maintained by the US Department of Energy. MEFS provides long-run regional forecasts of delivered prices for electricity, coal, gasoline, residual, distillate, and natural gas. A number of sets of MEFS forecasts are usually issued, each set corresponding to a different scenario. Because it forecasts prices and since these forecasts are regularly disseminated, MEFS is of considerable practical interest. A critical guide of the model's output for potential users is provided in this paper. The model's logic is described, the latest forecasts from MEFS are presented, and the reasonableness of both the forecasts and the methodology are critically evaluated. The manner in which MEFS interfaces with the Oil Market Simulation Model, which forecasts crude oil price, is also discussed. The evaluation concludes that while there are serious problems with MEFS, selective use can prove very helpful. 17 references, 1 figure, 2 tables.

DeSouza, G.

1980-01-01T23:59:59.000Z

80

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

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

Note: This page contains sample records for the topic "forecast period figure" 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

Forecast of thermal-hydrological conditions and air injection test results of the single heater test at Yucca Mountain  

E-Print Network (OSTI)

29127, Berkeley, CA, 1990. Forecast of Thermal-HydrologicalDecember 1996 Figures A-l Forecast ofThermal-HydrologicalT I O N A L L A B ORATORY Forecast o f T h e n n a l - H y d

Birkholzer, J.T.

2010-01-01T23:59:59.000Z

82

Airborne Volcanic Ash Forecast Area Reliability  

Science Conference Proceedings (OSTI)

In support of aircraft flight safety operations, daily comparisons between modeled, hypothetical, volcanic ash plumes calculated with meteorological forecasts and analyses were made over a 1.5-yr period. The Hybrid Single-Particle Lagrangian ...

Barbara J. B. Stunder; Jerome L. Heffter; Roland R. Draxler

2007-10-01T23:59:59.000Z

83

Medium- and Long-Range Forecasting  

Science Conference Proceedings (OSTI)

In contrast to short and extended range forecasts, predictions for periods beyond 5 days use time-averaged, midtropospheric height fields as their primary guidance. As time ranges are increased to 3O- and 90-day outlooks, guidance increasingly ...

A. James Wagner

1989-09-01T23:59:59.000Z

84

Microsoft Word - figure_17.doc  

Gasoline and Diesel Fuel Update (EIA)

3 3 Commercial All Other States Wisconsin M innesota Pennsylvania Ohio M ichigan Texas New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Residential Colorado Indiana Texas New Jersey Pennsylvania Ohio M ichigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Figure 18. Natural gas delivered to consumers in the United States, 2011 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Residential 4,713,695 21% Commercial 3,153,605 14% Industrial 6,904,843 31% Electric Power 7,573,863 34% Industrial All Other States M innesota Iowa Oklahoma Pennsylvania Ohio Illinois Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power

85

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Ohio Texas Michigan New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Wisconsin Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2007 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,841,408 33% Industrial 6,624,846 31% Commercial 3,017,105 14% Residential 4,717,311 22% Industrial All Other States Georgia Oklahom a Michigan Pennsylvania Illinois Indiana Ohio Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Electric Power All Other States Alabam a

86

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 20088 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 25.8 0.7 0.2 3.6 3.589 0.267 0.012 0.365 0.590 0.050 20.3 1.0 3.4 3.4 1.9 3.1 6.7 0.03 6.7 0.055 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

87

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Egypt Algeria Figure 2. Natural Gas Supply and Disposition in the United States, 2006 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 23.5 0.7 0.1 3.3 3.590 0.389 0.017 0.057 0.322 0.341 0.061 18.5 0.9 3.0 2.5 1.7 4.4 2.8 6.5 0.02 6.2 0.120 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895A, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to Consumers"; Form EIA-816, "Monthly Natural Gas Liquids

88

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2008 (Million Cubic Feet) Norway Trinidad/ Tobago Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 45,772 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates.

89

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

,833 ,833 35 Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2009 (Million Cubic Feet) Norway Trinidad/ Tobago Trinidad/ Tobago Egypt Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 111,144 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates

90

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 2010 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 26.8 0.8 0.2 3.4 3.280 0.190 0.042 0.333 0.739 0.033 21.3 1.1 3.3 3.3 2.0 3.1 6.5 0.03 7.4 0.073 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

91

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 2009 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 26.0 0.7 0.2 3.5 3.271 0.236 0.013 0.338 0.701 0.031 20.6 1.0 3.4 3.0 1.9 3.1 6.2 0.03 6.9 0.160 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

92

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Algeria Figure 2. Natural Gas Supply and Disposition in the United States, 2007 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 24.6 0.6 0.2 3.8 3.783 0.448 0.077 0.095 0.292 0.482 0.047 19.1 0.9 3.2 3.4 1.8 3.0 6.6 0.03 6.8 0.115 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895A, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

93

Microsoft Word - figure_14.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 14. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2010 (Million Cubic Feet) Norway India Trinidad/ Tobago Egypt Yemen Japan Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 53,122 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada Gulf of Mexico Canada Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates based on historical data. Energy Information

94

Microsoft Word - figure_17.doc  

Gasoline and Diesel Fuel Update (EIA)

5 5 C ommercial All O ther States W isconsin Minnesota Pennsylvania Michigan O hio N ew Jersey Texas California N ew York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Residential Indiana G eorgia N ew Jersey Pennsylvania Texas O hio Michigan Illinois California All O ther States N ew York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Figure 17. Natural Gas Delivered to Consumers in the United States, 2010 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet E lectric P ower 7,387,184 34% Industrial 6,517,477 30% C om m ercial 3,101,675 14% R esidential 4,787,320 22% Industrial All O ther States Minnesota Iowa Pennsylvania O klahoma Illinois O hio Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 E lectric Power All O ther States Arizona Mississippi Louisiana Alabama

95

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Texas Ohio New Jersey Michigan California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Wisconsin Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2008 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,668,379 31% Industrial 6,650,276 31% Commercial 3,135,852 15% Residential 4,872,107 23% Industrial All Other States Georgia Iow a Oklahom a Pennsylvania Illinois Indiana Ohio Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power All Other States Mississippi New Jersey Louisiana

96

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Ohio Michigan Texas New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Minnesota Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2009 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,872,049 33% Industrial 6,167,193 29% Commercial 3,118,833 15% Residential 4,778,478 23% Industrial All Other States Georgia Iow a Pennsylvania Oklahom a Ohio Illinois Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power All Other States Nevada Pennsylvania Alabam a Arizona

97

Forecasts, Meteorology Services, Environmental Sciences Department  

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

Forecasts Short Term Forecast Suffolk County Northern Nassau Southern Nassau Area Forecast Discussion - OKX Area Forecast Discussion - NYS Area Forecast Discussion Mount Holly Area...

98

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Highlights Highlights World energy consumption is projected to increase by 57 percent from 2002 to 2025. Much of the growth in worldwide energy use in the IEO2005 reference case forecast is expected in the countries with emerging economies. Figure 1. World Marketed Energy Consumptiion by Region, 1970-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world marketed energy consumption is projected to increase on average by 2.0 percent per year over the 23-year forecast horizon from 2002 to 2025—slightly lower than the 2.2-percent average annual growth rate from 1970 to 2002. Worldwide, total energy use is projected to grow from 412 quadrillion British thermal units (Btu) in 2002 to 553 quadrillion Btu in

99

Figure 37. Carbon dioxide emissions from electricity ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 37. Carbon dioxide emissions from electricity generation in three cases, 2005-2040 (million metric tons carbon dioxide ...

100

Energy Efficiency Report: Chapter 3 Figures (Residential)  

U.S. Energy Information Administration (EIA)

Figure 3.1. Total Site Residential Energy Consumption and Personal Consumption Expenditures Indices, 1980 to 1993. Notes: Personal consumption expenditures used ...

Note: This page contains sample records for the topic "forecast period figure" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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to obtain the most current and comprehensive results.


101

Figure 70. Delivered energy consumption for transportation ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 70. Delivered energy consumption for transportation by mode, 2011 and 2040 (quadrillion Btu) Total Rail Pipeline Marine ...

102

Figure F2. Electricity market module regions  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration Annual Energy Outlook 2013 227 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information ...

103

Figure 4.17 Geothermal Resources  

U.S. Energy Information Administration (EIA)

Figure 4.17 Geothermal Resources 124 U.S. Energy Information Administration / Annual Energy Review 2011 Notes: • Data are for locations of identified hydrothermal ...

104

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

105

A Comprehensive Assessment of CFS Seasonal Forecasts over the Tropics  

Science Conference Proceedings (OSTI)

The 15-member ensemble hindcasts performed with the National Centers for Environmental Prediction Climate Forecast System (CFS) for the period 1981–2005, as well as real-time forecasts for the period 2006–09, are assessed for seasonal prediction ...

K. P. Sooraj; H. Annamalai; Arun Kumar; Hui Wang

2012-02-01T23:59:59.000Z

106

Verifying Forecasts Spatially  

Science Conference Proceedings (OSTI)

Numerous new methods have been proposed for using spatial information to better quantify and diagnose forecast performance when forecasts and observations are both available on the same grid. The majority of the new spatial verification methods can be ...

Eric Gilleland; David A. Ahijevych; Barbara G. Brown; Elizabeth E. Ebert

2010-10-01T23:59:59.000Z

107

Forecasting of Supercooled Clouds  

Science Conference Proceedings (OSTI)

Using parameterizations of cloud microphysics, a technique to forecast supercooled cloud events is suggested. This technique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircraft icing forecasts. The ...

André Tremblay; Anna Glazer; Wanda Szyrmer; George Isaac; Isztar Zawadzki

1995-07-01T23:59:59.000Z

108

Time Series and Forecasting  

Science Conference Proceedings (OSTI)

Time Series and Forecasting. Leigh, Stefan and Perlman, S. (1991). "An Index for Comovement of Time Sequences With ...

109

1993 Solid Waste Reference Forecast Summary  

SciTech Connect

This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

1993-08-01T23:59:59.000Z

110

Forecast Technical Document Volume Increment  

E-Print Network (OSTI)

Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast

111

Price forecasting for notebook computers  

E-Print Network (OSTI)

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.

Rutherford, Derek Paul

1997-01-01T23:59:59.000Z

112

The Strategy of Professional Forecasting  

E-Print Network (OSTI)

This paper develops and compares two theories of strategic behavior of professional forecasters. The first theory posits that forecasters compete in a forecasting contest with pre-specified rules. In equilibrium of a winner-take-all contest, forecasts are excessively differentiated. According to the alternative reputational cheap talk theory, forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecaster honesty, forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded.

Marco Ottaviani; Peter Norman Sørensen

2003-01-01T23:59:59.000Z

113

Microsoft Word - Figure_03_04.doc  

U.S. Energy Information Administration (EIA) Indexed Site

8 8 0 2 4 6 8 10 12 14 16 18 20 22 2010 2011 2012 2013 2014 Residential Commercial Industrial Electric Power Citygate dollars per thousand cubic feet Figure 3 and 4 0 2 4 6 8 10 12 14 16 18 20 22 2010 2011 2012 2013 2014 NGPL Composite Spot Price NG Spot Price at Henry Hub dollars per thousand c ubic feet Note: Prices are in nominal dollars. Source: Table 3. Figure 3. Average citygate and consumer prices of natural gas in the United States, 2010-2013 Figure 4. Spot prices of natural gas and natural gas plant liquids in the United States, 2010-2013

114

Kaganovich et al Supplementary Figure S1  

E-Print Network (OSTI)

n n Kaganovich et al Supplementary Figure S1 WT+MG13237°Ccim3-1 Ubc9 ts Ubc9 ts 37°C a b n n cim3 al Supplementary Figure S2 c b ts cim3-1 (min): 0 5 10 15 60 60 GFP-Ubc9 + 20M Benomyltime at 37 °C Figure S3 GFP-VHL T S P T S P 30°C 37°C 1hr Ub-GFP Sup-Pellet assay cim3-1 GFP-VHL a b VHL in cim3

Bedwell, David M.

115

Robust optimal decisions with imprecise forecasts  

Science Conference Proceedings (OSTI)

A robust minimax approach for optimal investment decisions with imprecise return forecasts and risk estimations in financial portfolio management is considered. Single-period and multi-period mean-variance optimization models are extended to worst-case ... Keywords: Minimax, Rival scenarios, Robust optimization

Nalan Gülp?nar; Berc Rustem

2007-04-01T23:59:59.000Z

116

A Diagnostic Verification of the Precipitation Forecasts Produced by the Canadian Ensemble Prediction System  

Science Conference Proceedings (OSTI)

A comparatively long period of relative stability in the evolution of the Canadian Ensemble Forecast System was exploited to compile a large homogeneous set of precipitation forecasts. The probability of exceedance of a given threshold was ...

Syd Peel; Laurence J. Wilson

2008-08-01T23:59:59.000Z

117

Monthly Forecast of the Madden–Julian Oscillation Using a Coupled GCM  

Science Conference Proceedings (OSTI)

A set of five-member ensemble forecasts initialized daily for 48 days during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment period are performed with the ECMWF monthly forecasting system in order to assess its ...

Frédéric Vitart; Steve Woolnough; M. A. Balmaseda; A. M. Tompkins

2007-07-01T23:59:59.000Z

118

The Role of Latent Heat Release in Explosive Cyclogenesis: Three Examples Based on ECMWF Operational Forecasts  

Science Conference Proceedings (OSTI)

Operational forecasts from the European Centre for Medium Range Weather Forecasts of three cases of explosive cyclogenesis of large magnitude that occurred in the North Atlantic during a 1-week period in January 1986 are presented, and results of ...

Richard J. Reed; Mark D. Albright; Adrian J. Sammons; Per Undén

1988-09-01T23:59:59.000Z

119

Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part I: Two-Meter Temperatures  

Science Conference Proceedings (OSTI)

Recently, the European Centre for Medium-Range Weather Forecasts (ECMWF) produced a reforecast dataset for a 2005 version of their ensemble forecast system. The dataset consisted of 15-member reforecasts conducted for the 20-yr period 1982–2001, ...

Renate Hagedorn; Thomas M. Hamill; Jeffrey S. Whitaker

2008-07-01T23:59:59.000Z

120

Evaluation of the IRI'S “Net Assessment” Seasonal Climate Forecasts: 1997–2001  

Science Conference Proceedings (OSTI)

The International Research Institute for Climate Prediction (IRI) net assessment seasonal temperature and precipitation forecasts are evaluated for the 4-yr period from October–December 1997 to October–December 2001. These probabilistic forecasts ...

L. Goddard; A. G. Barnston; S. J. Mason

2003-12-01T23:59:59.000Z

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


121

Impact Of Cumulus Initialization on the Spinup of Precipitation Forecasts in the Tropics  

Science Conference Proceedings (OSTI)

In order to ameliorate the precipitation spinup problem (prediction models’ inability to produce realistic precipitation rates at the beginning of the forecast period), the impact of a tropical initialization procedure on precipitation forecasts ...

