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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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1

(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

2

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Eighth Electric Utility Forecasting Symposium in Baltimore,Development of a Residential Forecasting Database. Lawrenceand Methodology for End-Use Forecasting with EPRI-REEPS 2.1.

Johnson, F.X.

2010-01-01T23:59:59.000Z

3

Bias Correction and Forecast Skill of NCEP GFS Ensemble Week-1 and Week-2 Precipitation, 2-m Surface Air Temperature, and Soil Moisture Forecasts  

Science Conference Proceedings (OSTI)

A simple bias correction method was used to correct daily operational ensemble week-1 and week-2 precipitation and 2-m surface air temperature forecasts from the NCEP Global Forecast System (GFS). The study shows some unexpected and striking ...

Yun Fan; Huug van den Dool

2011-06-01T23:59:59.000Z

4

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

E-Print Network (OSTI)

Development of a Residential Forecasting Database. Lawrenceand Methodology for End-Use Forecasting with EPRI-REEPS 2.1.and Methodology for End-Use Forecasting with EPRI-REEPS 2.1.

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

5

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

6

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

7

Does Money Matter in Inflation Forecasting? JM Binner 1  

E-Print Network (OSTI)

1 Does Money Matter in Inflation Forecasting? JM Binner 1 P Tino 2 J Tepper 3 R Anderson4 B Jones 5 or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide collections of included monetary assets. In our forecasting experiment we use two non-linear techniques

Tino, Peter

8

Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1  

E-Print Network (OSTI)

Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1 David Levinson 2 February the accuracy of demand forecasts using a sample of recently-completed projects in Minnesota and identifies the factors influencing the inaccuracy in forecasts. The fore- cast traffic data for this study is drawn from

Levinson, David M.

9

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

10

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...

11

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

12

12-32021E2_Forecast  

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

FORECAST OF VACANCIES FORECAST OF VACANCIES Until end of 2014 (Issue No. 20) Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff at the P4-P5 levels: * Advanced university degree (or equivalent postgraduate degree); * 7 or 10 years, respectively, of experience in a field of relevance to the post; * Resource management experience; * Strong analytical skills; * Computer skills: standard Microsoft Office software; * Languages: Fluency in English. Working knowledge of other official languages (Arabic, Chinese, French, Russian, Spanish) advantageous; * Ability to work effectively in multidisciplinary and multicultural teams; * Ability to communicate effectively. Professional staff at the P1-P3 levels:

13

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

14

Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1  

Science Conference Proceedings (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

1994-05-01T23:59:59.000Z

15

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

Science Conference Proceedings (OSTI)

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

Templeton, K.J.

1996-05-23T23:59:59.000Z

16

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

Science Conference Proceedings (OSTI)

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

Valero, O.J.

1996-02-22T23:59:59.000Z

17

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

18

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; Malaquas Pea Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

19

Verification of RUC 01-h Forecasts and SPC Mesoscale Analyses Using VORTEX2 Soundings  

Science Conference Proceedings (OSTI)

This study uses radiosonde observations obtained during the second phase of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) to verify base-state variables and severe-weather-related parameters calculated from Rapid ...

Michael C. Coniglio

2012-06-01T23:59:59.000Z

20

Accuracy of RUC-1 and RUC-2 Wind and Aircraft Trajectory Forecasts by Comparison with ACARS Observations  

Science Conference Proceedings (OSTI)

As part of an investigation into terminal airspace productivity sponsored by the NASA Ames Research Center, a study was performed at the Forecast Systems Laboratory to investigate sources of wind forecast error and to assess differences in wind ...

Barry E. Schwartz; Stanley G. Benjamin; Steven M. Green; Matthew R. Jardin

2000-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

energy policy initiatives (EIA 1990). Utilities rely on end-use forecasting models in order to assess market trends

Johnson, F.X.

2010-01-01T23:59:59.000Z

22

SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2  

Science Conference Proceedings (OSTI)

This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

BARCOT, R.A.

2003-12-01T23:59:59.000Z

23

Assimilation of Remote-sensing Soil Moisture in Short-term River Forecasting M. Pan1, E. F. Wood1, W. Crow2, J. Schaake3  

E-Print Network (OSTI)

Assimilation of Remote-sensing Soil Moisture in Short-term River Forecasting M. Pan1, E. F. Wood1 Hydrology and Remote Sensing Lab, US Department of Agriculture 3 National Weather Service, National Oceanic and Atmospheric Administration 1. Introduction This study focuses on evaluation of hydrologic remote sensing

Pan, Ming

24

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

E-Print Network (OSTI)

=1 Index 1990=1 Lighting 0-1 hrs 1-2 hrs Usage level 2-3 hrsMiscellaneous Lighting 0-1 hrs 1-2 hrs Usage level 2-3 hrsMiscellaneous Lighting 0-1 hrs 1-2 hrs Usage level 2-3 hrs

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

25

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

E-Print Network (OSTI)

Natural Gas Oil Lighting 0-1 hrs 1-2 his 2-3 hrs Usage levelgas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usagegas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usage

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

26

WP1: Targeted and informative forecast system design  

E-Print Network (OSTI)

WP1: Targeted and informative forecast system design Emma Suckling, Leonard A. Smith and David Stainforth EQUIP Meeting ­ August 2011 Edinburgh #12;Targeted and informative forecast system design Develop models to support decision making (1.4) #12;Targeted and informative forecast system design KEY QUESTIONS

Stevenson, Paul

27

Downscaling Ensemble Weather Predictions for Improved Week-2 Hydrologic Forecasting  

Science Conference Proceedings (OSTI)

This study investigates the use of large-scale ensemble weather predictions provided by the National Centers for Environmental Prediction (NCEP) Global Forecast System [GFS; formerly known as Medium-Range Forecast (MRF)] for improving week-2 ...

Xiaoli Liu; Paulin Coulibaly

2011-12-01T23:59:59.000Z

28

Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1  

E-Print Network (OSTI)

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

Washington at Seattle, University of

29

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting-uses include Heating, Ventilation and Air Conditioning (HVAC). Our analysis uses the modeling framework provided by the HVAC module in the Residential End-Use Energy Planning System (REEPS), which was developed

30

Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting. DE-AC03-76SF00098 #12;i ABSTRACT This report details the data, assumptions and methodology for end-use provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which

31

Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results  

SciTech Connect

This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

Koomey, J.G.; Brown, R.E.; Richey, R. [and others

1995-12-01T23:59:59.000Z

32

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

H $2,000 hl S z % Reduction in Total Space Conditioning LoadAppliances and Space Conditioning Equipment. Arthur D.3.1 and 3.4. The space conditioning loads are based on the

Johnson, F.X.

2010-01-01T23:59:59.000Z

33

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 SEPTEMBER 14, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 ­ SEPTEMBER 14 percent of) climatology. These new two-week forecasts have replaced the monthly forecasts that we have This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

34

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

35

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

36

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

37

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Efficiency Choice 6.3 New Home HVAC System Choice 6.4. NewJuly. EPRI. 1990. REEPS 2.0 HVAC Model Logic, prepared by1990. Review of Equipment HVAC Choice Parameters. Cambridge

Johnson, F.X.

2010-01-01T23:59:59.000Z

38

Annual Energy Outlook Forecast Evaluation - Tables 2-18  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Consumption: AEO Forecasts, Actual Values, and Total Energy Consumption: AEO Forecasts, Actual Values, and Absolute and Percent Errors, 1985-1999 Publication 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Average Absolute Error (Quadrillion Btu) AEO82 79.1 79.6 79.9 80.8 82.0 83.3 1.8 AEO83 78.0 79.5 81.0 82.4 83.8 84.6 89.5 1.2 AEO84 78.5 79.4 81.2 83.1 85.0 86.4 93.5 1.5 AEO85 77.6 78.5 79.8 81.2 82.6 83.3 84.2 85.2 85.9 86.7 87.7 1.3 AEO86 77.0 78.8 79.8 80.6 81.5 82.9 84.0 84.8 85.7 86.5 87.9 88.4 87.8 88.7 3.6 AEO87 78.9 80.0 81.9 82.8 83.9 85.3 86.4 87.5 88.4 1.5 AEO89 82.2 83.7 84.5 85.4 86.4 87.3 88.2 89.2 90.8 91.4 90.9 91.7 1.8

39

A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction  

E-Print Network (OSTI)

A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction Xing, the Climate Forecast System version 2 (CFSv2), with advanced physics, increased resolution and refined initiali- zation to improve the seasonal climate forecasts. We present a first look at the capability

Pan, Ming

40

Radiation fog forecasting using a 1-dimensional model  

E-Print Network (OSTI)

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

Peyraud, Lionel

2001-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

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

42

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

43

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

44

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

45

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

46

Statistical Journal of the United Nations ECE 23 (2006) 110 1 New forecast: Population decline postponed  

E-Print Network (OSTI)

Statistical Journal of the United Nations ECE 23 (2006) 1­10 1 IOS Press New forecast: Population, Finland fStatistics Norway, Oslo, Norway Abstract. We present results of a probabilistic forecast for the population in 18 European countries, to 2050. Other forecasts have recently predicted a falling population

Løw, Erik

47

322 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 1, FEBRUARY 2010 Short-Term Load Forecasting: Similar  

E-Print Network (OSTI)

: Progress Report on Electricity Price Forecast As part of the Mid Term Assessment, staff is preparing a long-term wholesale electricity market price forecast. Staff will review how the forecasts are made and some Forecast Update #12;Process Overview 2 Regional Portfolio Model Electric Demand Forecasting System (Long

Luh, Peter

48

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

49

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

50

Short-Term Load Forecasting by Feed-Forward Neural Networks Saied S. Sharif1  

E-Print Network (OSTI)

1 Sixth Northwest Conservation & Electric Power Plan Draft Wholesale Power Price Forecasts Maury Price Forecasts 4. Updated load-resource balance by zones\\ regions · Energy · Capacity 5. Impact. Updated transmission links between the modeled load-resource zones 3. Updated demand forecasts for each

Taylor, James H.

51

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

52

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

53

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the U.S. residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute (McMenamin et al. 1992). In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70 % of electricity consumption and 30 % of natural gas consumption in the U.S. residential sector (EIA 1993). Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific

J. Hwang; Francis X. Johnson; Richard E. Brown; James W. Hanford; Jonathan G. Koomey

1994-01-01T23:59:59.000Z

54

Prediction Skill and Bias of Tropical Pacific Sea Surface Temperatures in the NCEP Climate Forecast System Version 2  

Science Conference Proceedings (OSTI)

The prediction skill and bias of tropical Pacific sea surface temperature (SST) in the retrospective forecasts of the Climate Forecast System, version 2 (CFSv2), of the National Centers for Environmental Prediction were examined. The CFSv2 was ...

Yan Xue; Mingyue Chen; Arun Kumar; Zeng-Zhen Hu; Wanqiu Wang

2013-08-01T23:59:59.000Z

55

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

56

hal-00122749,version1-8Jan2007 Time Series Forecasting: Obtaining Long Term Trends with  

E-Print Network (OSTI)

. For example when forecast- ing an electrical consumption, it could be advan- tageous to predict all hourly As second example, we use the Polish electrical load time series [ 6]. This series contains hourly valueshal-00122749,version1-8Jan2007 Time Series Forecasting: Obtaining Long Term Trends with Self

Paris-Sud XI, Université de

57

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

58

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

59

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

60

Subgrid Scale Physics in 1-Month Forecasts. Part I: Experiment with Four Parameterization Packages  

Science Conference Proceedings (OSTI)

Four packages of subgrid scale (SGS) physics parameterization are tested by including them in a general circulation model and by applying the four models to 1-month forecasts. The four models are formulated by accumulatively increasing the ...

J. Sirutis; K. Miyakoda

1990-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

Impact of Kalpana-1-Derived Water Vapor Winds on Indian Ocean Tropical Cyclone Forecasts  

Science Conference Proceedings (OSTI)

The water vapor winds from the operational geostationary Indian National Satellite (INSAT) Kalpana-1 have recently become operational at the Space Applications Centre (SAC). A series of experimental forecasts are attempted here to evaluate the ...

S. K. Deb; C. M. Kishtawal; P. K. Pal

2010-03-01T23:59:59.000Z

62

The possible reasons for the misrepresented long-term climate trends in the seasonal forecasts of HFP2  

Science Conference Proceedings (OSTI)

The climate trend in a dynamical seasonal forecasting system is examined using 33-year multi-model ensemble (MME) forecasts from the second phase of the Canadian Historical Forecasting Project (HFP2). It is found that the warming trend of the ...

XiaoJing Jia; Hai Lin

63

A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307  

Science Conference Proceedings (OSTI)

This paper describes a fully automated scheme that has provided calibrated 110-day ensemble river discharge forecasts and predictions of severe flooding of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational ...

Thomas M. Hopson; Peter J. Webster

2010-06-01T23:59:59.000Z

64

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.

65

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

Open Energy Info (EERE)

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

66

Factors Influencing Skill Improvements in the ECMWF Forecasting System  

Science Conference Proceedings (OSTI)

During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. There are three major contributing factors: 1) improvements in the forecast model, 2) improvements in the data assimilation, and 3) the increased number of ...

Linus Magnusson; Erland Klln

2013-09-01T23:59:59.000Z

67

International Statistical Review (2012), 80, 1, 223 doi:10.1111/j.1751-5823.2011.00168.x Short-Term Wind Speed Forecasting  

E-Print Network (OSTI)

. KEY WORDS Load Pocket Modeling, Load Forecasting 1. Introduction Electric power load forecasting is important for electric utilities. Load forecasting helps an electric utility in making important decisions in the industry for the electric load forecasting. When the model #12;presented in this paper was applied

Genton, Marc G.

68

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

69

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

70

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts  

E-Print Network (OSTI)

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts.com Abstract The seasonal prediction skill of the Asian summer monsoon is assessed using retrospective predic and the maritime continent. The southwest monsoon flow and the Somali Jet are stronger in SYS4, while the south

Webster, Peter J.

