Sample records for weather forecast model

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

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

  2. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01T23:59:59.000Z

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

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

    E-Print Network [OSTI]

    Niyogi, Dev

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

  4. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  7. 11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL

    E-Print Network [OSTI]

    Chow, Fotini Katopodes

    11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL Katherine A. Lundquist1 , Fotini K. Chow 2 , Julie K. Lundquist 3 , and Jeffery D. Mirocha 3 in urban areas are profoundly influenced by the presence of build- ings which divert mean flow, affect

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2...://collaboration.cmc.ec.gc.ca/cmc/cmoi/SolarScribe/SolarScribe/ CMC NWP datasets for Day 2 Forecasts ? Regional Deterministic Prediction System (RDPS) ? RDPS raw model data ? 10 km resolution, North America, 000-054 forecasts ? Data at: http...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

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

  10. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP

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

    SciTech Connect (OSTI)

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

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    GEPS 21 members ? Provides probabilistic forecasts ? Can give useful outlooks for longer term weather forecasts ? Scribe matrix from GDPS ? includes UMOS post processed model data ? Variables like Temperature, humidity post processed by UMOS ? See...://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products/ ? Link to experimental 3-day outlook of REPS quilts ? http://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products.reps Users can also make their own products from ensemble forecast data? Sample ascii matrix of 2m temperature could be fed...

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    numerical weather prediction models operated by the weather services are refined by taking into account stock exchange. The typical predic- tion time horizon which is needed for these purposes is 3 to 48 are applied taking into account the effects from lo- cal roughness, thermal stratification of the atmosphere

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

    SciTech Connect (OSTI)

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

    2009-03-01T23:59:59.000Z

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

  16. Optimization Online - Data Assimilation in Weather Forecasting: A ...

    E-Print Network [OSTI]

    M. Fisher

    2007-02-14T23:59:59.000Z

    Feb 14, 2007 ... Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization. M. Fisher(Mike.Fisher ***at*** ecmwf.int)

  17. Weather

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

    Weather Weather We provide access to the latest meteorological observations, climatological information, and weather forecast products for the Los Alamos area. December 14, 2011...

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

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2010-03-03T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2012-08-15T23:59:59.000Z

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

  1. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Allanach, B C; Cranmer, Kyle; Lester, Christopher G; Weber, Arne M

    2007-08-07T23:59:59.000Z

    ar X iv :0 70 5. 04 87 v3 [ he p- ph ] 5 J ul 20 07 Preprint typeset in JHEP style - HYPER VERSION DAMTP-2007-18 Cavendish-HEP-2007-03 MPP-2007-36 Natural Priors, CMSSM Fits and LHC Weather Forecasts Benjamin C Allanach1, Kyle Cranmer2... ’s likely discoveries. There are big differences between nature of the questions answered by a forecast, and the ques- tions that will be answered by the experiments themselves when they have acquired compelling data. A weather forecast predicting “severe...

  2. ASSESSING THE QUALITY AND ECONOMIC VALUE OF WEATHER AND CLIMATE FORECASTS

    E-Print Network [OSTI]

    Katz, Richard

    INFORMATION SYSTEM · Forecast -- Conditional probability distribution for event Z = z indicates forecast tornado #12;(1.2) FRAMEWORK · Joint Distribution of Observations & Forecasts Observed Weather = Forecast probability p (e.g., induced by Z) · Reliability Diagram Observed weather: = 1 (Adverse weather occurs) = 0

  3. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

    /effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a...

  4. Exploiting weather forecast data for cloud detection 

    E-Print Network [OSTI]

    Mackie, Shona

    2009-01-01T23:59:59.000Z

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

  5. The Galactic Center Weather Forecast M. Moscibrodzka1

    E-Print Network [OSTI]

    Gammie, Charles F.

    The Galactic Center Weather Forecast M. Mo´scibrodzka1 , H. Shiokawa2 , C. F. Gammie2,3 , J*. The > 3M cloud will #12;­ 2 ­ interact strongly with gas near nominal pericenter at rp 300AU 8000GM/c2 transient phase while the flow circularizes-- accompanied by transient emission--it is natural to think

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

    E-Print Network [OSTI]

    Shenoy, Prashant

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

  7. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

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

  8. Exploiting weather forecasts for sizing photovoltaic energy bids

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    1 Exploiting weather forecasts for sizing photovoltaic energy bids Antonio Giannitrapani, Simone for a photovoltaic (PV) power producer taking part into a competitive electricity market characterized by financial set from an Italian PV plant. Index Terms--Energy market, bidding strategy, photovoltaic power

  9. Robust Pareto Optimum Routing of Ships Deterministic and Ensemble Weather Forecasts

    E-Print Network [OSTI]

    Berlin,Technische Universität

    Robust Pareto ­ Optimum Routing of Ships utilizing Deterministic and Ensemble Weather Forecasts the SEAROUTES project, who provided me with exquisite weather forecasts, and who inspired me to apply ensemble ship operation. The more reliable weather forecasts and performance simulation of ships in a seaway

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  12. timber quality Modelling and forecasting

    E-Print Network [OSTI]

    Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe M E F Y Q U E #12;Valuing and the UK ­ are working closely together to develop a model to help forecast timber growth, yield, quality

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

    E-Print Network [OSTI]

    Doswell III, Charles A.

    -scale Severe Weather and Technology of Reduction of Relevant Disasters (Tokyo, Japan), 22-26 February 1993, 181 technology and powerful workstation approaches in the forecasting workplace. Training and education leading to the weather events should form the basis for any scientific approaches to forecasting those

  14. 6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO

    E-Print Network [OSTI]

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

  15. Products and Service of Center for Weather Forecast and Climate Studies

    E-Print Network [OSTI]

    LOG O Products and Service of Center for Weather Forecast and Climate Studies Simone Sievert da products Supercomputer Facilities DSA/CPTEC-INPE Monitoring products based on remote sensing Training products Numerical Forecast Products Weather discussion Colleting data platform #12;Atmospheric Chemistry

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Ed.. Editor: Jan

  17. Exploiting Weather Forecast Information in the Operation of ...

    E-Print Network [OSTI]

    Victor M Zavala

    2009-03-04T23:59:59.000Z

    Mar 4, 2009 ... We argue that anticipating the weather conditions can lead to more ... The necessary uncertainty information is extracted from the weather ...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

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

  19. Thunderstorm lightning and radar characteristics: insights on electrification and severe weather forecasting

    E-Print Network [OSTI]

    Steiger, Scott Michael

    2007-04-25T23:59:59.000Z

    THUNDERSTORM LIGHTNING AND RADAR CHARACTERISTICS: INSIGHTS ON ELECTRIFICATION AND SEVERE WEATHER FORECASTING A Dissertation by SCOTT MICHAEL STEIGER Submitted to the Office of Graduate Studies of Texas A&M University in partial... fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY December 2005 Major Subject: Atmospheric Sciences THUNDERSTORM LIGHTNING AND RADAR CHARACTERISTICS: INSIGHTS ON ELECTRIFICATION AND SEVERE WEATHER...

  20. Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD

    E-Print Network [OSTI]

    Plale, Beth

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

  1. A Comparison of Parallel Programming Paradigms and Data Distributions for a Limited Area Numerical Weather Forecast Routine

    E-Print Network [OSTI]

    van Engelen, Robert A.

    . Published in proceedings of the 9 th ACM International Conference on Supercomputing, July 1995, Barcelona for producing routine weather forecasts at several European meteorological institutes. Results are shown

  2. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

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

    2007-07-05T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Sripada, Yaji

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

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

    E-Print Network [OSTI]

    Reiter, Ehud

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

  5. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

  6. Observations and simulations improve space weather models

    E-Print Network [OSTI]

    - 1 - Observations and simulations improve space weather models June 25, 2014 Los Alamos with fast-moving particles and a space weather system that varies in response to incoming energy computer simulations of the space weather that can affect vital technology, communication and navigation

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

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

  8. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    SciTech Connect (OSTI)

    Chiswell, S.; Buckley, R.

    2009-01-15T23:59:59.000Z

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

  9. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

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

    2008-03-20T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Model uncertainty in a mesoscale ensemble prediction system:monsoon experiment using a mesoscale two-dimensional model.Prediction operational mesoscale Eta model. Journal of

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

    E-Print Network [OSTI]

    Douches, David S.

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

  12. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

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

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

    E-Print Network [OSTI]

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2008-01-01T23:59:59.000Z

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

  14. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

    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.

  15. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

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

  17. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Schrijver, Karel

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

  19. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    and validation.   Solar Energy.   73:5, 307? Perez, R. , forecast database.   Solar Energy.   81:6, 809?812.  forecasts in the US.   Solar Energy.   84:12, 2161?2172.  

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

    E-Print Network [OSTI]

    Hudlow, M.D.

    Techniques for streamflow forecasting are developed and tested for the Little Washita River in Oklahoma. The basic input for streamflow forecasts is rainfall. the rainfall amounts may be obtained from several sources; however, this study...

  2. A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION

    E-Print Network [OSTI]

    Boyer, Edmond

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

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  4. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    procurement process at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    Downward surface solar radiation  data released at 12 UTC forecast shortwave radiation with data obtained from the radiation:   A statistical approach using satellite data.   

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

    E-Print Network [OSTI]

    G. Michalek; N. Gopalswamy; S. Yashiro

    2007-10-24T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Katz, Richard

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

  8. Forecasting model of the PEPCO service area economy. Volume 3

    SciTech Connect (OSTI)

    Not Available

    1984-03-01T23:59:59.000Z

    Volume III describes and documents the regional economic model of the PEPCO service area which was relied upon to develop many of the assumptions of future values of economic and demographic variables used in the forecast. The PEPCO area model is mathematically linked to the Wharton long-term forecast of the U.S. Volume III contains a technical discussion of the structure of the regional model and presents the regional economic forecast.

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

    SciTech Connect (OSTI)

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

    2007-06-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

    capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

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

    SciTech Connect (OSTI)

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

    2014-06-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2007-12-01T23:59:59.000Z

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

  14. GENERALIZED LINEAR MODELING APPROACH TO STOCHASTIC WEATHER GENERATORS

    E-Print Network [OSTI]

    Katz, Richard

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

  15. Weather

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsing Maps1DOETHE FUTURE LOOKSofthe Geeks:WeaponsWeather

  16. Weather Research and Forecasting Model 2.2 Documentation

    E-Print Network [OSTI]

    Sadjadi, S. Masoud

    : Javier Munoz, Diego Lopez, and David Villegas Undergraduate REU Students: Javier Figueroa, Xabriel J International University (FIU) 11200 SW 8th St., Miami, Florida 33199, USA #12;2 Contents Project Motivation

  17. Evaluation of the Weather Research and Forecasting Model on

    E-Print Network [OSTI]

    Basu, Sukanta

    : Implications for Wind Energy Brandon Storm*, Wind Science and Engineering Research Center, Texas Tech this region more favorable for wind energy production. At the same time, the presence of LLJs can direct ramifications for renewable wind energy production (e.g. Sisterson and Frenzen8

  18. An analysis of winter precipitation in the northeast and a winter weather precipitation type forecasting tool for New York City 

    E-Print Network [OSTI]

    Gordon, Christopher James

    1999-01-01T23:59:59.000Z

    1's accuracy in forecasting frozen precipitation. . . . 60 23 25 Same as FIG. 22 except for model 2 . . . . Same as FIG. 22 except for model 3 . . . . Same as FIG. 22 except for model 4 . . . . 61 62 26 Histogram of responses for snow cases... to the logistic regression analysis of snow cases versus rain cases for model 1. 64 FIGURE Page 27 Histogram of responses for rain cases to the logistic regression analysis of snow cases versus rain cases for model 1 28 Histogram of responses for snow cases...

  19. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

  1. A model for short term electric load forecasting

    E-Print Network [OSTI]

    Tigue, John Robert

    1975-01-01T23:59:59.000Z

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

  2. 13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS FOR SEVERE CONVECTIVE WEATHER

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

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

    2014-10-27T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Xue, Ming

    THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF NOAA's Hazardous Weather Testbed (HWT) is a joint facility managed by the National Severe Storms and technologies into advances in forecasting and warning for hazardous mesoscale weather events throughout

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16T23:59:59.000Z

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

  8. Weather Research and Forecasting Model Goals: Develop an advanced mesoscale forecast

    E-Print Network [OSTI]

    , hierarchical design, coding standards ­ Plug compatible physics, dynamical cores ­ Registry to describe Driver Layer Driver Package Independent Mediation Layer Config Inquiry I/O API Package Dependent Config

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

    E-Print Network [OSTI]

    Raftery, Adrian

    the chance of winds high enough to pose dangers for boats or aircraft. In situations calling for a cost/loss analysis, the probabilities of different outcomes need to be known. For wind speed, this issue often arisesProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

  10. Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging

    E-Print Network [OSTI]

    Washington at Seattle, University of

    February 24, 2006 1J. McLean Sloughter is Graduate Research Assistant, Adrian E. Raftery is BlumsteinProbabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging J. McLean Sloughter, Adrian E. Raftery and Tilmann Gneiting 1 Department of Statistics, University of Washington

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

    E-Print Network [OSTI]

    Raftery, Adrian

    : J. McLean Sloughter, Department of Mathematics, Seattle University, 901 12th Ave., P.O. Box 222000Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN SLOUGHTER Seattle University, Seattle, Washington TILMANN GNEITING Heidelberg University, Heidelberg

  12. Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting

    E-Print Network [OSTI]

    can the forecasts completely cover the evolution of earthquake-generated tsunami waves: generationDevelopment, testing, and applications of site-specific tsunami inundation models for real and applications of site-specific tsunami inundation models (forecast models) for use in NOAA's tsunami forecast

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

    SciTech Connect (OSTI)

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

    2011-03-28T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2009-02-14T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Chiswell, S

    2009-01-11T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Zhou, Shujia

    2009-01-01T23:59:59.000Z

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

  17. A first large-scale flood inundation forecasting model

    SciTech Connect (OSTI)

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04T23:59:59.000Z

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.

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

    SciTech Connect (OSTI)

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

    1995-05-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-03-19T23:59:59.000Z

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

  20. Winter Weather Introduction

    E-Print Network [OSTI]

    Taylor, Jerry

    Winter Weather Management #12;Introduction · Campus Facilities Staff · Other Campus Organizations #12;Purpose · Organize and coordinate the campus response to winter weather events to maintain campus for use by 7 AM. · Response will be modified depending upon forecast and current weather conditions. #12

  1. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  2. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  3. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  4. P2.3 DEVELOPMENT OF A COMPREHENSIVE SEVERE WEATHER FORECAST VERIFICATION SYSTEM AT THE STORM PREDICTION CENTER

    E-Print Network [OSTI]

    : Andrew R. Dean, CIMMS, Univ. of Oklahoma, National Weather Center, Suite 2300, Norman, OK 73072-7268; e PREDICTION CENTER Andrew R. Dean*1,2 , Russell S. Schneider 2 , and Joseph T. Schaefer 2 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 2 NOAA/NWS Storm

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

    E-Print Network [OSTI]

    McGovern, Amy

    dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun of the transportation systems. The annual economic impact of these mesoscale storms is estimated to be greater than $13B

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

    E-Print Network [OSTI]

    Boyer, Edmond

    Air-Conditioning Effect Estimation for Mid-Term Forecasts of Tunisian Electricity Consumption Tunisian electricity consumption (the residential sector represents 68% of this class of consumers). Nevertheless, with the Tunisian electricity consumption context, models elaborating which take account weather

  7. AIR QUALITY ENSEMBLE FORECAST COUPLING ARPEGE AND CHIMERE OVER WESTERN EUROPE

    E-Print Network [OSTI]

    Menut, Laurent

    AIR QUALITY ENSEMBLE FORECAST COUPLING ARPEGE AND CHIMERE OVER WESTERN EUROPE Carvalho of the results encountered on numerical weather prediction ensemble runs has encouraged the air quality modellers' community to test the same methodology to foresee air pollutants concentrations

  8. Volatility Forecasts in Financial Time Series with HMM-GARCH Models

    E-Print Network [OSTI]

    Chen, Yiling

    Volatility Forecasts in Financial Time Series with HMM-GARCH Models Xiong-Fei Zhuang and Lai {xfzhuang,lwchan}@cse.cuhk.edu.hk Abstract. Nowadays many researchers use GARCH models to generate of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH

  9. Model bias correction for dust storm forecast using ensemble Kalman filter

    E-Print Network [OSTI]

    Model bias correction for dust storm forecast using ensemble Kalman filter Caiyan Lin,1,2 Jiang Zhu Kalman filter (EnKF) assimilation targeting heavy dust episodes during the period of 15­24 March 2002. Wang (2008), Model bias correction for dust storm forecast using ensemble Kalman filter, J. Geophys

  10. Econometric model and futures markets commodity price forecasting

    E-Print Network [OSTI]

    Just, Richard E.; Rausser, Gordon C.