Akira Kasahara; Arthur P. Mizzi; Leo J. Donner

1992-07-01T23:59:59.000Z

122

Figure ES1. Map of Northern Alaska  

U.S. Energy Information Administration (EIA) Indexed Site

Figure ES1. Map of Northern Alaska figurees1.jpg (61418 bytes) Source: Edited from U.S. Geological Survey, "The Oil and Gas Resource Potential of the Arctic National Wildlife...

123

arXiv.org help - Bitmapping Figures  

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

Bitmapping Figures Many graphics and plotting programs do not take into account that people might want to send their output over the internet instead of to a local printer. These...

124

Microsoft Word - figure_08_2008.doc  

Annual Energy Outlook 2012 (EIA)

9 48.5 Egypt Japan Canada Mexico Figure 8. Flow of Natural Gas Imports and Exports, 2007 (Billion Cubic Feet) Note: U.S. exports to Canada and Mexico include liquefied natural gas...

125

Microsoft Word - Figure_8_Oct2009.doc  

Gasoline and Diesel Fuel Update (EIA)

19 50 Japan Canada Mexico Figure 8. Flow of Natural Gas Imports and Exports, 2008 (Billion Cubic Feet) Note: U.S. exports to Canada and Mexico include liquefied natural gas (LNG)....

126

EIS-0023-FEIS-Figures-1979.pdf  

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

NORTM NORTM CAROLINA 2 -- r /'- 3Charlo,te Gree,v:; I, o s. \ '~ ( % SOUTH CAROLINA ".4 o " .Alkenoco'"mb'a A1l.a,to \ August. ( SRP O Macon \ GEORGIA ? Charleston 50 MI ".* / 100 Ml 150 Mi 1 \ ATLANTIC OCEAN Sov.nn.h / FIGURE III-1. Location of SRP Relative to Surrounding Population Centers III-2 --- - FIGURE III-2. The Savannah River Plant III-3 FIGURE 'III-3. Profile of Geologic Formation Beneath the Savannah River Plant . III-5 ,-, -,.. . . . . . 5 .-- -612 CRYSTALLINE ROCK . II rfoce FIGURE III-4. Hydrostatic Head in Ground Water Near H Area III-8 ~'z 'Kw ) -.- ________ Alu EN F PLATEAU ";<--'-----% \ ~//i.s,t,,7 --- I '220--- Heed in Tuscaloosa ft H20 obove me.. $,0 level - 5 0 5 10 ,5 MILES FIGURE III-5. Flow in Tuscaloosa Aquifer (Ongoing hydrographic measurements indicate that this flow pattern has remained the same under the SRP site since the early 1950' s.) 111-10 . FIGURE

127

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

128

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

129

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

130

Wet-Etch Figuring Optical Figuring by Controlled Application of Liquid Etchant  

SciTech Connect

WET-ETCH FIGURING (WEF) is an automated method of precisely figuring optical materials by the controlled application of aqueous etchant solution. This technology uses surface-tension-gradient-driven flow to confine and stabilize a wetted zone of an etchant solution or other aqueous processing fluid on the surface of an object. This wetted zone can be translated on the surface in a computer-controlled fashion for precise spatial control of the surface reactions occurring (e.g. chemical etching). WEF is particularly suitable for figuring very thin optical materials because it applies no thermal or mechanical stress to the material. Also, because the process is stress-free the workpiece can be monitored during figuring using interferometric metrology, and the measurements obtained can be used to control the figuring process in real-time--something that cannot be done with traditional figuring methods.

Britten, J

2001-02-13T23:59:59.000Z

131

Probabilistic Forecasts from the National Digital Forecast Database  

Science Conference Proceedings (OSTI)

The Bayesian processor of forecast (BPF) is developed for a continuous predictand. Its purpose is to process a deterministic forecast (a point estimate of the predictand) into a probabilistic forecast (a distribution function, a density function, ...

Roman Krzysztofowicz; W. Britt Evans

2008-04-01T23:59:59.000Z

132

forecast | OpenEI  

Open Energy Info (EERE)

Browse Upload data GDR Community Login | Sign Up Search Facebook icon Twitter icon forecast Dataset Summary Description The EIA's annual energy outlook (AEO) contains yearly...

133

Seasonal tropical cyclone forecasts  

E-Print Network (OSTI)

Seasonal forecasts of tropical cyclone activity in various regions have been developed since the first attempts in the early 1980s by Neville

Suzana J. Camargo; Anthony G. Barnston; Philip J. Klotzbach; Christopher W. Landsea

2007-01-01T23:59:59.000Z

134

Solar forecasting review  

E-Print Network (OSTI)

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

Inman, Richard Headen

2012-01-01T23:59:59.000Z

135

Solar forecasting review  

E-Print Network (OSTI)

Online 24-h solar power forecasting based on weather typeweather observations at blue hill massachusetts,” Solarof weather patterns on the intensity of solar irradiance;

Inman, Richard Headen

2012-01-01T23:59:59.000Z

136

Temperature Forecast Biases Associated with Snow Cover in the Northeast  

Science Conference Proceedings (OSTI)

The sensitivity of temperature forecast biases to the presence or absence of snow cover is investigated for the December–March periods of 1985–1986 and 1986–87 at ten stations in the northeastern United States. Forecast biases are consistently “...

Gary S. Wojcik; Daniel S. Wilks

1992-09-01T23:59:59.000Z

137

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

138

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

139

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

140

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

Note: This page contains sample records for the topic "forecast period figure" 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

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

142

Does the term structure forecast  

E-Print Network (OSTI)

provides more accurate forecasts of real consumption growth14. Harvey, C.R. (1989): \\Forecasts of economic growth fromC.R. (1993): \\Term structure forecasts economic growth", Fi-

Berardi, Andrea; Torous, Walter

2002-01-01T23:59:59.000Z

143

Distortion Representation of Forecast Errors  

Science Conference Proceedings (OSTI)

Forecast error is decomposed into three components, termed displacement error, amplitude error, mid residual error, respectively. Displacement error measures how much of the forecast error can be accounted for by moving the forecast to best fit ...

Ross N. Hoffman; Zheng Liu; Jean-Francois Louis; Christopher Grassoti

1995-09-01T23:59:59.000Z

144

Composite forecasting in commodity systems  

E-Print Network (OSTI)

Paper No. COMPOSI1E FORECASTING IN CO/Yt.flDITI SYSTfu\\1S1980 .i CfIAPTER COMPOSITE FORECASTING IN COMMOOITY SYSTEMS*to utilizeeconometric .modelsfor forecasting ! ,urposes. The

Johnson, Stanley R; Rausser, Gordon C.

1980-01-01T23:59:59.000Z

145

Coefficients for Debiasing Forecasts  

Science Conference Proceedings (OSTI)

Skill-score decompositions can be used to analyze the effects of bias on forecasting skill. However, since bias terms are typically squared, and bias is measured in skill-score units rather than in units of the forecasts, such decompositions only ...

Thomas R. Stewart; Patricia Reagan-Cirincione

1991-08-01T23:59:59.000Z

146

Evaluating Point Forecasts  

E-Print Network (OSTI)

Typically, point forecasting methods are compared and assessed by means of an error measure or scoring function, such as the absolute error or the squared error. The individual scores are then averaged over forecast cases, to result in a summary measure of the predictive performance, such as the mean absolute error or the (root) mean squared error. I demonstrate that this common practice can lead to grossly misguided inferences, unless the scoring function and the forecasting task are carefully matched. Effective point forecasting requires that the scoring function be specified ex ante, or that the forecaster receives a directive in the form of a statistical functional, such as the mean or a quantile of the predictive distribution. If the scoring function is specified ex ante, the forecaster can issue the optimal point forecast, namely, the Bayes rule. If the forecaster receives a directive in the form of a functional, it is critical that the scoring function be consistent for it, in the sense that the expect...

Gneiting, Tilmann

2009-01-01T23:59:59.000Z

147

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

148

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2004 with Projections to 2025 Forecast Comparisons Index (click to jump links) Economic Growth World Oil Prices Total Energy Consumption Electricity Natural Gas Petroleum Coal The AEO2004 forecast period extends through 2025. One other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a similar time horizon. Several others provide forecasts that address one or more aspects of energy markets over different time horizons. Recent projections from GII and others are compared here with the AEO2004 projections. Economic Growth Printer Friendly Version Average annual percentage growth Forecast 2002-2008 2002-2013 2002-2025 AEO2003 3.2 3.3 3.1 AEO2004 Reference 3.3 3.2 3.0

149

A RELM earthquake forecast based on pattern informatics  

E-Print Network (OSTI)

We present a RELM forecast of future earthquakes in California that is primarily based on the pattern informatics (PI) method. This method identifies regions that have systematic fluctuations in seismicity, and it has been demonstrated to be successful. A PI forecast map originally published on 19 February 2002 for southern California successfully forecast the locations of sixteen of eighteen M>5 earthquakes during the past three years. The method has also been successfully applied to Japan and on a worldwide basis. An alternative approach to earthquake forecasting is the relative intensity (RI) method. The RI forecast map is based on recent levels of seismic activity of small earthquakes. Recent advances in the PI method show considerable improvement, particularly when compared with the RI method using relative operating characteristic (ROC) diagrams for binary forecasts. The RELM application requires a probability for each location for a number of magnitude bins over a five year period. We have therefore co...

Holliday, J R; Donnelan, A; Rundle, J B; Tiampo, K F; Turcotte, D L; Chen, Chien-chih; Donnelan, Andrea; Holliday, James R.; Rundle, John B.; Tiampo, Kristy F.; Turcotte, Donald L.

2005-01-01T23:59:59.000Z

150

Multimodel Approach Based on Evidence Theory for Forecasting Tropical Cyclone Tracks  

Science Conference Proceedings (OSTI)

In this paper a new multimodel approach for forecasting tropical cyclone tracks is presented. The approach is based on the Dempster–Shafer theory of evidence. At each forecast period, the multimodel forecast is given as an area where the tropical ...

Svetlana V. Poroseva; Nathan Lay; M. Yousuff Hussaini

2010-02-01T23:59:59.000Z

151

Optimization and adjustment policy of two-echelon reservoir inventory management with forecast updates  

Science Conference Proceedings (OSTI)

A finite-horizon, periodic-review inventory model with inflow forecasting updates following the Martingale Model of Forecast Evolution (MMFE) in multiresevoirs is considered. This model introduces a new method of determining an operating policy in which ... Keywords: Adjustment, DP, Inflow forecasts, MMFE, Reservoir

Yingcheng Xu; Li Wang; Zhisong Chen; Siqing Shan; Guoping Xia

2012-12-01T23:59:59.000Z

152

A New Verification Score for Public Forecasts  

Science Conference Proceedings (OSTI)

CREF, a new verification score for public forecasts, is introduced. This verification score rewards a forecaster who forecasts a rare event accurately. CREF was used to verify local forecasts at the Weather Service Forecast Office (WSFO) in ...

Dean P. Gulezian

1981-02-01T23:59:59.000Z

153

EIS-0317-S1: Environmental Impact Statement, Maps and Figures...  

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

Environmental Impact Statement, Maps and Figures Kangley-Echo Lake Transmission Line Project Maps and Figures Bonneville Power Administration is proposing to build a new...

154

Sheet Metal Forming: A Review - Figure 18 - TMS  

Science Conference Proceedings (OSTI)

Figure 18. Fracture and local necking strains in aluminum alloy 5154. Under balanced biaxial tension, failure occurs by fracture before local necking. Figure 18 ...

155

Figure 2. Energy Consumption of Vehicles, Selected Survey Years  

U.S. Energy Information Administration (EIA) Indexed Site

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 2 Figure 2. Energy Consumption of Vehicles, Selected Survey Years...

156

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

157

The NCEP Climate Forecast System Reanalysis  

Science Conference Proceedings (OSTI)

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to ...

Suranjana Saha; Shrinivas Moorthi; Hua-Lu Pan; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; Robert Kistler; John Woollen; David Behringer; Haixia Liu; Diane Stokes; Robert Grumbine; George Gayno; Jun Wang; Yu-Tai Hou; Hui-Ya Chuang; Hann-Ming H. Juang; Joe Sela; Mark Iredell; Russ Treadon; Daryl Kleist; Paul Van Delst; Dennis Keyser; John Derber; Michael Ek; Jesse Meng; Helin Wei; Rongqian Yang; Stephen Lord; Huug Van Den Dool; Arun Kumar; Wanqiu Wang; Craig Long; Muthuvel Chelliah; Yan Xue; Boyin Huang; Jae-Kyung Schemm; Wesley Ebisuzaki; Roger Lin; Pingping Xie; Mingyue Chen; Shuntai Zhou; Wayne Higgins; Cheng-Zhi Zou; Quanhua Liu; Yong Chen; Yong Han; Lidia Cucurull; Richard W. Reynolds; Glenn Rutledge; Mitch Goldberg

2010-08-01T23:59:59.000Z

158

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

159

The WGNE Assessment of Short-term Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

Twenty-four-hour and 48-h quantitative precipitation forecasts (QPFs) from 11 operational numerical weather prediction models have been verified for a 4-yr period against rain gauge observations over the United States, Germany, and Australia to ...

Elizabeth E. Ebert; Ulrich Damrath; Werner Wergen; Michael E. Baldwin

2003-04-01T23:59:59.000Z

160

An Assessment of the Quality of Forecast Trajectories  

Science Conference Proceedings (OSTI)

Forecast and “analysis” (reference) trajectories were computed from six sites over North America at three altitudes (500, 1000, and 1500 m above ground) twice a day for a one-year period using Nested Grid Model wind fields. The reference ...

Barbara J. B. Stunder

1996-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Microsoft Word - Figure_14_15.doc  

Gasoline and Diesel Fuel Update (EIA)

44 0 2 4 6 8 10 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 Dollars per Thousand Cubic Meters Constant Dollars Nominal Dollars Figure 14. Average Price of Natural Gas Delivered to Residential Consumers, 1980-2002 Figure 15. Average City Gate Price of Natural Gas in the United States, 2002 (Dollars per Thousand Cubic Feet) Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2002 dollars using the chain-type price indexes for Gross Domestic Product (1996 = 1.0) as published by the U.S. Department of Commerce, Bureau of Economic Analysis.

162

Figure and finish of grazing incidence mirrors  

SciTech Connect

Great improvement has been made in the past several years in the quality of optical components used in synchrotron radiation (SR) beamlines. Most of this progress has been the result of vastly improved metrology techniques and instrumentation permitting rapid and accurate measurement of the surface finish and figure on grazing incidence optics. A significant theoretical effort has linked the actual performance of components used as x-ray wavelengths to their topological properties as measured by surface profiling instruments. Next-generation advanced light sources will require optical components and systems to have sub-arc second surface figure tolerances. This paper will explore the consequences of these requirements in terms of manufacturing tolerances to see if the present manufacturing state-of-the-art is capable of producing the required surfaces. 15 refs., 14 figs., 2 tabs.