71

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2013  

E-Print Network (OSTI)

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY activity is predicted. (as of 10 April 2013) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well as past forecasts and verifications are available via the World Wide Web at http://hurricane.atmos.colostate.edu/Forecasts

72

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2012  

E-Print Network (OSTI)

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY activity is predicted. (as of 4 April 2012) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well as past forecasts and verifications are available via the World Wide Web at http://hurricane.atmos.colostate.edu/Forecasts

73

FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2009  

E-Print Network (OSTI)

FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2009 We have reduced our forecast slightly from early June due largely to the development of an El Niño. We continue. Klotzbach1 and William M. Gray2 This forecast as well as past forecasts and verifications are available via

74

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 ­ AUGUST 16, 2012 relative to climatology. (as of 3 August 2012) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

75

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

76

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

77

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

78

Long-term Stock Market Forecasting using Gaussian Processes  

E-Print Network (OSTI)

Address3 email4 Abstract5 Forecasting stock market prices is an attractive topic to researchers from6 to analyze18 and forecast stock prices and index changes. The accuracy of these techniques is still an19-term predictions in stock prices.32 33 1.2 Motivation34 In stock market, investors need long-term forecasting

de Freitas, Nando

79

Forecasting the Path of China's CO2 Emissions Using Province Level Information  

E-Print Network (OSTI)

Garin-Mu oz, T. : 2002, Forecasting chinas carbon dioxideF. X. : 2001, Elements of Forecasting, South-Western College2003, Macroeconomic forecasting in the euro area: Country

Auffhammer, Maximilian; Carson, Richard T.

2007-01-01T23:59:59.000Z

80

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

Note: This page contains sample records for the topic "forecast 2 1" 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

Probabilistic Transmission Congestion and Constraints Forecast (PCF) Version 1.0  

Science Conference Proceedings (OSTI)

The Probabilistic Transmission Congestion and Constraints Forecast (PCF) Version 1.0 program provides the user the capability to compute the probabilistic distribution functions of line flows with consideration of generation, load and network uncertainties. Description PCF Version 1.0 models the generation and load in a probabilistic way, and computes the probabilistic distribution functions of line flows. The program can handle generation and load uncertainties in a probabilistic model. It can handle tr...

2008-12-12T23:59:59.000Z

82

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

83

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

84

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...

85

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

86

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

87

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

E-Print Network (OSTI)

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

Birner, Thomas

88

CFSv2-Based Seasonal Hydroclimatic Forecasts over the Conterminous United States  

Science Conference Proceedings (OSTI)

There is a long history of debate on the usefulness of climate modelbased seasonal hydroclimatic forecasts as compared to ensemble streamflow prediction (ESP). In this study, the authors use NCEP's operational forecast system, the Climate ...

Xing Yuan; Eric F. Wood; Joshua K. Roundy; Ming Pan

2013-07-01T23:59:59.000Z

89

California Wind Energy Forecasting System Development and Testing Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

This report describes results from the second phase of the California Wind Energy Forecasting System Development and Testing Project.

2003-07-22T23:59:59.000Z

90

Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

We have shown that it is possible to predict the skill of numerical weather forecastsa 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

91

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

92

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

93

SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2  

Science Conference Proceedings (OSTI)

This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

BARCOT, R.A.

2005-08-17T23:59:59.000Z

94

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

SciTech Connect

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

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

2011-09-29T23:59:59.000Z

95

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

96

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

97

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

98

U.S. diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon  

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

diesel fuel price forecast to be 1 penny lower this summer diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon The retail price of diesel fuel is expected to average $3.94 a gallon during the summer driving season that which runs from April through September. That's close to last summer's pump price of $3.95, according to the latest monthly energy outlook from the U.S. Energy Information Administration. Demand for distillate fuel, which includes diesel fuel, is expected to be up less than 1 percent from last summer. Daily production of distillate fuel at U.S. refineries is forecast to be 70,000 barrels higher this summer. With domestic distillate output exceeding demand, U.S. net exports of distillate fuel are expected to average 830,000 barrels per day this summer. That's down 12 percent from last summer's

99

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 14 weeks are vital to many applications in the context of weather and climate risk management, ...

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

2008-12-01T23:59:59.000Z

100

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

Note: This page contains sample records for the topic "forecast 2 1" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

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

102

California Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting uses sophisticated numerical weather forecasting and wind plant power generation models to predict the hourly energy generation of a wind power plant up to 48 hours in advance. As a result, it has great potential to address the needs of the California Independent System Operator (ISO) and the wind plant operators, as well as power marketers and buyers and utility system dispatch personnel. This report gives the results of 28 days of testing of wind energy forecasting at a Californ...

2003-01-31T23:59:59.000Z

103

Texas Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

This report describes initial results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2003-12-31T23:59:59.000Z

104

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 nave method), or highly complex such as neural nets and econometric systems of simultaneous equations. The

Rob J Hyndman

2009-01-01T23:59:59.000Z

105

Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision  

Science Conference Proceedings (OSTI)

A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

Not Available

1994-12-01T23:59:59.000Z

106

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2013  

E-Print Network (OSTI)

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY-average forecast, we are calling for an above-average probability of United States and Caribbean major hurricane landfall. (as of 3 June 2013) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well as past

107

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

108

Texas Wind Energy Forecasting System Development and Testing: Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting systems are expected to support system operation in cases where wind generation contributes more than a few percent of total generating capacity. This report presents final results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2004-09-30T23:59:59.000Z

109

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

110

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

111

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

112

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

Science Conference Proceedings (OSTI)

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

Samuel Rmy; Thierry Bergot

2010-05-01T23:59:59.000Z

113

Generated using V3.1.2 of the official AMS LATEX templatejournal page layout FOR AUTHOR USE ONLY, NOT FOR SUBMISSION! Quantifying uncertainty for climate change and long range forecasting scenarios with  

E-Print Network (OSTI)

out in the training phase of the unperturbed climate. 1. Introduction One of the ultimate goals atmosphere-ocean simulation (AOS) models which necessarily parameterize some physical features such as clouds, sea ice cover, etc., as well as turbulent fluxes due subgrid processes in the resolved dynamics

Majda, Andrew J.

114

322 IEEE TRANSACTIONS ON POWER SYSTEMS. VOL. 25. NO. I. FEBRUARY 2010 Short-Term Load Forecasting: Similar  

E-Print Network (OSTI)

for Short Term Electrical Load Forecasting," IEEE Trans. PWRS, vol. 11, no. 1, Feb. 1996, pp. 397-402. [4Short-Term Load Forecasting by Feed-Forward Neural Networks Saied S. Sharif1 , James H. Taylor2) is presented for the hourly load forecasting of the coming days. In this approach, 24 independent networks

Luh, Peter

115

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

Science Conference Proceedings (OSTI)

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

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

2013-06-01T23:59:59.000Z

116

Expert Panel: Forecast Future Demand for Medical Isotopes  

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

Expert Panel: Expert Panel: Forecast Future Demand for Medical Isotopes March 1999 Expert Panel: Forecast Future Demand for Medical Isotopes September 25-26, 1998 Arlington, Virginia The Expert Panel ............................................................................................. Page 1 Charge To The Expert Panel........................................................................... Page 2 Executive Summary......................................................................................... Page 3 Introduction ...................................................................................................... Page 4 Rationale.......................................................................................................... Page 6 Economic Analysis...........................................................................................

117

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

118

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

119

Review/Verify Strategic Skills Needs/Forecasts/Future Mission...  

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

ReviewVerify Strategic Skills NeedsForecastsFuture Mission Shifts Annual Lab Plan (1-10 yrs) Fermilab Strategic Agenda (2-5 yrs) Sector program Execution Plans (1-3...

120

Long range forecast of power demands on the Baltimore Gas and Electric Company system. Volume 1  

SciTech Connect

The report presents the results of an econometric forecast of peak and electric power demands for the Baltimore Gas and Electric Company (BGandE) through the year 2003. The report describes the methodology, the results of the econometric estimations and associated summary statistics, the forecast assumptions, and the calculated forecasts of energy usage and peak demand. Separate models were estimated for summer and winter residential electricity usage in both Baltimore city and the non-city portion of the BGandE service area. Equations were also estimated for commercial energy usage, industrial usage, streetlighting, and for losses plus Company use. Non-econometric techniques were used to estimate future energy use by Bethlehem Steel Corporation's Sparrows Point plant in Baltimore County, Conrail, and the Baltimore Mass Transit Administration underground rail system. Models of peak demand for summer and winter were also estimated.

Estomin, S.L.; Kahal, M.I.

1985-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

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

E-Print Network (OSTI)

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

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

2004-01-01T23:59:59.000Z

122

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast Summary............................................................................................................ 2 Sixth Power Plan Demand Forecast................................................................................................ 4 Demand Forecast Range

123

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

124

1) INTRODUCTION The accuracy of short-term wind power forecasts is besides  

E-Print Network (OSTI)

unconsidered outages of single turbines reflect a higher forecast error than expected from NWP. Wind power. The wind farm was in the commissioning phase in early 2001, when gradually more and more turbines became due to turbine wakes in the wind park and vi) accounting the availability of turbines with respect

Heinemann, Detlev

125

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

126

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations  

Gasoline and Diesel Fuel Update (EIA)

AEO82 to AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 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

127

Nambe Pueblo Water Budget and Forecasting model.  

SciTech Connect

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

Brainard, James Robert

2009-10-01T23:59:59.000Z

128

Description of the NMC Global Data Assimilation and Forecast System  

Science Conference Proceedings (OSTI)

The National Meteorological Center's (NMC) Global Data Assimilation and Forecast System is described in some detail. The system consists of 1) preprocessing of the initial guess, 2) optimum interpolation objective analysis, 3) update of the ...

Masao Kanamitsu

1989-09-01T23:59:59.000Z

129

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

130

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

131

> 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

132

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

E-Print Network (OSTI)

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

Inesc Coimbra; Joo Loureno; Paulo Santos; Loureno J. M; Santos P. J

2010-01-01T23:59:59.000Z

133

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

Science Conference Proceedings (OSTI)

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

McNamara, Laura A.

2010-08-01T23:59:59.000Z

134

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 oceanatmosphere 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

135

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

136

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

E-Print Network (OSTI)

the accuracy of two methods to forecast natural gas prices:forecasting models along with the AEO forecast. Appendix ATable 1. Forecast Year AEO Predicted Price from 1996-2003

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

2005-01-01T23:59:59.000Z

137

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

138

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"

139

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

140

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

Note: This page contains sample records for the topic "forecast 2 1" 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

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

142

Summary Short?Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1  

E-Print Network (OSTI)

It is often noted that energy prices are quite volatile, reflecting market participants adjustments to new information from physical energy markets and/or markets in energyrelated financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the marketclearing process for risk transfer can be used to generate price bands around observed futures prices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to trade. The Energy Information Administrations (EIA) monthly Short-Term Energy Outlook (STEO) publishes base case projections for a variety of energy prices that go out 12 to 24 months (every January the STEO forecast is extended through December of the following year). EIA has recognized that all price forecasts are highly uncertain and has described the uncertainty by identifying the market factors that may significantly move prices away from their expected paths, such as economic growth, Organization of Petroleum Exporting Countries (OPEC) behavior, geo-political events, and hurricanes.

unknown authors

2009-01-01T23:59:59.000Z

143

Blue Chip Consensus US GDP Forecast  

E-Print Network (OSTI)

and metro area from Moodys 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

144

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

145

Annual Energy Outlook with Projections to 2025 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2005 Forecast Comparisons Table 32. Forecasts of annual average economic growth, 2003-2025 Printer Friendly Version Average annual percentage growth Forecast 2003-2009 2003-2014 2003-2025 AEO2004 3.5 3.2 3.0 AEO2005 Reference 3.4 3.3 3.1 Low growth 2.9 2.8 2.5 High growth 4.1 3.9 3.6 GII 3.4 3.2 3.1 OMB 3.6 NA NA CBO 3.5 3.1 NA OEF 3.5 3.5 NA Only one other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a time horizon similar to that of AEO2005. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as other forecasts that concentrate on economic growth, international oil prices, energy

146

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

147

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

148

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

149

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 OCTOBER 12, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 ­ OCTOBER 12 (greater than 130 percent of climatology.) These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

150

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 ­ OCTOBER 11) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

151

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 SEPTEMBER 26, 2013  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 ­ SEPTEMBER 26) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

152

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 SEPTEMBER 28, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 ­ SEPTEMBER 28 (greater than 130 percent of climatology.) These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

153

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 OCTOBER 25, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 ­ OCTOBER 25%) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

154

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

155

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

156

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

157

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

158

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

159

Forecasting the market for SO sub 2 emission allowances under uncertainty  

SciTech Connect

This paper deals with the effects of uncertainty and risk aversion on market outcomes for SO{sub 2} emission allowance prices and on electric utility compliance choices. The 1990 Clean Air Act Amendments (CAAA), which are briefly reviewed here, provide for about twice as many SO{sub 2} allowances to be issued per year in Phase 1 (1995--1999) than in Phase 2. Considering the scrubber incentives in Phase 1, there is likely to be substantial emission banking for use in Phase 2. Allowance prices are expected to increase over time at a rate less than the return on alternative investments, so utilities which are risk neutral, or potential speculators in the allowance market, are not expected to bank allowances. The allowances will be banked by utilities that are risk averse. The Argonne Utility Simulation Model (ARGUS2) is being revised to incorporate the provisions of the CAAA acid rain title and to simulate SO{sub 2} allowance prices, compliance choices, capacity expansion, system dispatch, fuel use, and emissions using a unit level data base and alternative scenario assumptions. 1 fig.

Hanson, D.; Molburg, J.; Fisher, R.; Boyd, G.; Pandola, G.; Lurie, G.; Taxon, T.

1991-01-01T23:59:59.000Z

160

Update On The Wholesale Electricity Price Forecast & Modeling Results  

E-Print Network (OSTI)

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

Note: This page contains sample records for the topic "forecast 2 1" 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

Forecasting exurban development to evaluate the influence of land-use policies on wildland and farmland conservation  

E-Print Network (OSTI)

Planning Vol 1 (2005) 4057 Forecasting exurban developmentof general plans for forecasting future development can be

Merenlender, Adina M.; Brooks, Colin; Shabazian, David; Gao, Shengyi; Johnston, Robert A.