    1979-01-01T23:59:59.000Z

    Versus CCll1rnercial Econometric M:ldels." Uni- versity ofWorking Paper No. 72 ECONOMETRIC ! 'econometric forecasts with the futures

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

    E-Print Network [OSTI]

    Webster, Peter J.

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

  12. Calibration of a Distributed Flood Forecasting Model with Input Uncertainty Using a Bayesian Framework

    E-Print Network [OSTI]

    Hubbard, Susan

    Calibration of a Distributed Flood Forecasting Model with Input Uncertainty Using a Bayesian, Berkeley, CA, United States. In the process of calibrating distributed hydrological models, accounting in calibrating GBHM parameters and in estimating their associated uncertainty. The calibration ignoring input

  13. Weather Radar and Hydrology 1 Influence of rainfall spatial variability on hydrological modelling: a

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Weather Radar and Hydrology 1 Influence of rainfall spatial variability on hydrological modelling variability as well as characteristics and hydrological behavior of catchments, we have proceeded simulator and a distributed hydrological model (with four production functions and a distributed transfer

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS to develop a methodology to generate solar radiation maps using information from different sources. First with conclusions and next works in the last section. Keywords: Solar Radiation maps, Numerical Weather Predictions

  15. Forecasting Volatility in Stock Market Using GARCH Models

    E-Print Network [OSTI]

    Yang, Xiaorong

    2008-01-01T23:59:59.000Z

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

  16. Absolute Percent Error Based Fitness Functions for Evolving Forecast Models AndyNovobilski,Ph.D.

    E-Print Network [OSTI]

    Fernandez, Thomas

    Absolute Percent Error Based Fitness Functions for Evolving Forecast Models Andy computfi~gas a methodof data mining,is its intrinsic ability to drive modelselection accordingto a mixedset of criteria. Basedon natural selection, evolutionary computing utilizes evaluationof candidatesolutions

  17. A forecasting model of tourist arrivals from major markets to Thailand

    E-Print Network [OSTI]

    Hao, Ching

    1998-01-01T23:59:59.000Z

    important to forecast tourism demand in the region and understand the factors affecting demand. Considering the national importance of tourism, Thailand was chosen as the destination country with nine major markets as the countries of origin. A model...

  18. Probabilistic Performance Forecasting for Unconventional Reservoirs With Stretched-Exponential Model

    E-Print Network [OSTI]

    Can, Bunyamin

    2011-08-08T23:59:59.000Z

    a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow...

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

    E-Print Network [OSTI]

    Cheng, Chi

    1993-01-01T23:59:59.000Z

    has been the center of considerable attention in the applied econometric literature. The criterion Predictive Least Squares (PLS) based on actual postsample forecasting performance is proposed to identify a time series model. The criterion is applied...

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

    E-Print Network [OSTI]

    Boyer, Edmond

    2001-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Boyer, Edmond

    2003-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-06-28T23:59:59.000Z

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

  3. Wet-Weather Flow Characterization for the Rock Creek through Monitoring and Modeling

    E-Print Network [OSTI]

    District of Columbia, University of the

    support of the following organizations: ­ DC Water Resources Research Institute ­ U.S. Geological Survey..................................................................16 Modeling of Urban Stormwater Management discharged to receiving waters demand that wet-weather flow control systems be planned and engineered

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

    SciTech Connect (OSTI)

    Finley, Cathy [WindLogics

    2014-04-30T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Jackson, Ben Douglas

    1973-01-01T23:59:59.000Z

    the orders estimates should be minimal, and the benefits of forecasting should exceed the costs. Included in this matter of convenience is the mathematical simplicity of the computations and their evaluation. With these essential characteristics in mind... FORECASTING THE MONTHLY VOLUME OF ORDERS FOR SOUTHERN PINE LUMBER - AH ECONOMETRIC MODEL A Thesis by BEN DOUGLAS JACKSON Submitted to the Graduate College of Texas ASM University in Partial fulfillment of the requirement for the degree...

  6. Radiation fog forecasting using a 1-dimensional model

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01T23:59:59.000Z

    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...

  7. P9.137 The SPC Storm-Scale Ensemble of Opportunity: Overview and Results from the 2012 Hazardous Weather Testbed Spring Forecasting Experiment

    E-Print Network [OSTI]

    P9.137 The SPC Storm-Scale Ensemble of Opportunity: Overview and Results from the 2012 Hazardous) available to forecasters at the Storm Prediction Center (SPC) has been increasing over the past few years to examine and scrutinize the data in creating a forecast has not changed. Thus, the concept of the SPC Storm

  8. Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts Hélène of the shocks on the volatility by estimating a structural model with a periodic threshold GARCH. We show model, Markov chain, threshold GARCH, Monte- Carlo simulations, pricing, Value-at-Risk. JEL

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    to accurately forecast natural gas prices. Many policyseek alternative methods to forecast natural gas prices. Thethe accuracy of forecasts for natural gas prices as reported

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  11. Addressing model bias and uncertainty in three dimensional groundwater transport forecasts for a physical aquifer experiment

    E-Print Network [OSTI]

    Vermont, University of

    Addressing model bias and uncertainty in three dimensional groundwater transport forecasts, and D. M. Rizzo (2008), Addressing model bias and uncertainty in three dimensional groundwater transport. Introduction [2] Eigbe et al. [1998] provide an excellent review of groundwater applications of the linear

  12. Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging J. MCLEAN SLOUGHTER, ADRIAN E. RAFTERY, TILMANN GNEITING, AND CHRIS FRALEY

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging J. MCLEAN SLOUGHTER, ADRIAN E. RAFTERY, TILMANN GNEITING, AND CHRIS FRALEY Department of Statistics, University of precipitation (PoP) forecasts using this approach. Bayesian model averaging (BMA) was introduced by Raftery et

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

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    pockets and to modify the existing ones. Index Terms--Load forecasting, power system planning I by electric utilities to estimate and forecast the load growth in different service areas. The software builds statistical load models for various service areas (load pockets), estimates weather-normalized loads

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsing Maps toValidatingCloud Properties Derived from

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompanyPCN Technology Jump to: navigation,Analysis

  16. Initial Development and Genesis of Hurricane Dolly (2008) Key Laboratory of Mesoscale Severe Weather (MOE), Department of Atmospheric Sciences, Nanjing University, Nanjing, China

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    Severe Weather (MOE), Department of Atmospheric Sciences, Nanjing University, Nanjing, China FUQING ZHANG-resolving simulation with the Weather Research and Forecasting Model, this study examines key processes that led- tudinal stretching deformation) alters the characteristics of equatorial waves to form regions of energy

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

    E-Print Network [OSTI]

    Ribes, Aurélien

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE significant. This led to the implementation of an ensemble Kalman filter (EnKF) within COBEL-ISBA. The new by using an ensemble Kalman filter (EnKF; Evensen 1994, 2003). Theoreti- cally, ensemble filters

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

    E-Print Network [OSTI]

    Hubbard, Susan

    Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian; revised 20 June 2012; accepted 28 June 2012; published 15 August 2012. [1] In the process of calibrating that the developed method generally is effective in calibrating GBHM parameters and in estimating their associated

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

    SciTech Connect (OSTI)

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

    2013-09-01T23:59:59.000Z

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

  20. Time series modeling and large scale global solar radiation forecasting from geostationary satellites data

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Time series modeling and large scale global solar radiation forecasting from geostationary global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory

  1. Developing a TeraGrid Based Land Surface Hydrology and Weather Modeling Interface

    E-Print Network [OSTI]

    Jiang, Wen

    Developing a TeraGrid Based Land Surface Hydrology and Weather Modeling Interface Hsin-I Chang1 iclimate@purdue.edu -------------------- -------------------- 1 INTRODUCTION Real world hydrologic cyberinfrastructure (CI) has been articulated in many workshops and meetings of the environmental and hydrologic

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

    SciTech Connect (OSTI)

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

    2014-11-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01T23:59:59.000Z

    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.

  4. Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales

    E-Print Network [OSTI]

    Akbarnejad Nesheli, Babak

    2012-07-16T23:59:59.000Z

    stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale...

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

    SciTech Connect (OSTI)

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

    2008-11-15T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake. The in- crease in computer power in recent years and advances in numerical mesoscale models of both ocean Forecasting System (GLCFS) can be used to validate wind forecasts for the Great Lakes using observed

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

    E-Print Network [OSTI]

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

    2013-01-01T23:59:59.000Z

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

  8. Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , in order to be able to absorb a large fraction of wind power in the electrical systems reliable short from refer- ence MET forecasts to the actual wind farm, wind farm power curve models, dynamical models of art wind power prediction system is outlined in Section 2. Numerical Weather Prediction (NWP

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

    E-Print Network [OSTI]

    Pyles, R. D.

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

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

    E-Print Network [OSTI]

    Xu, L.

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

  11. Parametric inference and forecasting for continuously invertible volatility models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    recover known results on univariate and multivariate GARCH type models where the estima- tor coincides estimation, strong consistency, asymptotic normality, asymmetric GARCH, exponential GARCH, stochastic (1986), the General Au- toregressive Conditional Heteroskedasticity (GARCH) type models have been

  12. Update On The Wholesale Electricity Price Forecast & Modeling Results

    E-Print Network [OSTI]

    ,877 Replacement #12;CO2 Emission Modeling § The AURORAxmp® electric market model calculates CO2 emission) Assumptions § CO2 emission modeling § Base Case Results § Scenario/Sensitivities § Emission Projections Database ­ eGRID 2012 Year 2009 ­ Emissions, including CO2, are estimated using information from various

  13. accelerated weathering tests: Topics by E-print Network

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

    managed by the National Severe Storms Laboratory (NSSL), the Storm Prediction Center (SPC), and the NWS Oklahoma CityNorman Weather Forecast Xue, Ming 30 Testing General...

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

    SciTech Connect (OSTI)

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

    2013-10-19T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kulkarni, Siddhivinayak

    2009-01-01T23:59:59.000Z

    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...

  17. Increasing NOAA's computational capacity to improve global forecast modeling

    E-Print Network [OSTI]

    Hamill, Tom

    Systems Division Stephen J. Lord Director, NWS NCEP Environmental Modeling Center 19 July 2010 (303) 4973060 tom.hamill@noaa.gov #12; 2 Executive Summary The accuracy of many

  18. Implementation of a Corporate Energy Accounting and Forecasting Model

    E-Print Network [OSTI]

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

    1981-01-01T23:59:59.000Z

    The development and implementation of a Frito-Lay computer based energy consumption reporting and modeling program is discussed. The system has been designed to relate actual plant energy consumption to a standard consumption which incorporates...

  19. Development of a real-time quantitative hydrologic forecasting model

    E-Print Network [OSTI]

    Bell, John Frank

    1986-01-01T23:59:59.000Z

    data made in each domain. Fit3ur e 1. Lieatner Radar Carr ection Procedures (by drtmatni ( Bussel I et a 1 . , (97EI ) (Weeks and Hebbert, 1980) and the Boughton Model (Weeks and Hebbert, 1980) are but a few. Models range from sophisticated... of hydroelectric power with existing facilities, $73 million, e) benefits to navigation, $2 million and f) more efFective use of recreational facilities and wildlife habitat, $3 million. Total $485 million The resulting expected benefits in 1983 dollars...

  20. Weather Radar Control System Seidu Ibrahim; Advisor: Eric J. Knapp

    E-Print Network [OSTI]

    Mountziaris, T. J.

    Weather Radar Control System Seidu Ibrahim; Advisor: Eric J. Knapp Dept. of Electrical and Computer Engineering University of Massachusetts, Amherst Abstract Weather radar is an important part of the national infrastructure that is used in producing forecasts and issuing hazardous weather warnings. Traditional weather

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

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Almohammadi, Hisham

    2013-07-26T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2011-08-15T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    1993-05-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Arumugam, Sankar

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

  6. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17T23:59:59.000Z

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

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

    E-Print Network [OSTI]

    Choi, Hankyeung

    2012-10-19T23:59:59.000Z

    on the forecasting models for crude oil prices and the hedging models for gasoline prices, and to study the change in the contemporaneous causal relationship between investors' activities and stock price movements in the Korean stock market. In the first essay...

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

    E-Print Network [OSTI]

    Choi, Hankyeung

    2012-10-19T23:59:59.000Z

    on the forecasting models for crude oil prices and the hedging models for gasoline prices, and to study the change in the contemporaneous causal relationship between investors' activities and stock price movements in the Korean stock market. In the first essay...

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

    E-Print Network [OSTI]

    Costanzo, Sabatino; Dehne, Wafaa; Prato, Hender

    2007-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    The Role of "Citizen Science" in Weather and Climate Research Presented at PPSR 2012 August 4, 2012 50 years of weather records Early Traditions in Citizen Science #12;Benjamin Franklin #12;Joseph stations to help document Climate resources of the country And provide science-based weather forecasts

  11. Physics 137, Section 1, Fall Semester Severe and Hazardous Weather

    E-Print Network [OSTI]

    Hart, Gus

    Physics 137, Section 1, Fall Semester Severe and Hazardous Weather OBSERVATION PROJECTS During project or present one TV-type weather forecast. A list of a few possible observational projects is here of the project, information in the report might include times, dates and places of observations; weather

  12. Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Forecasting the conditional volatility of oil spot and futures prices with structural breaks of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural that oil price fluctuations influence economic activity and financial sector (e.g., Jones and Kaul, 1996

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

    E-Print Network [OSTI]

    Liu, Chang

    2009-05-15T23:59:59.000Z

    forecasts of well and reservoir performance, accessible at any time. It can be used to optimize long-term reservoir performance at field scale....

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

    derivatives and risk management. Energy, 31. [Dutton, 2002]exposed to weather risk because the energy demand is highlyin the energy industry showing that volumetric risk caused

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

    E-Print Network [OSTI]

    Lascaux, Franck; Fini, Luca

    2015-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Henderson, Gideon

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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2011-12-06T23:59:59.000Z

    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.

  19. Phys1063-Physics of Weather August 23, 2010 S. Boyd Page 1 of 4

    E-Print Network [OSTI]

    Boyd, Sylke

    Phys1063-Physics of Weather August 23, 2010 S. Boyd Page 1 of 4 Physics of Weather Credit: 4 and air masses, thunderstorms, tornadoes, past and present climate, weather forecasting, problems requirements. #12;Phys1063-Physics of Weather August 23, 2010 S. Boyd Page 2 of 4 F (or N) -- Represents

  20. Commercial Weatherization

    Broader source: Energy.gov [DOE]

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

  1. Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets

    SciTech Connect (OSTI)

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

    2005-06-30T23:59:59.000Z

    The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

  2. PV powering a weather station for severe weather

    SciTech Connect (OSTI)

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

    1997-12-31T23:59:59.000Z

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

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

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

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

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

    E-Print Network [OSTI]

    Juarez Torres, Miriam 77-

    2012-08-31T23:59:59.000Z

    , or even conclusive criterion (Genest and Favre 2007a). Data from three weather stations located in Montana, Washington and Texas are used for this research. 5 Background and Motivation Climatological and meteorological phenomena are complex...: [ )| ), ), ? , ) = ), Montana, one...