Takacs, P.Z. (Brookhaven National Lab., Upton, NY (USA)); Church, E.L. (Picatinny Arsenal, Dover, NJ (USA). Army Armament Research, Development and Engineering Center)

1989-08-01T23:59:59.000Z

163

Figure correction of multilayer coated optics  

DOE Patents (OSTI)

A process is provided for producing near-perfect optical surfaces, for EUV and soft-x-ray optics. The method involves polishing or otherwise figuring the multilayer coating that has been deposited on an optical substrate, in order to correct for errors in the figure of the substrate and coating. A method such as ion-beam milling is used to remove material from the multilayer coating by an amount that varies in a specified way across the substrate. The phase of the EUV light that is reflected from the multilayer will be affected by the amount of multilayer material removed, but this effect will be reduced by a factor of 1-n as compared with height variations of the substrate, where n is the average refractive index of the multilayer.

Chapman; Henry N. (Livermore, CA), Taylor; John S. (Livermore, CA)

2010-02-16T23:59:59.000Z

164

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

165

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.

166

Factors Driving Prices & Forecast  

Gasoline and Diesel Fuel Update (EIA)

This spread is a function of the balance between demand and fresh supply (production and net imports). Finally I will discuss the current forecast for distillate prices this winter...

167

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

168

Valuing Climate Forecast Information  

Science Conference Proceedings (OSTI)

The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...

Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon

1987-09-01T23:59:59.000Z

169

Multivariate Forecast Evaluation And Rationality Testing  

E-Print Network (OSTI)

1062—1088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): “OnKingdom. MULTIVARIATE FORECASTS Kirchgässner, G. , and U. K.2005): “Estimation and Testing of Forecast Rationality under

Komunjer, Ivana; OWYANG, MICHAEL

2007-01-01T23:59:59.000Z

170

Forecasting in the Presence of Level Shifts  

E-Print Network (OSTI)

accuracy. Journal of Forecasting 19 : 537-560. Hamilton JD.430. Harvey AC. 1989. Forecasting, structural time seriesMH, Timmermann A. 1994. Forecasting stock returns: An

Smith, Aaron

2004-01-01T23:59:59.000Z

171

Short-Term Energy Outlook Figures  

U.S. Energy Information Administration (EIA) Indexed Site

Independent Statistics & Analysis" Independent Statistics & Analysis" ,"U.S. Energy Information Administration" ,"Short-Term Energy Outlook Figures, December 2013" ,"U.S. Prices" ,,"West Texas Intermediate (WTI) Crude Oil Price" ,,"U.S. Gasoline and Crude Oil Prices" ,,"U.S. Diesel Fuel and Crude Oil Prices" ,,"Henry Hub Natural Gas Price" ,,"U.S. Natural Gas Prices" ,"World Liquid Fuels" ,,"World Liquid Fuels Production and Consumption Balance" ,,"Estimated Unplanned Crude Oil Production Outages Among OPEC Producers" ,,"Estimated Unplanned Crude Oil Production Disruptions Among non-OPEC Producers" ,,"World Liquid Fuels Consumption" ,,"World Liquid Fuels Consumption Growth"

172

Microsoft Word - Figure_18_19.doc  

Gasoline and Diesel Fuel Update (EIA)

9 9 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK MD 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK Figure 18. Average Price of Natural Gas Delivered to U.S. Onsystem Industrial Consumers, 2004 (Dollars per Thousand Cubic Feet) Figure 19. Average Price of Natural Gas Delivered to U.S. Electric Power Consumers, 2004 (Dollars per Thousand Cubic Feet) Source: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition." Note: States where the electric power price has been withheld (see Table 23) are included in the $0.00-$2.49 price category.

173

Microsoft Word - Figure_14_15.doc  

Gasoline and Diesel Fuel Update (EIA)

5 5 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DC NC SC GA AL MS LA FL HI AK DE 0 2 4 6 8 10 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 360 Dollars per Thousand Cubic Meters Constant Dollars Nominal Dollars Figure 14. Average Price of Natural Gas Delivered to Residential Consumers, 1980-2004 Figure 15. Average City Gate Price of Natural Gas in the United States, 2004 (Dollars per Thousand Cubic Feet) Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2004 dollars using the chain-type price indexes for Gross Domestic Product

174

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

175

An Evaluation of the Darwin Area Forecast Experiment Storm Occurrence Forecasts  

Science Conference Proceedings (OSTI)

Results from real-time forecasting the occurrence of storm activity during “break” and “transition” season flow within two 10-km-radius circles for periods up to 3 h in the tropics near Darwin, Australia (12°S, 131°E), are described. The ...

T. Keenan; R. Potts; T. Stevenson

1992-09-01T23:59:59.000Z

176

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

177

Microsoft Word - Figure_3_4.doc  

Gasoline and Diesel Fuel Update (EIA)

7 7 None 1-15,000 15,001-100,000 100,001-200,000 200,001-500,000 500,001-and over WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK GOM 0 1 2 3 4 5 6 7 T e x a s G u l f o f M e x i c o N e w M e x i c o O k l a h o m a W y o m i n g L o u i s i a n a C o l o r a d o A l a s k a K a n s a s A l a b a m a A l l O t h e r S t a t e s Trillion Cubic Feet 0 30 60 90 120 150 180 Billion Cubic Meters 2002 2003 2002 Figure 4. Marketed Production of Natural Gas in Selected States and the Gulf of Mexico, 2002-2003 Figure 3. Marketed Production of Natural Gas in the United States and the Gulf of Mexico, 2003 (Million Cubic Feet) GOM = Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-895, "Monthly and Annual Quantity and Value of Natural Gas Report," and the United States Mineral Management

178

Consensus Coal Production Forecast for  

E-Print Network (OSTI)

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

Mohaghegh, Shahab

179

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

180

Forecast Technical Document Technical Glossary  

E-Print Network (OSTI)

Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others

Note: This page contains sample records for the topic "forecast period figure" 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

Forecast Technical Document Tree Species  

E-Print Network (OSTI)

Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 ­ List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically

182

3, 21452173, 2006 Probabilistic forecast  

E-Print Network (OSTI)

HESSD 3, 2145­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC ­ Department­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction

Paris-Sud XI, Université de

183

4, 189212, 2007 Forecast and  

E-Print Network (OSTI)

OSD 4, 189­212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction

Paris-Sud XI, Université de

184

FINANCIAL FORECASTING USING GENETIC ALGORITHMS  

E-Print Network (OSTI)

predecessors to forecast stock prices and manage portfolios for approximately 3 years.) We examineFINANCIAL FORECASTING USING GENETIC ALGORITHMS SAM MAHFOUD and GANESH MANI LBS Capital Management entitled Genetic Algorithms for Inductive Learning). Time-series forecasting is a special type

Boetticher, Gary D.

185

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

186

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

SciTech Connect

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

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

2012-08-15T23:59:59.000Z

187

Microsoft Word - Figure_3_4.doc  

Gasoline and Diesel Fuel Update (EIA)

7 7 0 1 2 3 4 5 6 7 T e x a s G u l f o f M e x i c o O k l a h o m a N e w M e x i c o W y o m i n g L o u i s i a n a C o l o r a d o A l a s k a K a n s a s C a l i f o r n i a A l l O t h e r S t a t e s Trillion Cubic Feet 0 30 60 90 120 150 180 Billion Cubic Meters 2003 2004 2003 Figure 4. Marketed Production of Natural Gas in Selected States and the Gulf of Mexico, 2003-2004 GOM = Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA -895, "Monthly Quantity and Value of Natural Gas Report," and the United States Mineral Management Service. Sources: Energy Information Administration (EIA), Form EIA -895, "Monthly Quantity and Value of Natural Gas Report," and the United States Mineral Management Service. None 1-15,000 15,001-100,000 100,001-200,000 200,001-500,000 500,001-and over

188

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,

189

The Past as Prologue? Business Cycles and Forecasting since the 1960s  

E-Print Network (OSTI)

from their peak) following a sharp decline in oil prices, peak to trough period for each cycle. Figure 3 Oil Prices

Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany

2010-01-01T23:59:59.000Z

190

Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts  

E-Print Network (OSTI)

2012. This is because high natural gas prices result in a shift to wind and coal generation. Figure 2 the Aurora forecast was based on medium trend natural gas prices and average water conditions. The spike in electric prices during the fall and winter of 2005 are due to high natural gas prices following hurricanes

191

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

2005-01-01T23:59:59.000Z

192

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

193

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Richard A. Berk; Brian Kriegler; Jong-Ho Baek

2011-01-01T23:59:59.000Z

194

Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy  

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

Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. Minh Le Minh Le Program Manager, Solar Program What Do These Projects Do? The Energy Department is investing $8 million in two cutting-edge projects to increase the accuracy of solar forecasting at sub-hourly,

195

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.

196

UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM  

SciTech Connect

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

Werth, D.; Garrett, A.

2009-04-15T23:59:59.000Z

197

Southern hemisphere tropical cyclone intensity forecast methods used at the Joint Typhoon Warning Center, Part II: statistical – dynamical forecasts  

E-Print Network (OSTI)

The development and performance of a statistical- dynamical tropical cyclone intensity forecast model, which was developed for the United States of America’s Joint Typhoon Warning Center (JTWC), is described. This model, called the Southern Hemisphere Statistical Typhoon Intensity Prediction Scheme (SH STIPS), mirrors similar capabilities created for use in the western North Pacific and North Indian Ocean tropical cyclone basins. The model is created by fitting an optimal combination of factors related to climatology and persistence, intensification potential, vertical wind shear, dynamic size/intensity forecasts and atmospheric stability. All of these factors except the climatology and persistence information are derived from global forecast model analyses and forecasts. In July 2005 the SH STIPS model began a real-time evaluation period. The forecasts from the SH STIPS model have outperformed the combined climatology and persistence based forecast and thus are skillful in independent testing since that time. Since October 2006, SH STIPS has been the primary member in an operational consensus forecast of tropical cyclone intensity change provided to the JTWC. Documentation

John A. Knaff; Charles R. Sampson

2008-01-01T23:59:59.000Z

198

Solar Wind Forecasting with Coronal Holes  

E-Print Network (OSTI)

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

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

2007-01-09T23:59:59.000Z

199

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

Forecasting Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels MICHAEL YE, ∗ JOHN ZYREN, ∗∗ AND JOANNE SHORE ∗∗ Abstract This paper presents a short-term monthly forecasting model of West Texas Intermedi- ate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigat- ing the impacts of changes on price, should inventories,

200

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

Note: This page contains sample records for the topic "forecast period figure" 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

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

202

Wind forecasting objectives for utility schedulers and energy traders  

DOE Green Energy (OSTI)

The wind energy industry and electricity producers can benefit in a number of ways from increased wind forecast accuracy. Higher confidence in the reliability of wind forecasts can help persuade an electric utility to increase the penetration of wind energy into its operating system and to augment the capacity value of wind electric generation. Reliable forecasts can also assist daily energy traders employed by utilities in marketing the available and anticipated wind energy to power pools and other energy users. As the number of utilities with wind energy experience grows, and wind energy penetration levels increase, the need for reliable wind forecasts will likely grow as well. This period of wind energy growth also coincides with advances in computer weather prediction technology that could lead to more accurate wind forecasts. Thus, it is important to identify the type of forecast information needed by utility schedulers and energy traders. This step will help develop approaches to the challenge of wind forecasting that will result in useful products being supplied to utilities or other energy generating entities. This paper presents the objectives, approach, and current findings of a US Department of Energy National Renewable Energy Laboratory (DOE/NREL) initiative to develop useful wind forecasting tools for utilities involved with wind energy generation. The focus of this initiative thus far has been to learn about the needs of prospective utility users. NREL representatives conducted a series of onsite interviews with key utility staff, usually schedulers and research planners, at seven US utilities. The purpose was to ascertain information on actual scheduling and trading procedures, and how utilities could integrate wind forecasting into these activities.

Schwartz, M.N. [National Renewable Energy Lab., Golden, CO (United States); Bailey, B.H. [AWS Scientific, Inc., Albany, NY (United States)

1998-05-01T23:59:59.000Z

203

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

204

Forecast Technical Document Growing Stock Volume  

E-Print Network (OSTI)

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

205

Figure 5. Percentage change in natural gas dry production and ...  

U.S. Energy Information Administration (EIA)

Figure 5. Percentage change in natural gas dry production and number of gas wells in the United States, 2007?2011 annual ...

206

Figure 8. Renewable energy share of U.S. electricity ...  

U.S. Energy Information Administration (EIA)

Title: Figure 8. Renewable energy share of U.S. electricity generation in four cases, 2000-2040 (percent) Subject: Annual Energy Outlook 2013 Author

207

Figure 79. Electricity sales and power sector generating ...  

U.S. Energy Information Administration (EIA)

Title: Figure 79. Electricity sales and power sector generating capacity, 1949-2040 (index, 1949 = 1.0) Subject: Annual Energy Outlook 2013 Author

208

Figure 15. Renewable electricity generation in three cases ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 15. Renewable electricity generation in three cases, 2005-2040 (billion kilowatthours) Extended Policies No Sunset ...

209

Figure 17. Electricity generation from natural gas in ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 17. Electricity generation from natural gas in three cases, 2005-2040 (billion kilowatthours) Extended Policies No Sunset

210

Figure 14. Lease condensate and natural gas plant liquids ...  

U.S. Energy Information Administration (EIA)

Figure 14 Date % LC % NGPL NGL Reserves Bn Barrels OGR-Brent Average 2009-2011 Liquids Reserves NGPL Reserves Condensate Reserves % Lease condensate ...

211

Figure 38. Levelized costs of nuclear electricity generation in ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 38. Levelized costs of nuclear electricity generation in two cases, 2025 (2011 dollars per megawatthour) Reference Small Modular Reactor

212

Figure 18. Energy-related carbon dioxide emissions in three ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 18. Energy-related carbon dioxide emissions in three cases, 2005-2040 (million metric tons) Extended Policies No Sunset

213

Ayn Rand, Alberti and the Authorial Figure of the Architect  

E-Print Network (OSTI)

Authorial Figure of the Architect Marvin Trachtenberg Whatnor was it written by an architect, historian, or critic. InRoark, an aspiring architect who, echoing the megalomania of

Trachtenberg, Marvin

2011-01-01T23:59:59.000Z

214

Figure 1. Microsupercapacitors developed with novel carbon nano-  

E-Print Network (OSTI)

Figure 1. Microsupercapacitors developed with novel carbon nano- onion electrodes exhibit extremely resolution (Balke et al, Nano Letters 10, 3420, 2010). #12;

215

Mobility of Ions in Lanthanum Fluoride Nanoclusters--Figure 9  

Science Conference Proceedings (OSTI)

c, d. Figure 9. Shows the r-dependence of this function at several different temperatures. At each temperature the upper graph represents the F- van Hove ...

216

Figure 58. Residential sector adoption of renewable energy ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 58. Residential sector adoption of renewable energy technologies in two cases, 2005-2040 PV and wind (gigawatts) Heat pump ...

217

Figure 64. Industrial energy consumption by fuel, 2011, 2025, and ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 64. Industrial energy consumption by fuel, 2011, 2025, and 2040 (quadrillion Btu) Natural Gas Petroleum and other liquids

218

Figure 63. Industrial delivered energy consumption by application ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 63. Industrial delivered energy consumption by application, 2011-2040 (quadrillion Btu) Manufacturing heat and power Nonmanufacturing heat ...