2005-01-01T23:59:59.000Z

162

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

163

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

164

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

165

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

166

APPENDIX D-2 DETAILED RESULTS  

E-Print Network (OSTI)

.3 Industry #12;Industrial Sector Forecast Summary Electricity as Primary energy Page 4 CEF-NEMS Business.850 1.787 Appendix D-2.xls D-2.4 Industry #12;Industrial Sector Forecast Summary Electricity as Primary.241 29.674 30.010 Appendix D-2.xls D-2.10 Industry #12;Industrial Sector Forecast Summary Electricity

167

GenForecast(26yr)(avg).PDF  

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

SLCAIP Historical & Forecast Generation at Plant Total Range of Hydrology 0 2,000,000,000 4,000,000,000 6,000,000,000 8,000,000,000 10,000,000,000 12,000,000,000 1 9 7 0 1 9 7 2 1...

168

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

169

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

170

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

171

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

172

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.

173

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

174

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

175

Tape 2, Side 1  

E-Print Network (OSTI)

Suri Kamara 270 323 1/2 29/12/61 Story of two women Suri Kamara 323 270 10/1 1964 Jan to Feb (not in...

Finnegan, Ruth

176

Tape 1, Side 2  

E-Print Network (OSTI)

Suri Kamara 270 323 1/2 29/12/61 Story of two women Suri Kamara 323 270 10/1 1964 Jan to Feb (not in...

Finnegan, Ruth

177

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

E-Print Network (OSTI)

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

Cattuto, Ciro

178

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

179

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...

180

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

Note: This page contains sample records for the topic "forecast 2 1" 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

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

Science Conference Proceedings (OSTI)

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

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

2006-05-01T23:59:59.000Z

182

FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2013  

E-Print Network (OSTI)

FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2013 We continue to anticipate an above-average season in 2013, although we have lowered our forecast slightly due and William M. Gray2 This forecast as well as past forecasts and verifications are available online at: http://hurricane.atmos.colostate.edu/Forecasts

183

Page 1 of2  

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

Page 1 of2 The DOE Executive Salary Approval parameters contained in AL2000-12 are hereby reinstated pending final issuance of revised DOE Order 350.1 X, Contractor Human Resources...

184

A Short-Term Ensemble Wind Speed Forecasting System for Wind Power Applications  

Science Conference Proceedings (OSTI)

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 h ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather ...

Justin J. Traiteur; David J. Callicutt; Maxwell Smith; Somnath Baidya Roy

2012-10-01T23:59:59.000Z

185

EUROCONTROL EUROCONTROL Long-Term Forecast: IFR Flight Movements 2010-2030  

E-Print Network (OSTI)

published in September 2010 (Ref.1). This forecast replaces the EUROCONTROL Long-Term Forecast issued in November 2008. The forecast uses four scenarios to explore the future of the aviation and the risks that lie

Flight Movements

2010-01-01T23:59:59.000Z

186

Simulations of Arctic Mixed-Phase Clouds in Forecasts with CAM3 and AM2 for M-PACE  

SciTech Connect

Simulations of mixed-phase clouds in short-range forecasts with the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed under the DOE CCPP-ARM Parameterization Testbed (CAPT), which initializes the climate models with analysis data produced from numerical weather prediction (NWP) centers. It is shown that CAM3 significantly underestimates the observed boundary layer mixed-phase clouds and cannot realistically simulate the variations with temperature and cloud height of liquid water fraction in the total cloud condensate based an oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer clouds while its clouds contain much less cloud condensate than CAM3 and the observations. Both models underestimate the observed cloud top and base for the boundary layer clouds. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used. The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes in CAM3. It is shown that the Bergeron-Findeisen process, i.e., the ice crystal growth by vapor deposition at the expense of coexisting liquid water, is important for the models to correctly simulate the characteristics of the observed microphysical properties in mixed-phase clouds. Sensitivity tests show that these results are not sensitive to the analysis data used for model initializations. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. Ice crystal number density has large impact on the model simulated mixed-phase clouds and their microphysical properties and needs to be accurately represented in climate models.

Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Liu, Xiaohong; Ghan, Steven J.

2008-02-29T23:59:59.000Z

187

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

188

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 ...

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

1995-07-01T23:59:59.000Z

189

Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision  

Science Conference Proceedings (OSTI)

This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

Not Available

1993-12-01T23:59:59.000Z

190

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4  

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

Current Forecast: December 10, 2013; Previous Forecast: November 13, 2013 Current Forecast: December 10, 2013; Previous Forecast: November 13, 2013 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 2011 2012 2013 2014 2011-2012 2012-2013 2013-2014 U.S. Energy Supply U.S. Crude Oil Production (million barrels per day) Current 6.22 6.29 6.42 7.02 7.11 7.29 7.61 7.97 8.26 8.45 8.57 8.86 5.65 6.49 7.50 8.54 14.8% 15.6% 13.8% Previous 6.22 6.30 6.43 7.04 7.13 7.30 7.60 7.91 8.22 8.40 8.52 8.80 5.65 6.50 7.49 8.49 15.0% 15.2% 13.3% Percent Change 0.0% -0.1% -0.2% -0.2% -0.3% -0.1% 0.1% 0.7% 0.5% 0.5% 0.6% 0.6% 0.0% -0.1% 0.1% 0.6% U.S. Dry Natural Gas Production (billion cubic feet per day) Current 65.40 65.49 65.76 66.34 65.78 66.50 67.11 67.88 67.99 67.74 67.37 67.70 62.74 65.75 66.82 67.70 4.8% 1.6% 1.3% Previous 65.40 65.49 65.76 66.34 65.78 66.50 67.11 67.30 67.47 67.41 67.04 67.37 62.74 65.75 66.68 67.32

191

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 ...

192

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

193

Building Energy Software Tools Directory: Degree Day Forecasts  

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

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

194

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

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

Abdel-Aal, Radwan E.

195

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 Srensen

2003-01-01T23:59:59.000Z

196

Phase 1 -- 2  

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

2 2 Revised 8/7/02 " "Sample Statement of Work - Standard Service Offerings for Contractor-Identified Project" "Task #","Task Title","Work Scope","Deliverable","Agency Requirements" " " "Phase Two - Initial Project Development" "2-1","DO RFP Development - Direct Support","Based upon interviews Agency/site staff and consultation support, FEMP Services will prepare DO RFP for Agency/site. FEMP Services will provide onsite or telecon review of draft DO RFP with agency staff. FEMP Services will prepare 2nd draft DO RFP based on telecon and written agency review comments and recommendations. ","Draft DO RFP Document. On-site review of draft DO RFP.

197

Phase 1 --2  

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

2 2 Rev 4-01-05 " "Statement of Work - Standard Service Offerings for Contractor-Identified Project at (insert project site)" "Task #","Task Title","Work Scope","Deliverable","Agency Requirements" " " "Phase Two - Initial Project Development" "2-1","DO RFP Development - Direct Support","Based upon interviews Agency/site staff and consultation support, FEMP Services will prepare DO RFP for Agency/site. FEMP Services will provide onsite or telecon review of draft DO RFP with agency staff. FEMP Services will prepare 2nd draft DO RFP based on telecon and written agency review comments and recommendations. ","Draft DO RFP Document. On-site review of draft DO RFP.

198

BEAMLINE 2-1  

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

1 1 CURRENT STATUS: Open SUPPORTED TECHNIQUES: Powder diffraction Thin film diffraction MAIN SCIENTIFIC DISCIPLINES: Materials / Environmental % TIME GENERAL USE: 100% SCHEDULING: Proposal Submittal and Scheduling Procedures Current SPEAR and Beam Line Schedules SOURCE: 1.3 Tesla Bend Magnet BEAM LINE SPECIFICATIONS: energy range resolution DE/E spot size flux angular acceptance focused 4000-14500 eV ~5 x 10-4 .20 x 0.45 mm 1.5 mrad OPTICS: Bent cylinder, single-crystal Si, Rh-coated mirror Radii: 2900 m (adjustable) x 52 mm Mean angle of incidence: 4.2 milliradians Cut off energy: 14.5 keV, Magnification: 1.1 MONOCHROMATOR: Si(111), Si(220) Si(400), upward reflecting, double-crystal Monochromator Crystal Glitch Library Crystal changes need to be scheduled and coordinated in advance with BL

199

Forecasting project progress and early warning of project overruns with probabilistic methods  

E-Print Network (OSTI)

Forecasting is a critical component of project management. Project managers must be able to make reliable predictions about the final duration and cost of projects starting from project inception. Such predictions need to be revised and compared with the projects objectives to obtain early warnings against potential problems. Therefore, the effectiveness of project controls relies on the capability of project managers to make reliable forecasts in a timely manner. This dissertation focuses on forecasting project schedule progress with probabilistic methods. Currently available methods, for example, the critical path method (CPM) and earned value management (EVM) are deterministic and fail to account for the inherent uncertainty in forecasting and project performance. The objective of this dissertation is to improve the predictive capabilities of project managers by developing probabilistic forecasting methods that integrate all relevant information and uncertainties into consistent forecasts in a mathematically sound procedure usable in practice. In this dissertation, two probabilistic methods, the Kalman filter forecasting method (KFFM) and the Bayesian adaptive forecasting method (BAFM), were developed. The KFFM and the BAFM have the following advantages over the conventional methods: (1) They are probabilistic methods that provide prediction bounds on predictions; (2) They are integrative methods that make better use of the prior performance information available from standard construction management practices and theories; and (3) They provide a systematic way of incorporating measurement errors into forecasting. The accuracy and early warning capacity of the KFFM and the BAFM were also evaluated and compared against the CPM and a state-of-the-art EVM schedule forecasting method. Major conclusions from this research are: (1) The state-of-the-art EVM schedule forecasting method can be used to obtain reliable warnings only after the project performance has stabilized; (2) The CPM is not capable of providing early warnings due to its retrospective nature; (3) The KFFM and the BAFM can and should be used to forecast progress and to obtain reliable early warnings of all projects; and (4) The early warning capacity of forecasting methods should be evaluated and compared in terms of the timeliness and reliability of warning in the context of formal early warning systems.

Kim, Byung Cheol

2007-12-01T23:59:59.000Z

200

Forecasting project progress and early warning of project overruns with probabilistic methods  

E-Print Network (OSTI)

Forecasting is a critical component of project management. Project managers must be able to make reliable predictions about the final duration and cost of projects starting from project inception. Such predictions need to be revised and compared with the project's objectives to obtain early warnings against potential problems. Therefore, the effectiveness of project controls relies on the capability of project managers to make reliable forecasts in a timely manner. This dissertation focuses on forecasting project schedule progress with probabilistic methods. Currently available methods, for example, the critical path method (CPM) and earned value management (EVM) are deterministic and fail to account for the inherent uncertainty in forecasting and project performance. The objective of this dissertation is to improve the predictive capabilities of project managers by developing probabilistic forecasting methods that integrate all relevant information and uncertainties into consistent forecasts in a mathematically sound procedure usable in practice. In this dissertation, two probabilistic methods, the Kalman filter forecasting method (KFFM) and the Bayesian adaptive forecasting method (BAFM), were developed. The KFFM and the BAFM have the following advantages over the conventional methods: (1) They are probabilistic methods that provide prediction bounds on predictions; (2) They are integrative methods that make better use of the prior performance information available from standard construction management practices and theories; and (3) They provide a systematic way of incorporating measurement errors into forecasting. The accuracy and early warning capacity of the KFFM and the BAFM were also evaluated and compared against the CPM and a state-of-the-art EVM schedule forecasting method. Major conclusions from this research are: (1) The state-of-the-art EVM schedule forecasting method can be used to obtain reliable warnings only after the project performance has stabilized; (2) The CPM is not capable of providing early warnings due to its retrospective nature; (3) The KFFM and the BAFM can and should be used to forecast progress and to obtain reliable early warnings of all projects; and (4) The early warning capacity of forecasting methods should be evaluated and compared in terms of the timeliness and reliability of warning in the context of formal early warning systems.

Kim, Byung Cheol

2007-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

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

SciTech Connect

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

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

1992-02-01T23:59:59.000Z

202

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

SciTech Connect

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

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

1992-02-01T23:59:59.000Z

203

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

204

Draft Forecast of Electricity Demand for the 5th  

E-Print Network (OSTI)

products has been below the medium-low. Future natural gas prices are expected to be higher in this power's draft natural gas price forecasts. The medium natural gas price forecast for this plan in 2015 is about Council Document 2001-23, sited above. #12;DRAFT DRAFT DRAFT 11 Table 1 Natural Gas Price Forecasts

205

Power load forecasting Organization: Huizhou Electric Power, P. R. China  

E-Print Network (OSTI)

, regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting are essential to the operation and planning of a utility company. Load forecasting helps an electric utility as electric load forecasting. In particular, ARMA (autoregressive moving average), ARIMA (autore- gressive

206

Draft for Public Comment Appendix A. Demand Forecast  

E-Print Network (OSTI)

Draft for Public Comment A-1 Appendix A. Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required component of the Council's Northwest Regional Conservation had a tradition of acknowledging the uncertainty of any forecast of electricity demand and developing

207

Distribution Based Data Filtering for Financial Time Series Forecasting  

E-Print Network (OSTI)

of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain/selling strategies to gain competitive advantage. Classic and popular methods for stock price forecasting [3Distribution Based Data Filtering for Financial Time Series Forecasting Goce Ristanoski1 , James

Bailey, James

208

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Average Absolute Percent Error Variable AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 Consumption Total Energy Consumption 1.7 1.7 1.8 1.9 1.9 2.1 Total Petroleum Consumption 2.9 2.8 2.9 3.0 2.9 2.9 Total Natural Gas Consumption 5.7 5.6 5.6 5.5 5.5 6.5 Total Coal Consumption 3.0 3.2 3.3 3.5 3.6 3.7 Total Electricity Sales 1.7 1.8 1.9 2.4 2.5 2.4 Production Crude Oil Production 4.3 4.5 4.5 4.5 4.5 4.7 Natural Gas Production 4.8 4.7 4.6 4.6 4.4 4.4 Coal Production 3.6 3.6 3.5 3.7 3.6 3.8 Imports and Exports Net Petroleum Imports 9.5 8.8 8.4 7.9 7.4 7.5 Net Natural Gas Imports 16.7 16.0 15.9 15.8 15.8 15.4

209

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

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

210

NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts  

E-Print Network (OSTI)

· NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt;#12;Copyright ©2012 by WVU Research Corporation Unless otherwise noted, data used for this forecast is from IHS Population 2 GlOBAl OUTlOOk 3 Current Trends 3 Forecast 6 UNITED STATES OUTlOOk 9 Global and United States

Mohaghegh, Shahab

211

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

212

Page 1 of 2  

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

~ ~ Page 1 of 2 1) This memorandum provides reminders on the proper use of non-DOE contracting vehicles. including Economy Act transactions. Government-wide Acquisition Contracts. and Federal Supply Schedules. The recent discovery of improper use of such contracting vehicles has led to investigations ,:>f procurement activities at the General Services Administration and Department of Defense. Contracting Officers are cautioned to be diligent in the use of other agencies' contracting vehicles. 2) This memorandwn provides an overview of a Biobased Products Procurement Preference Program being developed as a result of the F8ml Security and Rural Development Act of 2002 and a recent rulemaking issued by the U.S. Department of Agriculture. It will highlight

213

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

214

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...