  5. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom [Vanderbilt University, Nashville; Quaranta, Vito [Vanderbilt University, Nashville; Evans, Katherine J [ORNL; Rericha, Erin [Vanderbilt University, Nashville

    2015-01-01T23:59:59.000Z

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

  6. Developing a model for explaining and forecasting international tourist arrivals from the major markets to Malaysia

    E-Print Network [OSTI]

    Chin, Loi Young

    1996-01-01T23:59:59.000Z

    to forecast the potential of tourism in the region and understand the factors behind such growth. Malaysia was chosen as the destination country with nine major markets as the countries of origin. The nine countries selected were geographically dispersed over...

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

    E-Print Network [OSTI]

    Makaudze, Ephias

    1993-01-01T23:59:59.000Z

    The Zimbabwean government utilizes the corn supply forecasts to establish producer prices for the following growing season, estimate corn storage and handling costs, project corn import needs and associated costs, and to assess the Grain Marketing...

  8. Weatherization Roundup

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Balakrishnan, Hamsa

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

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

    E-Print Network [OSTI]

    Cirne, Walfredo

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

  11. Weatherizing America

    ScienceCinema (OSTI)

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

    2013-05-29T23:59:59.000Z

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

  12. Weatherizing America

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Oren, Shmuel S.

    . There- fore, energy companies face two types of risk, price risk in the spot market and 1 Manuscript weather changes will affect energy demand and sudden de- mand increases result in spot price spikes-day ice storm in February 2003 electricity prices spiked to $990/MWh causing a retail energy provider

  15. Interactive dust-radiation modeling: A step to improve weather Carlos Perez,1

    E-Print Network [OSTI]

    radiative effects could lead to a significant improvement in the radiation balance of numerical weather 2002 is selected to assess the radiative dust effects on the atmosphere at a regional level. A strong unresolved and depend on the optical properties of dust, its vertical distribution, cloud cover, and albedo

  16. Wavelet-Based Nonlinear Multiscale Decomposition Model for Electricity Load Forecasting

    E-Print Network [OSTI]

    Murtagh, Fionn

    electrical power systems. Furthermore, power systems need to operate at even higher efficiency lead to extra power being generated and therefore may result in excessive investment in electric plant that is not fully utilized. On the other hand, a forecast that is too low may lead to some revenue loss from sales

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

    E-Print Network [OSTI]

    Jerez Vera, Sergio Armando

    2007-04-25T23:59:59.000Z

    , and (2) to use the single-layer match to demonstrate the error that can occur when forecasting long-term gas production for such complex gas reservoirs. A finite-difference reservoir simulator was used to simulate gas production from various layered tight...

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

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

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

    E-Print Network [OSTI]

    Hogan, Robin

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

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

    E-Print Network [OSTI]

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

    2015-01-01T23:59:59.000Z

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

  1. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

    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.

  2. EXPANDING THE MODIFIED GAUSSIAN MODEL TO INCLUDE THE SPACE WEATHERING EFFECTS: ESTIMATION OF THE WEATHERING DEGREES OF PULSE-LASER TREATED OLIVINE SAMPLES. Y.

    E-Print Network [OSTI]

    Hiroi, Takahiro

    OF THE WEATHERING DEGREES OF PULSE-LASER TREATED OLIVINE SAMPLES. Y. Ueda1, 2 , T. Hiroi2 , C. M. Pieters2 and M creating the npFe0 by treating olivine (Fo91) pow- der samples with pulse laser at 1064 nm in wavelength of their olivine samples treated with laser energies of 0, 15, and 30 mJ. The refractive index spectra of Fe

  3. Physics 137, Section 1, Winter Semester Introduction to the Atmosphere and Weather

    E-Print Network [OSTI]

    Hart, Gus

    Physics 137, Section 1, Winter Semester Introduction to the Atmosphere and Weather OBSERVATIONAL observational project or present one TV-type weather forecast. A list of a few possible observational projects; weather conditions at times of observations, data tables, charts, sketches, graphs, descriptions of what

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

    E-Print Network [OSTI]

    Mass, Clifford F.

    1 The Uncoordinated Giant: Why U.S. Weather Research and Prediction Are Not Achieving.S. meteorological community has made significant strides in weather diagnosis and prediction, progress has been such problems in a number of areas, ranging from numerical weather prediction to forecast dissemination

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

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

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

    2009-01-01T23:59:59.000Z

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

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

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

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

    2009-01-01T23:59:59.000Z

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

  7. Development of a neural network model to nowcast/forecast the coastal water level anomalies on the entrance to Galveston Bay, Texas

    E-Print Network [OSTI]

    Nam, Young Joo

    2002-01-01T23:59:59.000Z

    level fluctuations are forced primarily by the remote effects which was the water level at the mouth of the estuary, consistent with earlier findings in the literature. A neural network model was optimized to forecast the remote forcing at Galveston Bay...

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

    SciTech Connect (OSTI)

    Morrison, PI Hugh

    2012-09-21T23:59:59.000Z

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

  9. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect (OSTI)

    Wegley, H.L.; Formica, W.J.

    1983-07-01T23:59:59.000Z

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

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

    E-Print Network [OSTI]

    Li, M.

    2013-01-01T23:59:59.000Z

    error model for calibration and uncertainty estimation ofand T. Wagener (2005), Model calibration and uncertaintyand A. Mailhot (2008), Calibration of hydrological model

  11. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  13. Weatherization Training for South Carolina's Muggy Weather

    Broader source: Energy.gov [DOE]

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

  14. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions forecasts is 0.05o in latitude and longitude. Solar Radiation model: The model presented in this paper

  15. Cathy Zoi on Weatherization

    ScienceCinema (OSTI)

    Zoi, Cath

    2013-05-29T23:59:59.000Z

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

  16. Cathy Zoi on Weatherization

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

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

  18. DREAM tool increases space weather predictions

    E-Print Network [OSTI]

    - 1 - DREAM tool increases space weather predictions April 13, 2012 Predicting space weather improved by new DREAM modeling tool Earth's radiation belts can now be studied with a new modeling tool DREAM comes into play. Radiation belt structure and dynamics revealed DREAM is a modeling tool

  19. Agricultural commodity price forecasting accuracy: futures markets versus commercial econometric models

    E-Print Network [OSTI]

    Rausser, Gordon C.; Just, Richard E.

    1979-01-01T23:59:59.000Z

    versus commercial econometric models Gordon C. RausserMARKETS VERSUS COM4ERCIAL ECONOMETRIC IDDELS by Gordon C.Futures Markets, snd Econometric Models Deeember, 19'7'6,

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

    E-Print Network [OSTI]

    Gottlieb, Joshua

    2011-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Irwin, Mark E.

    2005-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bronson, J. D.

    1992-01-01T23:59:59.000Z

    DOE-2 yields hourly data on specific variables provided the user specifies the HOURLY-REPORT instruction. Analyzing the simulation results with hourly data gives a more detailed picture of how well the model is predicting the monitored energy...

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

    E-Print Network [OSTI]

    Perez, Richard R.

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

  4. Paper accepted for presentation at 2003 IEEE Bologna PowerTech Conference, June 23-26, Bologna, Italy Wind Power Forecasting using Fuzzy Neural Networks

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , Italy Wind Power Forecasting using Fuzzy Neural Networks Enhanced with On-line Prediction Risk) as input, to predict the power production of wind park8 48 hours ahead. The prediction system integrates of the numerical weather predictions. Index Term-Wind power, short-term forecasting, numerical weather predictions

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

    E-Print Network [OSTI]

    Cheng, Chi

    1993-01-01T23:59:59.000Z

    and the significance level between different models is discussed. At the 20% significance level cash prices and futures prices are generated in efficient markets, as the random walk models, specified by PLS, result in significantly lower RMSFE relative to the non...

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

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

  7. THE ROLE OF STORM PREDICTION CENTER PRODUCTS IN DECISION MAKING LEADING UP TO SEVERE WEATHER EVENTS

    E-Print Network [OSTI]

    to ultimately protect the lives and property of the American people. First-order users of SPC services, which responsibility is to release a suite of severe weather forecast and watch products for the #12;2 protection play key societal roles of efficiently relaying hazardous weather information to the public through

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Sitnov, Mikhail I.

    with the AL index, which measures the magnetic field disturbances produced by the substorm current system, such as turbulence, bursty bulk flows [Angelopolous et. al., 1999], and fluctuations in the near-Earth current sheet to reconstruct behavior of the system independent of modeling assump- tions, long time series data of geomagnetic

  10. Financial time series forecasting with a bio-inspired fuzzy model Jos Luis Aznarte a,

    E-Print Network [OSTI]

    Granada, Universidad de

    Alcalá-Fdez b , Antonio Arauzo-Azofra c , José Manuel Benítez b a Center for Energy and Processes (CEP series, as stock prices or level of indices, is a controversial issue which has been questioned nature, the most salient of which is the well-known ARMA model by Box and Jenkins (1970). However, due

  11. Multi-objective calibration of forecast ensembles using Bayesian model averaging

    E-Print Network [OSTI]

    Vrugt, Jasper A.

    for selecting the appropriate BMA model. Citation: Vrugt, J. A., M. P. Clark, C. G. H. Diks, Q. Duan, and B. A Martyn P. Clark,2 Cees G. H. Diks,3 Qinyun Duan,4 and Bruce A. Robinson1 Received 6 June 2006; revised 9 performance than the best of the ensemble members, or the ensemble mean [Raftery et al., 2005; Sloughter et al

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

    SciTech Connect (OSTI)

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

    2011-11-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

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

  14. Time series modeling and large scale global solar radiation forecasting from geostationary satellites data

    E-Print Network [OSTI]

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

    2014-01-01T23:59:59.000Z

    When a territory is poorly instrumented, geostationary satellites data can be useful to predict global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory, the Corsica Island, but as data used are available for the entire surface of the globe, our method can be easily exploited to another place. Indeed 2-D hourly time series are extracted from the HelioClim-3 surface solar irradiation database treated by the Heliosat-2 model. Each point of the map have been used as training data and inputs of artificial neural networks (ANN) and as inputs for two persistence models (scaled or not). Comparisons between these models and clear sky estimations were proceeded to evaluate the performances. We found a normalized root mean square error (nRMSE) close to 16.5% for the two best predictors (scaled persistence and ANN) equivalent to 35-45% related to ground measurements. F...

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

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

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

    E-Print Network [OSTI]

    Xue, Y; Fennessy, M; sellers, P

    2015-01-01T23:59:59.000Z

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

  17. Multi-horizon solar radiation forecasting for Mediterranean locations using time series models

    E-Print Network [OSTI]

    Voyant, Cyril; Muselli, Marc; Nivet, Marie Laure

    2013-01-01T23:59:59.000Z

    Considering the grid manager's point of view, needs in terms of prediction of intermittent energy like the photovoltaic resource can be distinguished according to the considered horizon: following days (d+1, d+2 and d+3), next day by hourly step (h+24), next hour (h+1) and next few minutes (m+5 e.g.). Through this work, we have identified methodologies using time series models for the prediction horizon of global radiation and photovoltaic power. What we present here is a comparison of different predictors developed and tested to propose a hierarchy. For horizons d+1 and h+1, without advanced ad hoc time series pre-processing (stationarity) we find it is not easy to differentiate between autoregressive moving average (ARMA) and multilayer perceptron (MLP). However we observed that using exogenous variables improves significantly the results for MLP . We have shown that the MLP were more adapted for horizons h+24 and m+5. In summary, our results are complementary and improve the existing prediction techniques ...

  18. WEATHER HAZARDS Basic Climatology

    E-Print Network [OSTI]

    Prediction Center (SPC) Watch Atmospheric conditions are right for hazardous weather ­ hazardous weather is likely to occur Issued by SPC Warning Hazardous weather is either imminent or occurring Issued by local NWS office #12;Outlooks--SPC Storm Prediction Center (SPC) Outlook=Convective Outlook Day 1 Day 2

  19. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

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

  20. Forecasting the demand for electric vehicles: accounting for attitudes and perceptions

    E-Print Network [OSTI]

    Bierlaire, Michel

    prediction, transportation, attitudes and perceptions, hybrid choice models, fractional factorial design: survey design, model estimation and forecasting. We develop a stated preferences (SP) survey with issues related to the application of models designed to forecast demand for new alternatives, most

  1. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

    This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks...

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

    E-Print Network [OSTI]

    Masciadri, E; 10.1117/12.925924

    2012-01-01T23:59:59.000Z

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

  3. Modelling surface ozone during the 2003 heat-wave in the UK 

    E-Print Network [OSTI]

    Vieno, Massimo; Dore, A J; Stevenson, David S; Doherty, Ruth; Heal, Mathew R; Reis, Stefan; Hallsworth, Stephen; Tarrason, L; Wind, P; Fowler, David; Simpson, David; Sutton, Mark A

    2010-01-01T23:59:59.000Z

    of ground-level ozone (O3) during the extreme August 2003 heat-wave. Meteorology is generated by the Weather Research and Forecast (WRF) model, nudged every six hours with reanalysis data. We focus on SE England, where hourly average O3 reached up to 140 ppb...

  4. CSU ATS703 Fall 2012 Numerical Weather Prediction

    E-Print Network [OSTI]

    CSU ATS703 Fall 2012 Numerical Weather Prediction ATS703 is based on the course notes and papers method. A crucial element of accurate weather prediction is initialization, which is briefly discussed in Chapter 11. In the next decade, numerical weather prediction will expe- rience a revolution in model

  5. Forecasted Opportunities

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField8,Dist.New MexicoFinancingProofWorkingEnergyGo modelP eForForAForecasted

  6. The wind power probability density forecast problem can be formulated as: forecast the wind power pdf at time step t for each look-ahead time step t+k of a given time-horizon

    E-Print Network [OSTI]

    Kemner, Ken

    The wind power probability density forecast problem can be formulated as: forecast the wind power ahead) knowing a set of explanatory variables (e.g. numerical weather predictions (NWPs), wind power measured values). Translating this sentence to an equation, we have: where pt+k is the wind power

  7. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

  8. Critical Fire Weather Patterns

    E-Print Network [OSTI]

    Clements, Craig

    .1 Sundowner Winds FAT -- 1.1 Southeastern U.S. Fire Weather LIT -- 1.1 East Winds MFR -- 1.1 East Winds OLM

  9. The Weatherization Training program at Pennsylvania College

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

    A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

  10. The Weatherization Training program at Pennsylvania College

    ScienceCinema (OSTI)

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

    2013-05-29T23:59:59.000Z

    A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

  11. Predicting Solar Generation from Weather Forecasts Using Machine Learning

    E-Print Network [OSTI]

    Shenoy, Prashant

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

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

    E-Print Network [OSTI]

    of atmospheric data, increased computational power, and the continued im- provement of ... speed, and radiances, and are taken from satellites, buoys, planes, boats, ..... there is a large difference in cost between these two operations

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

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

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

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonantNovember 15 toAdvancesRock PhysicsRodney Ellis

  15. Home Weatherization Visit

    ScienceCinema (OSTI)

    Chu, Steven

    2013-05-29T23:59:59.000Z

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

  16. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

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

  17. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

    ;2Rainfall-River Forecasting Joint Summit II NOAA Integrated Water Forecasting Program · Minimize losses due management and enhance America's coastal assets · Expand information for managing America's Water Resources, Precipitation and Water Quality Observations · USACE Reservoir Operation Information, Streamflow, Snowpack

  18. Today's Space Weather Space Weather Case Studies

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

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

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

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

    E-Print Network [OSTI]

    Mancco, Richard

    2012-01-01T23:59:59.000Z

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

  1. Weatherizing Wilkes-Barre

    ScienceCinema (OSTI)

    Calore, Joe

    2013-05-29T23:59:59.000Z

    Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

  2. Weatherizing Wilkes-Barre

    Broader source: Energy.gov [DOE]

    Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

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

    E-Print Network [OSTI]

    Xue, Ming

    . In the study, water and ice phase microphysical variables are first derived from the polariza- tion for an adjoint that should include detailed physics parameterizations and the high computational cost, 4DVAR,mxue@ou.edu. et al (2000) being one exception. In the latter, the ice mi- crophysics scheme used

  4. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

    PROBABILISTIC MANPOWER FORECASTING A Thesis JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas ASSAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May, 1966 Major Subject...: Computer Science and Statistics PROBABILISTIC MANPOWER FORECASTING A Thesis By JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas A@M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    data and locations with no cloud cover were ignored (whitewith no cloud cover were ignored (white areas). Since thea) GOES cloud mask, where green is cloudy and white is clear

  6. Unified Surface Analysis Manual Weather Prediction Center

    E-Print Network [OSTI]

    -bone in stage IV. The stages in the respective cyclone evolutions are separated by approximately 6­ 24 h's) National Weather Service (NWS) were generally based on the Norwegian Cyclone Model (Bjerknes 1919) over below shows a typical evolution according to both models of cyclone development. Conceptual models

  7. UPF Forecast | Y-12 National Security Complex

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

    Uranium Processing Facility UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be...