219

Figure 51. World production of liquids from biomass, coal ...  

U.S. Energy Information Administration (EIA)

Title: Figure 51. World production of liquids from biomass, coal, and natural gas in three cases, 2011 and 2040 (million barrels per day) Subject

220

Figure 57. Change in residential delivered energy consumption ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 57. Change in residential delivered energy consumption for selected end uses in four cases, 2011-2040 (percent) Best Available Technology

Note: This page contains sample records for the topic "forecast period figure" from the National Library of EnergyBeta (NLEBeta).
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to obtain the most current and comprehensive results.


221

Figure 59. Commercial delivered energy intensity in four cases ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 59. Commercial delivered energy intensity in four cases, 2005-2040 (index, 2005 = 1) Reference case 2011 Technology case

222

Figure 55. Residential delivered energy intensity in four ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 55. Residential delivered energy intensity in four cases, 2005-2035 (index, 2005 = 1) Best Available Technology case High Technology case

223

Annual Energy Outlook with Projections to 2025-Figure 1. Energy...  

Gasoline and Diesel Fuel Update (EIA)

With Projections to 2025 Figure 1. Energy price projectionsm 2001-2025: AEO2002 and AEO2003 compared (2001 dollars). For more detailed information, contact the National Energy...

224

Figure 34. Ratio of average per megawatthour fuel costs ...  

U.S. Energy Information Administration (EIA)

Title: Figure 34. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the RFC west ...

225

Figure 77. Electricity generation capacity additions by fuel type ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 77. Electricity generation capacity additions by fuel type, including combined heat and power, 2012-2040 (gigawatts) Coal

226

Figure 6. Type of Homes by Insulation, 2001  

U.S. Energy Information Administration (EIA)

Home >>Residential Home Page>>Insulation > Figure 6. Type of Homes by Insulation, 2001. To Top. Contacts: Specific questions may be directed to:

227

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

228

Studies of inflation and forecasting.  

E-Print Network (OSTI)

??This dissertation contains five research papers in the area of applied econometrics. The two broad themes of the research are inflation and forecasting. The first… (more)

Bermingham, Colin

2011-01-01T23:59:59.000Z

229

UWIG Forecasting Workshop -- Albany (Presentation)  

SciTech Connect

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

Lew, D.

2011-04-01T23:59:59.000Z

230

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

231

Development and testing of improved statistical wind power forecasting methods.  

DOE Green Energy (OSTI)

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

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

2011-12-06T23:59:59.000Z

232

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

Science Conference Proceedings (OSTI)

An ensemble of cloud-resolving forecasts from the Weather Research and Forecasting model (WRF) was used to study error covariance for Hurricane Katrina (2005) during a 64-h period in which the storm progressed from a tropical storm to a category-4 ...

Jonathan Poterjoy; Fuqing Zhang

2011-08-01T23:59:59.000Z

233

On the Prediction of Forecast Skill  

Science Conference Proceedings (OSTI)

Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The first, giving the consistency between adjacent forecasts, ...

T. N. Palmer; S. Tibaldi

1988-12-01T23:59:59.000Z

234

Equitable Skill Scores for Categorical Forecasts  

Science Conference Proceedings (OSTI)

Many skill scores used to evaluate categorical forecasts of discrete variables are inequitable, in the sense that constant forecasts of some events lead to better scores than constant forecasts of other events. Inequitable skill scores may ...

Lev S. Gandin; Allan H. Murphy

1992-02-01T23:59:59.000Z

235

Evaluation of errors in national energy forecasts.  

E-Print Network (OSTI)

??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts… (more)

Sakva, Denys

2005-01-01T23:59:59.000Z

236

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

237

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

2013-10-01T23:59:59.000Z

238

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

239

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

240

Improving Forecast Communication: Linguistic and Cultural Considerations  

Science Conference Proceedings (OSTI)

One goal of weather and climate forecasting is to inform decision making. Effective communication of forecasts to various sectors of the public is essential for meeting that goal, yet studies repeatedly show that forecasts are not well understood ...

Karen Pennesi

2007-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

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

242

Probabilistic Verification of Monthly Temperature Forecasts  

Science Conference Proceedings (OSTI)

Monthly forecasting bridges the gap between medium-range weather forecasting and seasonal predictions. While such forecasts in the prediction range of 1–4 weeks are vital to many applications in the context of weather and climate risk management, ...

Andreas P. Weigel; Daniel Baggenstos; Mark A. Liniger; Frédéric Vitart; Christof Appenzeller

2008-12-01T23:59:59.000Z

243

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

244

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

245

A Forecast for the California Labor Market  

E-Print Network (OSTI)

issue for the state. A Forecast for the California Laborto Go? ” The UCLA Anderson Forecast for the Nation andAngeles: UCLA Anderson Forecast: Nation 1.1 – 1.9. Dhawan,

Mitchell, Daniel J. B.

2001-01-01T23:59:59.000Z

246

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2

247

Operational Forecaster Uncertainty Needs and Future Roles  

Science Conference Proceedings (OSTI)

Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are ...

David R. Novak; David R. Bright; Michael J. Brennan

2008-12-01T23:59:59.000Z

248

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

249

CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST  

E-Print Network (OSTI)

1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find

Paris-Sud XI, Université de

250

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

251

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

252

Forecasting Electric Vehicle Costs with Experience Curves  

E-Print Network (OSTI)

April, 5. R 2~1. Dino. "Forecasting the Price Evolution of 1ElectromcProducts," Ioumal of Forecasting, ¥oL4, No I, 1985.costs and a set of forecasting tools that can be refined as

Lipman, Timonthy E.; Sperling, Daniel

2001-01-01T23:59:59.000Z

253

Evaluating Probabilistic Forecasts Using Information Theory  

Science Conference Proceedings (OSTI)

The problem of assessing the quality of an operational forecasting system that produces probabilistic forecasts is addressed using information theory. A measure of the quality of the forecasting scheme, based on the amount of a data compression ...

Mark S. Roulston; Leonard A. Smith

2002-06-01T23:59:59.000Z

254

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

255

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

256

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

257

The evolution of consensus in macroeconomic forecasting  

E-Print Network (OSTI)

When professional forecasters repeatedly forecast macroeconomic variables, their forecasts may converge over time towards a consensus. The evolution of consensus is analyzed with Blue Chip data under a parametric polynomial decay function that permits flexibility in the decay path. For the most part, this specification fits the data. We test whether forecast differences decay to zero at the same point in time for a panel of forecasters, and discuss possible explanations for this, along with its implications for studies using panels of forecasters.

Allan W. Gregory; James Yetman; Jel Codes C E; Robert Eggert; Fred Joutz

2004-01-01T23:59:59.000Z

258

Background pollution forecast over bulgaria  

Science Conference Proceedings (OSTI)

Both, the current level of air pollution studies and social needs in the country, are in a stage mature enough for creating Bulgarian Chemical Weather Forecasting and Information System The system is foreseen to provide in real time forecast of the spatial/temporal ...

D. Syrakov; K. Ganev; M. Prodanova; N. Miloshev; G. Jordanov; E. Katragkou; D. Melas; A. Poupkou; K. Markakis

2009-06-01T23:59:59.000Z

259

Frequency Dependence in Forecast Skill  

Science Conference Proceedings (OSTI)

A method is proposed to calculate measures of forecast skill for high, medium and low temporal frequency variations in the atmosphere. This method is applied to a series of 128 consecutive 1 to 10-day forecasts produced at NMC with their ...

H. M. van Den Dool; Suranjana Saha

1990-01-01T23:59:59.000Z

260

41 List of Figures, Tables and Examples  

E-Print Network (OSTI)

This report was prepared by Brian Curtis as an independent consultant to the U.S. Department of Energy. It is intended to provide an objective view of the evolving ethanol industry and many of its key participants. It is the first effort to establish an annual “Year in Review, ” report for use by industry, investors, policy makers and regulators. This report covers the period Jan 2007 – Feb 2008. FUNDED BY THE OFFICE OF THE BIOMASS PROGRAM The Office of Energy Efficiency and Renewable Energy’s Biomass Program works with industry, academia and national laboratory partners on a balanced approach to advance biomass as a significant and sustainable energy source for the 21st century. Through research, development and demonstration efforts geared towards establishing the integrated biorefinery model, the Biomass Program is helping transform the nation’s renewable and abundant biomass resources into cost competitive high performance biofuels, bioproducts and biopower. In his 2007 State of the Union address, the President established aggressive goals to reduce gasoline consumption through efficiency and adoption of alternative fuels, resulting in the December 2007 passage of the Energy Independence and Security Act of 2007. Consequently, the Biomass Program is focusing its efforts to ensure that advanced biofuels are cost competitive by 2012. Another major effort of the Program is to further develop infrastructure and opportunities for market penetration of biobased fuels and products.

unknown authors

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Essays in International Macroeconomics and Forecasting  

E-Print Network (OSTI)

This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks, is capable of explaining the highly positive correlation across the industrialized countries' inflation even though their cross-country correlation in money growth rate is negligible. The structure of this model generates cross-country correlations of inflation, output and consumption that appear to closely correspond to the data. Additionally, this model can explain the internal correlation between inflation and output observed in the data. The second essay presents two important results. First, gains from monetary policy cooperation are different from zero when the elasticity of substitution between domestic and imported goods consumption is different from one. Second, when monetary policy is endogenous in a two-country model, the only Nash equilibria supported by this model are those that are symmetrical. That is, all exporting firms in both countries choose to price in their own currency, or all exporting firms in both countries choose to price in the importer's currency. The last essay provides both conditional and unconditional predictive ability evaluations of the aluminum futures contracts prices, by using five different econometric models, in forecasting the aluminum spot price monthly return 3, 15, and 27-months ahead for the sample period 1989.01-2010.10. From these evaluations, the best model in forecasting the aluminum spot price monthly return 3 and 15 months ahead is followed by a (VAR) model whose variables are aluminum futures contracts price, aluminum spot price and risk free interest rate, whereas for the aluminum spot price monthly return 27 months ahead is a single equation model in which the aluminum spot price today is explained by the aluminum futures price 27 months earlier. Finally, it shows that iterated multiperiod-ahead time series forecasts have a better conditional out-of-sample forecasting performance of the aluminum spot price monthly return when an estimated (VAR) model is used as a forecasting tool.

Bejarano Rojas, Jesus Antonio

2011-08-01T23:59:59.000Z

262

Electricity price forecasting in a grid environment.  

E-Print Network (OSTI)

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate… (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

263

Improving Forecasting: A plea for historical retrospectives  

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

Improving Forecasting: A plea for historical retrospectives Title Improving Forecasting: A plea for historical retrospectives Publication Type Journal Article Year of Publication...

264

Application of DSM evaluation studies to utility forecasting and planning  

SciTech Connect

Utilities and their customers have made substantial investments in utility demand-side management (DSM) programs. These DSM programs also represent a substantial electricity resource. DSM program performance has been studied more systematically in recent years than over any previous period. DSM program evaluations are traditionally targeted to meet the program manager`s need for information on program costs and performance and, more recently, to verify savings to regulators for incentive awards and lost revenue recovery. Yet evaluations may also be used to produce results relevant to utility forecasting and planning. Applying evaluation results is especially important for utilities with substantial current and future commitments to acquiring demand-side resources. This report discusses the application of evaluation results to utility forecasting and planning. The report has three objectives. First, we identify what demand forecasters, DSM forecasters, and resource planners want to learn from evaluations. Second, we identify and describe the major obstacles and problems associated with applying evaluation results and illustrate many of these issues through a specific evaluation application exercise. Finally, we suggest approaches for addressing these major problems. The report summarizes results from interviews with utilities, regulators, and consultants to determine how the industry currently applies evaluation results in forecasting and planning. The report also includes results from case studies of Sacramento Municipal Utility District and Southern California Edison Company, utilities with large DSM programs and active evaluation efforts. Finally, we draw on a specific application exercise in which we used a set of impact evaluations to revise a utility DSM forecast.

Baxter, L.W.

1995-02-01T23:59:59.000Z

265

Weather-based forecasts of California crop yields  

SciTech Connect

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

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

2005-09-26T23:59:59.000Z

266

Forecasting cosmological constraints from age of high-z galaxies  

E-Print Network (OSTI)

We perform Monte Carlo simulations based on current age estimates of high-z objects to forecast constraints on the equation of state (EoS) of the dark energy. In our analysis, we use two different EoS parameterizations, namely, the so-called CPL and its uncorrelated form and calculate the improvements on the figure of merit for both cases. Although there is a clear dependence of the FoM with the size and accuracy of the synthetic age samples, we find that the most substantial gain in FoM comes from a joint analysis involving age and baryon acoustic oscillation data.

C. A. P. Bengaly Jr.; M. A. Dantas; J. C. Carvalho; J. S. Alcaniz

2013-08-28T23:59:59.000Z

267

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

268

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

269

Probabilistic aspects of meteorological and ozone regional ensemble forecasts  

SciTech Connect

This study investigates whether probabilistic ozone forecasts from an ensemble can be made with skill; i.e., high verification resolution and reliability. Twenty-eight ozone forecasts were generated over the Lower Fraser Valley, British Columbia, Canada, for the 5-day period 11-15 August 2004, and compared with 1-hour averaged measurements of ozone concentrations at five stations. The forecasts were obtained by driving the CMAQ model with four meteorological forecasts and seven emission scenarios: a control run, {+-} 50% NO{sub x}, {+-} 50% VOC, and {+-} 50% NO{sub x} combined with VOC. Probabilistic forecast quality is verified using relative operating characteristic curves, Talagrand diagrams, and a new reliability index. Results show that both meteorology and emission perturbations are needed to have a skillful probabilistic forecast system--the meteorology perturbation is important to capture the ozone temporal and spatial distribution, and the emission perturbation is needed to span the range of ozone-concentration magnitudes. Emission perturbations are more important than meteorology perturbations for capturing the likelihood of high ozone concentrations. Perturbations involving NO{sub x} resulted in a more skillful probabilistic forecast for the episode analyzed, and therefore the 50% perturbation values appears to span much of the emission uncertainty for this case. All of the ensembles analyzed show a high ozone concentration bias in the Talagrand diagrams, even when the biases from the unperturbed emissions forecasts are removed from all ensemble members. This result indicates nonlinearity in the ensemble, which arises from both ozone chemistry and its interaction with input from particular meteorological models.