215

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

216

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

217

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

218

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

219

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

220

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

Note: This page contains sample records for the topic "forecast 2 1" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

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

222

Maintaining the Role of Humans in the Forecast Process: Analyzing the Psyche of Expert Forecasters  

Science Conference Proceedings (OSTI)

The Second Forum on the Future Role of the Human in the Forecast Process occurred on 23 August 2005 at the American Meteorological Society's Weather Analysis and Forecasting Conference in Washington, D.C. The forum consisted of three sessions. ...

Neil A. Stuart; David M. Schultz; Gary Klein

2007-12-01T23:59:59.000Z

223

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

224

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

225

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.

Ivn Marinovic; Marco Ottaviani; Peter Norman Srensen

2011-01-01T23:59:59.000Z

226

An Objective Basis for Forecasting Tornado Intensity  

Science Conference Proceedings (OSTI)

Although violent tornadoes comprise only 2.3% of tornado occurrences in the United States, they cause 68% of the fatalities attributed to tornadoes and severe thunderstorms. Despite these statistics, no attempt is made to forecast or warn of ...

J. R. Colquhoun; D. J. Shepherd

1989-03-01T23:59:59.000Z

227

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

228

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2012  

E-Print Network (OSTI)

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY increased our forecast slightly from early April, due to large amounts of uncertainty in both the phase and William M. Gray2 This forecast as well as past forecasts and verifications are available via the World

229

Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal  

E-Print Network (OSTI)

--Congestion forecasting, price forecasting, wholesale power market, locational marginal price, load partitioning, convex for system planning.1 Many studies have focused on electricity price forecasting based on statistical tools distributed loads and DC-OPF system variable solutions was identified and applied to forecast congestion

Abdel-Aal, Radwan E.

230

MLWFA: A Multilingual Weather Forecast Text Generation Tianfang YAO Dongmo ZHANG Qian WANG  

E-Print Network (OSTI)

MLWFA: A Multilingual Weather Forecast Text Generation System1 Tianfang YAO Dongmo ZHANG Qian WANG generation; Weather forecast generation system Abstract In this demonstration, we present a system for multilingual text generation in the weather forecast domain. Multilingual Weather Forecast Assistant (MLWFA

Wu, Dekai

231

ib:12-07-a Closer than You Think: Latest U.S. CO 2 Pollution Data and Forecasts Show Target Within Reach  

E-Print Network (OSTI)

How about a little good news for a change? Despite Congress failure to enact comprehensive energy and climate legislation, surprising, and underappreciated, progress has been made in reducing U.S. carbon dioxide emissions during the last few years. In 2011 U.S. emissions of energy-related carbon dioxide were 8.7 percent below 2005 levels despite a 5.5 percent increase in the size of our economy. This remarkable result is due primarily to reduced reliance on coal-fired power plants and increased passenger vehicle efficiency, driven by a combination of policy and market forces. The forecast for 2020, assuming extensions to existing policies that can be reasonably anticipated, is for a further reduction to 10.5 percent below 2005 levels. This contrasts sharply with the forecast made by the Energy Information Agency 7 years ago that emissions would increase by 25 percent between then and 2020, and it puts the 17 percent reduction target embraced by President Obama squarely within reach. Recent Trends U.S. energy-related CO 2 emissions were 5473 million metric

Dan Lashof

2012-01-01T23:59:59.000Z

232

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

233

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

234

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

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

235

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

236

Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts  

Science Conference Proceedings (OSTI)

The value of the model output statistics (MOS) approach to improving 610-day and week 2 probabilistic forecasts of surface temperature and precipitation is demonstrated. Retrospective 2-week ensemble reforecasts were computed using a version ...

Thomas M. Hamill; Jeffrey S. Whitaker; Xue Wei

2004-06-01T23:59:59.000Z

237

Relationship between Precipitation Forecast Errors and Skill Scores of Dichotomous Forecasts  

Science Conference Proceedings (OSTI)

In this paper, the sensitivities of the equitable threat score (ETS) and the true skill score (TSS), obtained with a 2 2 contingency table, to continuous precipitation forecast errors are investigated. Two idealized error models are adopted to ...

Nazario Tartaglione

2010-02-01T23:59:59.000Z

238

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.

239

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

240

September 2000Forecasting Future Variance from Option Prices  

E-Print Network (OSTI)

Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option

Allen M. Poteshman; Mark R. Manfredo; Allen M. Poteshman; Allen M. Poteshman; Champaign Helpful; Jegadeesh Narasimhan

2000-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

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...

242

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

243

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

244

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices

245

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

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

246

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]—also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to

247

On L 1 L 2 ???M 2  

Science Conference Proceedings (OSTI)

The well-known inequality L 1 L 2 ???M 2 connecting the coefficients of self- and mutual inductances for a pair of coupled circuits is derived by analytical methods

Edwin A. Power

1969-01-01T23:59:59.000Z

248

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

249

Multivariate Forecast Evaluation And Rationality Testing  

E-Print Network (OSTI)

10621088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): OnKingdom. MULTIVARIATE FORECASTS Kirchgssner, G. , and U. K.2005): Estimation and Testing of Forecast Rationality under

Komunjer, Ivana; OWYANG, MICHAEL

2007-01-01T23:59:59.000Z

250

Page 1 of 2  

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

FLASH 2004-02 FLASH 2004-02 February 11, 2004 As discussed in Policy Flash 2003-05, the BPN, an element under the Integrated Acquisition Environment (IAE) 'which is part of the e-government initiative, is a grouping of systems that track vendor data. ()nline Representations and Certifications (ORCA) is another application to the BPN, similar to 1:he Central Contractor Registration (CCR), and the Federal Procurement Data System-Next Cieneration (FPDS-NG). This electronic application replaces the paper based Representations and Certifications (reps. and certs.) process. Also, ORCA is desi;~ed to eliminate the administrative burden on contractors who are required to provide reps. and certs. infonnation to various contracting offices as many times as an otTer is submitted. The use1ulness of the Online Representations and Certifications allows Federal

251

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

252

MPX V1.2  

Energy Science and Technology Software Center (OSTI)

002209WKSTN00 Hardware Counter Multiplexing V1.2 https://computation.llnl.gov/casc/mpx/mpx.home.html

253

Page 1 of 2  

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

The purpose of this memorandum is to revise the discretionary set-aside authority addressed on The purpose of this memorandum is to revise the discretionary set-aside authority addressed on Page 13 of Acquisition Letter 2004-03 from SSO,(XX) to SIOO,(XX). Questions may be addressed to Steve Zvolensky at (202) 287-1307 or St~hen.zvolensk~@hg.doe.£ov Attachment cc: PP AG Members ;k..t ./ /!k~ --'"' Michael P. Fischetti Acting Director Office of Procurement and Assistance Policy Michael Acting I Office 0 Page 2 of 2 MEMORANDUM FOR DISTRIBUTION 6tfJ FROM: RICHARD H. HOPF, DIRECT~ OFFICE OF PROCUREMENT AND ASSIST ANCE ~ Discretionary Set-Aside A:tho} SUBJECT: The purpose of this memorandum is to revise the discretionary set-aside authority addressed on Page 13 of Acquisition Letter 2004-03 from $50,000 to $100,000. The paragraph entitled, Discretionary Set-Asides, is revised to read:

254

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

SciTech Connect

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

Platt, H.D.

1981-08-01T23:59:59.000Z

255

Page 1 of2  

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

new product, the E-DEAR, is packaged as a single file in Microsoft Wordc fontlat and is new product, the E-DEAR, is packaged as a single file in Microsoft Wordc fontlat and is fontlatted to be word processor friendly. It is "searchable" in the "edit/find" sense but lacks any sophisticated search al1d list capability. The E-DEAR has bookmarks for each Part, and in Part 970, bookmarks exist for each subpart. After opening the file in WordC, you access the bookmarks by selectmg "insert," then "bookmark." Select the part or subpart you wish to access from the drop down menu and click the "Go To" icon. We have retained the current "read by Subpart" capability and added a link to the Hill AFB FarSite. Also a librar)' of final rules which amended the DEAR is also available. These tools

256

Page 1 of 2  

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

"benchmark compensation amount" is to be used for contractor FY 2004 and subsequent "benchmark compensation amount" is to be used for contractor FY 2004 and subsequent contractor FY s unless and until revised by OFFP. This benchmark compensation amount applies to contract costs incurred after January 1,2004, under covered contracts of both defense and civilian procurement agencies, as specified in Section 808 of Pub. L.I05-85. This "benchmark compensation amount" supersedes the amount cited in Headquarters Policy Flash 2003-19, August 26,2003. Applicability of the FAR to M&O contracts is addressed at 48 CFR 31.205-6(p) and 48CFR 970.3102-O5-6(p), respectively. For questions related to this Flash, contact Terry Sheppard at (202) 586-8193 or via e-mail at terrv.sheQoard@hg.doe.gov Attachment Cc: PP AG Members FLASH 2004.16

257

Double SOM for long-term time series prediction Geoffroy Simon1  

E-Print Network (OSTI)

-term prediction, self-organizing maps, Santa Fe, electrical load Abstract --- Many time series forecasting, the Santa Fe A series and a problem of electrical load forecasting. 2 Time series prediction The classical in one bloc, rather than a single t+1 scalar value. For example, in an electrical load forecasting

Paris-Sud XI, Université de

258

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 analysts 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

259

Remote Sensing Of Snow Cover For Operational Forecasts  

E-Print Network (OSTI)

The areal extent of the seasonal snow cover is an important input variable for operational snowmelt runoff forecasts. It can be monitored by satellites and used by the SRM Snowmelt Runoff Model. An example is presented of simulated dayto -day runoff forecasts for a hydroelectric station Sedrun (108 km , 1840-3210 m a.s.l.). For realtime runoff forecasts it will be necessary to evaluate the satellite data within several days after each overflight. 1

K. Seidel; J. Martinec; C. Steinmeier; W. Bruesch

1993-01-01T23:59:59.000Z

260

table1.2_02  

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

2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; 2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE NAICS Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 230 13 19 582 5 184 1 89 0 6.8 311221 Wet Corn Milling 217 23 * * 61 * 121 0 11 0 1.1 31131 Sugar 112 2 2 1 22 * 37 1 46 0 0.9 311421 Fruit and Vegetable Canning 47 7 1 1 36 Q 0 0 1 0 11 312 Beverage and Tobacco Products 105 26 2 2 46 1 17 0 11

Note: This page contains sample records for the topic "forecast 2 1" 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

Bulk flows from galaxy luminosities: application to 2MASS redshift survey and forecast for next-generation datasets  

E-Print Network (OSTI)

We present a simple method for measuring cosmological bulk flows from large redshift surveys, based on the apparent dimming or brightening of galaxies due to their peculiar motion. It is aimed at estimating bulk flows of cosmological volumes containing large numbers of galaxies. Constraints on the bulk flow are obtained by minimizing systematic variations in galaxy luminosities with respect to a reference luminosity function measured from the whole survey. This method offers two advantages over more popular bulk flow estimators: it is independent of error-prone distance indicators and of the poorly-known galaxy bias. We apply the method to the 2MASS redshift survey (2MRS) to measure the local bulk flows of spherical shells centered on the Milky Way (MW). The result is consistent with that obtained by Nusser and Davis (2011) using the SFI++ catalogue of Tully-Fisher distance indicators. We also make an assessment of the ability of the method to constrain bulk flows at larger redshifts ($z=0.1-0.5$) from next generation datasets. As a case study we consider the planned EUCLID survey. Using this method we will be able to measure a bulk motion of $ \\sim 200 \\kms$ of $10^6$ galaxies with photometric redshifts, at the $3\\sigma$ level for both $z\\sim 0.15$ and $z\\sim 0.5$. Thus the method will allow us to put strong constraints on dark energy models as well as alternative theories for structure formation.

Adi Nusser; Enzo Branchini; Marc Davis

2011-02-21T23:59:59.000Z

262

Verification of Authors' Seasonal Forecast for Winter 2001/02 NAO and Central England Temperature  

E-Print Network (OSTI)

1 Verification of Authors' Seasonal Forecast for Winter 2001/02 NAO and Central England Temperature of our experimental seasonal forecasts, released on the 16th November 2001, for the winter 2001 Temperature (CET). 1. Winter 2001/02 NAO Forecast Key: NAO Index 1 = Mean sea level pressure difference

Saunders, Mark

263

Spider 2, Version 2.1  

Science Conference Proceedings (OSTI)

The EPRI Spider 2, Version 2.1 software application (product ID # 1016529) allows a user to create a detailed assessment plan for evaluating the conditions of equipment, systems, processes and plans, and to make quantitative decisions based on qualitative data. Description Using basic concepts and technology developed over the years by the Electric Power Research Institute (EPRI), the Spider 2 software application provides a unique method for an organization to automate assessments of equipment, systems ...

2008-06-16T23:59:59.000Z

264

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

Science Conference Proceedings (OSTI)

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

Qin Zhang; Huug van den Dool

2012-08-01T23:59:59.000Z

265

A methodology for forecasting carbon dioxide flooding performance  

E-Print Network (OSTI)

A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very helpful when time and data resources are limited. The methodology consists of five tasks: 1) select a section of the reservoir with the most detailed geologic, reservoir, and production data, 2) perform material balance analysis for the selected section to determine 001? and the history of total expansion, voidage, and injectage, 3) establish an average 5-spot pattern within the selected section, 4) develop a black oil numerical simulation model for a quarter of the 5-spot pattern and simulate the primary and waterflood recovery processes, and 5) forecast carbon dioxide performance using Shell's Scoping model, Texaco's "PROPHET" model, and VIP miscible simulator. One of the major limitations of the methodology is that details of individual well performance and reservoir pressure and fluid saturation distributions in the project area are not available. Therefore, the forecast is limited to the average pattern and to the reservoir as a whole. Results of the Dollarhide Clearfork simulation study show that 9.7 % to 14.1 % of OOIP may be recovered by C02 flood in the selected section. It would require WAG injection cycles with a total fluid injection of 0.831 HCPV.