  8. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

    : ImproveImprove NOAANOAA''ss understandingunderstanding and forecast capabilityand forecast capability inin

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

    SciTech Connect (OSTI)

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

    2009-01-10T23:59:59.000Z

    The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratio of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (~;;25percent total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator.

  10. The Puerto Rico Weather Camp 2013 is a summer experience hosted by the NOAA Center for Atmospheric Sciences at UPR Mayagez (UPRM) and co-sponsored by the

    E-Print Network [OSTI]

    Gilbes, Fernando

    The Puerto Rico Weather Camp 2013 is a summer experience hosted by the NOAA Center for Atmospheric forecasters and administrators, Emergency Management officers, and TV weather broadcasters. The Puerto Rico in the vicinity of La Parguera, Lajas (southwestern Puerto Rico). Applicants must be rising sophomore, junior

  11. The Puerto Rico Weather Camp 2012 is a summer experience hosted by the NOAA Center for Atmospheric Sciences at UPR Mayagez (UPRM) and co-sponsored by the

    E-Print Network [OSTI]

    Gilbes, Fernando

    The Puerto Rico Weather Camp 2012 is a summer experience hosted by the NOAA Center for Atmospheric forecasters and administrators, Emergency Management officers, and TV weather broadcasters. The Puerto Rico in the vicinity of La Parguera, Lajas (southwestern Puerto Rico). Applicants must be rising sophomore, junior

  12. Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1

    E-Print Network [OSTI]

    Miami, University of

    for crop yield forecasting and risk analysis. Using the Census Agriculture Region (CAR) as the unit Climate Decision Support and Adaptation, Agriculture and Agri-Food Canada, 1011, Innovation Blvd, Saskatoon, SK S7V 1B7, Canada The Canadian Crop Yield Forecaster (CCYF) is a statistical modelling tool

  13. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co for the modeled wind- CAES system would not cover annualized capital costs. We also estimate market prices-ahead market is roughly $100, with large variability due to electric power prices. Wind power forecast errors

  14. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  15. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  16. Intelligent weather agent for aircraft severe weather avoidance

    E-Print Network [OSTI]

    Bokadia, Sangeeta

    2002-01-01T23:59:59.000Z

    Severe weather conditions pose a large threat to the safety of aircraft, since they are responsible for a large percentage of aviation related accidents. With the advent of the free flight environment, the exigency for an autonomous severe weather...

  17. 2008 European PV Conference, Valencia, Spain COMPARISON OF SOLAR RADIATION FORECASTS FOR THE USA

    E-Print Network [OSTI]

    Perez, Richard R.

    2008 European PV Conference, Valencia, Spain COMPARISON OF SOLAR RADIATION FORECASTS FOR THE USA J models 1 INTRODUCTION Solar radiation and PV production forecasts are becoming increasingly important/) three teams of experts are benchmarking their solar radiation forecast against ground truth data

  18. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

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

    2011-01-01T23:59:59.000Z

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

  19. Steam System Forecasting and Management

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01T23:59:59.000Z

    '. This and the complex and integrated nature of the plants energy balance makes steam system forecasting and management essential for optimum use of the plant's energy. This paper discusses the method used by Union carbide to accomplish effective forecasting...

  20. accelerated weathering: Topics by E-print Network

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

    Winter Weather Safety www.weather.gov SnowIce Blizzards Flooding Cold Temperatures 12;Building a Weather 5 Weather Theory Weather Reports, Forcasts and...

  1. Portland Diversifying Weatherization Workforce

    Broader source: Energy.gov [DOE]

    An agreement signed by a diverse group of stakeholders ensures that those in disadvantaged communities have access to some of the weatherization jobs stemming from the pilot phase of the Clean Energy Works Portland program, which has almost 500 homes receiving retrofits through the summer with the help of federal dollars.

  2. What Constrains Spread Growth in Forecasts Initialized from Ensemble Kalman Filters?

    E-Print Network [OSTI]

    Hamill, Tom

    1 What Constrains Spread Growth in Forecasts Initialized from Ensemble Kalman Filters? Thomas M workshop on 4D-Var and Ensemble Kalman Filter Intercomparisons (Herschel Mitchell, editor) 24 August 2010 of weather predictions initialized from an ensemble Kalman filter may grow slowly relative to other methods

  3. What Constrains Spread Growth in Forecasts Initialized from Ensemble Kalman Filters?

    E-Print Network [OSTI]

    Hamill, Tom

    1 What Constrains Spread Growth in Forecasts Initialized from Ensemble Kalman Filters? Thomas M workshop on 4D-Var and Ensemble Kalman Filter Intercomparisons (Herschel Mitchell, editor) 27 May 2010 of weather predictions initialized from an ensemble Kalman filter may grow slowly relative to other methods

  4. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  5. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

    EMGT 835 FIELD PROJECT: Improving Inventory Control Using Forecasting By Juan Mario Balandran jmbg@hotmail.com Master of Science The University of Kansas Fall Semester, 2005 An EMGT Field Project report submitted...............................................................................................................................................10 Current Inventory Forecast Process ...........................................................................................10 Development of Alternative Forecast Process...

  6. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    electricity demand forecast means that the region's electricity needs would grow by 5,343 average megawattsDemand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping

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

    SciTech Connect (OSTI)

    Hollander, A.

    2014-09-01T23:59:59.000Z

    The U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Programs Office (WIPO) launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of low-income residences without the utilization of additional taxpayer funding. Sixteen WIPP grantees were awarded a total of $30 million in Weatherization Assistance Program (WAP) funds in September 2010. These projects focused on: including nontraditional partners in weatherization service delivery; leveraging significant non-federal funding; and improving the effectiveness of low-income weatherization through the use of new materials, technologies, behavior-change models, and processes.

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

    SciTech Connect (OSTI)

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

    2005-07-01T23:59:59.000Z

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  9. QUANTIFICATION OF WEATHERING Robert Hack

    E-Print Network [OSTI]

    Hack, Robert

    sandstone, limestone and dolomites, slates, shales, and in- Weathering and especially future weathering 40 60 80 H slate medium H slate v.thin H slate tick lam. Tg21 thick Tg21 medium Tg21 thin Tg21 v

  10. CLEAR SKY MODELS ASSESSMENT FOR AN OPERATIONAL PV PRODUCTION FORECASTING Sylvain Cros, Olivier Liandrat, Nicolas Sbastien, Nicolas Schmutz

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    reanalysis instead of punctual measurements significantly reduces errors in clear sky models. 1 INTRODUCTION the concentration of atmospheric components absorbing and diffusing solar radiation in the shortwave. Concerned

  11. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

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

  12. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price because oil, coal, and natural gas are potential fuels for electricity generation. Natural gas

  13. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    Quantifying PV power output variability,” Solar Energy, vol.each solar sen at node i, P(t) the total power output of theSolar Forecasting Historically, traditional power generation technologies such as fossil and nu- clear power which were designed to run in stable output

  14. Road Weather and Transportation Systems

    E-Print Network [OSTI]

    Bertini, Robert L.

    Road Weather and Transportation Systems Rhonda Young, P.E., PhD Associate Professor Dept. of Civil & Arch. Engineering Portland State University April 18, 2014 #12;Engineering Perspective of Road Weather · How does weather impact transportation systems? · As engineers, is there anything we can do

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

    SciTech Connect (OSTI)

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

    2014-07-25T23:59:59.000Z

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

  16. Leveraging Resources for the Weatherization Innovation Pilot...

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

    the Weatherization Innovation Pilot Program (WIPP) - Webinar Transcript Leveraging Resources for the Weatherization Innovation Pilot Program (WIPP) - Webinar Transcript This...

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

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

    Weatherization Innovation Pilot Projects (WIPP) Presentation Leveraging Resources for Weatherization Innovation Pilot Projects (WIPP) Presentation As a WIPP agency, reporting...

  18. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kockelman, Kara M.

    , as well as energy consumption and greenhouse gas emissions. This work describes the modeling of year-2030 policies significantly impact the region's future land use patterns, traffic conditions, greenhouse gas (emitting over 6 billion metric tons of CO2-equivalents annually, and accounting for 22.2% of the world

  20. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    ......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

  1. An econometric analysis and forecasting of Seoul office market

    E-Print Network [OSTI]

    Kim, Kyungmin

    2011-01-01T23:59:59.000Z

    This study examines and forecasts the Seoul office market, which is going to face a big supply in the next few years. After reviewing several previous studies on the Dynamic model and the Seoul Office market, this thesis ...

  2. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

    Bradley, M.E. (Univ. of Chicago, IL (United States)); Wood, A.R.O. (BP Exploration, Anchorage, AK (United States))

    1994-11-01T23:59:59.000Z

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended.

  3. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

    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.

  4. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005.................................................................................................................................3 PACIFIC GAS & ELECTRIC PLANNING AREA ........................................................................................9 Commercial Sector

  5. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL

  6. Bishop Paiute Weatherization Training Program

    SciTech Connect (OSTI)

    Carlos Hernandez

    2010-01-28T23:59:59.000Z

    The DOE Weatherization Training Grant assisted Native American trainees in developing weatherization competencies, creating employment opportunities for Bishop Paiute tribal members in a growing field. The trainees completed all the necessary training and certification requirements and delivered high-quality weatherization services on the Bishop Paiute Reservation. Six tribal members received all three certifications for weatherization; four of the trainees are currently employed. The public benefit includes (1) development of marketable skills by low-income Native individuals, (2) employment for low-income Native individuals in a growing industry, and (3) economic development opportunities that were previously not available to these individuals or the Tribe.

  7. Weatherization Apprenticeship Program

    SciTech Connect (OSTI)

    Watson, Eric J

    2012-12-18T23:59:59.000Z

    Weatherization improvement services will be provided to Native people by Native people. The proposed project will recruit, train and hire two full-time weatherization technicians who will improve the energy efficiency of homes of Alaska Natives/American Indians residing in the Indian areas, within the Cook Inlet Region of Alaska. The Region includes Anchorage as well as 8 small tribal villages: The Native Villages of Eklutna, Knik, Chickaloon, Seldovia, Ninilchik, Kenaitze, Salamatof, and Tyonek. This project will be a partnership between three entities, with Cook Inlet Tribal Council (CITC) as the lead agency: CITCA's Employment and Training Services Department, Cook Inlet Housing Authority and Alaska Works Partnership. Additionally, six of the eight tribal villages within the Cook Inlet Region of Alaska have agreed to work with the project in order to improve the energy efficiency of their tribally owned buildings and homes. The remaining three villages will be invited to participate in the establishment of an intertribal consortium through this project. Tribal homes and buildings within Anchorage fall under Cook Inlet Region, Inc. (CIRI) tribal authority.

  8. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Research West Virginia University College of Business and Economics P.O. Box 6527, Morgantown, WV 26506 EXPERT OPINION PROVIDED BY Keith Burdette Cabinet Secretary West Virginia Department of Commerce

  9. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

    & Resources Creating Mr. Toad's Wild Ride for the PNW's Energy Efficiency InCreating Mr. Toad's Wild RideNorthwest Power and Conservation Council The Northwest ForecastThe Northwest Forecast ­­ Energy EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman

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

    E-Print Network [OSTI]

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

    2015-03-29T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

    2015-01-01T23:59:59.000Z

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

  12. NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)

    E-Print Network [OSTI]

    and the Ohio State University, and is supported by the National Weather Service. Model output is available 734-741-2235 www.glerl.noaa.gov PREDICTING WHAT'S HAPPENING IN THE NEARSHORE ZONE Most human Lakes coasts. To date, two high resolution grid experimental models have been developed for Lake

  13. artificial weathering environment: Topics by E-print Network

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

    Nation Winter Weather Hazards Winter Weather Safety www.weather.gov SnowIce Blizzards Flooding Cold Temperatures 12;Building a Weather 37 4....

  14. 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. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  15. Mathematical Forecasting Donald I. Good

    E-Print Network [OSTI]

    Boyer, Robert Stephen

    Mathematical Forecasting Donald I. Good Technical Report 47 September 1989 Computational Logic Inc the physical behavior of computer programs can reduce these risks for software engineering in the same way that it does for aerospace and other fields of engineering. Present forecasting capabilities for computer

  16. SpaceWeather RESEARCH ARTICLE

    E-Print Network [OSTI]

    Lockwood, Mike

    ), The Solar Stormwatch CME catalogue: Results from the first space weather citizen science project, Space is properly cited. The Solar Stormwatch CME catalogue: Results from the first space weather citizen science citizen science project, the aim of which is to identify and track coronal mass ejections (CMEs) observed

  17. ATS 680 A6: Applied Numerical Weather Prediction MW, 1:00-1:50 PM, ACRC Room 212B

    E-Print Network [OSTI]

    , Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models, Cambridge University Press in class. Numerical model The primary numerical model that will be u

  18. Using Wikipedia to forecast diseases

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

    said. "In the same way we check the weather each morning, individuals and public health officials can monitor disease incidence and plan for the future based on today's...

  19. Weatherization Formula Grants - American Recovery and Reinvestment...

    Energy Savers [EERE]

    Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) U.S. Department of...

  20. New York: Weatherizing Westbeth Reduces Energy Consumption |...

    Energy Savers [EERE]

    New York: Weatherizing Westbeth Reduces Energy Consumption New York: Weatherizing Westbeth Reduces Energy Consumption August 21, 2013 - 12:00am Addthis The New York State Homes and...

  1. Tacoma Power- Residential Weatherization Rebate Program

    Broader source: Energy.gov [DOE]

    Tacoma Power helps residential customers increase the energy efficiency of homes through the utility's residential weatherization program. Weatherization upgrades to windows are eligible for an...

  2. Survey and Analysis of Weather Data for Building Energy Simulations

    SciTech Connect (OSTI)

    Bhandari, Mahabir S [ORNL; Shrestha, Som S [ORNL; New, Joshua Ryan [ORNL

    2012-01-01T23:59:59.000Z

    In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data plays an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data for 20-35 km2 grid across the globe. Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct, diffuse and horizontal solar radiation; and wind speed are statistically compared. Moreover, we ascertain the relative contributions of each weather variable and its impact on building loads. Annual simulations are calculated for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by 7% while monthly building loads can vary by 40% as a function of the provided location s weather data.