Monache, L D; Hacker, J; Zhou, Y; Deng, X; Stull, R

2006-03-20T23:59:59.000Z

270

Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets  

Science Conference Proceedings (OSTI)

This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

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

2005-02-09T23:59:59.000Z

271

Forecasting Cloud Cover and Atmospheric Seeing for Astronomical Observing: Application and Evaluation of the Global Forecast System  

E-Print Network (OSTI)

To explore the issue of performing a non-interactive numerical weather forecast with an operational global model in assist of astronomical observing, we use the Xu-Randall cloud scheme and the Trinquet-Vernin AXP seeing model with the global numerical output from the Global Forecast System to generate 3-72h forecasts for cloud coverage and atmospheric seeing, and compare them with sequence observations from 9 sites from different regions of the world with different climatic background in the period of January 2008 to December 2009. The evaluation shows that the proportion of prefect forecast of cloud cover forecast varies from ~50% to ~85%. The probability of cloud detection is estimated to be around ~30% to ~90%, while the false alarm rate is generally moderate and is much lower than the probability of detection in most cases. The seeing forecast has a moderate mean difference (absolute mean difference <0.3" in most cases) and root-mean-square-error or RMSE (0.2"-0.4" in most cases) comparing with the obs...

Ye, Q -z

2010-01-01T23:59:59.000Z

272

shown in Figure1. Figure 1- Site Plan National Grid Reference  

E-Print Network (OSTI)

Scroby Sands Offshore Wind Farm’s third year of operation is summarised in this report. The operation in the two previous years has similarly been reported previously. Scroby Sands Offshore Wind Farm is situated on a sand bank a little over two nautical miles off the coast of Norfolk and consists of 30 2MW turbines giving a capacity of 60MW. The wind farm has completed its third year of operation as summarised within this report. Scroby Sands is a pioneering project being one of the first offshore wind farms in the UK. The learning and experience in operating and maintaining the wind farm has been instrumental in improving reliability, reducing maintenance costs and reducing repair durations. The third year of operation has been successful with both the availability and production performance of the wind farm better than forecast. This was achieved despite the unexpected failure in April of both a cable transition joint (repaired promptly in April) and a sub-sea cable on one of

unknown authors

2007-01-01T23:59:59.000Z

273

Current Forecast for Sunspot Cycle 24 Parameters  

Science Conference Proceedings (OSTI)

Our prediction for the development of sunspot cycle 23 activity came true; one of the very few to have attained this status. We use the 3?cycle quasi?periodicity observed in the planetary index Ap. We improve our method by including data for 150 years and draw inferences as to what to expect for the development phase of cycle 24. Our forecast for the smoothed sunspot number at cycle 24 peak 78±5 in June 2013; the possibility that next three cycles may be progressively less active cannot be ruled out; the trend may possibly continue for the rest of the 21st century.

H. S. Ahluwalia; R. C. Ygbuhay

2010-01-01T23:59:59.000Z

274

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

Science Conference Proceedings (OSTI)

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

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

2011-08-15T23:59:59.000Z

275

Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns  

DOE Green Energy (OSTI)

The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

2011-09-13T23:59:59.000Z

276

Verification of The Weather Channel Probability of Precipitation Forecasts  

Science Conference Proceedings (OSTI)

The Weather Channel (TWC) is a leading provider of weather information to the general public. In this paper the reliability of their probability of precipitation (PoP) forecasts over a 14-month period at 42 locations across the United States is ...

J. Eric Bickel; Seong Dae Kim

2008-12-01T23:59:59.000Z

277

A Classical-REEP Short-Range Forecast Procedure  

Science Conference Proceedings (OSTI)

A statistical technique has been designed to assist in the forecasting of weather elements in the 0–12-h time period. The method uses only the last two surface hourly observations for a particular station as predictors, and thus is suitable for ...

L. J. Wilson; Réal Sarrazin

1989-12-01T23:59:59.000Z

278

Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast  

E-Print Network (OSTI)

Forecast Introduction................................................................... 16 The Base Case Forecast..................................................................... 16 Base Case Price Forecast

279

Remarks on Northern Hemisphere Forecast Error Sensitivity from 1996 to 2000  

Science Conference Proceedings (OSTI)

The sensitivity of 2-day Northern Hemisphere extratropical forecast errors to changes in initial conditions, computed daily over a 4-yr period, is documented. The sensitivity is computed using the (dry) adjoint of the Navy Operational Global ...

C. A. Reynolds; R. Gelaro

2001-08-01T23:59:59.000Z

280

The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and Current Status  

Science Conference Proceedings (OSTI)

The first World Weather Research Programme (WWRP) Forecast Demonstration Project (FDP), with a focus on nowcasting, was conducted in Sydney, Australia, from 4 September to 21 November 2000 during a period associated with the Sydney 2000 Olympic ...

T. Keenan; P. Joe; J. Wilson; C. Collier; B. Golding; D. Burgess; P. May; C. Pierce; J. Bally; A. Crook; A. Seed; D. Sills; L. Berry; R. Potts; I. Bell; N. Fox; E. Ebert; M. Eilts; K. O'Loughlin; R. Webb; R. Carbone; K. Browning; R. Roberts; C. Mueller

2003-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Comparison of Methods Used to Generate Probabilistic Quantitative Precipitation Forecasts over South America  

Science Conference Proceedings (OSTI)

In this work, the quality of several probabilistic quantitative precipitation forecasts (PQPFs) is examined. The analysis is focused over South America during a 2-month period in the warm season. Several ways of generating and calibrating the ...

Juan Ruiz; Celeste Saulo; Eugenia Kalnay

2009-02-01T23:59:59.000Z

282

Heat Budgets of Analyses and Forecasts of an Explosively Deepening Maritime Cyclone  

Science Conference Proceedings (OSTI)

Diagnosis of the conditions associated with explosive maritime cyclogenesis is hindered by the lack of observations. A heat budget approach with analyses and forecasts for a rapid cyclogenesis event during the FGGE period is used in this study. ...

Chi-Sann Liou; Russel L. Elsberry

1987-09-01T23:59:59.000Z

283

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

284

Quantitative Precipitation Forecast Techniques for Use in Hydrologic Forecasting  

Science Conference Proceedings (OSTI)

Quantitative hydrologic forecasting usually requires knowledge of the spatial and temporal distribution of precipitation. First, it is important to accurately measure the precipitation falling over a particular watershed of interest. Second, ...

Konstantine P. Georgakakos; Michael D. Hudlow

1984-11-01T23:59:59.000Z

285

Figure 33. Ratio of average per megawatthour fuel costs for ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 33. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the SERC southeast ...

286

Figure 27. Ratio of average per megawatthour fuel costs for ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 27. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in five cases, 2008-2040

287

Figure 6. Transportation energy consumption by fuel, 1990-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 6. Transportation energy consumption by fuel, 1990-2040 (quadrillion Btu) Motor Gasoline, no E85 Pipeline Other E85 Jet Fuel

288

Figure 5. Energy-related carbon dioxide emissions in four ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Reference High Oil/Gas Resouce CO2$15 CO2$15HR Released: May 2, 2013 Figure 5. Energy-related carbon dioxide emissions in four ...

289

Figure 88. Annual average Henry Hub spot prices for natural ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 88. Annual average Henry Hub spot prices for natural gas in five cases, 1990-2040 (2011 dollars per million Btu) Reference

290

Figure 86. Annual average Henry Hub spot natural gas prices ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 86. Annual average Henry Hub spot natural gas prices, 1990-2040 (2011 dollars per million Btu) Henry Hub Spot Price 1990.00

291

A system-wide productivity figure of merit  

Science Conference Proceedings (OSTI)

The goal of this note is to combine productivity and performance benchmark measurement and subjective evaluations into a single system-wide figure of merit that could, for example, be used for budget justifications and procurements. With simplifying ...

Declan Murphy; Thomas Nash; Lawrence Votta

2006-01-01T23:59:59.000Z

292

Figure 3 from "Plutonium: Coping with Instability" by Siegfried S ...  

Science Conference Proceedings (OSTI)

This figure shows the (a) U.S. and (b) Russian versions of the Pu-Ga phase diagram. The Russian version, with a eutectoid point of 97°C and 7.9 at.% Ga, is

293

Figure ES2. Annual Indices of Real Disposable Income, Vehicle...  

U.S. Energy Information Administration (EIA) Indexed Site

ES2 Figure ES2. Annual Indices of Real Disposable Income, Vehicle-Miles Traveled, Consumer Price Index (CPI-U), and Real Average Retail Gasoline Price, 1978-2004, 1985100...

294

Figure 7.9 Coal Prices - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Figure 7.9 Coal Prices Total, 1949-2011 By Type, 1949-2011 By Type, 2011 214 U.S. Energy Information Administration / Annual Energy Review 2011

295

Figure 10.1 Renewable Energy Consumption (Quadrillion Btu)  

U.S. Energy Information Administration (EIA)

Figure 10.1 Renewable Energy Consumption (Quadrillion Btu) Total and Major Sources, 1949–2012 By Source, 2012 By Sector, 2012 Compared With Other Resources, 1949–2012

296

Particle Data Group - Figures from 2012 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (rev.) Fig. 1 Fig. 2 Higgs Bosons:...

297

Particle Data Group - Figures from 2009 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (Rev.) Fig. 1 Fig. 2 Higgs Bosons:...

298

Particle Data Group - Figures from 2007 web update of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass of the W Boson Fig. 1 Searches for Higgs Bosons Fig. 1 Fig. 2...

299

Particle Data Group - Figures from 2008 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson Fig. 1 Fig. 2 Higgs Bosons: Theory and...

300

Particle Data Group - Figures from 2010 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (rev.) Fig. 1 Fig. 2 Higgs Bosons:...

Note: This page contains sample records for the topic "forecast period figure" 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

Particle Data Group - Figures from 2011 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (2010) Fig. 1 Fig. 2 Higgs Bosons:...

302

Sheet Metal Forming: A Review - Figure 6 - TMS  

Science Conference Proceedings (OSTI)

Figure 6. Forming-limit diagram for low-carbon steel. Data of Reference 6 have been replotted and a dashed line has been added for maximum tension (T = st), ...

303

Figure SR2. Net Imports as Percentage of Domestic Consumption ...  

U.S. Energy Information Administration (EIA)

Figure SR2 of the U.S. Natural Gas Imports & Exports: 2009. This report provides an overview of U.S. international natural gas trade in 2009. Natural gas import and ...

304

Load Forecast For use in Resource Adequacy  

E-Print Network (OSTI)

Load Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l­ Load forecast methodology ­ Drivers of the forecast f i­ Treatment of conservation ­ Incorporating impact of weather ­ Forecast for 2019 #12;Regional Loads (MWA and MW)Regional Loads (MWA and MW

305

Forecast Technical Document Felling and Removals  

E-Print Network (OSTI)

Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Felling and removals forecasts Background A fellings and removals

306

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

307

Combining forecast weights: Why and how?  

Science Conference Proceedings (OSTI)

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions

Yip Chee Yin; Ng Kok-Haur; Lim Hock-Eam

2012-01-01T23:59:59.000Z

308

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network (OSTI)

1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY dmitry.kucharavy@insa-strasbourg.fr Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast

Paris-Sud XI, Université de

309

Using reforecasts for probabilistic forecast calibration  

E-Print Network (OSTI)

1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating

Hamill, Tom

310

Assessing Forecast Accuracy Measures Department of Economics  

E-Print Network (OSTI)

Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form

311

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

312

Can earnings forecasts be improved by taking into account the forecast bias?  

E-Print Network (OSTI)

Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi

Paris-Sud XI, Université de

313

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

314

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

315

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

316

Sampling Errors in Seasonal Forecasting  

Science Conference Proceedings (OSTI)

The limited numbers of start dates and ensemble sizes in seasonal forecasts lead to sampling errors in predictions. Defining the magnitude of these sampling errors would be useful for end users as well as informing decisions on resource ...

Stephen Cusack; Alberto Arribas

2009-03-01T23:59:59.000Z

317

Scoring Rules for Forecast Verification  

Science Conference Proceedings (OSTI)

The problem of probabilistic forecast verification is approached from a theoretical point of view starting from three basic desiderata: additivity, exclusive dependence on physical observations (“locality”), and strictly proper behavior. By ...

Riccardo Benedetti

2010-01-01T23:59:59.000Z

318

Wavelets and Field Forecast Verification  

Science Conference Proceedings (OSTI)

Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous ...

William M. Briggs; Richard A. Levine

1997-06-01T23:59:59.000Z

319

Richardson's Barotropic Forecast: A Reappraisal  

Science Conference Proceedings (OSTI)

To elucidate his numerical technique and to examine the effectiveness of geostrophic initial winds, Lewis Fry Richardson carried out an idealized forecast using the linear shallow-water equations and simple analytical pressure and velocity ...

Peter Lynch

1992-01-01T23:59:59.000Z

320

Comparison of Energy Information Administration and Bonneville Power Administration load forecasts  

SciTech Connect

Comparisons of the modeling methodologies underlying the project Independence Evaluation System (PIES) and the Bonneville Power Administration forecasts are discussed in this paper. This Technical Memorandum is presented in order to reconcile apparent inconsistencies between the forecasts. These represent different purposes for the modeling effort as well as different forecasts. Nonetheless, both are appropriate within the context that they are intended. The BPA forecasts are site-specific, detailed, micro-level, yearly forecasts of the demand for electricity. PIES develops regional, macro forecasts and does not contain estimates of the timing of the completion of plants within the period of the forecast. The BPA forecast is intended to be utilized in analyzing a sub-regional capacity expansion program. PIES is a regional energy market-clearing, non-normative model which allows different scenarios to be compared by changing input variables. Clearly, both forecasts are dependent upon the accuracy of the assumptions and input variables included. However, the differing levels of aggregation and objectives require different types of input variables.

Reed, H.J.

1978-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

The Potential Impact of Using Persistence as a Reference Forecast on Perceived Forecast Skill  

Science Conference Proceedings (OSTI)

Skill is defined as actual forecast performance relative to the performance of a reference forecast. It is shown that the choice of reference (e.g., random or persistence) can affect the perceived performance of the forecast system. Two scores, ...

Marion P. Mittermaier

2008-10-01T23:59:59.000Z

322

The Complex Relationship between Forecast Skill and Forecast Value: A Real-World Analysis  

Science Conference Proceedings (OSTI)

For routine forecasts of temperature and precipitation, the relative skill advantage of human forecasters with respect to the numerical–statistical guidance is small (and diminishing). Since the relationship between forecast skill and the value ...

Paul J. Roebber; Lance F. Bosart

1996-12-01T23:59:59.000Z

323

Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts  

Science Conference Proceedings (OSTI)

An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from ...

Charles R. Sampson; Paul A. Wittmann; Efren A. Serra; Hendrik L. Tolman; Jessica Schauer; Timothy Marchok

2013-02-01T23:59:59.000Z

324

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

E-Print Network (OSTI)

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

Goto, Susumu

2007-01-01T23:59:59.000Z

325

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

326

Spatial Structure, Forecast Errors, and Predictability of the South Asian Monsoon in CFS Monthly Retrospective Forecasts  

Science Conference Proceedings (OSTI)

The spatial structure of the boreal summer South Asian monsoon in the ensemble mean of monthly retrospective forecasts by the Climate Forecast System of the National Centers for Environmental Prediction is examined. The forecast errors and ...