Marroquin Cabrera, Juan Carlos

1998-01-01T23:59:59.000Z

266

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

SciTech Connect

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

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

2007-06-01T23:59:59.000Z

267

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

268

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

269

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

270

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.

271

Validation of short and medium term operational solar radiation forecasts in the US  

SciTech Connect

This paper presents a validation of the short and medium term global irradiance forecasts that are produced as part of the US data set. The short term forecasts that extend up to 6-h ahead are based upon cloud motion derived from consecutive geostationary satellite images. The medium term forecasts extend up to 6-days-ahead and are modeled from gridded cloud cover forecasts from the US National Digital Forecast Database. The forecast algorithms are validated against ground measurements for seven climatically distinct locations in the United States for 1 year. An initial analysis of regional performance using satellite-derived irradiances as a benchmark reference is also presented. (author)

Perez, Richard; Kivalov, Sergey; Schlemmer, James; Hemker, Karl Jr. [ASRC, University at Albany, Albany, New York (United States); Renne, David [National Renewable Energy Laboratory, Golden, Colorado (United States); Hoff, Thomas E. [Clean Power Research, Napa, California (United States)

2010-12-15T23:59:59.000Z

272

Forecast Skill of the MaddenJulian Oscillation in Two Canadian Atmospheric Models  

Science Conference Proceedings (OSTI)

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

Hai Lin; Gilbert Brunet; Jacques Derome

2008-11-01T23:59:59.000Z

273

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 Undn

1988-09-01T23:59:59.000Z

274

Mesoscale Forecasts Generated from Operational Numerical Weather-Prediction Model Output  

Science Conference Proceedings (OSTI)

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

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

1988-01-01T23:59:59.000Z

275

Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events  

Science Conference Proceedings (OSTI)

The development of NWP models with grid spacing down to 1 km should produce more realistic forecasts of convective storms. However, greater realism does not necessarily mean more accurate precipitation forecasts. The rapid growth of errors on ...

Nigel M. Roberts; Humphrey W. Lean

2008-01-01T23:59:59.000Z

276

Impacts of Forecaster Involvement on Convective Storm Initiation and Evolution Nowcasting  

Science Conference Proceedings (OSTI)

A forecaster-interactive capability was added to an automated convective storm nowcasting system [Auto-Nowcaster (ANC)] to allow forecasters to enhance the performance of 1-h nowcasts of convective storm initiation and evolution produced every 6 ...

Rita D. Roberts; Amanda R. S. Anderson; Eric Nelson; Barbara G. Brown; James W. Wilson; Matthew Pocernich; Thomas Saxen

2012-10-01T23:59:59.000Z

277

Comparative Verification of Guidance and Local Quantitative Precipitation Forecasts: Calibration Analyses  

Science Conference Proceedings (OSTI)

A comparative verification is reported of 2631 matched pairs of quantitative precipitation forecasts (QPFs) prepared daily from 1 October 1992 to 31 October 1996 by the Hydrometeorological Prediction Center (HPC) and the Weather Service Forecast ...

Roman Krzysztofowicz; Ashley A. Sigrest

1999-06-01T23:59:59.000Z

278

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

279

2.1E Supplement  

E-Print Network (OSTI)

GENERATOR Introduction Gas Turbine Steam Turbine SIMULATIONSModes 1: Chillers, Gas Turbine, and Boiler 2: Chillers,O R SIMULATIONS Introduction Gas Turbine Steam Turbine PLANT

Winkelmann, F.C.

2010-01-01T23:59:59.000Z

280

Solar forecasting review  

E-Print Network (OSTI)

2.1.2 European Solar Radiation Atlas (ESRA)for supplementing solar radiation network data, FinalEstimating incident solar radiation at the surface from geo-

Inman, Richard Headen

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

Characterization and Simulation of ECBM: History Matching of Forecasting CO2 Sequestration in Marshal County, West Virginia.  

E-Print Network (OSTI)

into an unmineable coal seam in the Marshall Country West Virginia. Two coal seams (Pittsburgh and Upper Freeport) are the subject of this pilot CO2 sequestration project. Methane is produced from both coal seams; however CO2 is injected only in the Upper Freeport which includes four wells. The shallower Pittsburgh coal is used

Mohaghegh, Shahab

282

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,

283

Experimental Determination of Forecast Sensitivity and the Degradation of Forecasts through the Assimilation of Good Quality Data  

Science Conference Proceedings (OSTI)

The case of a small vigorous cyclone crossing the United Kingdom on 1 November 2009 is investigated. Met Office Global Model forecasts at the time displayed a marked change in solutions at a forecast range of 72 h, with those at longer ranges ...

Adrian Semple; Michael Thurlow; Sean Milton

2012-07-01T23:59:59.000Z

284

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

Reports and Publications (EIA)

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

Information Center

2010-06-01T23:59:59.000Z

285

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF

286

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

287

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

288

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

289

Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part II: Precipitation  

E-Print Network (OSTI)

Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part II: Precipitation for Medium-Range Weather Forecasts, Reading, United Kingdom JEFFREY S. WHITAKER NOAA/Earth System Research As a companion to Part I, which discussed the calibration of probabilistic 2-m temperature forecasts using large

Hamill, Tom

290

Table H.1co2  

U.S. Energy Information Administration (EIA)

AC Argentina AR Aruba AA Bahamas, The BF Barbados BB Belize BH Bolivia BL ... Table H.1co2 World Carbon Dioxide Emissions from the Consumption and Flaring of Fossil ...

291

A new hybrid iterative method for short-term wind speed forecasting  

E-Print Network (OSTI)

Electric Load Model (HELM).1 HELM takes many specific end-use forecasts for each sector and applies for electricity. It is driven by detailed forecasts of economic activity, demographic patterns, and alternative of electricity. Demand forecasts both determine, and are determined by, electricity prices. Therefore demand

292

Air-Conditioning Effect Estimation for Mid-Term Forecasts of Tunisian Electricity Consumption  

E-Print Network (OSTI)

: Engineering-industry, secondary: Econometrics. 1 Introduction The electric power mid-term loads forecasting: Estimated annual temperature sensitive electricity load components 3 Mid-term load forecasting StatisticalAir-Conditioning Effect Estimation for Mid-Term Forecasts of Tunisian Electricity Consumption

Paris-Sud XI, Université de

293

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

E-Print Network (OSTI)

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

Sibille, Etienne

294

Associations Between Management Forecast Accuracy and Pricing of IPOs in Athens Stock  

E-Print Network (OSTI)

1 Associations Between Management Forecast Accuracy and Pricing of IPOs in Athens Stock Exchange Dimitrios Gounopoulos* University of Surrey, U.K. This study examines the earnings forecast accuracy earnings forecast and pricing ofIPOs. It uses a unique data set of 208 IPOs, which were floated during

Jensen, Max

295

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 AUGUST 30, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 ­ AUGUST 30, 2012 percent) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 17 August 2012) By Philip J. Klotzbach1

Gray, William

296

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2011  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 ­ SEPTEMBER 13 percent) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 31 August 2011) By Philip J. Klotzbach1

Birner, Thomas

297

The stock index forecast based on dynamic recurrent neural network trained with GA  

E-Print Network (OSTI)

neural networks applied in forecasting stock price, at present, the most widely used neural network is BPThe stock index forecast based on dynamic recurrent neural network trained with GA Fang Yixian1In order to forecast the stock market more accurately, according to the dynamic property for the stock

298

Concepts of medium-range (13 days) geomagnetic forecasting Hans Gleisner *, Jurgen Watermann  

E-Print Network (OSTI)

Concepts of medium-range (1­3 days) geomagnetic forecasting Hans Gleisner *, Ju¨rgen Watermann to geomagnetic forecasting. In this report from an ongoing study within the ESA Space Weather Appli- cations of geomagnetic activity forecasts hours to days ahead. Observations of eruptive events on the Sun are nowadays

Gleisner, Hans

299

Appendix: Selected Answers Section 1.2  

E-Print Network (OSTI)

Appendix: Selected Answers Chapter 1 Section 1.2 1.2.1 (a) 5/6. (b) 1. (c) 1/2. 1.2.4 No. 1.2.8 No/4. 1.6.3 limn P(An) = P(A) = P(S) = 1. 1 #12;2 APPENDIX: SELECTED ANSWERS Chapter 2 Section 2.1 2.1.1(a Negative Binomial(r + s, ) . Section 2.4 2.4.1 (a) P(U 0) = 0. (b) P(U = 1/2) = 0. (c) P(U

Rosenthal, Jeffrey S.

300

286 IEEE TRANSACTIONS ON SMART GRID, VOL. 1, NO. 3, DECEMBER 2010 Short-Term Load Forecast of Microgrids by a New  

E-Print Network (OSTI)

of Microgrids by a New Bilevel Prediction Strategy Nima Amjady, Senior Member, IEEE, Farshid Keynia, Member, IEEE, and Hamidreza Zareipour, Senior Member, IEEE Abstract--Microgrids are a rapidly growing sector. In the operation of a microgrid, forecasting the short-term load is an important task. With a more accurate short

Note: This page contains sample records for the topic "forecast 2 1" 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

96 2 97 1 ......................................................................4  

E-Print Network (OSTI)

........................................................................ 17 6 ICDF............................................................ 17 7MediaTek Scholarship Mxic Scholarship 3 TSMC Sponsorship ICDF TIGP94 96 2 96 1 175 3 86% 2 94 96 ICDF TIGP TSMC 94 35 15 16 11 -- 77 95 59 37 23 19 -- 138 96 84 65 20 21 3 193 3 96

Huang, Haimei

302

2.1E Supplement  

E-Print Network (OSTI)

o. (o. (o. (o. (o- (o. UTILITY-RATE RESOURCE = NATURAL-GAS CHG In this example, two utility rates have been defined3 / 9 2.1E- 8 1 / 3 E - UTILITY-RATE MINOR-OVHL-COST MIN-O-C

Winkelmann, F.C.

2010-01-01T23:59:59.000Z

303

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

304

Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas  

E-Print Network (OSTI)

Ten years (1997 - 2006) of summer (June, July, August) daytime (14 - 00 Z) Weather Surveillance Radar - 1988 Doppler data for Houston, TX were examined to determine the best radar-derived lightning forecasting predictors. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to cloud-to-ground lightning data from the National Lightning Detection Network (NLDN). Combinations of three radar reflectivity values (30, 35, and 40 dBZ) at four isothermal levels (-10, -15, -20, and updraft -10 degrees C) and a new radar-derived product, vertically integrated ice (VII), were used to optimize a radar-based lightning forecast algorithm. Forecasts were also delineated by range and the number of times a cell was identified and tracked by the modified SCIT algorithm. This study objectively analyzed 65,399 unique cells, and 1,028,510 to find the best lightning forecast criteria. Results show that using 30 dBZ at the -20 degrees C isotherm on cells within 75 km of the radar that have been tracked for at least 2 consecutive scan produces the best forecasts with a critical success index (CSI) of 0.71. The best VII predictor was 0.734 kg m-2 on cells within 75 km of the radar that have been tracked for at least 2 consecutive scans producing a CSI of 0.68. Results of this study further suggest that combining the radar reflectivity and VII methods can result in a more accurate lightning forecast than either method alone.

Mosier, Richard Matthew

2009-12-01T23:59:59.000Z

305

1. INTRODUCTION 1.1 SABAP1 AND SABAP2  

E-Print Network (OSTI)

that have uniform habitat and limited landscape features (e.g. in the Karoo or Kalahari Coastal Belt & Little Karoo (Blue) Field Data Sheet 2 = West Coast and Succulent Karoo (Beige) Field Data was in the Karoo, but that you saw the House Sparrow only at the farm house. 2.6.5 Behaviour Use this category

de Villiers, Marienne

306

Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System  

DOE Green Energy (OSTI)

Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

Chin, H S

2005-07-26T23:59:59.000Z

307

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

308

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

309

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

310

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

311

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

312

Appendix I1-2 to Wind HUI Initiative 1: Field Campaign Report  

DOE Green Energy (OSTI)

This report is an appendix to the Hawaii WindHUI efforts to dev elop and operationalize short-term wind forecasting and wind ramp event forecasting capabilities. The report summarizes the WindNET field campaign deployment experiences and challenges. As part of the WindNET project on the Big Island of Hawaii, AWS Truepower (AWST) conducted a field campaign to assess the viability of deploying a network of monitoring systems to aid in local wind energy forecasting. The data provided at these monitoring locations, which were strategically placed around the Big Island of Hawaii based upon results from the Oahu Wind Integration and Transmission Study (OWITS) observational targeting study (Figure 1), provided predictive indicators for improving wind forecasts and developing responsive strategies for managing real-time, wind-related system events. The goal of the field campaign was to make measurements from a network of remote monitoring devices to improve 1- to 3-hour look ahead forecasts for wind facilities.

John Zack; Deborah Hanley; Dora Nakafuji

2012-07-15T23:59:59.000Z

313

Lattice QCD-2+1  

E-Print Network (OSTI)

We consider a 2+1-dimensional SU(N) lattice gauge theory in an axial gauge with the link field U in the 1-direction set to one. The term in the Hamiltonian containing the square of the electric field in the 1-direction is non-local. Despite this non-locality, we show that weak-coupling perturbation theory in this term gives a finite vacuum-energy density to second order, and suggest that this property holds to all orders. Heavy quarks are confined, the spectrum is gapped, and the space-like Wilson loop has area decay.