  3. WeatherMaker: Weather file conversion and evaluation

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1999-07-01T23:59:59.000Z

    WeatherMaker is a weather-data utility for use with the ENERGY-10 design-tool computer program. The three main features are: Convert--Weather files can be converted from one format to another. For example, a TMY2 format file can be converted to an ENERGY-10 binary file that can be used in a simulation. This binary file can then be converted to a text format that allows it to be read and/or manipulated in WordPad or Excel. Evaluate--ENERGY-10 weather files can be studied in great detail. There are 8 graphical displays of the data that provide insight into the data, and a summary tables that presents results calculated from the hourly data. Adjust--Hourly temperature data can be adjusted starting with hourly data from a nearby TMY2 site. Dry-bulb and wet-bulb temperatures are adjusted up or down as required to match given monthly statistics. This feature can be used to generate weather files for any of 3,958 sites in the US where such monthly statistics are tabulated. The paper shows a variety of results, explains the methods used, and discusses the rationale for making the adjustments. It is anticipated that WeatherMaker will be released by the time of the ASES Solar 99 conference.

  4. Emissions of crustal material in air quality forecast systems: Use of satellite observations

    E-Print Network [OSTI]

    Menut, Laurent

    Emissions of crustal material in air quality forecast systems: Use of satellite observations) Natural (dust, fires, volcanos) Meteorology: Transport, turbulence Clouds and radiation, precipitations Chemistry-transport model Gas and particles concentrations Use of model outputs: Analysis Direct: model vs

  5. An adaptive neural network approach to one-week ahead load forecasting

    SciTech Connect (OSTI)

    Peng, T.M. (Pacific Gas and Electric Co., San Francisco, CA (United States)); Hubele, N.F.; Karady, G.G. (Arizona State Univ., Tempe, AZ (United States))

    1993-08-01T23:59:59.000Z

    A new neural network approach is applied to one-week ahead load forecasting. This approach uses a linear adaptive neuron or adaptive linear combiner called Adaline.'' An energy spectrum is used to analyze the periodic components in a load sequence. The load sequence mainly consists of three components: base load component, and low and high frequency load components. Each load component has a unique frequency range. Load decomposition is made for the load sequence using digital filters with different passband frequencies. After load decomposition, each load component can be forecasted by an Adaline. Each Adaline has an input sequence, an output sequence, and a desired response-signal sequence. It also has a set of adjustable parameters called the weight vector. In load forecasting, the weight vector is designed to make the output sequence, the forecasted load, follow the actual load sequence; it also has a minimized Least Mean Square error. This approach is useful in forecasting unit scheduling commitments. Mean absolute percentage errors of less than 3.4 percent are derived from five months of utility data, thus demonstrating the high degree of accuracy that can be obtained without dependence on weather forecasts.

  6. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN with primary contributions in the area of decision support for reservoir planning and management Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project

  7. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN: California Energy Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL RESEARCH Martha

  8. Arizona Foundation Expands Weatherization Training Center

    Broader source: Energy.gov [DOE]

    Read about one weatherization training center that's looking forward to an onslaught of new trainees.

  9. Low-Income Weatherization: The Human Dimension

    Broader source: Energy.gov [DOE]

    This presentation focuses on how the human dimension saves energy within low-income weatherization programs.

  10. Weatherization and Intergovernmental Program Success Stories

    Broader source: Energy.gov [DOE]

    Weatherization and Intergovernmental Programs Office (WIPO) success stories, news clips, and press releases.

  11. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01T23:59:59.000Z

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  12. 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

    SciTech Connect (OSTI)

    KETUSKY, EDWARD

    2005-10-31T23:59:59.000Z

    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.

  13. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  14. Short-term planning and forecasting for petroleum. Master's thesis

    SciTech Connect (OSTI)

    Elkins, R.D.

    1988-06-01T23:59:59.000Z

    The Defense Fuel Supply Center (DFSC) has, in recent past, been unable to adequately forecast for short-term petroleum requirements. This has resulted in inaccurate replenishment quantities and required short-notice corrections, which interrupted planned resupply methods. The relationship between the annual CINCLANTFLT DFM budget and sales from the the Norfolk Defense Fuel Support Point (DFSP) is developed and the past sales data from the Norfolk DFSP is used to construct seasonality indices. Finally, the budget/sales relationship is combined with the seasonality indices to provide a new forecasting model. The model is then compared with the current one for FY-88 monthly forecasts. The comparison suggests that the new model can provide accurate, timely requirements data and improve resupply of the Norfolk Defense Fuel Support Point.

  15. Development and Deployment of an Advanced Wind Forecasting Technique

    E-Print Network [OSTI]

    Kemner, Ken

    findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power and applications of power market simulation models around the world. Argonne's software tools are used extensively

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

    E-Print Network [OSTI]

    Genton, Marc G.

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

  17. Ensemble-based air quality forecasts: A multimodel approach applied to ozone

    E-Print Network [OSTI]

    Boyer, Edmond

    Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1 21 September 2006. [1] The potential of ensemble techniques to improve ozone forecasts ozone-monitoring networks. We found that several linear combinations of models have the potential

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

    E-Print Network [OSTI]

    because natural gas fired electric generating plants are on the margin much of the time in Western marketsBiennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts Electricity prices in the Council's Power Plan are forecast using the AURORATM Electricity Market Model of the entire

  19. Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    1 Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines H. In this paper, the MARS technique is applied to forecast the hourly Ontario energy price (HOEP). The MARS models values of the latest pre- dispatch price and demand information, made available by the Ontario

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Physical Sciences, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran, Saudi for forecasting next-day hourly loads have been developed. Evaluated on data for the 6th year, the models give. INTRODUCTION Accurate load forecasting is a key requirement for the planning and economic and secure operation

  1. SIMULATION-BASED WEATHER NORMALIZATION APPROACH TO STUDY THE IMPACT OF WEATHER ON ENERGY USE OF BUILDINGS IN THE U.S.

    SciTech Connect (OSTI)

    Makhmalbaf, Atefe; Srivastava, Viraj; Wang, Na

    2013-08-05T23:59:59.000Z

    Weather normalization is a crucial task in several applications related to building energy conservation such as retrofit measurements and energy rating. This paper documents preliminary results found from an effort to determine a set of weather adjustment coefficients that can be used to smooth out impacts of weather on energy use of buildings in 1020 weather location sites available in the U.S. The U.S. Department of Energy (DOE) commercial reference building models are adopted as hypothetical models with standard operations to deliver consistency in modeling. The correlation between building envelop design, HVAC system design and properties for different building types and the change in heating and cooling energy consumption caused by variations in weather is examined.

  2. The Incremental Benefits of the Nearest Neighbor Forecast of U.S. Energy Commodity Prices 

    E-Print Network [OSTI]

    Kudoyan, Olga

    2012-02-14T23:59:59.000Z

    This thesis compares the simple Autoregressive (AR) model against the k- Nearest Neighbor (k-NN) model to make a point forecast of five energy commodity prices. Those commodities are natural gas, heating oil, gasoline, ethanol, and crude oil...

  3. The Incremental Benefits of the Nearest Neighbor Forecast of U.S. Energy Commodity Prices

    E-Print Network [OSTI]

    Kudoyan, Olga

    2012-02-14T23:59:59.000Z

    This thesis compares the simple Autoregressive (AR) model against the k- Nearest Neighbor (k-NN) model to make a point forecast of five energy commodity prices. Those commodities are natural gas, heating oil, gasoline, ethanol, and crude oil...

  4. Arnold Schwarzenegger PHYSICAL/STATISTICAL AND MODELING

    E-Print Network [OSTI]

    California's electricity and natural gas ratepayers. The PIER Program strives to conduct the most promising gratitude to Dr. J. Dudhia for consulting related to utilization of the Weather Research Forecast (WRF

  5. 2008 Weatherization and Intergovernmental Program (WIP) Market Report

    SciTech Connect (OSTI)

    Doris, E.; Taylor, R.

    2009-07-01T23:59:59.000Z

    The Weatherization and Intergovernmental Program (WIP) integrates local needs and interests in order to promote markets for energy efficiency (EE) and renewable energy (RE). Its activities are integrative across disparate technologies and market boundaries. In order to analyze the historical performance and forward-looking potential of this broad program, this report assesses market developments and outlooks at the following aggregated levels: states, cities and communities, Indian tribes, and low-income residential efficiency. The analytical goals of the report are to: identify market drivers for EE and RE, paying attention to subsidies, taxes, targets and mandates, environmental policy, energy security, and economic development; assess efficacy of existing policies; discuss challenges and barriers; evaluate high-impact measures for overcoming challenges and barriers; and forecast future market trends.

  6. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01T23:59:59.000Z

    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 ...

  7. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  8. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  9. Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations

    E-Print Network [OSTI]

    Kemner, Ken

    forecasting methods and better integration of advanced wind power forecasts into system and plant operations and wind power plants) ­ Review and assess current practices Propose and test new and improved approachesWind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud

  10. A Kalman-filter bias correction of ozone deterministic, ensemble-averaged, and probabilistic forecasts

    SciTech Connect (OSTI)

    Monache, L D; Grell, G A; McKeen, S; Wilczak, J; Pagowski, M O; Peckham, S; Stull, R; McHenry, J; McQueen, J

    2006-03-20T23:59:59.000Z

    Kalman filtering (KF) is used to postprocess numerical-model output to estimate systematic errors in surface ozone forecasts. It is implemented with a recursive algorithm that updates its estimate of future ozone-concentration bias by using past forecasts and observations. KF performance is tested for three types of ozone forecasts: deterministic, ensemble-averaged, and probabilistic forecasts. Eight photochemical models were run for 56 days during summer 2004 over northeastern USA and southern Canada as part of the International Consortium for Atmospheric Research on Transport and Transformation New England Air Quality (AQ) Study. The raw and KF-corrected predictions are compared with ozone measurements from the Aerometric Information Retrieval Now data set, which includes roughly 360 surface stations. The completeness of the data set allowed a thorough sensitivity test of key KF parameters. It is found that the KF improves forecasts of ozone-concentration magnitude and the ability to predict rare events, both for deterministic and ensemble-averaged forecasts. It also improves the ability to predict the daily maximum ozone concentration, and reduces the time lag between the forecast and observed maxima. For this case study, KF considerably improves the predictive skill of probabilistic forecasts of ozone concentration greater than thresholds of 10 to 50 ppbv, but it degrades it for thresholds of 70 to 90 ppbv. Moreover, KF considerably reduces probabilistic forecast bias. The significance of KF postprocessing and ensemble-averaging is that they are both effective for real-time AQ forecasting. KF reduces systematic errors, whereas ensemble-averaging reduces random errors. When combined they produce the best overall forecast.

  11. U.S. Department of Energy Weatherization Assistance Program Homes...

    Energy Savers [EERE]

    U.S. Department of Energy Weatherization Assistance Program Homes Weatherized By State through 06302010 (Calendar Year) U.S. Department of Energy Weatherization Assistance...

  12. Essays on Weather Indexed Insurance and Energy Use in Mexico

    E-Print Network [OSTI]

    Fuchs, Alan

    2011-01-01T23:59:59.000Z

    and O. Mahul, 2007. “Weather Index Insurance for Agricultureand J. Vickery, 2005. “Weather Insurance in Semi-AridBinswanger, 1993. “Wealth, Weather Risk and the Composition

  13. Identification of High Collision Concentration Locations Under Wet Weather Conditions

    E-Print Network [OSTI]

    Hwang, Taesung; Chung, Koohong; Ragland, David; Chan, Chin-Yao

    2008-01-01T23:59:59.000Z

    conducted under wet weather conditions. Observations fromLeahy, M. , and Suggett, J. Weather as a Chronic Hazard forLocations Under Wet Weather Conditions Taesung Hwang,

  14. 1995 shipment review & five year forecast

    SciTech Connect (OSTI)

    Fetherolf, D.J. Jr. [East Penn Manufacturing Co., Inc., Lyon Station, PA (United States)

    1996-01-01T23:59:59.000Z

    This report describes the 1995 battery shipment review and five year forecast for the battery market. Historical data is discussed.

  15. Towards Ultra-High Resolution Models of Climate and Weather To appear in the International Journal of High Performance Computing Applications, 2008.

    E-Print Network [OSTI]

    Oliker, Leonid

    of anthropogenic climate change are highly dependent on cloud-radiation interactions. In this paper, we Keywords Climate model, atmospheric general circulation model, finite volume model, global warming scientists today, with economic ramifications in the trillions of dollars. Effectively performing

  16. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  17. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

  18. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-08-01T23:59:59.000Z

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. This information is then applied to stitch images together into largermore »views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  19. Urban Form Energy Use and Emissions in China: Preliminary Findings and Model Proof of Concept

    E-Print Network [OSTI]

    Aden, Nathaniel

    2011-01-01T23:59:59.000Z

    China's building sector--A review of energy and climate models forecast,China's building sector--A review of energy and climate models forecast,

  20. Winter Weather FAQs | Argonne National Laboratory

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

    Winter Weather FAQs As Argonne prepares for the winter season, employees should be aware of the laboratory's procedures and policies in severe weather events. Below are some of the...

  1. Weatherization Innovation Pilot Program: Program Overview and Philadelphia Project Highlight (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-01-01T23:59:59.000Z

    Case Study with WIPP program overview, information regarding eligibility, and successes from Pennsylvania's Commission on Economic Opportunity (CEO) that demonstrate innovative approaches that maximize the benefit of the program. The Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) recently launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of homes of low-income families. Since 2010, WIPP has helped weatherization service providers as well as new and nontraditional partners leverage non-federal financial resources to supplement federal grants, saving taxpayer money. WIPP complements the Weatherization Assistance program (WAP), which operates nation-wide, in U.S. territories and in three Native American tribes. 16 grantees are implementing weatherization innovation projects using experimental approaches to find new and better ways to weatherize homes. They are using approaches such as: (1) Financial tools - by understanding a diverse range of financing mechanisms, grantees can maximize the impact of the federal grant dollars while providing high-quality work and benefits to eligible low-income clients; (2) Green and healthy homes - in addition to helping families reduce their energy costs, grantees can protect their health and safety. Two WIPP projects (Connecticut and Maryland) will augment standard weatherization services with a comprehensive green and healthy homes approach; (3) New technologies and techniques - following the model of continuous improvement in weatherization, WIPP grantees will continue to use new and better technologies and techniques to improve the quality of work; (4) Residential energy behavior change - Two grantees are rigorously testing home energy monitors (HEMs) that display energy used in kilowatt-hours, allowing residents to monitor and reduce their energy use, and another is examining best-practices for mobile home energy efficiency; (5) Workforce development and volunteers - with a goal of creating a self-sustaining weatherization model that does not require future federal investment, three grantees are adapting business models successful in other sectors of the home performance business to perform weatherization work. Youthbuild is training youth to perform home energy upgrades to eligible clients and Habitat for Humanity is developing a model for how to incorporate volunteer labor in home weatherization. These innovative approaches will improve key weatherization outcomes, such as: Increasing the total number of homes that are weatherized; Reducing the weatherization cost per home; Increasing the energy savings in each weatherized home; Increasing the number of weatherization jobs created and retained; and Reducing greenhouse gas emissions.

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

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30T23:59:59.000Z

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP)--Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute – 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 – 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 – 3 hours.

  3. Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract

    E-Print Network [OSTI]

    Dalang, Robert C.

    Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract] Nicolas Gast EPFL, IC generation. The use of energy storage compensates to some extent these negative effects; it plays a buffer role between demand and production. We revisit a model of real storage proposed by Bejan et al.[1]. We

  4. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

  5. Integrating agricultural pest biocontrol into forecasts of energy biomass production

    E-Print Network [OSTI]

    Gratton, Claudio

    Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T), University of Lome, 114 Rue Agbalepedogan, BP: 20679, Lome, Togo e Center for Agricultural & Energy Policy model of potential biomass supply that incorporates the effect of biological control on crop choice

  6. What constrains spread growth in forecasts ini2alized from

    E-Print Network [OSTI]

    Hamill, Tom

    1 What constrains spread growth in forecasts ini2alized from ensemble Kalman filters? Tom from manner in which ini2al condi2ons are generated, some due to the model (e.g., stochas2c physics as error; part of spread growth from manner in which ini2al condi2ons are generated, some due

  7. Weather-Corrected Performance Ratio

    SciTech Connect (OSTI)

    Dierauf, T.; Growitz, A.; Kurtz, S.; Cruz, J. L. B.; Riley, E.; Hansen, C.