Hae-Kyung Lee Drbohlav; V. Krishnamurthy

2010-09-01T23:59:59.000Z

327

What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting  

Science Conference Proceedings (OSTI)

Differences of opinion exist among forecasters—and between forecasters and users—regarding the meaning of the phrase “good (bad) weather forecasts.” These differences of opinion are fueled by a lack of clarity and/or understanding concerning the ...

Allan H. Murphy

1993-06-01T23:59:59.000Z

328

Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs  

Science Conference Proceedings (OSTI)

Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need ...

Barbara G. Brown; Allan H. Murphy

1987-09-01T23:59:59.000Z

329

Light truck forecasts  

SciTech Connect

The recent dramatic increase in the number of light trucks (109% between 1963 and 1974) has prompted concern about the energy consequences of the growing popularity of the light truck. An estimate of the future number of light trucks is considered to be a reasonable first step in assessing the energy impact of these vehicles. The monograph contains forecasts based on two models and six scenarios. The coefficients for the models have been derived by ordinary least squares regression of national level time series data. The first model is a two stage model. The first stage estimates the number of light trucks and cars (together), and the second stage applies a share's submodel to determine the number of light trucks. The second model is a simultaneous equation model. The two models track one another remarkably well, within about 2%. The scenarios were chosen to be consistent with those used in the Lindsey-Kaufman study Projection of Light Truck Population to Year 2025. Except in the case of the most dismal economic scenario, the number of light trucks is expected to increase from the 1974 level of 0.09 light truck per person to about 0.12 light truck per person in 1995.

Liepins, G.E.

1979-09-01T23:59:59.000Z

330

Base Resource Forecasts - Power Marketing - Sierra Nevada Region...  

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

Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...

331

Annual Energy Outlook Forecast Evaluation-Table 1  

Annual Energy Outlook 2012 (EIA)

Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...

332

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

333

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

334

Overestimation Reduction in Forecasting Telecommuting as a TDM Policy  

E-Print Network (OSTI)

M. , Ethics and advocacy in forecasting for public policy.change and social forecasting: the case of telecommuting asOverestimation Reduction in Forecasting Telecommuting as a

Tal, Gil

2008-01-01T23:59:59.000Z

335

Forecasting US CO2 Emissions Using State-Level Data  

E-Print Network (OSTI)

F. Hendry (eds), Economic Forecasting, Blackwell Publishing,W. : 2002, Macroeconomic forecasting using di?usion indexes,2003, Macroeconomic forecasting in the euro area: Country

Steinhauser, Ralf; Auffhammer, Maximilian

2005-01-01T23:59:59.000Z

336

NoVaS Transformations: Flexible Inference for Volatility Forecasting  

E-Print Network (OSTI)

and Correlation Forecasting” in G. Elliott, C.W.J.Handbook of Economic Forecasting, Amsterdam: North-Holland,Transformations”, forthcoming in Forecasting in the Presence

Politis, Dimitris N; Thomakos, Dimitrios D

2008-01-01T23:59:59.000Z

337

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

338

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

339

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

340

Forecasting Danerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

costs could alter forecasting skill and the predictors thatForecasting Dangerous Inmate Misconduct: An Applications ofOn-Line Working Paper Series Forecasting Dangerous Inmate

Berk, Richard A.; Kriegler, Brian; Baek, John-Ho

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Developing a Practical Forecasting Screener for Domestic Violence Incidents  

E-Print Network (OSTI)

Developing a Practical Forecasting Screener for Domesticcomplicated did not improve forecasting skill. Taking thethe local costs of forecasting errors. It is also feasible

Richard A. Berk; Susan B. Sorenson; Yan He

2011-01-01T23:59:59.000Z

342

Forecasting with Dynamic Microsimulation: Design, Implementation, and Demonstration  

E-Print Network (OSTI)

Goulias Page 84 Forecasting with Dynamic Microsimulation:Goulias Page 80 Forecasting with Dynamic Microsimulation:L. Demographic Forecasting with a Dynamic Stochastic

Ravulaparthy, Srinath; Goulias, Konstadinos G.

2011-01-01T23:59:59.000Z

343

BILIWG: Consistent "Figures of Merit" (Presentation)  

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

BILIWG: Consistent "Figures of Merit" BILIWG: Consistent "Figures of Merit" A finite set of results reported in consistent units * To track progress of individual projects on a consistent basis * To enable comparing projects in a transparent manner Potential BILIWG Figures of Merit Key BILI Distributed Reforming Targets * Cost ($/kg of H2): H2A analysis - Distributed reforming station,1000 kg/day ave./daily dispensed, 5000/6250 psi (and 10,000/12,000 psi) dispensing, 500 units/yr. * nth unit vs. 500 units/yr ? * production unit only (with 300 psi outlet pressure) ? * Production unit efficiency: LHV H2 out/(LHV of feedstocks and all other energy in) GTG - WTG efficiency? - Feedstock conversion energy efficiency? * Production unit capital cost: Distributed reforming station,1000 kg/day ave./daily dispensed, 300 psi outlet pressure

344

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

345

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

346

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

347

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

348

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Ensemble prediction systems produce forecasts that represent the probability distribution of a continuous forecast variable. Most often, the verification problem is simplified by transforming the ensemble forecast into probability forecasts for ...

A. Allen Bradley; Stuart S. Schwartz

2011-09-01T23:59:59.000Z

349

A Review of Numerical Forecast Guidance for Hurricane Hugo  

Science Conference Proceedings (OSTI)

Numerical forecast guidance for Hurricane Hugo from the National Meteorological Center is examined, as well as forecasts from the European Center for Medium Range Forecasting and the United Kingdom Meteorological Office. No one forecast product ...

John H. Ward

1990-09-01T23:59:59.000Z

350

Using Customers' Reported Forecasts to Predict Future Sales  

E-Print Network (OSTI)

Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery orders using forecasts provided by their customers. Our goal is to improve the supplier's operations through a better un- derstanding of the customers's forecast behavior. Unfortunately, customer forecasts

Murphy, Robert F.

351

Short-Range Ensemble Forecasts of Precipitation Type  

Science Conference Proceedings (OSTI)

Short-range ensemble forecasting is extended to a critical winter weather problem: forecasting precipitation type. Forecast soundings from the operational NCEP Short-Range Ensemble Forecast system are combined with five precipitation-type ...

Matthew S. Wandishin; Michael E. Baldwin; Steven L. Mullen; John V. Cortinas Jr.

2005-08-01T23:59:59.000Z

352

List of Figures xii List of Tables xv  

E-Print Network (OSTI)

. . . . . . . . . . . . . . . . . . . . . . . . 137 II Energy Supply Chains 139 6 Electric Power Supply Chains 141 6.1 The Supply Chain ModelContents List of Figures xii List of Tables xv Preface xvi I Supply Chain Networks 1 1 Introduction and Overview 3 2 Supply Chain Networks 9 2.1 The Supply Chain Network Model . . . . . . . . . . . . . . . 11 2

Nagurney, Anna

353

Figure 62. Additions to electricity generation capacity in the ...  

U.S. Energy Information Administration (EIA)

Microturbines Wind Solar photovoltaics Released: April 30, 2013 No Sunset $0.90 $0.80 $2.27 $2.15 $5.04 $4.65 $2.96 $0.66 $13.72 $10.17. Title: Figure 62.

354

Thermoelectric figure of merit of LSCoO-Mn perovskites  

Science Conference Proceedings (OSTI)

Oxide ceramics with nominal composition of La"0"."8Sr"0"."2Co"1"-"xMn"xO"3(0= Keywords: 72.20.Pa, 84.60.Bk, 84.60.Rb, 85.80.Fi, LSCoO compounds, Thermoelectric figure of merit, Thermoelectric materials

J. E. Rodríguez; D. Cadavid; L. C. Moreno

2008-11-01T23:59:59.000Z

355

Object Recognition by Sequential Figure-Ground Ranking  

Science Conference Proceedings (OSTI)

We present an approach to visual object-class segmentation and recognition based on a pipeline that combines multiple figure-ground hypotheses with large object spatial support, generated by bottom-up computational processes that do not exploit knowledge ... Keywords: Learning and ranking, Object recognition, Semantic segmentation

João Carreira; Fuxin Li; Cristian Sminchisescu

2012-07-01T23:59:59.000Z

356

The Automated Tropical Cyclone Forecasting System (ATCF)  

Science Conference Proceedings (OSTI)

The U.S. Navy Automated Tropical Cyclone Forecasting System (ATCF) is an IBM-AT compatible software package developed for the Joint Typhoon Warning Center (JTWC), Guam. ATCF is designed to assist forecasters with the process of making tropical ...

Ronald J. Miller; Ann J. Schrader; Charles R. Sampson; Ted L. Tsui

1990-12-01T23:59:59.000Z

357

Local Forecast Communication In The Altiplano  

Science Conference Proceedings (OSTI)

Forecasts play an important role in planting decisions for Andean peasant producers. Predictions of the upcoming cropping season determine when, where, and what farmers will plant. This research looks at the sources of forecast information used ...

Jere L. Gilles; Corinne Valdivia

2009-01-01T23:59:59.000Z

358

Evaluation of LFM-2 Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

The results of a near real time experiment designed to assess the state of the art of quantitative precipitation forecasting skill of the operational NMC LFM-2 are described. All available LFM-2 quantitative precipitation forecasts were verified ...

Lance F. Bosart

1980-08-01T23:59:59.000Z

359

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

360

Value from Ambiguity in Ensemble Forecasts  

Science Conference Proceedings (OSTI)

This study explores the objective application of ambiguity information, that is, the uncertainty in forecast probability derived from an ensemble. One application approach, called uncertainty folding, merges ambiguity with forecast uncertainty ...

Mark S. Allen; F. Anthony Eckel

2012-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Forecaster Workstation Design: Concepts and Issues  

Science Conference Proceedings (OSTI)

Some basic ideas about designing a meteorological workstation for operational weather forecasting are presented, in part as a complement to the recently published discussion of workstation design by R. R. Hoffman. Scientific weather forecasting ...

Charles A. Doswell III

1992-06-01T23:59:59.000Z

362

Economic and Statistical Measures of Forecast Accuracy  

E-Print Network (OSTI)

This paper argues in favour of a closer link between decision and forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued...

Granger, Clive W J; Pesaran, M Hashem

2004-06-16T23:59:59.000Z

363

2013 Midyear Economic Forecast Sponsorship Opportunity  

E-Print Network (OSTI)

2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing

de Lijser, Peter

364

Forecasting consumer products using prediction markets  

E-Print Network (OSTI)

Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

Trepte, Kai

2009-01-01T23:59:59.000Z

365

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

366

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

367

Probabilistic Quantitative Precipitation Forecasts for River Basins  

Science Conference Proceedings (OSTI)

A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with ...

Roman Krzysztofowicz; William J. Drzal; Theresa Rossi Drake; James C. Weyman; Louis A. Giordano

1993-12-01T23:59:59.000Z

368

A General Framework for Forecast Verification  

Science Conference Proceedings (OSTI)

A general framework for forecast verification based on the joint distribution of forecasts and observations is described. For further elaboration of the framework, two factorizations of the joint distribution are investigated: 1) the calibration-...

Allan H. Murphy; Robert L. Winkler

1987-07-01T23:59:59.000Z

369

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Conference Proceedings (OSTI)

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

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

2003-02-01T23:59:59.000Z

370

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

371

Quantile Forecasting of Commodity Futures' Returns: Are Implied Volatility Factors Informative?  

E-Print Network (OSTI)

This study develops a multi-period log-return quantile forecasting procedure to evaluate the performance of eleven nearby commodity futures contracts (NCFC) using a sample of 897 daily price observations and at-the-money (ATM) put and call implied volatilities of the corresponding prices for the period from 1/16/2008 to 7/29/2011. The statistical approach employs dynamic log-returns quantile regression models to forecast price densities using implied volatilities (IVs) and factors estimated through principal component analysis (PCA) from the IVs, pooled IVs and lagged returns. Extensive in-sample and out-of-sample analyses are conducted, including assessment of excess trading returns, and evaluations of several combinations of quantiles, model specifications, and NCFC's. The results suggest that the IV-PCA-factors, particularly pooled return-IV-PCA-factors, improve quantile forecasting power relative to models using only individual IV information. The ratio of the put-IV to the call-IV is also found to improve quantile forecasting performance of log returns. Improvements in quantile forecasting performance are found to be better in the tails of the distribution than in the center. Trading performance based on quantile forecasts from the models above generated significant excess returns. Finally, the fact that the single IV forecasts were outperformed by their quantile regression (QR) counterparts suggests that the conditional distribution of the log-returns is not normal.

Dorta, Miguel

2012-05-01T23:59:59.000Z

372

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.

373

Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event  

Science Conference Proceedings (OSTI)

Meteorologists within the Forecast Branch (FB) of the National Meteorological Center (NMC) produce operational quantitative precipitation forecasts (QPFs). These manual forecasts are prepared utilizing various forecasting techniques, which are ...

Theodore W. Funk

1991-12-01T23:59:59.000Z

374

Application of Forecast Verification Science to Operational River Forecasting in the U.S. National Weather Service  

Science Conference Proceedings (OSTI)

Forecast verification in operational hydrology has been very limited to date, mainly due to the complexity of verifying both forcing input forecasts and hydrologic forecasts on multiple space–time scales. However, forecast verification needs to ...

Julie Demargne; Mary Mullusky; Kevin Werner; Thomas Adams; Scott Lindsey; Noreen Schwein; William Marosi; Edwin Welles

2009-06-01T23:59:59.000Z

375

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

376

Forecasting for energy and chemical decision analysis  

SciTech Connect

This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

Cazalet, E.G.

1984-08-01T23:59:59.000Z

377

A Rank Approach to Equity Forecast Construction  

E-Print Network (OSTI)

that are fit for their purpose; for example, returningaggregate county and sector forecasts that are consistent by construction....

Satchell, Stephen E; Wright, Stephen M

2006-03-14T23:59:59.000Z

378

Consensus Coal Production And Price Forecast For  

E-Print Network (OSTI)

Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

Mohaghegh, Shahab

379

Load Forecasting for Modern Distribution Systems  

Science Conference Proceedings (OSTI)

Load forecasting is a fundamental activity for numerous organizations and activities within a utility, including planning, operations, and control. Transmission and Distribution (T&D) planning and design engineers use the load forecast to determine whether any changes and additions are needed to the electric system to satisfy the anticipated load. Other load forecast users include system operations, financial ...

2013-03-08T23:59:59.000Z

380

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

Note: This page contains sample records for the topic "forecast period figure" 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

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

382

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

383

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

384

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

385

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

386

STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 report, Staff Forecast: Retail Electricity Prices, 2005 to 2018, was prepared with contributions from the technical assistance provided by Greg Broeking of R.W. Beck, Inc. in preparing retail price forecasts

387

Blue Chip Consensus US GDP Forecast  

E-Print Network (OSTI)

and metro area from Moody’s Economy.com Equivalent to US-level Gross Domestic Product ? The GMP forecasts have a large impact on the peak load forecasts Rule of thumb: 1 % growth in RTO GMP ? approx. 1,000 MW growth in forecast RTO peak load

James F. Wilson

2007-01-01T23:59:59.000Z

388

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

389

System Demonstration Multilingual Weather Forecast Generation System  

E-Print Network (OSTI)

System Demonstration Multilingual Weather Forecast Generation System Tianfang Yao DongmoZhang Qian (Multilingual Weather Forecasts Assistant) system will be demonstrated. It is developed to generate the multilingual text of the weather forecasts automatically. The raw data from the weather observation can be used

390

(1) Ensemble forecast calibration & (2) using reforecasts  

E-Print Network (OSTI)

1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast ­ Rationale 1: Infer large-sample probabilities from small ensemble. ­ Rationale 2: Remove bias, increase forecast reliability while preserving

Hamill, Tom

391

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.