Peter Orland

2005-01-26T23:59:59.000Z

314

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

315

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

316

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

317

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

318

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

319

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

320

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

Note: This page contains sample records for the topic "forecast 2 1" 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

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

322

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

323

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

324

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

325

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

326

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

327

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

328

SF424_2_1-V2.1.pdf  

Gasoline and Diesel Fuel Update (EIA)

Number: 4040-0004 Number: 4040-0004 Expiration Date: 03/31/2012 * 1. Type of Submission: * 2. Type of Application: * 3. Date Received: 4. Applicant Identifier: 5a. Federal Entity Identifier: * 5b. Federal Award Identifier: 6. Date Received by State: 7. State Application Identifier: * a. Legal Name: * b. Employer/Taxpayer Identification Number (EIN/TIN): * c. Organizational DUNS: * Street1: Street2: * City: County/Parish: * State: Province: * Country: * Zip / Postal Code: Department Name: Division Name: Prefix: * First Name: Middle Name: * Last Name: Suffix: Title: Organizational Affiliation: * Telephone Number: Fax Number: * Email: * If Revision, select appropriate letter(s): * Other (Specify): State Use Only: 8. APPLICANT INFORMATION: d. Address: e. Organizational Unit: f. Name and contact information of person to be contacted on matters involving this application:

329

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

330

Online short-term solar power forecasting  

SciTech Connect

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

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

2009-10-15T23:59:59.000Z

331

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

332

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

333

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

334

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...

335

Weather Regimes and Forecast Errors in the Pacific Northwest  

Science Conference Proceedings (OSTI)

Despite overall improvements in numerical weather prediction and data assimilation, large short-term forecast errors of sea level pressure and 2-m temperature still occur. This is especially true for the west coast of North America where short-...

Lynn A. McMurdie; Joseph H. Casola

2009-06-01T23:59:59.000Z

336

EIA forecasts increased oil demand, need for additional supply ...  

U.S. Energy Information Administration (EIA)

World oil demand is forecast to increase by 1.7 million barrels per day (bbl/d) ... Cooling demand in the Middle East is expected to rise to record levels this summer.

337

Retail Motor Gasoline Price* Forecast Doesn't Reflect Potential...  

Gasoline and Diesel Fuel Update (EIA)

5 Notes: EIA's gasoline price forecast has gasoline prices, on a monthly average, possibly exceeding 1.70 per gallon. Of course, weekly prices would likely peak this summer even...

338

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

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

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

339

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

340

Beamline 3.2.1  

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

2.1 Print 2.1 Print Commercial deep-etch x-ray lithography (LIGA) GENERAL BEAMLINE INFORMATION Operational Yes, but not open to users Source characteristics Bend magnet Energy range 3-12 keV Monochromator None Endstations Hutch with automated scanner Calculated spot size at sample 100 x 10 mm Sample format 3- and 4-in. wafer format; x-ray mask and LIGA substrate Sample environment Ambient, air Scientific disciplines Applied science Scientific applications Deep-etch x-ray lithography (LIGA) Spokesperson This e-mail address is being protected from spambots. You need JavaScript enabled to view it Advanced Light Source, Berkeley Lab Phone: (510) 486-5527 Fax: (510) 486-4102 This e-mail address is being protected from spambots. You need JavaScript enabled to view it AXSUN Technology

Note: This page contains sample records for the topic "forecast 2 1" 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

Beamline 3.2.1  

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

2.1 Print 2.1 Print Commercial deep-etch x-ray lithography (LIGA) GENERAL BEAMLINE INFORMATION Operational Yes, but not open to users Source characteristics Bend magnet Energy range 3-12 keV Monochromator None Endstations Hutch with automated scanner Calculated spot size at sample 100 x 10 mm Sample format 3- and 4-in. wafer format; x-ray mask and LIGA substrate Sample environment Ambient, air Scientific disciplines Applied science Scientific applications Deep-etch x-ray lithography (LIGA) Spokesperson This e-mail address is being protected from spambots. You need JavaScript enabled to view it Advanced Light Source, Berkeley Lab Phone: (510) 486-5527 Fax: (510) 486-4102 This e-mail address is being protected from spambots. You need JavaScript enabled to view it AXSUN Technology

342

Beamline 3.2.1  

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

2.1 Print 2.1 Print Commercial deep-etch x-ray lithography (LIGA) GENERAL BEAMLINE INFORMATION Operational Yes, but not open to users Source characteristics Bend magnet Energy range 3-12 keV Monochromator None Endstations Hutch with automated scanner Calculated spot size at sample 100 x 10 mm Sample format 3- and 4-in. wafer format; x-ray mask and LIGA substrate Sample environment Ambient, air Scientific disciplines Applied science Scientific applications Deep-etch x-ray lithography (LIGA) Spokesperson This e-mail address is being protected from spambots. You need JavaScript enabled to view it Advanced Light Source, Berkeley Lab Phone: (510) 486-5527 Fax: (510) 486-4102 This e-mail address is being protected from spambots. You need JavaScript enabled to view it AXSUN Technology

343

Beamline 3.2.1  

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

2.1 Print 2.1 Print Commercial deep-etch x-ray lithography (LIGA) GENERAL BEAMLINE INFORMATION Operational Yes, but not open to users Source characteristics Bend magnet Energy range 3-12 keV Monochromator None Endstations Hutch with automated scanner Calculated spot size at sample 100 x 10 mm Sample format 3- and 4-in. wafer format; x-ray mask and LIGA substrate Sample environment Ambient, air Scientific disciplines Applied science Scientific applications Deep-etch x-ray lithography (LIGA) Spokesperson This e-mail address is being protected from spambots. You need JavaScript enabled to view it Advanced Light Source, Berkeley Lab Phone: (510) 486-5527 Fax: (510) 486-4102 This e-mail address is being protected from spambots. You need JavaScript enabled to view it AXSUN Technology

344

Beamline 3.2.1  

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

2.1 Print 2.1 Print Commercial deep-etch x-ray lithography (LIGA) GENERAL BEAMLINE INFORMATION Operational Yes, but not open to users Source characteristics Bend magnet Energy range 3-12 keV Monochromator None Endstations Hutch with automated scanner Calculated spot size at sample 100 x 10 mm Sample format 3- and 4-in. wafer format; x-ray mask and LIGA substrate Sample environment Ambient, air Scientific disciplines Applied science Scientific applications Deep-etch x-ray lithography (LIGA) Spokesperson This e-mail address is being protected from spambots. You need JavaScript enabled to view it Advanced Light Source, Berkeley Lab Phone: (510) 486-5527 Fax: (510) 486-4102 This e-mail address is being protected from spambots. You need JavaScript enabled to view it AXSUN Technology

345

Beamline 8.2.1  

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

1 Print 1 Print Berkeley Center for Structural Biology (BCSB) Multiple-Wavelength Anomalous Diffraction (MAD) and Macromolecular Crystallography (MX) Scientific discipline: Structural biology GENERAL BEAMLINE INFORMATION Operational Yes Proposal cycle Proposals for Structural Biology Beamlines (2-month cycle) Source characteristics Superbend magnet (5.0 T, single pole) Energy range 5-16 keV Monochromator Double crystal, Si(111) Measured flux (1.9 GeV, 400 mA) 3.0 x 1011 photons/sec Resolving power (E/ΔE) 7,000 Divergence (max at sample) 3.0 (h) x 0.5 (v) mrad Measured spot size (FWHM) 100 µm Endstations Minihutch Detectors 3x3 CCD array (ADSC Q315R) Sample format Single crystals of biological molecules Sample preparation Support labs available Sample environment Ambient or ~100 K

346

Beamline 8.2.1  

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

1 Print 1 Print Berkeley Center for Structural Biology (BCSB) Multiple-Wavelength Anomalous Diffraction (MAD) and Macromolecular Crystallography (MX) Scientific discipline: Structural biology GENERAL BEAMLINE INFORMATION Operational Yes Proposal cycle Proposals for Structural Biology Beamlines (2-month cycle) Source characteristics Superbend magnet (5.0 T, single pole) Energy range 5-16 keV Monochromator Double crystal, Si(111) Measured flux (1.9 GeV, 400 mA) 3.0 x 1011 photons/sec Resolving power (E/ΔE) 7,000 Divergence (max at sample) 3.0 (h) x 0.5 (v) mrad Measured spot size (FWHM) 100 µm Endstations Minihutch Detectors 3x3 CCD array (ADSC Q315R) Sample format Single crystals of biological molecules Sample preparation Support labs available Sample environment Ambient or ~100 K

347

Beamline 8.2.1  

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

1 Print 1 Print Berkeley Center for Structural Biology (BCSB) Multiple-Wavelength Anomalous Diffraction (MAD) and Macromolecular Crystallography (MX) Scientific discipline: Structural biology GENERAL BEAMLINE INFORMATION Operational Yes Proposal cycle Proposals for Structural Biology Beamlines (2-month cycle) Source characteristics Superbend magnet (5.0 T, single pole) Energy range 5-16 keV Monochromator Double crystal, Si(111) Measured flux (1.9 GeV, 400 mA) 3.0 x 1011 photons/sec Resolving power (E/ΔE) 7,000 Divergence (max at sample) 3.0 (h) x 0.5 (v) mrad Measured spot size (FWHM) 100 µm Endstations Minihutch Detectors 3x3 CCD array (ADSC Q315R) Sample format Single crystals of biological molecules Sample preparation Support labs available Sample environment Ambient or ~100 K

348

Beamline 8.2.1  

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

1 Print 1 Print Berkeley Center for Structural Biology (BCSB) Multiple-Wavelength Anomalous Diffraction (MAD) and Macromolecular Crystallography (MX) Scientific discipline: Structural biology GENERAL BEAMLINE INFORMATION Operational Yes Proposal cycle Proposals for Structural Biology Beamlines (2-month cycle) Source characteristics Superbend magnet (5.0 T, single pole) Energy range 5-16 keV Monochromator Double crystal, Si(111) Measured flux (1.9 GeV, 400 mA) 3.0 x 1011 photons/sec Resolving power (E/ΔE) 7,000 Divergence (max at sample) 3.0 (h) x 0.5 (v) mrad Measured spot size (FWHM) 100 µm Endstations Minihutch Detectors 3x3 CCD array (ADSC Q315R) Sample format Single crystals of biological molecules Sample preparation Support labs available Sample environment Ambient or ~100 K

349

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

Science Conference Proceedings (OSTI)

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

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

2009-02-01T23:59:59.000Z

350

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

Science Conference Proceedings (OSTI)

In this paper, the results of an examination of precipitation forecasts for 130-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ...

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

2010-12-01T23:59:59.000Z

351

Monsoons: Processes, predictability, and the prospects for P. J. Webster1, V. O. Magana2, T. N. Palmer3, J. Shukla4, R. A. Tomas1, M. Yanai5, and T. Yasunari6  

E-Print Network (OSTI)

Monsoons: Processes, predictability, and the prospects for prediction P. J. Webster1, V. O. Magana2 planetary heat sources and sinks, and interactions between them. The Asian-Australian monsoon system, which timescales is a major focus of GOALS. Empirical seasonal forecasts of the monsoon have been made

Webster, Peter J.

352

Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint  

DOE Green Energy (OSTI)

The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

2012-09-01T23:59:59.000Z

353

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

354

Slide 1  

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

Forecasted CVP Transmission Rates Forecasted CVP Transmission Rates Central Valley Project Transmission Rates Forecast (as of May 2013) Rate or Revenue Requirement Current Non-Binding Forecast FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 Transmission Revenue Requirement (TRR) $39.6 Million $39.5 Million $41.7 Million $44.9 Million $47.2 Million Network Integrated Transmission Service (NITS) $28.4 Million $27.4 Million $29.0 Million $31.3 Million $32.8 Million Point-to-Point Transmission Rate (P-to-P) $/kW Mo. $1.33 $1.44 $1.52 $1.63 $1.72 Transmission Plant Ratio 61.70% 62.24% 63.82% 66.28% 67.45% SNR Rates Group - Customer Meeting, May 23, 2013 Factors used in forecast: 1.O&M based on FY 2012 actual, then inflated 3% per year starting FY 2015. 2. Plant Additions: FY 2014: Elverta Maintenance Facility Rehab ($4.2M); Hurley-Tracy Fiber ($3.3M).

355

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

356

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

357

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

358

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

359

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

360

Forecasting Economic and Financial Variables with Global VARs  

E-Print Network (OSTI)

Suppose one were interested in forecasting output growth and inflation across a number of different countries; how would one go about it? What additional variables might help in such forecasting (the oil price comes to mind), and should one also consider... .2. Ideally evaluation is done with a separate sample, though that can often be prohibitively costly, one reason why techniques like cross-validation have considerable appeal. Essentially these first two stages can be considered as trading off bias (build...

Pesaran, M Hashem; Schuermann, Til; Smith, L Vanessa

Note: This page contains sample records for the topic "forecast 2 1" 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

A Comparison of Skill between Two Versions of the NCEP Climate Forecast System (CFS) and CPCs Operational Short-Lead Seasonal Outlooks  

Science Conference Proceedings (OSTI)

Analyses of the relative prediction skills of NOAAs Climate Forecast System versions 1 and 2 (CFSv1 and CFSv2, respectively), and the NOAA/Climate Prediction Centers (CPC) operational seasonal outlook, are conducted over the 15-yr common period ...

Peitao Peng; Anthony G. Barnston; Arun Kumar

2013-04-01T23:59:59.000Z

362

Nation Weekly May 2, 2004, Volume 1, Number 2  

E-Print Network (OSTI)

;#2;#3;#4; #5;#6;#7;#8;#2;#8; #8; #1;#2;#2;#3;#4;#5;#6; #7;#8; #11; #12;#1;#8; #2; cover.pm6 4/25/04, 3:46 AM1 For your tailor-madefinancial services #1;#2;#3;#4;#5;#6;#7;#8;#7;#2;#3; #4; #11;#3;#12;#3;#4; #14;#15;#6;#7;#3;#15;#15; #4;#2... : 4249388/ 4249396/ 4266101 | Fax: 977-1-4249477 | Email:ace@ace.com.np #1;#2;#3;#4;#5; #6;#7;#1;#7;#2;#3;#4;#2;#8; #1;#7;#11; cover.pm6 4/25/04, 3:47 AM2 #1;#2;#3;#4;#5;#6;#7; #1; #2;#3;#4;#5;#6;#7;#8; #5;#11; #12;#5; #4;#7;#14;#3;#15;#16; #1...

Upadhyay, Akhilesh

363

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":""}]}

364

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

365

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

366

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

367

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

368

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

369

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

370

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

E-Print Network (OSTI)

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

Mass, Clifford F.