    2013-04-01T23:59:59.000Z

    Photovoltaic (PV) system performance depends on both the quality of the system and the weather. One simple way to communicate the system performance is to use the performance ratio (PR): the ratio of the electricity generated to the electricity that would have been generated if the plant consistently converted sunlight to electricity at the level expected from the DC nameplate rating. The annual system yield for flat-plate PV systems is estimated by the product of the annual insolation in the plane of the array, the nameplate rating of the system, and the PR, which provides an attractive way to estimate expected annual system yield. Unfortunately, the PR is, again, a function of both the PV system efficiency and the weather. If the PR is measured during the winter or during the summer, substantially different values may be obtained, making this metric insufficient to use as the basis for a performance guarantee when precise confidence intervals are required. This technical report defines a way to modify the PR calculation to neutralize biases that may be introduced by variations in the weather, while still reporting a PR that reflects the annual PR at that site given the project design and the project weather file. This resulting weather-corrected PR gives more consistent results throughout the year, enabling its use as a metric for performance guarantees while still retaining the familiarity this metric brings to the industry and the value of its use in predicting actual annual system yield. A testing protocol is also presented to illustrate the use of this new metric with the intent of providing a reference starting point for contractual content.

  8. Calculator simplifies field production forecasting

    SciTech Connect (OSTI)

    Bixler, B.

    1982-05-01T23:59:59.000Z

    A method of forecasting future field production from an assumed average well production schedule and drilling schedule has been programmed for the HP-41C hand-held programmable computer. No longer must tedious row summations be made by hand for staggered well production schedules. Details of the program are provided.

  9. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    modeling of solar steam- generators, solar water heating systems, Heating Ventilating and Air Conditioning (HVAC) systems, wind speed predictions, control in power generation systems,

  10. Pantex receives National Weather Service recognition | National...

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

    receives National Weather Service recognition | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile Preventing...

  11. California climate change, hydrologic response, and flood forecasting

    SciTech Connect (OSTI)

    Miller, Norman L.

    2003-11-11T23:59:59.000Z

    There is strong evidence that the lower atmosphere has been warming at an unprecedented rate during the last 50 years, and it is expected to further increase at least for the next 100 years. Warmer air mass implies a higher capacity to hold water vapor and an increased likelihood of an acceleration of the global water cycle. This acceleration is not validated and considerable new research has gone into understanding aspects of the water cycle (e.g. Miller et al. 2003). Several significant findings on the hydrologic response to climate change can be reported. It is well understood that the observed and expected warming is related to sea level rise. In a recent seminar at Lawrence Berkeley National Laboratory, James Hansen (Director of the Institute for Space Studies, National Aeronautics and Space Administration) stressed that a 1.25 Wm{sup -2} increase in radiative forcing will lead to an increase in the near surface air temperature by 1 C. This small increase in temperature from 2000 levels is enough to cause very significant impacts to coasts. Maury Roos (Chief Hydrologist, California Department of Water Resources) has shown that a 0.3 m rise in sea level shifts the San Francisco Bay 100-year storm surge flood event to a 10-year event. Related coastal protection costs for California based on sea level rise are shown. In addition to rising sea level, snowmelt-related streamflow represents a particular problem in California. Model studies have indicated that there will be approximately a 50% decrease in snow pack by 2100. This potential deficit must be fully recognized and plans need to be put in place well in advance. In addition, the warmer atmosphere can hold more water vapor and result in more intense warm winter-time precipitation events that result in flooding. During anticipated high flow, reservoirs need to release water to maintain their structural integrity. California is at risk of water shortages, floods, and related ecosystem stresses. More research needs to be done to further improve our ability to forecast weather events at longer time scales. Seasonal predictions have been statistical and only recently have studies begun to use ensemble simulations and historical observations to constrain such predictions. Understanding the mechanisms of large-scale atmospheric dynamics and its local impacts remain topics of intensive research. The ability to predict extreme events and provide policy makers with this information, along with climate change and hydrologic response information, will help to guide planning to form a more resilient infrastructure in the future.

  12. Karimar Ledesma Puerto Rico Weather Camp 2009

    E-Print Network [OSTI]

    Gilbes, Fernando

    Karimar Ledesma Puerto Rico Weather Camp 2009 Me llamo Karimar Ledesma Maldonado y soy una "Weather Camper 2009". Mi participación en el Puerto Rico Weather Camp fue lo que finalmente me convenció y motivo Física Teórica en adición a la certificación de meteorología en la Universidad de Puerto Rico en Mayagüez

  13. Internship opportunity with National Weather Service

    E-Print Network [OSTI]

    Internship opportunity with National Weather Service Pacific Regional Headquarters Fall 2008 deadline: August 8, 2008 The Pacific Region of the National Weather Service administers the programs and the general public. The Pacific Regional Headquarters of the National Weather Service, located in downtown

  14. EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -

    E-Print Network [OSTI]

    Boyer, Edmond

    the fluctuating output from wind farms into power plant dispatching and energy trading, wind power predictionsEWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state

  15. Weathering the cold of `94. A review of the January 1994 energy supply disruptions in the Eastern United States

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

    This report examines the causes of and responses to the very low temperatures over a wide region of the Eastern US causing unprecedented sustained demand for energy during the week of January 16--22, 1994. The topics of the report include the vagaries of the weather, the North American power supply structure, a chronology of major events of January, natural gas industry operations during peak demand periods, and recommendations for fuel supply, load forecasting, and energy emergency response exercises.

  16. Watching ColoradoWatching Colorado WeatherWeather

    E-Print Network [OSTI]

    ­ Evapotranspiration #12;CoAgMet Southeast Colorado #12;Hoehne CoAgMet Weather Station #12;Hoehne Daily Temperatures #12;Hoehne Relative Humidity #12;Hoehne Solar Radiation #12;Hoehne Wind Speed #12;Hoehne ET Reference Hoehne ET Reference 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Jan-04 Jan-04 Feb-04 M ar-04 M

  17. Procedures for Filling Short Gaps in Energy Use and Weather Data

    E-Print Network [OSTI]

    Chen, H.; Claridge, D. E.

    2000-01-01T23:59:59.000Z

    data. Single variable regression, polynomial models, Lagrange interpolation, and linear interpolation models are developed, demonstrated, and used to fill 1-6 hour gaps in weather data, heating data and cooling data for commercial buildings...

  18. Explaining the road accident risk: weather effects Ruth Bergel-Hayat1*

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Explaining the road accident risk: weather effects Ruth Bergel-Hayat1* , Mohammed Debbarh1 conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road accidents. Time series analysis models with explanatory variables that measure the weather quantitatively

  19. 200,000 homes weatherized under the Recovery Act

    Broader source: Energy.gov [DOE]

    Today Vice President Biden announced that the Weatherization Assistance Program has weatherized 200,000 homes under the Recovery Act.

  20. Regional dust model performance during SAMUM 2006 K. Haustein,1

    E-Print Network [OSTI]

    established forecast model delivering daily products for North Africa, Europe, Middle East and Asia http

  1. Program evaluation: Weatherization Residential Assistance Partnership (WRAP) Program

    SciTech Connect (OSTI)

    Jacobson, Bonnie B.; Lundien, Barbara; Kaufman, Jeffrey; Kreczko, Adam; Ferrey, Steven; Morgan, Stephen

    1991-12-01T23:59:59.000Z

    The Weatherization Residential Assistance Partnership,'' or WRAP program, is a fuel-blind conservation program designed to assist Northeast Utilities' low-income customers to use energy safely and efficiently. Innovative with respect to its collaborative approach and its focus on utilizing and strengthening the existing low-income weatherization service delivery network, the WRAP program offers an interesting model to other utilities which traditionally have relied on for-profit energy service contractors and highly centralized program implementation structures. This report presents appendices with surveys, participant list, and computers program to examine and predict potential energy savings.

  2. A COMPARATIVE ANALYSIS OF THE INFLUENCE OF WEATHER ON THE

    E-Print Network [OSTI]

    Loon, E. Emiel van

    conditions (Bouten et al. 2003). This model will be used by experts as a decision support tool to reduceA COMPARATIVE ANALYSIS OF THE INFLUENCE OF WEATHER ON THE FLIGHT ALTITUDES OF BIRDS Meteorological/Bash/stats.html). The International Civil Aviation Organization (ICAO) has long acknowledged the risk of bird hazards to civil

  3. NCAR WRF-based data assimilation and forecasting systems for wind energy applications power

    E-Print Network [OSTI]

    Kim, Guebuem

    NCAR WRF-based data assimilation and forecasting systems for wind energy applications power Yuewei of these modeling technologies w.r.t. wind energy applications. Then I'll discuss wind farm

  4. Freeway Short-Term Traffic Flow Forecasting by Considering Traffic Volatility Dynamics and Missing Data Situations

    E-Print Network [OSTI]

    Zhang, Yanru

    2012-10-19T23:59:59.000Z

    , assuming constant variance when perform forecasting. This method does not consider the volatility nature of traffic flow data. This paper demonstrated that the variance part of traffic flow data is not constant, and dependency exists. A volatility model...

  5. Application of Fast Marching Methods for Rapid Reservoir Forecast and Uncertainty Quantification

    E-Print Network [OSTI]

    Olalotiti-Lawal, Feyisayo

    2013-05-17T23:59:59.000Z

    Rapid economic evaluations of investment alternatives in the oil and gas industry are typically contingent on fast and credible evaluations of reservoir models to make future forecasts. It is often important to also quantify inherent risks...

  6. Forecasting the Standard & Poor's 500 stock index futures price: interest rates, dividend yields, and cointegration

    E-Print Network [OSTI]

    Fritsch, Roger Erwin

    1997-01-01T23:59:59.000Z

    forward price series is constructed using interest rate and dividend yield data. Out-of-sample forecasts from error correction models are compared to those from vector autoregressions (VAR) fit to levels and VARs fit to first differences. This comparison...

  7. Joint models for concept-to-text generation 

    E-Print Network [OSTI]

    Konstas, Ioannis

    2014-06-27T23:59:59.000Z

    Much of the data found on the world wide web is in numeric, tabular, or other nontextual format (e.g., weather forecast tables, stock market charts, live sensor feeds), and thus inaccessible to non-experts or laypersons. ...

  8. Hybrid methodology for hourly global radiation forecasting in Mediterranean area

    E-Print Network [OSTI]

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

    2012-01-01T23:59:59.000Z

    The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, ARMA techniques are more dedicated to sunny days without cloud occurrences. Thus, three hybrids models are suggested: the first proposes simply to use ARMA for 6 months in spring and summer and to use an optimized ANN for the other part of the year; the second model is equivalent to the first but with a seasonal learning; the last model depends on the error occurred the previous hour. These models were used to forecast the hourly global radiation for five places in Mediterranean area. The forecasting performance was compared among several models: the 3 above mentioned models, the best ANN and ARMA for each location. In t...

  9. Single-Pass Flow-Through Test Elucidation of Weathering Behavior and Evaluation of Contaminant Release Models for Hanford Tank Residual Radioactive Waste

    SciTech Connect (OSTI)

    Cantrell, Kirk J.; Carroll, Kenneth C.; Buck, Edgar C.; Neiner, Doinita; Geiszler, Keith N.

    2013-01-01T23:59:59.000Z

    Contaminant release models are required to evaluate and predict long-term environmental impacts of even residual amounts of high-level radioactive waste after cleanup and closure of radioactively contaminated sites such as the DOE’s Hanford Site. More realistic and representative models have been developed for release of uranium, technetium, and chromium from Hanford Site tanks C-202, C-203, and C-103 residual wastes using data collected with a single-pass flow-through test (SPFT) method. These revised models indicate that contaminant release concentrations from these residual wastes will be considerably lower than previous estimates based on batch experiments. For uranium, a thermodynamic solubility model provides an effective description of uranium release, which can account for differences in pore fluid chemistry contacting the waste that could occur through time and as a result of different closure scenarios. Under certain circumstances in the SPFT experiments various calcium rich precipitates (calcium phosphates and calcite) form on the surfaces of the waste particles, inhibiting dissolution of the underlying uranium phases in the waste. This behavior was not observed in previous batch experiments. For both technetium and chromium, empirical release models were developed. In the case of technetium, release from all three wastes was modeled using an equilibrium Kd model. For chromium release, a constant concentration model was applied for all three wastes.

  10. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecasting NREL researchers use

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

    SciTech Connect (OSTI)

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

    2008-02-29T23:59:59.000Z

    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.

  12. Regional Climate Model Projections for the State of Washington

    SciTech Connect (OSTI)

    Salathe, E.; Leung, Lai-Yung R.; Qian, Yun; Zhang, Yongxin

    2010-05-05T23:59:59.000Z

    Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional heterogeneity of the climate of the State of Washington. If future large-scale weather patterns interact differently with the local terrain and coastlines than current weather patterns, local changes in temperature and precipitation could be quite different from the coarse-scale changes projected by global models. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year climate simulations using the Weather and Research Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970-1999) to the mid 21st century (2030-2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.

  13. Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

    E-Print Network [OSTI]

    Randall, David A.

    , Paris, France e Canadian Centre for Climate Modelling and Analysis, Victoria, British Columbia, Canada f, Melbourne, Victoria, Australia i Monash University, Melbourne, Victoria, Australia j Department of Earth for the season June­July­August

  14. Ensemble bayesian model averaging using markov chain Monte Carlo sampling

    SciTech Connect (OSTI)

    Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL

    2008-01-01T23:59:59.000Z

    Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.

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

    SciTech Connect (OSTI)

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

    2005-02-09T23:59:59.000Z

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

  16. Pressure Normalization of Production Rates Improves Forecasting Results

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07T23:59:59.000Z

    reservoir conditions, psi 2/cp ?wf Pseudopressure at flowing conditions, psi 2/cp ? Characteristic time parameter for SEPD model, D ?g Gas viscosity, cp ?o Oil viscosity, cp Acronyms BDF Boundary-Dominated Flow DCA Decline Curve Analysis EUR..., as the advanced analytical and numerical models depend on copious inputs, there is a high probability that different combinations of those parameters could generate equivalent and acceptable history matches, but different production forecasts and EUR...

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

    SciTech Connect (OSTI)

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

    2013-11-01T23:59:59.000Z

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

  18. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2005-10-31T23:59:59.000Z

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  19. Navy Mobility Fuels Forecasting System. Phase I report

    SciTech Connect (OSTI)

    Davis, R.M.; Hadder, G.R.; Singh, S.P.N.; Whittle, C.

    1985-07-01T23:59:59.000Z

    The Department of the Navy (DON) requires an improved capability to forecast mobility fuel availability and quality. The changing patterns in fuel availability and quality are important in planning the Navy's Mobility Fuels R and D Program. These changes come about primarily because of the decline in the quality of crude oil entering world markets as well as the shifts in refinery capabilities domestically and worldwide. The DON requested ORNL's assistance in assembling and testing a methodology for forecasting mobility fuel trends. ORNL reviewed and analyzed domestic and world oil reserve estimates, production and price trends, and recent refinery trends. Three publicly available models developed by the Department of Energy were selected as the basis of the Navy Mobility Fuels Forecasting System. The system was used to analyze the availability and quality of jet fuel (JP-5) that could be produced on the West Coast of the United States under an illustrative business-as-usual and a world oil disruption scenario in 1990. Various strategies were investigated for replacing the lost JP-5 production. This exercise, which was strictly a test case for the forecasting system, suggested that full recovery of lost fuel production could be achieved by relaxing the smoke point specifications or by increasing the refiners' gate price for the jet fuel. A more complete analysis of military mobility fuel trends is currently under way.