392

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

393

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

394

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

395

NOvA (Fermilab E929) Official Plots and Figures  

DOE Data Explorer (OSTI)

The NOvA collaboration, consisting of 180 researchers across 28 institutions and managed by the Fermi National Accelerator Laboratory (FNAL), is developing instruments for a neutrino-focused experiment that will attempt to answer three fundamental questions in neutrino physics: 1) Can we observe the oscillation of muon neutrinos to electron neutrinos; 2) What is the ordering of the neutrino masses; and 3) What is the symmetry between matter and antimatter? The collaboration makes various data plots and figures available. These are grouped under five headings, with brief descriptions included for each individual figure: Neutrino Spectra, Detector Overview, Theta12 Mass Hierarchy CP phase, Theta 23 Delta Msqr23, and NuSterile.

396

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

397

Figure 30. Decomposition 4941 of Energy Use by Effect, 1988-1994 ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 30

398

Figure ES4. Sales-Weighted Inertia Weight and On-Road Fuel Mileage ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES4

399

Figure ES3. Sales-Weighted Horsepower and On-Road Fuel Mileage for ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES3

400

Figure ES1. Schema for Estimating Energy and Energy-Related ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES1

Note: This page contains sample records for the topic "forecast period figure" 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

Essays on macroeconomics and forecasting  

E-Print Network (OSTI)

This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the �black box� of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the �price puzzle� and the �liquidity puzzle� are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate explanatory variables. Compared to Stock and Watson (2002)�s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson�s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.

Liu, Dandan

2005-08-01T23:59:59.000Z

402

How deep in molecular space can periodicity be found?  

Science Conference Proceedings (OSTI)

We find occasional echoes of periodicity, i.e. the trends found in the chart of the elements, in several-atom (up to 32) molecules and use it to make forecasts for molecular data, some of which have been confirmed. Keywords: binary compounds, data mining, halogenated organic compounds, molecular periodicity

Ken Luk; Ray Hefferlin; Gabriel Johnson

2005-07-01T23:59:59.000Z

403

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

404

Critical Operating Constraint Forecasting (COCF)  

Science Conference Proceedings (OSTI)

This document represents the progress report and Task 1 letter report of the California Institute for Energy and Environment (CIEE) contract funded by the California Energy Commission (CEC), Critical Operating Constraint Forecasting (COCF) for California Independent System Operator (CAISO) Planning Phase. Task 1 was to accomplish the following items: Collect data from CAISO to set up the WECC power flow base case representing the CAISO system in the summer of 2006 Run TRACE for maximizing California Impo...

2006-06-30T23:59:59.000Z

405

Meese-Rogoff redux: Micro-based exchange-rate forecasting  

E-Print Network (OSTI)

Johnatban. "Exchange Rate Forecasting: The Errors We'veBased Exchange-Rate Forecasting By MARTIN D . D . EVANS ANDon longer-horizon forecasting, we examine forecasting over

Evans, MDD; Lyons, Richard K.

2005-01-01T23:59:59.000Z

406

The Past as Prologue? Business Cycles and Forecasting since the 1960s  

E-Print Network (OSTI)

Forecasters,” Journal of Forecasting, Vol. 28, No. 2, Mar,of Macroeconomic Forecasting” Journal of Macroeconomics,of Federal Reserve Forecasting,” Journal of Macroeconomics,

Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany

2010-01-01T23:59:59.000Z

407

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

408

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

409

Fermilab E866 (NuSea) Figures and Data Plots  

DOE Data Explorer (OSTI)

The NuSea Experiment at Fermilab studied the internal structure of protons, in particular the difference between up quarks and down quarks. This experiment also addressed at least two other physics questions: nuclear effects on the production of charmonia states (bound states of charm and anti-charm quarks) and energy loss of quarks in nuclei from Drell-Yan measurements on nuclei. While much of the NuSea data are available only to the collaboration, figures, data plots, and tables are presented as stand-alone items for viewing or download. They are listed in conjunction with the published papers, theses, or presentations in which they first appeared. The date range is 1998 to 2008. To see these figures and plots, click on E866 publications or go directly to http://p25ext.lanl.gov/e866/papers/papers.html. Theses are at http://p25ext.lanl.gov/e866/papers/e866theses/e866theses.html and the presentations are found at http://p25ext.lanl.gov/e866/papers/e866talks/e866talks.html. Many of the items are postscript files.

E866 NuSea Collaboration

410

Evaluation of solar mirror figure by moire contouring  

DOE Green Energy (OSTI)

Moire topography is applied to the figure assessment of solar mirrors. The technique is demonstrated on component facets of a six-meter diameter, four-meter focal length, parabolic dish collector. The relative ease of experimental implementation and subsequent data analysis suggests distinct advantages over the more established laser ray trace or BCS/ICS technique for many applications. The theoretical and experimental considerations necessary to fully implement moire topography on mirror surfaces are detailed. A procedure to de-specularize the mirror is demonstrated which conserves the surface morphology without damaging the reflective surface. The moire fringe patterns observed for the actual mirror facets are compared with theoretical contours generated for representative dish facets using a computer simulation algorithm. A method for evaluating the figure error of the real facet is presented in which the error parameter takes the form of an average absolute deviation of the surface slope from theoretical. The experimental measurement system used for this study employs a 200 line/inch Ronchi transmission grating. The mirror surface is illuminated by a collimated beam at 60/sup 0/. The fringe observation is performed normal to the grating. These parameters yield contour intervals for the fringe patterns of 0.073 mm. The practical considerations for extending the techniques to higher resolution are discussed.

Griffin, J.W.; Lind, M.A.

1980-06-01T23:59:59.000Z

411

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

412

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

413

Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts  

Science Conference Proceedings (OSTI)

The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to ...

Brian Eder; Daiwen Kang; S. Trivikrama Rao; Rohit Mathur; Shaocai Yu; Tanya Otte; Ken Schere; Richard Wayland; Scott Jackson; Paula Davidson; Jeff McQueen; George Bridgers

2010-03-01T23:59:59.000Z

414

A Probabilistic Forecast Contest and the Difficulty in Assessing Short-Range Forecast Uncertainty  

Science Conference Proceedings (OSTI)

Results are presented from a probability-based weather forecast contest. Rather than evaluating the absolute errors of nonprobabilistic temperature and precipitation forecasts, as is common in other contests, this contest evaluated the skill of ...

Thomas M. Hamill; Daniel S. Wilks

1995-09-01T23:59:59.000Z

415

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

Science Conference Proceedings (OSTI)

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

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

2010-01-01T23:59:59.000Z

416

Implications of Ensemble Quantitative Precipitation Forecast Errors on Distributed Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Evaluating the propagation of errors associated with ensemble quantitative precipitation forecasts (QPFs) into the ensemble streamflow response is important to reduce uncertainty in operational flow forecasting. In this paper, a multifractal ...

Giuseppe Mascaro; Enrique R. Vivoni; Roberto Deidda

2010-02-01T23:59:59.000Z

417

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

418

Reliable Probabilistic Quantitative Precipitation Forecasts from a Short-Range Ensemble Forecasting System  

Science Conference Proceedings (OSTI)

A simple binning technique is developed to produce reliable 3-h probabilistic quantitative precipitation forecasts (PQPFs) from the National Centers for Environmental Prediction (NCEP) multimodel short-range ensemble forecasting system obtained ...

David J. Stensrud; Nusrat Yussouf

2007-02-01T23:59:59.000Z

419

The Impact of Writing Area Forecast Discussions on Student Forecaster Performance  

Science Conference Proceedings (OSTI)

A brief study is provided on the forecast performance of students who write a mock area forecast discussion (AFD) on a weekly basis. Student performance was tracked for one semester (11 weeks) during the University of Missouri—Columbia's local ...

Patrick S. Market

2006-02-01T23:59:59.000Z

420

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

Note: This page contains sample records for the topic "forecast period figure" 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

Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development  

Science Conference Proceedings (OSTI)

Seasonal streamflow forecasts contingent on climate information are essential for water resources planning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are ...

A. Sankarasubramanian; Upmanu Lall; Susan Espinueva

2008-04-01T23:59:59.000Z

422

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

423

Forecasting Random Walks Under Drift Instability  

E-Print Network (OSTI)

Forecasting Random Walks Under Drift Instability? M. Hashem Pesaran University of Cambridge, CIMF, and USC Andreas Pick University of Cambridge, CIMF March 11, 2008 Abstract This paper considers forecast averaging when the same model is used... but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single...

Pesaran, M Hashem; Pick, Andreas

424

Solar future: 1978. [Market forecast to 1992  

SciTech Connect

The growth in sales of solar heating equipment is discussed. Some forecasts are made for the continued market growth of collectors, pool systems, and photovoltaics. (MOW)

Butt, S.H.

1978-03-01T23:59:59.000Z

425

Energy conservation and official UK energy forecasts  

SciTech Connect

Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.

Pearce, D.

1980-09-01T23:59:59.000Z

426

Geothermal wells: a forecast of drilling activity  

DOE Green Energy (OSTI)

Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

Brown, G.L.; Mansure, A.J.; Miewald, J.N.

1981-07-01T23:59:59.000Z

427

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

428

Time Series Prediction Forecasting the Future and ...  

Science Conference Proceedings (OSTI)

Time Series Prediction Forecasting the Future and Understanding the Past Santa Fe Institute Proceedings on the Studies in the Sciences of ...

2012-10-01T23:59:59.000Z

429

Rolling 12 Month Forecast November-2008.xls  

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

Month Exceedence Level: 90% (Dry) First Preference CVP Generation Project Use November 2008 October 2009 November 2008 Twelve-Month Forecast of CVP Generation and Base Resource...

430

Promotional forecasting in the grocery retail business  

E-Print Network (OSTI)

Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

Koottatep, Pakawkul

2006-01-01T23:59:59.000Z

431

Forecasting Prices andForecasting Prices and Congestion forCongestion for  

E-Print Network (OSTI)

Abstract--In deregulated electricity markets, short-term load forecasting is important for reliable power322 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 1, FEBRUARY 2010 Short-Term Load Forecasting presents a similar day-based wavelet neural network method to forecast tomorrow's load. The idea

Tesfatsion, Leigh

432

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network (OSTI)

Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12

Kemner, Ken

433

Specification, estimation, and forecasts of industrial demand and price of electricity  

Science Conference Proceedings (OSTI)

This paper discusses the specification of electricity-demand and price equations for manufacturing industries and presents empirical results based on the data for 16 Standard Industrial Classification (SIC) three-digit industries from 1959 to 1976. Performances of estimated equations are evaluated by sample-period simulation tests. The estimated coefficients are then used to forecast electricity demand by industry. Results show that most of the estimated coefficients have expected signs and are statistically significant. The estimated equations perform well in terms of sample-period simulation tests, registering small mean absolute percentage errors and mean square percentage errors for most of the industries studied. Forecasted results indicate that total electricity demand by manufacturing industries would grow at an average annual rate of 3.53% according to the baseline forecast, 2.39% in the high-price scenario, and 4.76% in the low-price scenario. The forecasted growth rates vary substantially among industries. The results also indicate that the price of electricity would continue to grow at a faster rate than the general price level in the forecasted period 1977 to 1990. 19 references, 6 tables.

Chang, H.S. (Univ. of Tennessee, Knoxville); Chern, W.S.

1981-01-01T23:59:59.000Z

434

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

435

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

436

Uses and Applications of Climate Forecasts for Power Utilities  

Science Conference Proceedings (OSTI)

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-...

Stanley A. Changnon; Joyce M. Changnon; David Changnon

1995-05-01T23:59:59.000Z

437

Forecasting and Verifying in a Field Research Project: DOPLIGHT '87  

Science Conference Proceedings (OSTI)

Verification of forecasts during research field experiments is discussed and exemplified using the DOPLIGHT '87 experiment. We stress the importance of forecast verification if forecasting is to be a serious component of the research. A direct ...

Charles A. Doswell III; John A. Flueck

1989-06-01T23:59:59.000Z

438

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

439

Precipitation and Temperature Forecast Performance at the Weather Prediction Center  

Science Conference Proceedings (OSTI)

The role of the human forecaster in improving upon the accuracy of numerical weather prediction is explored using multi-year verification of human-generated short-range precipitation forecasts and medium-range maximum temperature forecasts from ...

David R. Novak; Christopher Bailey; Keith Brill; Patrick Burke; Wallace Hogsett; Robert Rausch; Michael Schichtel

440

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

Note: This page contains sample records for the topic "forecast period figure" 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

An Experiment in Mesoscale Weather Forecasting in the Michigan Area  

Science Conference Proceedings (OSTI)

During an experiment in mesoscale weather forecasting in the Michigan area, consensus improved over NWS guidance in maximum/minimum temperature and probability of precipitation forecasts out to 24 hours. Forecasts were generally best in the ...

Dennis G. Baker

1986-12-01T23:59:59.000Z

442

The Economic Value Of Ensemble-Based Weather Forecasts  

Science Conference Proceedings (OSTI)

The potential economic benefit associated with the use of an ensemble of forecasts versus anequivalent or higher-resolution control forecast is discussed. Neither forecast systems are post-processed,except a simple calibration that is applied to ...

Yuejian Zhu; Zoltan Toth; Richard Wobus; David Richardson; Kenneth Mylne

2002-01-01T23:59:59.000Z

443

Diversity in Interpretations of Probability: Implications for Weather Forecasting  

Science Conference Proceedings (OSTI)

Over the last years, probability weather forecasts have become increasingly popular due in part to the development of ensemble forecast systems. Despite its widespread use in atmospheric sciences, probability forecasting remains a subtle and ...

Ramón de Elía; René Laprise

2005-05-01T23:59:59.000Z

444

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

445

On the Reliability and Calibration of Ensemble Forecasts  

Science Conference Proceedings (OSTI)

An important aspect of ensemble forecasting is that the resulting probabilities are reliable (i.e., the forecast probabilities match the observed frequencies). In the medium-range forecasting context, the literature tends to focus on the ...

Christine Johnson; Neill Bowler

2009-05-01T23:59:59.000Z

446

Scoring Probabilistic Forecasts: The Importance of Being Proper  

Science Conference Proceedings (OSTI)

Questions remain regarding how the skill of operational probabilistic forecasts is most usefully evaluated or compared, even though probability forecasts have been a long-standing aim in meteorological forecasting. This paper explains the ...