371

Voluntary Green Power Market Forecast through 2015  

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

158 158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-48158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory

372

Black-Scholes 2.1 . . . . . . . . . . . . . . . . . . . . 5  

E-Print Network (OSTI)

Black-Scholes #12;1 2 2 5 2.1 . . . . . . . . . . . . . . . . . . . . 5 2-Ocone) . . . . . . . . . . . . . . . . . 18 4 Black-Scholes 25 4.1 Black-Scholes . . . . . . . . . . . . . . . . . . . . . . . 25 4}(d) . , (t) , (t)S t dWt . = 1 [8] , Black-Scholes . [8] , Black-Scholes . , . , 1 t log(St S0 ) . , [8] [6

Hattori, Tetsuya

373

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

374

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 nearreal 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

375

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

376

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 numericalstatistical 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

377

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

378

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

379

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

380

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

Science Conference Proceedings (OSTI)

Differences of opinion exist among forecastersand between forecasters and usersregarding 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

Note: This page contains sample records for the topic "forecast 2 1" 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

Economic Forecast Report Economic Outlook and Forecasts  

E-Print Network (OSTI)

volatile prices such as food and energy, is even softer, averaging around 1% for the year. Inflation should in our last report, the rebound in economic activity has been weak and uninspiring with below-trend formation is far below desired level, the overall trend is positive. Despite these improve- ments, we fear

de Lijser, Peter

382

1. Sentence 9.25.2.1.(1) and Table 9.25.2.1. state:  

E-Print Network (OSTI)

The amendments to the Alberta Building Code 2006 addressing high-intensity residential fires include a requirement to provide a drywall finish (or other similar performing material), along with insulation and vapour barrier to the interior of attached garages. The requirement for the interior finish was added to delay the spread of a fire originating in an attached garage and to give occupants extra time to evacuate the associated dwelling unit. The requirement for insulation and a vapour barrier was added to the amendments as a precautionary measure due to the presence of the interior finish. It was felt that homeowners who purchase a house with a finished garage may be unaware that there was no insulation in the walls. If that homeowner were to then provide heat to the garage, thinking that it was in fact insulated, condensation would form within the exterior wall assembly which could lead to deterioration of the garage structural supports and the potential for the formation of mould and mildew. Sentence 9.25.2.1.(1) and Table 9.25.2.1. contain requirements for insulating heated garage, but does not contain any requirements for an unheated garage. This STANDATA has been developed to clarify what minimum insulation values are to be supplied in unheated attached garages.

unknown authors

2009-01-01T23:59:59.000Z

383

9:00 Opening and Welcome (Exactum Building Auditorium) Session 1: User-oriented Verification  

E-Print Network (OSTI)

of user-orientation in verification 9:50 1.2 Clive Wilson: Do key performance targets work? 10:10 1.3 Tressa Fowler: Wind forecast verification 10:30 1.4 Robert Maisha: UM model and Kalman Filter forecast verification at SAWS

Chair Pertti Nurmi

2009-01-01T23:59:59.000Z

384

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...

385

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) 109129 Forecasting new product penetration with ?

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

386

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

387

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

388

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) 109129 Forecasting new product penetration with

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

389

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

390

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

391

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

392

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

393

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

394

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

395

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

396

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

397

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

398

2.1E Supplement  

E-Print Network (OSTI)

unit with dehumidifier and heat exchanger, with regenerationa dehumdifier plus heat exchanger, as in Mode 1, but withoutoutside air leaving the heat exchanger is exhausted and does

Winkelmann, F.C.

2010-01-01T23:59:59.000Z

399

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

7 7 Range 10 4 48 Clothes Dryer 359 (2) 4 49 Water Heating Water Heater-Family of 4 40 64 (3) 26 294 Water Heater-Family of 2 40 32 (3) 12 140 Note(s): Source(s): 1) $1.139/therm. 2) Cycles/year. 3) Gallons/day. A.D. Little, EIA-Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case, Sept. 2, 1998, p. 30 for range and clothes dryer; LBNL, Energy Data Sourcebook for the U.S. Residential Sector, LBNL-40297, Sept. 1997, p. 62-67 for water heating; GAMA, Consumers' Directory of Certified Efficiency Ratings for Heating and Water Heating Equipment, Apr. 2002, for water heater capacity; and American Gas Association, Gas Facts 1998, December 1999, www.aga.org for range and clothes dryer consumption. Operating Characteristics of Natural Gas Appliances in the Residential Sector

400

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "forecast 2 1" 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

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

402

Table HC1.2.1. Living Space Characteristics by  

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

1. Living Space Characteristics by" 1. Living Space Characteristics by" " Total, Heated, and Cooled Floorspace, 2005" ,,,"Total Square Footage" ,"Housing Units",,"Total1",,"Heated",,"Cooled" "Living Space Characteristics","Millions","Percent","Billions","Percent","Billions","Percent","Billions","Percent" "Total",111.1,100,225.8,100,179.8,100,114.5,100 "Total Floorspace (Square Feet)1" "Fewer than 500",3.2,2.9,1.2,0.5,1.1,0.6,0.4,0.3 "500 to 999",23.8,21.4,17.5,7.7,15.9,8.8,7.3,6.4 "1,000 to 1,499",20.8,18.7,24.1,10.7,22.6,12.6,13,11.4 "1,500 to 1,999",15.4,13.9,24.5,10.9,22.2,12.4,14,12.2

403

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

404

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

405

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

406

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.

407

Predicting daily streamflow using rainfall forecasts, a simple loss module and unit hydrographs: Two Brazilian catchments  

Science Conference Proceedings (OSTI)

The performance of a simple, spatially-lumped, rainfall-streamflow model is compared with that of a more complex, spatially-distributed model. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000km^2 and 34,000km^2) ... Keywords: Brazil, Hydropower, Rainfall forecasts, River Paran, Streamflow forecasts, Unit hydrographs

I. G. Littlewood; R. T. Clarke; W. Collischonn; B. F. W. Croke

2007-09-01T23:59:59.000Z

408

Object-Based Evaluation of the Impact of Horizontal Grid Spacing on Convection-Allowing Forecasts  

Science Conference Proceedings (OSTI)

Forecasts generated by the Center for Analysis and Prediction of Storms with 1- and 4-km grid spacing using the Advanced Research Weather Research and Forecasting Model (ARW-WRF; ARW1 and ARW4, respectively) for the 200911 NOAA Hazardous Weather ...

Aaron Johnson; Xuguang Wang; Fanyou Kong; Ming Xue

2013-10-01T23:59:59.000Z

409

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

410

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

411

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 200211 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

412

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

413

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 Rpnack; Andreas Hense; Christoph Gebhardt; Detlev Majewski

2013-01-01T23:59:59.000Z

414

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

415

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

416

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

417

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

418

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

419

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

420

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

Note: This page contains sample records for the topic "forecast 2 1" 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

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

422

USE OF AN EQUILIBRIUM MODEL TO FORECAST DISSOLUTION EFFECTIVENESS, SAFETY IMPACTS, AND DOWNSTREAM PROCESSABILITY FROM OXALIC ACID AIDED SLUDGE REMOVAL IN SAVANNAH RIVER SITE HIGH LEVEL WASTE TANKS 1-15  

DOE Green Energy (OSTI)

This thesis details a graduate research effort written to fulfill the Magister of Technologiae in Chemical Engineering requirements at the University of South Africa. The research evaluates the ability of equilibrium based software to forecast dissolution, evaluate safety impacts, and determine downstream processability changes associated with using oxalic acid solutions to dissolve sludge heels in Savannah River Site High Level Waste (HLW) Tanks 1-15. First, a dissolution model is constructed and validated. Coupled with a model, a material balance determines the fate of hypothetical worst-case sludge in the treatment and neutralization tanks during each chemical adjustment. Although sludge is dissolved, after neutralization more is created within HLW. An energy balance determines overpressurization and overheating to be unlikely. Corrosion induced hydrogen may overwhelm the purge ventilation. Limiting the heel volume treated/acid added and processing the solids through vitrification is preferred and should not significantly increase the number of glass canisters.

KETUSKY, EDWARD

2005-10-31T23:59:59.000Z

423

Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems  

E-Print Network (OSTI)

Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAAs global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet the critical requirements associated with shipping, commercial and sport fishing vessel safety, and oil spill response. This dissertation also performs a detailed qualitative and quantitative assessment of the impact of various forcing functions on wave pre- dictions, and develops maps showing extreme variations in significant wave heights (SWHs). For instance, it is found that the SWH could vary by as much as 1 m in the northern CI region in the presence of currents (hence justifying the need for integration of the wave model with a circulation model). Such maps can be useful for several engineering operations, and could also serve as guidance tool as to what can be expected in certain regions. Aside from the system development, the issue of forecast reliability is also addressed for PWS region in the context of the associated uncertainty which confronts the manager of engineering operations or other planners. For this purpose, high-resolution 36-h daily forecasts of SWHs are compared with measurements from buoys and satellites for about a year. The results show that 70% of the peak SWHs in the range 5-8 m were predicted with an accuracy of 15% or less for a forecast lead time of 9 h. On average, results indicate 70% or greater likelihood of the prediction falling within a tolerance of (1*RMSE) for all lead times. This analysis could not be performed for CI due to lack of data sources.

Singhal, Gaurav

2011-08-01T23:59:59.000Z

424

2.1E Supplement  

E-Print Network (OSTI)

I T Y - R A T E Command Cogeneration B L O C K - C H A R G Econsultant for the P l a n t Cogeneration a n d t h e R e fa n d chillers for cogeneration, (2) simpler f u n c t i o n

Winkelmann, F.C.

2010-01-01T23:59:59.000Z

425

1434 VOLUME 132M O N T H L Y W E A T H E R R E V I E W Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using  

E-Print Network (OSTI)

-Range Forecast Skill Using Retrospective Forecasts THOMAS M. HAMILL University of Colorado and NOAA­CIRES Climate statistics (MOS) approach to improving 6­10-day and week 2 probabilistic forecasts of surface temperature of the NCEP medium-range forecast model with physics operational during 1998. An NCEP­NCAR reanalysis initial

Hamill, Tom

426

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

427

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.

428

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

429

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

430

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

431

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 spacetime 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

432

Microwave Engineering Lecture 1 & 2  

E-Print Network (OSTI)

& enclosed charge 2.M.flux & enclosed charge 3.EMF induced time varying magnetic flux 4.DC current flow generate H.flux 5. D=E ; B=µH ; J=E 6.Behavior of EM fields/wave 7.Static E.field (char. capacitor) 8 to current distribution. 14.Time varying fields/waves 15.Linear resistor law 16.Voltage and current law 17

Iqbal, Sheikh Sharif

433

Environmental Compliance 2-1 2. Environmental Compliance  

E-Print Network (OSTI)

at ORNL. RCRA permits (see Table 2.1). The K-1435 Toxic The HSWA permit requires DOE to address past changes to SWMUs that could alter further RCRA units. investigation or corrective action. DOE has pro- 2.2.1.1 RCRA Assessments, Closures, and Corrective Measures The Hazardous and Solid Waste Amendments (HSWA

Pennycook, Steve

434

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

435

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.

436

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

437

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

438

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

439

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

440

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

Note: This page contains sample records for the topic "forecast 2 1" 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

THERM 2.1 NFRC simulation manual  

E-Print Network (OSTI)

Heat Transfer Code Users Manual and Thermal Property DataTHERM 2.1 NFRC Simulation Manual JULY 2000 4. SUMMARY OFTHERM 2.1 NFRC Simulation Manual JULY 2000 9.5 Problem 4:

2000-01-01T23:59:59.000Z

442

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

Science Conference Proceedings (OSTI)

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

Christophe Accadia; Stefano Zecchetto; Alfredo Lavagnini; Antonio Speranza

2007-05-01T23:59:59.000Z

443

RSE Table S1.1 and S1.2. Relative Standard Errors for Tables S1.1 and S1.2  

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

S1.1 and S1.2. Relative Standard Errors for Tables S1.1 and S1.2;" S1.1 and S1.2. Relative Standard Errors for Tables S1.1 and S1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","Shipments" "SIC"," ",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy Sources" "Code(a)","Major Group and Industry","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)"

444

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.

445

TTW 2-1-10  

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

10 10 WIPP Quick Facts (As of 1-31-10) 8,188 Shipments received since opening (7,869 CH and 319 RH) 65,198 Cubic meters of waste disposed (65,043 CH and 155 RH) 127,413 Containers disposed in the underground (127,101 CH and 312 RH) WIPP operations resume following outage Employees work in WIPP's underground during the extended maintenance outage. The outage ended on December 31 and waste handling and disposal has resumed. WIPP is back in disposal mode following a six-week maintenance outage. The facility resumed disposal operations the week of January 4 with all essential projects completed. The annual outage is used to complete major maintenance and upgrade projects that cannot be done while WIPP is receiving shipments and disposing of waste underground.

446

Slide 1  

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

Business 322M SDB 8(a) 5M 8(a) 31M Native American 2-4.3M SDVOB 9M HUBSDV 5M FORECAST OF OPPORTUNITIES 7 Classification Funding HubSole Proprietor TBD TBD 360M FORECAST...

447

Freeway Analysis Manual: Parts 1 and 2  

E-Print Network (OSTI)

57 2.9.1 Existing Ramp Metering Operations 2.9.2 Existingof implementing ramp metering in combination with addingcorridor such as with ramp metering are to be modeled.

May, Dolf; Leiman, Lannon

2005-01-01T23:59:59.000Z

448

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

449

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

E-Print Network (OSTI)

LPG Furnace Oil Furnace Electric Heat Pump Gas BoilerOil Boiler Electric Room Heater Gas Room Heater Wood Stove (Electric Heat Pump Gas Boiler Oil Boiler Electric Room Gas

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

450

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

E-Print Network (OSTI)

Homes End-Use Equipment Type Equipment Market Shares Index Heating ElecFurnace Gas Furnace LPG Furnace OilHomes (millions) End-Use Equipment Type Appliance stock in millions of units Index Heating FJec Furnace Gas Furnace L P G Furnace OilHomes End-Use Equipment Type Units Efficiency for Stock Equipment Index Heating Elec Furnace Btu.out/Wh.in Gas Furnace AFUE LPG Furnace AFUE Oil

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

451

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Central Air, Fuels = Oil and Gas, Other = LPG and Misc. (3)Central Air, Fuels = Oil and Gas, LPG and Misc. (3) Sources:Central Air, Fuels = Oil and Gas, Other = LPG and Misc. (3)

Johnson, F.X.