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  2. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01T23:59:59.000Z

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford`s experience within the last six years. Hanford`s forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford`s annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford`s forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data.

  3. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

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

    1981-07-01T23:59:59.000Z

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

  4. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

    the single individual forecasts. Several studies have shown that combining forecasts can be a useful hedge against structural breaks, and forecast combinations are often more stable than single forecasts (e.g. Hendry and Clements, 2004, Stock and Watson, 2004... in expectations. Hence, we have the following. Corollary 4 Suppose maxt?T kl (Yt, hwt,Xti)kr ? A taking expectation on the left hand side, adding 2A ? T and setting ? = 0 in mT (?), i.e. TX t=1 E [lt (wt)? lt (ut...

  5. The Value of Wind Power Forecasting

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

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

  6. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

    2014-07-09T23:59:59.000Z

    Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

  7. U-M Construction Forecast December 15, 2011 U-M Construction Forecast

    E-Print Network [OSTI]

    Kamat, Vineet R.

    U-M Construction Forecast December 15, 2011 U-M Construction Forecast Spring ­ Fall 2012 As of December 15, 2011 Prepared by AEC Preliminary & Advisory #12;U-M Construction Forecast December 15, 2011 Overview · Campus by campus · Snapshot in time ­ Not all projects · Construction coordination efforts

  8. Five case studies of multifamily weatherization programs

    SciTech Connect (OSTI)

    Kinney, L; Wilson, T.; Lewis, G. [Synertech Systems Corp. (United States)] [Synertech Systems Corp. (United States); MacDonald, M. [Oak Ridge National Lab., TN (United States)] [Oak Ridge National Lab., TN (United States)

    1997-12-31T23:59:59.000Z

    The multifamily case studies that are the subject of this report were conducted to provide a better understanding of the approach taken by program operators in weatherizing large buildings. Because of significant variations in building construction and energy systems across the country, five states were selected based on their high level of multifamily weatherization. This report summarizes findings from case studies conducted by multifamily weatherization operations in five cities. The case studies were conducted between January and November 1994. Each of the case studies involved extensive interviews with the staff of weatherization subgrantees conducting multifamily weatherization, the inspection of 4 to 12 buildings weatherized between 1991 and 1993, and the analysis of savings and costs. The case studies focused on innovative techniques which appear to work well.

  9. Paper presented at EWEC 2008, Brussels, Belgium (31 March-03 April) Uncertainty Estimation of Wind Power Forecasts

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -Antipolis, France Abstract--Short-term wind power forecasting tools providing "single-valued" (spot) predictions associated to the future wind power produc- tion for performing more efficiently functions such as reserves and modelling architec- tures for probabilistic wind power forecasting. Then, a comparison is carried out

  10. EnergyPlus Weather Data for use with EnergyPlus Simulation Software

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

    EnergyPlus is simulation software from DOE's Office of Energy Efficiency and Renewable Energy (EE) that models heating, cooling, lighting, ventilating, and other energy flows as well as water in buildings. Because the environment surrounding any building is an important component of the energy choices that go into the building's design and the energy performance of that building thereafter, weather data from all parts of the world are made available through the EnergyPlus web site. The data are collected from more than 2100 locations — 1042 locations in the USA, 71 locations in Canada, and more than 1000 locations in 100 other countries throughout the world. The weather data are arranged by World Meteorological Organization region and Country. In addition to using the weather data via the utility installed automatically with EnergyPlus software, users may view and download EnergyPlus weather data directly using a weather data layer for Google Earth.

  11. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

  12. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  13. Aging and weathering of cool roofing membranes

    SciTech Connect (OSTI)

    Akbari, Hashem; Berhe, Asmeret A.; Levinson, Ronnen; Graveline,Stanley; Foley, Kevin; Delgado, Ana H.; Paroli, Ralph M.

    2005-08-23T23:59:59.000Z

    Aging and weathering can reduce the solar reflectance of cool roofing materials. This paper summarizes laboratory measurements of the solar spectral reflectance of unweathered, weathered, and cleaned samples collected from single-ply roofing membranes at various sites across the United States. Fifteen samples were examined in each of the following six conditions: unweathered; weathered; weathered and brushed; weathered, brushed and then rinsed with water; weathered, brushed, rinsed with water, and then washed with soap and water; and weathered, brushed, rinsed with water, washed with soap and water, and then washed with an algaecide. Another 25 samples from 25 roofs across the United States and Canada were measured in their unweathered state, weathered, and weathered and wiped. We document reduction in reflectivity resulted from various soiling mechanisms and provide data on the effectiveness of various cleaning approaches. Results indicate that although the majority of samples after being washed with detergent could be brought to within 90% of their unweathered reflectivity, in some instances an algaecide was required to restore this level of reflectivity.

  14. Idaho Falls Power- Residential Weatherization Loan Program

    Broader source: Energy.gov [DOE]

    Residential customers with permanently installed electric heat who receive service from the City of Idaho Falls, are eligible for 0% weatherization loans. City Energy Service will conduct an...

  15. The Weatherization Training program at Pennsylvania College ...

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

    alone. Speakers Jeff Melville, Jack Wilson, John Manz, Kirk Gannett, Franzenia Smith, Duration 4:07 Topic Home Weatherization Education & Training Credit Energy Department...

  16. Training Program Graduates Weatherization-Ready Workers

    Broader source: Energy.gov [DOE]

    Graduates of Human Capital Development Corporation's (HCDC) First Choice Program aren't just trained in areas of construction, they also can tackle home weatherization services.

  17. Weatherization Assistance Program: Spurring Innovation, Increasing...

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

    The SWS provide a common yardstick for consumers, financiers, and policy makers to measure the performance of their service providers. Training the Weatherization Workforce...

  18. Maine Company Growing with Weatherization Work

    Broader source: Energy.gov [DOE]

    Maine's BIOSAFE Environmental Services expands into weatherization, assisting low-income families with their services and creating jobs as business grows.

  19. Chelan County PUD- Residential Weatherization Rebate Program

    Broader source: Energy.gov [DOE]

    Chelan County PUD offers cash rebates to residential customers who make energy efficient weatherization improvements to eligible homes. Eligible measures include efficient windows doors as well as...

  20. Adjoint Sensitivity Analysis for Numerical Weather Prediction

    E-Print Network [OSTI]

    Alexandru Cioaca

    2011-09-02T23:59:59.000Z

    Sep 2, 2011 ... Adjoint Sensitivity Analysis for Numerical Weather Prediction: Applications to Power Grid Optimization. Alexandru Cioaca(alexgc ***at*** vt.edu)

  1. Weatherization Assistance Available at Florida Pie Shop

    Office of Energy Efficiency and Renewable Energy (EERE)

    Pie in the Sky, a seemingly simple store that offers customers fresh-baked desserts, is providing a second treat: weatherization.

  2. An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment

    E-Print Network [OSTI]

    Xue, Ming

    J. Melick1,9 , Christopher Siewert1,9 , Ryan A. Sobash3 , Patrick T. Marsh2,3 , Andrew R. Dean1. Bruce Entwistle7 , Tara L. Jensen8 , and James Correia, Jr.1,9 1 NOAA/Storm Prediction Center, Norman, OK 2 NOAA/National Severe Storms Laboratory, Norman, OK 3 University of Oklahoma School

  3. TechNoteswww.ll.mit.edu July 2014 Weather forecasts are critical to effectively

    E-Print Network [OSTI]

    Reif, Rafael

    contains the radiometer installed at the top and the CubeSat bus whose solar panels open out once in orbit a host satellite, it will fly with its solar panels opened out like petals of a flower. These panels

  4. Finding an Appropriate Profiler for the Weather Research and Forecasting Code

    E-Print Network [OSTI]

    Sadjadi, S. Masoud

    , and David Villegas Undergraduate REU Students: Alex Orta, Michael McFail, Xabriel J. Collazo-Mojica, Javier Figueroa School of Computing and Information Sciences (SCIS) Florida International University (FIU) 11200

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

    E-Print Network [OSTI]

    Shao, Hongbin

    1994-01-01T23:59:59.000Z

    models of primary, initial waterflood and infill drilling are developed for the San Andres and Clearfork reservoirs in Central Basin Platform and the Northern Shelf, west Texas. The geological parameters and well spacing are considered major factors...

  6. A New Method for History Matching and Forecasting Shale Gas/Oil Reservoir Production Performance with Dual and Triple Porosity Models

    E-Print Network [OSTI]

    Samandarli, Orkhan

    2012-10-19T23:59:59.000Z

    Different methods have been proposed for history matching production of shale gas/oil wells which are drilled horizontally and usually hydraulically fractured with multiple stages. These methods are simulation, analytical models, and empirical...

  7. On the Feasibility of Precisely Measuring the Properties of a Precipitating Cloud with a Weather Radar

    E-Print Network [OSTI]

    Runnels, R.C.

    In this paper the results of an investigation are presented that are concerned with the feasibility of employing a weather radar to make precise measurements of the properties of a precipitating cloud. A schematic cloud is proposed as a model...

  8. 1992 five year battery forecast

    SciTech Connect (OSTI)

    Amistadi, D.

    1992-12-01T23:59:59.000Z

    Five-year trends for automotive and industrial batteries are projected. Topic covered include: SLI shipments; lead consumption; automotive batteries (5-year annual growth rates); industrial batteries (standby power and motive power); estimated average battery life by area/country for 1989; US motor vehicle registrations; replacement battery shipments; potential lead consumption in electric vehicles; BCI recycling rates for lead-acid batteries; US average car/light truck battery life; channels of distribution; replacement battery inventory end July; 2nd US battery shipment forecast.

  9. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGermanFife Energy Park atFisiaFlorida:Forecast Energy Jump to:

  10. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29T23:59:59.000Z

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

  11. Exploration of Weather Impacts on Freeway Traffic Operations and Safety Using High-Resolution Weather Data

    E-Print Network [OSTI]

    Bertini, Robert L.

    Exploration of Weather Impacts on Freeway Traffic Operations and Safety Using High-Resolution Weather Data by Chengyu Dai A thesis submitted in partial fulfillment of the requirements for the degree Moradkhani Kristin Tufte Portland State University ©2011 #12;i ABSTRACT Adverse weather is considered as one

  12. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01T23:59:59.000Z

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  13. The Wind Forecast Improvement Project (WFIP): A Public/Private...

    Office of Environmental Management (EM)

    The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

  14. Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo

    E-Print Network [OSTI]

    Heinemann, Detlev

    Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo Oldenburg University have been presented more than twenty years ago (Jensenius, 1981), when daily solar radiation forecasts

  15. Lesson 33: Weather [hali ya hewa; hali ya anga

    E-Print Network [OSTI]

    Lesson 33: Weather Weather [hali ya hewa; hali ya anga] A). Weather baridi [cold] joto [warm. 7). Sayari inayozunguka Dunia huitwa mwezi. #12;D. Kuna [There is] Swahili expresses weather is not raining.)] Zingatia [Note] kuna hali ya anga / hali ya hewa namna gani [There is...] [weather conditions

  16. HMS Inclement Weather Policy FACULTY, STAFF AND STUDENTS

    E-Print Network [OSTI]

    Goodrich, Lisa V.

    HMS Inclement Weather Policy FACULTY, STAFF AND STUDENTS During a weather emergency or other inclement weather is that, short of a declared state of emergency, the School remains open. The teaching and research activities of HMS continue despite inclement weather. In such weather emergencies, however

  17. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    analysis. Better forecast performance for macroeconomic variables will lead to Paris School of Economics the speed of computers that can develop search algorithms from appropriate selection criteria, Devroye. 1 Introduction Forecasting macroeconomic variables such as GDP and inflation play an important role

  18. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

    APPROACH FOR EVALUATING ECONOMIC FORECASTS Tara M. Sinclair , H.O. Stekler, and Warren Carnow Department of Economics The George Washington University Monroe Hall #340 2115 G Street NW Washington, DC 20052 JEL Codes, Mahalanobis Distance Abstract This paper presents a new approach to evaluating multiple economic forecasts

  19. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

    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 and Economics at California State University, Fullerton, the largest accredited business school in California

  20. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  1. A Unit Commitment Model with Demand Response for the Integration of Renewable Energies

    E-Print Network [OSTI]

    Ikeda, Yuichi; Kataoka, Kazuto; Ogimoto, Kazuhiko

    2011-01-01T23:59:59.000Z

    The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast of output its error for renewable energies and the demand response of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms and analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increases with the forecast error. The effect of a sudden decrease in wind power is also analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total opera...

  2. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01T23:59:59.000Z

    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.

  3. Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method 

    E-Print Network [OSTI]

    Joshi, Krunal Jaykant

    2012-10-19T23:59:59.000Z

    variation of the Duong model proves to be a robust model for most of the well cases and flow regimes. The modified Duong has been shown to work best compared to other deterministic models in most cases. For grouped datasets the SPED & Duong models forecast...

  4. Alaska Native Weatherization Training and Jobs Program First Steps Toward Tribal Weatherization – Human Capacity Development

    SciTech Connect (OSTI)

    Wiita, Joanne

    2013-07-30T23:59:59.000Z

    The Alaska Native Weatherization Training and Jobs Project expanded weatherization services for tribal members’ homes in southeast Alaska while providing weatherization training and on the job training (OJT) for tribal citizens that lead to jobs and most probably careers in weatherization-related occupations. The program resulted in; (a) 80 Alaska Native citizens provided with skills training in five weatherization training units that were delivered in cooperation with University of Alaska Southeast, in accordance with the U.S. Department of Energy Core Competencies for Weatherization Training that prepared participants for employment in three weatherizationrelated occupations: Installer, Crew Chief, and Auditor; (b) 25 paid OJT training opportunities for trainees who successfully completed the training course; and (c) employed trained personnel that have begun to rehab on over 1,000 housing units for weatherization.

  5. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    Kondrashov, D.; Shen, J.; Berk, R.; D., F

    2006-01-01T23:59:59.000Z

    R, D’Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616–1627. Kimoto M,D, Ide K, Ghil M (2004) Weather regimes and preferred

  6. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    D. Kondrashov; J. Shen; R. Berk; F. D

    2011-01-01T23:59:59.000Z

    R, D’Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616–1627. Kimoto M,D, Ide K, Ghil M (2004) Weather regimes and preferred

  7. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    Kondrashov, Dmitri; Shen, Jie; Berk, Richard; D'Andrea, F.; Ghil, M.

    2006-01-01T23:59:59.000Z

    R, D'Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616-1627. Kimoto M ,D, Ide K , Ghil M (2004) Weather regimes and preferred

  8. Space Weather Effects on Imaging Detectors in Low Earth Orbit

    E-Print Network [OSTI]

    Johnson, Adam Alan

    2010-10-12T23:59:59.000Z

    of imaging sensors, the availability and access to proton and radia- tion sources, and the need to perform modeling and extrapolate the results from the experiments conducted on earth to the space weather environment. Another means of analysis is statistical... to the CCD plane, then the proton can cross multiple pixels, creating electron hole-pairs in each one, as illustrated in Figure (2). As with electrons created by photons, the electrons created by protons will be collected if inside the active region...

  9. Appendix K - GPRA06 Weatherization and Intergovernmental Program...

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

    Appendix K - GPRA06 Weatherization and Intergovernmental Program (WIP) Documentation Appendix K - GPRA06 Weatherization and Intergovernmental Program (WIP) Documentation State...

  10. DOE Announces $29 Million in Recovery Act Awards for Weatherization...

    Office of Environmental Management (EM)

    expand weatherization training centers across the country. These projects will provide green job training for local workers in energy efficiency retrofitting and weatherization...