Jochen Bröcker; Leonard A. Smith

2007-04-01T23:59:59.000Z

447

Experiments in Temperature and Precipitation Forecasting for Illinois  

Science Conference Proceedings (OSTI)

Six years of daily temperature and precipitation forecasting are studied for Urbana, Illinois. Minimum temperature forecast skills, measured against a climatological control, are 57%, 48%, 34% and 20% for the respective forecast ranges of one, ...

John R. Gyakum

1986-06-01T23:59:59.000Z

448

STAR (Solenoidal Tracker at RHIC) Figures and Data  

DOE Data Explorer (OSTI)

The primary physics task of STAR is to study the formation and characteristics of the quark-gluon plasma (QGP), a state of matter believed to exist at sufficiently high energy densities. STAR consists of several types of detectors, each specializing in detecting certain types of particles or characterizing their motion. These detectors work together in an advanced data acquisition and subsequent physics analysis that allows final statements to be made about the collision. The STAR Publications page provides access to all published papers by the STAR Collaboration, and many of them have separate links to the figures and data found in or supporting the paper. See also the data-rich summaries of the research at http://www.star.bnl.gov/central/physics/results/. [See also DDE00230

The STAR Collaboration

449

A1. Form EIA-176 Figure Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Form EIA-176 Form EIA-176 Figure Energy Information Administration / Natural Gas Annual 1996 214 EIA-176, ANNUAL REPORT OF NATURAL AND SUPPLEMENTAL GAS SUPPLY AND DISPOSITION, 19 PART IV: SUPPLY OF NATURAL AND SUPPLEMENTAL GAS RECEIVED WITHIN OR TRANSPORTED INTO REPORT STATE RESPONDENT COPY Page 2 PART III: TYPE OF COMPANY AND GAS ACTIVITIES OPERATED IN THE REPORT STATE 1.0 Type of Company (check one) 1.0 Control No. 2.0 Company Name 3.0 Report State 4.0 Resubmittal EIA Date: a b c d e Investor owned distributor Municipally owned distributor Interstate pipeline Intrastate pipeline Storage operator f g h i j SNG plant operator Integrated oil and gas Producer Gatherer Processor k Other (specify) 2.0 Gas Activities Operated On-system Within the Report State (check all that apply) a b c d e Produced Natural Gas

450

Price and Load Forecasting in Volatile Energy Markets  

Science Conference Proceedings (OSTI)

With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.

2001-12-05T23:59:59.000Z

451

Noise figure and photon probability distribution in Coherent Anti-Stokes Raman Scattering (CARS)  

E-Print Network (OSTI)

The noise figure and photon probability distribution are calculated for coherent anti-Stokes Raman scattering (CARS) where an anti-Stokes signal is converted to Stokes. We find that the minimum noise figure is ~ 3dB.

Dimitropoulos, D; Jalali, B; Solli, D R

2006-01-01T23:59:59.000Z

452

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

453

Blasting Vibration Forecast Base on Neural Network  

Science Conference Proceedings (OSTI)

The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved ... Keywords: Blasting vibration, Neural network, Forecast

Haiwang Ye; Fang Liu; Jian Chang; Lin Feng; Yang Wang; Peng Yao; Kai Wu

2010-10-01T23:59:59.000Z

454

Evaluating the Skill of Categorical Forecasts  

Science Conference Proceedings (OSTI)

A generalized skill score is presented for evaluating forecasts in any number of categories. Each forecast in a sample is given a mark; the skill score for the sample is just the average mark. Each mark has an expected value of zero for an ...

Neil D. Gordon

1982-07-01T23:59:59.000Z

455

Making Forecasts and Weather Normalization Work Together  

Science Conference Proceedings (OSTI)

Electric utility industry restructuring has changed the consistency between weather-normalized sales and energy forecasts. This Technology Review discusses the feasibility of integrating weather normalization and forecasting processes, and addresses whether the conflicting goal of obtaining greater consistency and accuracy with fewer staff resources can be met with more integrated approaches.

2000-09-11T23:59:59.000Z

456

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

457

The NCEP Climate Forecast System Version 2  

Science Conference Proceedings (OSTI)

The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled Reanalysis ...

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-ya Chuang; Mark Iredell; Michael Ek; Jesse Meng; Rongqian Yang; Malaquías Peña Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

458

Efficient forecasting for hierarchical time series  

Science Conference Proceedings (OSTI)

Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels based ... Keywords: forecasting, hierarchies, optimization, time series

Lars Dannecker; Robert Lorenz; Philipp Rösch; Wolfgang Lehner; Gregor Hackenbroich

2013-10-01T23:59:59.000Z

459

Time series forecasting with Qubit Neural Networks  

Science Conference Proceedings (OSTI)

This paper proposes a quantum learning scheme approach for time series forecasting, through the application of the new non-standard Qubit Neural Network (QNN) model. The QNN description was adapted in this work in order to resemble classical Artificial ... Keywords: artificial intelligence, artificial neural networks, quantum computing, qubit neural networks, time series forecasting

Carlos R. B. Azevedo; Tiago A. E. Ferreira

2007-08-01T23:59:59.000Z

460

Preemptive Forecasts Using an Ensemble Kalman Filter  

Science Conference Proceedings (OSTI)

An ensemble Kalman filter (EnKF) estimates the error statistics of a model forecast using an ensemble of model forecasts. One use of an EnKF is data assimilation, resulting in the creation of an increment to the first-guess field at the ...

Brian J. Etherton

2007-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

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

462

Incentives for Retailer Forecasting: Rebates vs. Returns  

Science Conference Proceedings (OSTI)

This paper studies a manufacturer that sells to a newsvendor retailer who can improve the quality of her demand information by exerting costly forecasting effort. In such a setting, contracts play two roles: providing incentives to influence the retailer's ... Keywords: endogenous adverse selection, forecasting, rebates, returns, supply chain contracting

Terry A. Taylor; Wenqiang Xiao

2009-10-01T23:59:59.000Z

463

Figure 1.6 State-Level Energy Consumption Estimates and Estimated ...  

U.S. Energy Information Administration (EIA)

Figure 1.6 State-Level Energy Consumption Estimates and Estimated Consumption per Capita, 2010 Consumption Consumption per Capita

464

SunShot Initiative: Forecasting and Influencing Technological...  

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

Forecasting and Influencing Technological Progress in Solar Energy to someone by E-mail Share SunShot Initiative: Forecasting and Influencing Technological Progress in Solar Energy...

465

New Climate Research Centers Forecast Changes and Challenges...  

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

Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering...

466

Exploiting Domain Knowledge to Forecast Heating Oil Consumption  

Science Conference Proceedings (OSTI)

The GasDay laboratory at Marquette University provides forecasts of energy consumption. One such service is the Heating Oil Forecaster

George F. Corliss; Tsuginosuke Sakauchi; Steven R. Vitullo; Ronald H. Brown

2011-01-01T23:59:59.000Z

467

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

Alphabetically Tools by Platform PC Mac UNIX Internet Tools by Country Related Links Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides...

468

The beneficial impact of radio occultation observations on Australian region forecasts  

E-Print Network (OSTI)

(COSMIC) was launched in April 2006. This system provides a new observation type for operational meteorology that has been shown to provide significant information on the thermodynamic state of the atmosphere and to allow improvements in atmospheric analysis and prognosis. A month of COSMIC radio occultation observations, together with a smaller number of radio occultation observations from the Meteorological Operational satellite (MetOp) and Gravity Recovery and Climate Experiment (GRACE) spacecraft, have been assimilated into the global ACCESS (Australian Community Climate Earth System Simulator) system, which is being employed at the Australian Bureau of Meteorology to provide real-time operational forecasts. In this study, four-dimensional variational assimilation (4DVAR) has been used to assimilate the radio occultation and other data into the global ACCESS system (ACCESS-G), which has been used to provide forecasts to five days ahead. For the period studied, the accuracy of these forecasts has been compared to forecasts generated without the use of the radio occultation data. The forecasts using radio occultation data have been found to be improved in the lower, middle and upper troposphere. These results, combined with the relatively unbiased nature of the radio occultation observations indicate their use has the potential to improve operational analysis and forecasting in the Australian Region and also to assist in important tasks such as a regional reanalysis and climate monitoring.

John Le Marshall; Yi Xiao; Robert Norman; Kefei Zhang; Anthony Rea; Lidia Cucurull; Rolf Seecamp; Peter Steinle; K. Puri; Tan Le

2010-01-01T23:59:59.000Z

469

Annual Energy Outlook 2006 with Projections to 2030 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2006 with Projections to 2030 Only GII produces a comprehensive energy projection with a time horizon similar to that of AEO2006. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2006 projections. Economic Growth In the AEO2006 reference case, the projected growth in real GDP, based on 2000 chain-weighted dollars, is 3.0 percent per year from 2004 to 2030 (Table 19). For the period from 2004 to 2025, real GDP growth in the AEO2006 reference case is similar to the average annual growth projected in AEO2005. The AEO2006 projections of economic growth are based on the August short-term forecast of GII, extended by EIA through 2030 and modified to reflect EIA’s view on energy prices, demand, and production.

470

1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.  

Science Conference Proceedings (OSTI)

This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

United States. Bonneville Power Administration.

1994-02-01T23:59:59.000Z

471

A Short-Range Forecasting Experiment Conducted during the Canadian Atlantic Storms Program  

Science Conference Proceedings (OSTI)

During the Canadian Atlantic Storms Program (CASP), a dedicated forecast center conducted experiments in mesoscale forecasting. Several forecast products, including a marine forecast and a site-specific public forecast, were written every 3 h. ...

K. A. Macdonald; M. Danks; J. D. Abraham

1988-06-01T23:59:59.000Z

472

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Coal Coal Although coal use is expected to be displaced by natural gas in some parts of the world, only a slight drop in its share of total energy consumption is projected by 2025. Coal continues to dominate electricity and industrial sector fuel markets in emerging Asia. Figure 50. World Coal Consumption by Region, 1970-2025 (Billion Short Tons). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 51. Coal Share of World Energy Consumption by Sector, 2002, 2015, and 2025 (Percent). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 52. World Recoverable Coal Reserves. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world

473

Skill of Seasonal Climate Forecasts in Canada Using Canonical Correlation Analysis  

Science Conference Proceedings (OSTI)

An empirical system for forecasting 3-month mean surface temperature T and total precipitation P for Canada—canonical correlation analysis (CCA)—has been developed using the 1956–90 data period. The levels and sources of predictive skill have ...

Amir Shabbar; Anthony G. Barnston

1996-10-01T23:59:59.000Z

474

Earthquake Forecast via Neutrino Tomography  

E-Print Network (OSTI)

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

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

2010-01-17T23:59:59.000Z

475

Decision support for financial forecasting  

SciTech Connect

A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

1988-10-01T23:59:59.000Z

476

Construction Safety Forecast for ITER  

SciTech Connect

The International Thermonuclear Experimental Reactor (ITER) project is poised to begin its construction activity. This paper gives an estimate of construction safety as if the experiment was being built in the United States. This estimate of construction injuries and potential fatalities serves as a useful forecast of what can be expected for construction of such a major facility in any country. These data should be considered by the ITER International Team as it plans for safety during the construction phase. Based on average U.S. construction rates, ITER may expect a lost workday case rate of < 4.0 and a fatality count of 0.5 to 0.9 persons per year.

cadwallader, lee charles

2006-11-01T23:59:59.000Z

477

MSSM Forecast for the LHC  

E-Print Network (OSTI)

We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered, the preferred region (for $\\mu>0$) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-$\\mu$ possibilities.

Maria Eugenia Cabrera; Alberto Casas; Roberto Ruiz de Austri

2009-11-24T23:59:59.000Z

478

Forecasting future volatility from option prices, Working  

E-Print Network (OSTI)

Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.

Allen M. Poteshman

2000-01-01T23:59:59.000Z

479

Forecast Bias Correction: A Second Order Method  

E-Print Network (OSTI)

The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.

Crowell, Sean

2010-01-01T23:59:59.000Z

480

Industrial production index forecast: Methods comparison  

Science Conference Proceedings (OSTI)

The purpose of this work is to investigate the suitability of different methods as short term forecast tools. It is studied and compared the application of the Kalman filter method with other forecasting methods when applied to a set of qualitative and quantitative information. The work data set is made of qualitative surveys of conjunture and the industrial production index (IPI). The objective is the attainment of short term forecast models for the Portuguese IPI of the transforming industry. After the previous treatment of the data

M. Filomena Teodoro

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast period figure" 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

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy  

E-Print Network (OSTI)

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy Criteria for Technical forecasts of monsoon can significantly aid many sectors like agriculture, power and production industries to the operational forecast, to develop and deliver customized monsoon forecasts based on user need is required

Swathi, P S

482

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

483

Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)  

DOE Green Energy (OSTI)

This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

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

2013-10-01T23:59:59.000Z

484

Optimal Updating of Forecasts for the Timing of Future Events  

Science Conference Proceedings (OSTI)

A major problem in forecasting is estimating the time of some future event. traditionally, forecasts are designed to minimize an error cost function that is evaluated once, possibly when the event occurs and forecast accuracy can be determined. However, ... Keywords: Air Transportation, Dynamic Programming Applications, Forecasting

Juhwen Hwang; Medini R. Singh; W. J. Hurley; Robert A. Shumsky

1998-03-01T23:59:59.000Z

485

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn

486

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

487

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti

488

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast uncertainty  

E-Print Network (OSTI)

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast, the uncertainty of the forecast FTLE fields is analyzed using ensemble forecasting. Unavoidable errors of the forecast velocity data due to the chaotic dynamics of the atmosphere is the salient reason for errors

Ross, Shane

489

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng  

E-Print Network (OSTI)

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations

Kim, Kiho

490

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT  

E-Print Network (OSTI)

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT OF USING FORECASTS Mohamed Zied Ch^atenay-Malabry Cedex, France Abstract: In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given

Paris-Sud XI, Université de

491

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

492

A Study on Training Criteria for Financial Time Series Forecasting  

E-Print Network (OSTI)

A Study on Training Criteria for Financial Time Series Forecasting JingTao YAO Dept of Information on goodness-of-fit which is also the most popular criterion forecasting. How ever, in the context of financial time series forecasting, we are not only concerned at how good the forecasts fit their target. In order

Yao, JingTao

493

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

494

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

495

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

496

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

497

New results in forecasting of photovoltaic systems output based on solar radiation forecasting  

Science Conference Proceedings (OSTI)

Accurate short term forecasting of photovoltaic (PV) systems output has a great significance for fast development of PV parks in South-East Europe

Laurentiu Fara

2013-01-01T23:59:59.000Z

498

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.

499

How Do Forecasters Utilize Output From A Convection-Permitting Ensemble Forecast System? Case Study Of A High-Impact Precipitation Event  

Science Conference Proceedings (OSTI)

The proliferation of ensemble forecast system output in recent years motivates this investigation into how operational forecasters utilize convection-permitting ensemble forecast system guidance in the forecast preparation process. A sixteen-...

Clark Evans; Donald F. Van Dyke; Todd Lericos

500

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122