2010-01-01T23:59:59.000Z

452

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

E-Print Network (OSTI)

Description Prices for oil, gas, electricity, liquidElectric Electric Electric Gas Oil Electric ElectricElectric Gas Electric Gas Oil Electric Electric Gas Oil

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

453

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

natural gas consumption and 90% of oil consumption in the U.S.natural gas consumption and 90% of oil consumption in the U.S.

Johnson, F.X.

2010-01-01T23:59:59.000Z

454

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

oil hydronic, electric room, and electric (air source) heatFuels = Oil and Gas, LPG and Misc. (3) Sources: 1990 RECS (Fuels = Oil and Gas, Other = LPG and Misc. (3) Sources: 1990

Johnson, F.X.

2010-01-01T23:59:59.000Z

455

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

E-Print Network (OSTI)

A comparison of national energy consumption by fuel typeenergy consumption in homes under differing assumptions, scenarios, and policies. At the national

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

456

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

apply: the thermal shell, heating and cooling equipment, orestimated the thermal shell heating and cooling loads usingPrice for Thermal Integrity Improvements Cooling Load Total

Johnson, F.X.

2010-01-01T23:59:59.000Z

457

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

E-Print Network (OSTI)

heaters, clothes washers, dishwashers, lighting, cooking,Refrigerators Water Heaters Dishwashers Clothes Washersof its useful life. For dishwashers, clothes washers, and

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

458

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

E-Print Network (OSTI)

gas Oil Secondary Heating Wood Stove Secondary Cooling RoomTotal Secondary Heating Wood Stove Secondary Cooling Room ACConsumption Secondary Heating Wood Stove Secondary Cooling

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

459

1 Forecasting Greenhouse Gas Emissions from Urban Regions: 2 Microsimulation of Land Use and Transport Patterns in Austin, Texas  

E-Print Network (OSTI)

the highest rates of increase. Average energy consumption per household is estimated to fall over 30 time (by.S. energy demands per capita have fallen over54 25% in the last 25 years, the nation`s population increases to increase dramatically -- by nearly 88% in terms of home energy consumption (in the 32 trend scenario

Kockelman, Kara M.

460

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

E-Print Network (OSTI)

G. Koomey. 1994. Residential Appliance Data, Assumptions andunits) Table A 3 : Number of Appliances in Existing Homes (sector, including appliances and heating, ventilation, and

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast 2 1" 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

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

E-Print Network (OSTI)

light bulbs having designated usage level in the average house. (3) Refrigerator marketlight bulbs having designated usage level in the average house. (3) Refrigerator market

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

462

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

E-Print Network (OSTI)

year consumption estimates. DISCUSSION The Importance of Miscellaneous ElectricityConsumption of New Equipment Index kWh/Year MMBtu/Year MMBtu/Year ElectricityConsumption of Equipment in Existing Homes Index kWh/Year MMBtu/Year MMBtu/Year Electricity

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

463

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

E-Print Network (OSTI)

Richard E. Brown, James W. Hanford, Alan H . Sanstad, andFrancis X . , James W. Hanford, Richard E. Brown, Alan H.place for these end-uses (Hanford et al. 1994, Hwang et al.

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

464

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Research, Inc. July 25. Hanford, James W. , Jonathan G.Francis X . and James W. Hanford. 1992. Memorandum toA : Ritschard, Ron L. , Jim W. Hanford and A. Osman Sezgen.

Johnson, F.X.

2010-01-01T23:59:59.000Z

465

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Analysis: Studies in Residential Energy Demand. AcademicHousing Characteristics 1987, Residential Energy ConsumptionHousing Characteristics 1990, Residential Energy Consumption

Johnson, F.X.

2010-01-01T23:59:59.000Z

466

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy  

DOE Green Energy (OSTI)

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

2011-10-01T23:59:59.000Z

467

DOE-2, BDL summary. Version 2.1E  

SciTech Connect

This document contains summary information on all commands and keywords in the DOE-2 Building Description Language (BDL). It also contains supplementary tables and maps. The fundamentals of BDL are discussed in Chapter II of the Reference Manual (2.1A); detailed descriptions of the commands and keywords summarized here can be found in the Reference Manual (2.1A) and in the Supplement (2.1E).

Winkelmann, F.C.; Birdsall, B.E.; Buhl, W.F.; Ellington, K.L.; Erdem, A.E. [Lawrence Berkeley Lab., CA (United States); Hirsch, J.J.; Gates, S. [Hirsch & Associates, Camarillo, CA (United States)

1993-11-01T23:59:59.000Z

468

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

Science Conference Proceedings (OSTI)

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

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

2008-12-01T23:59:59.000Z

469

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

Genton, Marc G.

470

Retrospective ENSO Forecasts: Sensitivity to Atmospheric Model and Ocean Resolution  

Science Conference Proceedings (OSTI)

Results are described from a series of 40 retrospective forecasts of tropical Pacific SST, starting 1 January and 1 July 198099, performed with several coupled oceanatmosphere general circulation models sharing the same ocean modelthe Modular ...

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

2003-12-01T23:59:59.000Z

471

Perils of Long-Range Energy Forecasting: Reflections on Looking Far Ahead  

E-Print Network (OSTI)

! #12;PERILS OF LONG-RANGE ENERGY FORCASTING 255 Fig. 1. Forecasts of the U.S. primary energy notable forecasts of the U.S. primary energy consumption in the year 2000 that were released between have been around energy matters for some time--is the goal of U.S. energy independence charted

Smil, Vaclav

472

The First Decade of Long-Lead U.S. Seasonal Forecasts  

Science Conference Proceedings (OSTI)

The first 10 yr (issued starting in mid-December 1994) of official, long-lead (out to 1 yr) U.S. 3-month mean temperature and precipitation forecasts are verified using a categorical skill score. Through aggregation of forecasts over overlapping ...

Robert E. Livezey; Marina M. Timofeyeva

2008-06-01T23:59:59.000Z

473

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

Science Conference Proceedings (OSTI)

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

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

2012-11-01T23:59:59.000Z

474

Comparing NWS PoP Forecasts to Third-Party Providers  

Science Conference Proceedings (OSTI)

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

J. Eric Bickel; Eric Floehr; Seong Dae Kim

2011-10-01T23:59:59.000Z

475

The Australian Air Quality Forecasting System. Part I: Project Description and Early Outcomes  

Science Conference Proceedings (OSTI)

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (15 km) short-term (2436 h) forecasts for the Australian coastal cities ...

M. E. Cope; G. D. Hess; S. Lee; K. Tory; M. Azzi; J. Carras; W. Lilley; P. C. Manins; P. Nelson; L. Ng; K. Puri; N. Wong; S. Walsh; M. Young

2004-05-01T23:59:59.000Z

476

Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000  

Science Conference Proceedings (OSTI)

The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

Das, S.

1991-12-01T23:59:59.000Z

477

RSE Table N1.1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2  

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

1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2;" 1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","Shipments" "NAICS"," ",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy Sources" "Code(a)","Subsector and Industry","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)"

478

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

DOE Green Energy (OSTI)

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

Milligan, M. R.

2002-05-01T23:59:59.000Z

479

Documentation - Price Forecast Uncertainty  

U.S. Energy Information Administration (EIA)

Energy Information Administration/Short-Term Energy Outlook Supplement October 2009 2 example, if a confidence level of 95 percent is specified, then a range of ...

480

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 â??black boxâ? of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the â??price puzzleâ? and the â??liquidity puzzleâ? 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)â??s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watsonâ??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

Note: This page contains sample records for the topic "forecast 2 1" 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

SNS FY 2013 Q1-4 Revision 2 Approved  

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

3 Q1-4 Revision 2 Approved Revised 6112013 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6...

482

table2.1_02.xls  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; 1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) Gas(c) NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States RSE Column Factors: 1.4 0.4 1.6 1.2 1.2 1.1 0.7 1.2 311 Food 8 * * 7 0 0 * * 311221 Wet Corn Milling * 0 * 0 0 0 0 * 31131 Sugar * 0 * * 0 0 * * 311421 Fruit and Vegetable Canning * * * 0 0 0 0 * 312 Beverage and Tobacco Products 1 * * * 0 0 0 1 3121 Beverages * * * 0 0 0 0 *

483

Fuel Price Forecasts INTRODUCTION  

E-Print Network (OSTI)

Another important consideration in natural gas supply and cost is the capacity to transport the gas from.75 trillion cubic feet of natural gas from Canada; and 1.1 trillion cubic feet of that were imported through would mean a growing role for frontier supply areas and liquefied natural gas imports. High prices

484

A.: Modeling and forecasting electricity loads: A comparison  

E-Print Network (OSTI)

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

Rafa? Weron

2004-01-01T23:59:59.000Z

485

Solar forecasting review  

E-Print Network (OSTI)

TSI taken at the University of California Merced on June 1,of the University of California, 2002. [29] A. Mills and R.Networks. University of California, Merced, 2011. [193] E.

Inman, Richard Headen

2012-01-01T23:59:59.000Z

486

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

487

Freeway Analysis Manual: Parts 1 and 2  

E-Print Network (OSTI)

BERKELEY Freeway Analysis Manual: Parts 1 and 2 Dolf May,AND 2 OF FREEWAY ANALYSIS MANUAL Prepared by Dolf May LannonThis Freeway Analysis Manual is intended for those who are

May, Dolf; Leiman, Lannon

2005-01-01T23:59:59.000Z

488

DOE M 231.1-2  

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

M 231.1-2 M 231.1-2 Approved: 08-19-03 OCCURRENCE REPORTING AND PROCESSING OF OPERATIONS INFORMATION U.S. DEPARTMENT OF ENERGY Office of Environment, Safety and Health DOE M 231.1-2 Page i (and ii) 08-19-03 SUBJECT: OCCURRENCE REPORTING AND PROCESSING OF OPERATIONS INFORMATION 1. PURPOSE. This Manual provides detailed requirements to supplement DOE O 231.1A, Environment, Safety, and Health Reporting, dated 08-19-03. This Manual is approved for use by all DOE Elements and their contractors. 2. REFERENCE. DOE O 231.1A, Environment, Safety, and Health Reporting, dated 08-19-03. 3. CANCELLATION. DOE M 232.1-1A, Occurrence Reporting and Processing of Operations Information, dated 7-21-97. Cancellation of a Manual does not, by itself, modify or otherwise

489

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

490

Load Pocket Forecasting Software E. A. Feinberg, D. Genethliou, J.T. Hajagos, B.G. Irrgang, and R. J. Rossin  

E-Print Network (OSTI)

Electricity RequirementsElectricity Requirements Council Load Forecast and Portfolio Model Range 10000 15000 and Conservation Council for the Load Forecasting Advisory Committee Friday June 27, 2008 2 Overview Electricity RequirementsElectricity Requirements 5th Plan Non-DSI Price Effects Sales Forecasts 12000 14000

Feinberg, Eugene A.

491

Weather Forecasting for Utility Companies For energy and utility companies, expected local weather conditions during the next day or two are  

E-Print Network (OSTI)

SUBJECT: Revised Short-term Electricity Loads and Forecast 2008-2017 As part of the Mid-term Assessment-term electricity loads and forecast 2008-2017- boise 2012 .docx #12;6/28/2012 1 REVISED SHORT-TERM ELECTRICITY and as input to the Resource Adequacy analysis, we have prepared an update to the regional load forecast

492

Liquid effluent FY 1996 program plan WBS 1.2.2.1. Revision 1  

Science Conference Proceedings (OSTI)

The Liquid Effluents Program supports the three Hanford Site mission components: (1) Clean up the site, (2) provide scientific and technological excellence to meet global needs, and (3) Partner in the economic diversification of the region. Nine Hanford Site objectives have been established for the Hanford Site programs to accomplish all three components of this mission.

NONE

1995-09-01T23:59:59.000Z

493

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

E-Print Network (OSTI)

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

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

494

Microsoft Word - UPDATE 2 - Unit 1.doc  

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

2 to: 2 to: A Dispersion Modeling Analysis of Downwash from Mirant's Potomac River Power Plant Modeling Unit 1 Emissions at Maximum and Minimum Loads ENSR Corporation December 20, 2005 Document Number 10350-002-410 (Update 2) December, 2005 1-1 1.0 INTRODUCTION This report describes AERMOD modeling results performed for Unit 1 at Mirant's Potomac River Generating Station. The purpose of these runs was to demonstrate that operation of Unit 1 for 24 hours a day at loads from 35 MW to 88 MW with the use of trona to reduce SO 2 emissions will not cause or contribute to modeled exceedances of the National Ambient Air Quality Standards (NAAQS). Mirant proposes to use trona on an as needed basis to limit SO 2 emissions to less than 0.89 lb/MMBtu

495

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

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

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2005-01-01T23:59:59.000Z

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

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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

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Environmental Compliance 2-1 2. Environmental Compliance  

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, and Portsmouth facilities. Both LMES and LMER are DOE prime contractors. DOE's operations on the reservation 1986. SWSA 6 is currently undergoing process knowledge, and repackaging activities. RCRA/CERCLA closure. A revised Closure Plan 2.2.1.1 RCRA Assessments, Closures, and Corrective Measures The Hazardous and Solid

Pennycook, Steve

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Environmental Compliance 2-1 2. Environmental Compliance  

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the individual RCRA units. 2.2.1.1 RCRA Assessments, Closures, and Corrective Measures The Hazardous and Solid-alone permit; TDEC's was issued as a modification to a Y-12 post-closure permit. DOE submitted comments process, mixed wastes, which are composed of a mixture which is expected to integrate the RCRA closure

Pennycook, Steve

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C:\\WEBSHARE\\WWWROOT\\forecastactuals\\tables2_18.wpd  

Annual Energy Outlook 2012 (EIA)

Tables 2 through 18 Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption,...

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Page 1 of 2 Revised 1 Feb 2013 UBC Utilities  

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SERVICES: WATER, SANITARY, STORM, GAS, and DISTRICT HEATING Part 3 (a). Water Distribution. Water service.5.7 and Section 02730, Clause 2.5.6). #12;Page 2 of 2 Revised 1 Feb 2013 Part 3 (c). Gas and District Heating (%) District Heating Contractor or UBC Dept Telephone Fax Contractor Primary Contact Email Design by (Company

Vellend, Mark