  11. Test Procedure for UV Weathering Resistance of Backsheet | Department...

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

    Test Procedure for UV Weathering Resistance of Backsheet Test Procedure for UV Weathering Resistance of Backsheet Presented at the PV Module Reliability Workshop, February 26 - 27...

  12. WEATHERIZATION PROGRAM NOTICE 10-10: REPROGRAMMING TRAINING AND...

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

    WEATHERIZATION PROGRAM NOTICE 10-10: REPROGRAMMING TRAINING AND TECHNICAL ASSISTANCE FUNDS TO PROGRAM OPERATIONS WEATHERIZATION PROGRAM NOTICE 10-10: REPROGRAMMING TRAINING AND...

  13. arctic weather conditions: Topics by E-print Network

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

    condition for a particular vessel. Keywords Weather Routing, Degraded Condition, Crisis Manage- ment Advice, Shortest Path Berlin,Technische Universitt 18 Weather...

  14. Presentation at the Weatherization Program Deep Dive Briefing...

    Energy Savers [EERE]

    4, 2009 U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Weatherization Assistance Program presentation at Weatherization Deep Dive...

  15. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    and water pumping sectors. Mark Ciminelli forecasted energy for transportation, communication and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  18. Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak

    E-Print Network [OSTI]

    Islam, M. Saif

    Page 1 Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey

  19. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

  20. Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

    Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

  1. Observations and simulations improve space weather models

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)IntegratedSpeeding access to scienceScientificObservation of a

  2. Observations and simulations improve space weather models

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for RenewableSpeeding accessSpeeding access(SC)Gas and OilPhaseObservation of

  3. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

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

    1993-08-01T23:59:59.000Z

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

  4. A Methodology of Quantifying Precipitation Exposure for Wet-Weather Collisions and Evaluating Effectiveness of Open-Grade Asphalt Concrete as a Countermeasure

    E-Print Network [OSTI]

    Chan, Ching-Yao; Jin, Eui-Jae; Oh, Soon Mi; Ragland, David R

    2010-01-01T23:59:59.000Z

    for multilane roads. Accident Analysis and Prevention. Vol.in rainy weather. Accident Analysis and Prevention. Vol. 20,time-series model. Accident Analysis and Prevention. Vol.

  5. ReseaRch at the University of Maryland Climate Modeling and Prediction

    E-Print Network [OSTI]

    Hill, Wendell T.

    for farmers and agricultural policy makers Antonio Busalacchi studies tropical ocean circulation to refine, and drought. Eugenia Kalnay uses chaos theory to improve weather forecasting. She also documents land to predict the complex atmospheric effects of polar ice loss. Improving Rainfall Forecasts for Farmers Rapid

  6. Weatherization Works: Final Report of the National Weatherization Evaluation

    SciTech Connect (OSTI)

    Brown, M.A.

    2001-02-01T23:59:59.000Z

    In 1990, the US Department of Energy (DOE) sponsored a comprehensive evaluation of its Weatherization Assistance Program, the nation's largest residential energy conservation program. Oak Ridge National Laboratory (ORNL) managed the five-part study. This document summarizes the findings of the evaluation. Its conclusions are based mainly on data from the 1989 program year. The evaluation concludes that the Program meets the objectives of its enabling legislation and fulfills its mission statement. Specifically, it saves energy, lowers fuel bills, and improves the health and safety of dwellings occupied by low-income people. In addition, the Program achieves its mission in a cost-effective manner based on each of three perspectives employed by the evaluators. Finally, the evaluation estimates that the investments made in 1989 will, over a 20-year lifetime, save the equivalent of 12 million barrels of oil, roughly the amount of oil added to the Strategic Petroleum Reserve in each of the past several years. The Program's mission is to reduce the heating and cooling costs for low-income families--particularly the elderly, persons with disabilities, and children by improving the energy efficiency of their homes and ensuring their health and safety. Substantial progress has been made, but the job is far from over. The Department of Health and Human Services (HHS) reports that the average low-income family spends 12 percent of its income on residential energy, compared to only 3% for the average-income family. Homes where low-income families live also have a greater need for energy efficiency improvements, but less money to pay for them.

  7. A Framework of Incorporating Spatio-temporal Forecast in Look-ahead Grid Dispatch with Photovoltaic Generation

    E-Print Network [OSTI]

    Yang, Chen

    2013-05-02T23:59:59.000Z

    , and is shown to have improved performance compared with conventional persistent model. The tradeoff between communication cost and improved forecast quality is studied using realistic data sets collected from California and Colorado. n IEEE 14 bus system test...

  8. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Cynthia Rogers generation, conservation, energy efficiency, climate zone, investorowned, public, utilities, additional

  9. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  10. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

  11. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  12. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

    This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a ...

  13. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  14. Human-Centered Systems Analysis of Aircraft Separation from Adverse Weather

    E-Print Network [OSTI]

    Vigeant-Langlois, Laurence

    Adverse weather significantly impacts the safety and efficiency of flight operations. Weather information

  15. Clark Public Utilities- Residential Weatherization Loan Program

    Broader source: Energy.gov [DOE]

    Loans of up to $15,000 at a 5.25% interest are available through Clark Public Utilities' Weatherization Loan Program. The loans can pay for the average local cost of eligible measures, based on...

  16. Cowlitz County PUD- Residential Weatherization Plus Program

    Broader source: Energy.gov [DOE]

    Cowlitz County PUD offers an incentive to residential customers who weatherize their homes. Eligible residences can be either site-built or manufactured homes, but must have a permanently installed...

  17. Calibrating DOE-2 to weather and non-weather-dependent loads for a commercial building

    E-Print Network [OSTI]

    Bronson, John Douglas

    1992-01-01T23:59:59.000Z

    CALIBRATING DOE-2 TO WEATHER AND NON-WEATHER-DEPENDENT LOADS FOR A COMMERCIAL BUILDING A Thesis by JOHN DOUGLAS BRONSON Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1992 Major Subject: Mechanical Engineering CALIBRATING DOE-2 TO WEATHER AND NON-WEATHER-DEPENDENT LOADS FOR A COMMERCIAL BUILDING A Thesis by JOHN DOUGLAS BRONSON Approved as to style and content by: M D~c Dennis...

  18. Calibrating DOE-2 to weather and non-weather-dependent loads for a commercial building 

    E-Print Network [OSTI]

    Bronson, John Douglas

    1992-01-01T23:59:59.000Z

    CALIBRATING DOE-2 TO WEATHER AND NON-WEATHER-DEPENDENT LOADS FOR A COMMERCIAL BUILDING A Thesis by JOHN DOUGLAS BRONSON Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1992 Major Subject: Mechanical Engineering CALIBRATING DOE-2 TO WEATHER AND NON-WEATHER-DEPENDENT LOADS FOR A COMMERCIAL BUILDING A Thesis by JOHN DOUGLAS BRONSON Approved as to style and content by: M D~c Dennis...

  19. Faces of the Recovery Act: National Weatherization Conference

    ScienceCinema (OSTI)

    None

    2010-09-01T23:59:59.000Z

    Personal stories from the 2009 National Weatherization Training Conference in Indianapolis, Indiana.

  20. Weatherization Plus — Opportunities for the 21st Century

    Broader source: Energy.gov [DOE]

    Millennium Committee Strategy Report for the DOE Weatherization Assistance Program; 15 pp.; April 1999.

  1. Faces of the Recovery Act: National Weatherization Conference

    Broader source: Energy.gov [DOE]

    Personal stories from the 2009 National Weatherization Training Conference in Indianapolis, Indiana.

  2. Faces of the Recovery Act: National Weatherization Conference

    ScienceCinema (OSTI)

    Chu, Sammy; Campanella, Leslie; Sewell, Travis; Gill, Tony; Fransen, Richard; Leuty, Steve; Qualls, Xavier; Bergeron, T.J.; Stewet, Zachary

    2013-05-29T23:59:59.000Z

    Personal stories from the 2009 National Weatherization Training Conference in Indianapolis, Indiana.

  3. Forecast calls for better models | EMSL

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

    Examining the core components of Arctic clouds to clear up their influence on climate Scanning transmission X-ray microscopy images of individual residues from Alaskan clouds....

  4. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

  5. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Gas Price Forecast W ith natural gas prices significantlyof AEO 2006 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  6. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2008 Natural Gas Price Forecast to NYMEX Futures

  7. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the base-case natural gas price forecast, but to alsogas price forecasts with contemporaneous natural gas pricesof AEO 2010 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Natural Gas Price Forecast Although natural gas prices areof AEO 2007 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  9. Essays on macroeconomics and forecasting

    E-Print Network [OSTI]

    Liu, Dandan

    2006-10-30T23:59:59.000Z

    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...

  10. Application of Improved Radiation Modeling to General Circulation Models

    SciTech Connect (OSTI)

    Michael J Iacono

    2011-04-07T23:59:59.000Z

    This research has accomplished its primary objectives of developing accurate and efficient radiation codes, validating them with measurements and higher resolution models, and providing these advancements to the global modeling community to enhance the treatment of cloud and radiative processes in weather and climate prediction models. A critical component of this research has been the development of the longwave and shortwave broadband radiative transfer code for general circulation model (GCM) applications, RRTMG, which is based on the single-column reference code, RRTM, also developed at AER. RRTMG is a rigorously tested radiation model that retains a considerable level of accuracy relative to higher resolution models and measurements despite the performance enhancements that have made it possible to apply this radiation code successfully to global dynamical models. This model includes the radiative effects of all significant atmospheric gases, and it treats the absorption and scattering from liquid and ice clouds and aerosols. RRTMG also includes a statistical technique for representing small-scale cloud variability, such as cloud fraction and the vertical overlap of clouds, which has been shown to improve cloud radiative forcing in global models. This development approach has provided a direct link from observations to the enhanced radiative transfer provided by RRTMG for application to GCMs. Recent comparison of existing climate model radiation codes with high resolution models has documented the improved radiative forcing capability provided by RRTMG, especially at the surface, relative to other GCM radiation models. Due to its high accuracy, its connection to observations, and its computational efficiency, RRTMG has been implemented operationally in many national and international dynamical models to provide validated radiative transfer for improving weather forecasts and enhancing the prediction of global climate change.

  11. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01T23:59:59.000Z

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  12. Adverse Weather Conditions If adverse weather conditions occur which affects tube, bus or rail services, Heads of Department/

    E-Print Network [OSTI]

    Adverse Weather Conditions If adverse weather conditions occur which affects tube, bus or rail to present him/herself for work. Where, due to the adverse weather conditions, public transport is affected as a result of the adverse weather conditions (for example a child's school is closed), they should consult

  13. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01T23:59:59.000Z

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

  14. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

    SciTech Connect (OSTI)

    Cassano, John [Principal Investigator

    2013-06-30T23:59:59.000Z

    The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

  15. Coupled Mesoscale-Large-Eddy Modeling of Realistic Stable Boundary Layer Turbulence

    E-Print Network [OSTI]

    Wang, Yao; Manuel, Lance

    2013-01-01T23:59:59.000Z

    Site-specific flow and turbulence information are needed for various practical applications, ranging from aerodynamic/aeroelastic modeling for wind turbine design to optical diffraction calculations. Even though highly desirable, collecting on-site meteorological measurements can be an expensive, time-consuming, and sometimes a challenging task. In this work, we propose a coupled mesoscale-large-eddy modeling framework to synthetically generate site-specific flow and turbulence data. The workhorses behind our framework are a state-of-the-art, open-source atmospheric model called the Weather Research and Forecasting (WRF) model and a tuning-free large-eddy simulation (LES) model. Using this coupled framework, we simulate a nighttime stable boundary layer (SBL) case from the well-known CASES-99 field campaign. One of the unique aspects of this work is the usage of a diverse range of observations for characterization and validation. The coupled models reproduce certain characteristics of observed low-level jets....

  16. Integration of space weather into space situational awareness

    SciTech Connect (OSTI)

    Reeves, Geoffrey D [Los Alamos National Laboratory

    2010-11-09T23:59:59.000Z

    Rapid assessment of space weather effects on satellites is a critical step in anomaly resolution and satellite threat assessment. That step, however, is often hindered by a number of factors including timely collection and delivery of space weather data and the inherent com plexity of space weather information. As part of a larger, integrated space situational awareness program, Los Alamos National Laboratory has developed prototype operational space weather tools that run in real time and present operators with customized, user-specific information. The Dynamic Radiation Environment Assimilation Model (DREAM) focuses on the penetrating radiation environment from natural or nuclear-produced radiation belts. The penetrating radiation environment is highly dynamic and highly orbit-dependent. Operators often must rely only on line plots of 2 MeV electron flux from the NOAA geosynchronous GOES satellites which is then assumed to be representative of the environment at the satellite of interest. DREAM uses data assimilation to produce a global, real-time, energy dependent specification. User tools are built around a distributed service oriented architecture (SOA) which will allow operators to select any satellite from the space catalog and examine the environment for that specific satellite and time of interest. Depending on the application operators may need to examine instantaneous dose rates and/or dose accumulated over various lengths of time. Further, different energy thresholds can be selected depending on the shielding on the satellite or instrument of interest. In order to rapidly assess the probability that space weather was the cause of anomalous operations, the current conditions can be compared against the historical distribution of radiation levels for that orbit. In the simplest operation a user would select a satellite and time of interest and immediately see if the environmental conditions were typical, elevated, or extreme based on how often those conditions occur in that orbit. This allows users to rapidly rule in or out environmental causes of anomalies. The same user interface can also allow users to drill down for more detailed quantitative information. DREAM can be run either from a distributed web-based user interface or as a stand-alone application for secure operations. In this paper we discuss the underlying structure of the DREAM model and demonstrate the user interface that we have developed . We also present some prototype data products and user interfaces for DREAM and discuss how space environment information can be seamlessly integrated into operational SSA systems.

  17. Control of Regional and Global Weather

    E-Print Network [OSTI]

    Alexander Bolonkin

    2007-01-09T23:59:59.000Z

    Author suggests and researches a new revolutionary idea for regional and global weather control. He offers to cover cities, bad regions of country, full country or a continent by a thin closed film with control clarity located at a top limit of the Earth troposphere (4 - 6 km). The film is supported at altitude by small additional atmospheric pressure and connected to ground by thin cables. It is known, the troposphere defines the Earth weather. Authors show this closed dome allows to do a full control of the weather in a given region (the day is always fine, the rain is only in night, no strong wind). The average Earth (white cloudy) reflectance equal 0.3 - 0.5. That means the Earth losses about 0.3 - 0.5 of a solar energy. The dome controls the clarity of film and converts the cold regions to subtropics and creates the hot deserts, desolate wildernesses to the prosperous regions with temperate climate. That is a realistic and the cheapest method of the weather control in the Earth at the current time. Key words: Global weather control, gigantic film dome, converting a cold region to subtropics, converting desolate wilderness to a prosperous region.

  18. Healthy Housing Opportunities During Weatherization Work

    SciTech Connect (OSTI)

    Wilson, J.; Tohn, E.

    2011-03-01T23:59:59.000Z

    In the summer and early fall of 2010, the National Center for Healthy Housing interviewed people from a selection of state and local agencies that perform weatherizations on low-income housing in order to gauge their approach to improving the health and safety of the homes. The interviews provided a strong cross section of what work agencies can do, and how they go about funding this work when funds from the Weatherization Assistance Program (WAP) do not cover the full extent of the repairs. The report also makes recommendations for WAP in how to assist agencies to streamline and maximize the health and safety repairs they are able to make in the course of a standard weatherization.

  19. Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast..................................................................................................................................... 2 Economic Growth Assumptions

  20. Design and Development of Dual Polarized, Stacked Patch Antenna Element for S-Band Dual-Pol Weather Radar Array

    E-Print Network [OSTI]

    Bhardwaj, Shubhendu

    2012-01-01T23:59:59.000Z

    in Weather Detection . . . . . . . . . . . . . . . . . .for S-Band Weather Radar . . . . . . . . . . . . . Dual-polpatterns of polarimetric weather radars,” Journal of