A5006628085- Energy Load and Power Forecasting
- Meteorological Phenomena and Simulations
- Traffic Prediction and Management Techniques
- Solar Radiation and Photovoltaics
- Wind and Air Flow Studies
- Matrix Theory and Algorithms
- Vehicle emissions and performance
- graph theory and CDMA systems
- Scientific Computing and Data Management
- Photovoltaic System Optimization Techniques
- Research Data Management Practices
- Graph Labeling and Dimension Problems
- Graph theory and applications
- Climate variability and models
- Smart Materials for Construction
- Distributed and Parallel Computing Systems
- Atmospheric aerosols and clouds
- Advanced Topics in Algebra
- Atmospheric and Environmental Gas Dynamics
- Transportation Planning and Optimization
- Air Quality Monitoring and Forecasting
- Infrastructure Maintenance and Monitoring
- Advanced Graph Theory Research
- Flood Risk Assessment and Management
- Precipitation Measurement and Analysis
NSF National Center for Atmospheric Research
2000-2020
Research Applications (United States)
2006-2020
Research Applications Laboratory
2017
Budapest University of Technology and Economics
2015
Colorado School of Mines
1988
University of Colorado Denver
1984-1987
A methodology is presented for the real-time automated identification, tracking, and short-term forecasting of thunderstorms based on volume-scan weather radar data. The emphasis concepts upon which based. “storm” defined as a contiguous region exceeding thresholds reflectivity size. Storms in this way are identified at discrete time intervals. An optimization scheme employed to match storms one with those following time, some geometric logic deal mergers splits. forecast both position size...
Abstract An automated procedure for forecasting mid- and upper-level turbulence that affects aircraft is described. This procedure, termed the Graphical Turbulence Guidance system, uses output from numerical weather prediction model forecasts to derive many diagnostics are combined as a weighted sum with relative weights computed give best agreement most recent available observations (i.e., pilot reports of or PIREPs). minimizes forecast errors due uncertainties in individual their...
Wind power forecasting can enhance the value of wind energy by improving reliability integrating this variable resource and economic feasibility. The National Center for Atmospheric Research (NCAR) has collaborated with Xcel Energy to develop a multifaceted prediction system. Both day-ahead forecast that is used in trading short-term are critical decision making. This system includes high resolution ensemble modeling capabilities, data assimilation, now-casting, statistical postprocessing...
Abstract As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting this highly variable renewable resource. Thus, a team researchers from public, private, and academic sectors partnered develop assess new system, Sun4Cast. The partnership focused on improving decision-making for utilities independent system operators, ultimately resulting in improved stability cost savings consumers. project followed value chain approach...
The National Center for Atmospheric Research (NCAR) recently updated the comprehensive wind power forecasting system in collaboration with Xcel Energy addressing users’ needs and requirements by enhancing expanding integration between numerical weather prediction machine-learning methods. While original was designed primary focus on day-ahead support of trading, enhanced provides short-term unit commitment economic dispatch, uncertainty quantification speed probabilistic forecasting, extreme...
A modern renewable energy forecasting system blends physical models with artificial intelligence to aid in operation and grid integration. This paper describes such a being developed for the Shagaya Renewable Energy Park, which is by State of Kuwait. The park contains wind turbines, photovoltaic panels, concentrated solar technologies storage capabilities. fully operational Kuwait Prediction System (KREPS) employs (AI) multiple portions structure processes, both short-range (i.e., next six...
A detailed account of various determinantal formulas is presented in a graph-theoretic form involving paths and cycles the digraph matrix. For cases which has special local properties, for example, cutpoint or bridge, particular are given that more efficient computing determinant than simply using matrix representation. Applications also to characteristic deter- minants, general minors, cofactors.
The Doppler velocity dealiasing problem has been discussed for many years. Because aliasing is easily identified by detecting abrupt changes in the data field, most existing algorithms use this technique to correct aliased data. Such are typically based on local expansion methods. methods make a decision each gate information of its dealiased neighbors and thus can be sensitive scattered incorrect This paper introduces new approach that attempts find all values given dataset solving linear...
Abstract The 2010 Development Test Environment Experiment (DTE10) took place from 28 January to 29 March in the Detroit, Michigan, metropolitan area for purposes of collecting and evaluating mobile data vehicles. To examine quality these data, over 239 000 air temperature atmospheric pressure observations were obtained nine vehicles compared with a weather station set up at testing site. first run through NCAR Vehicle Data Translator (VDT). As part VDT, quality-checking (QCh) tests applied;...
Operating modern multi-modal surface transportation systems are becoming increasingly automated and driven by decision support systems. One aspect necessary for successful, safe, reliable, efficient operation of any network is real-time forecasted weather pavement condition information. Providing such information requires an adaptive system capable blending large amounts observational model data that arrives quickly, in disparate formats times, blends optimizes their use via expert...
One of the goals RITA's IntelliDrive initiative is utilization by public and private organizations that collect, process, generate weather products vehicle sensor data to improve road condition hazard products. Some users may not be able to, or want contend with complexities associated data, such as quality, representativeness, format. With funding support from U.S. Department Transportation's RITA direction FHWA's Road Weather Management Program, National Center for Atmospheric Research...
Abstract Low cloud ceilings and poor visibility claim the lives of more general aviation (GA) pilots passengers than any other cause weather-related GA accidents. Experience shows that instrument-rated as well those rated only for visual flight are vulnerable to low ceiling (C&V), making total avoidance most powerful strategy available a pilot dealing with these hazards. The weather awareness needed begins recognition current conditions. This article outlines how fusion surface,...
Advances in geoscience research and discovery are fundamentally tied to data computation, but formal strategies for managing the diversity of models resources Earth sciences have not yet been resolved or fully appreciated. The U.S. National Science Foundation (NSF) EarthCube initiative ( http://earthcube.ning.com ), which aims support community‐guided cyberinfrastructure integrate information across geosciences, recently funded four community development activities: Geoscience Workflows;...
Numerical weather prediction (NWP), a method of forecasting using equations that describe atmospheric flows and behavior, is used extensively to help predict conditions along roadways has important implications for maintaining safety efficiency on the transportation network. An insufficiently dense surface observation network presents major limitation in obtaining current state atmosphere NWP at high spatial temporal resolutions, such as required by road applications. Connected vehicle...
The National Center for Atmospheric Research (NCAR) has developed a wind prediction system Xcel Energy, the power company with largest capacity in United States. forecasting includes advanced modeling capabilities, data assimilation, nowcasting, and statistical post-processing technologies. ingests both external model observations. NCAR produces deterministic mesoscale forecast of hub height winds on very fine resolution grid using Weather Forecasting (WRF) model, run Real Time Four...
Abstract We discuss one method of incorporating quantitative information into the theory qualitative matrices. Our consists imposing conditions upon principal minors matrix A which insure that their signs will be consistent with diagonal elements (all assumed to nonzero). new dominance theorem is proved gives sufficient for such consistency. When are we show how classify all and obtain precise sign about many −1. ∗The work this author was supported in part by grant no. 101/84 from Division...
The SunCast Solar Power Forecasting System is comprised of various models to predict the short term solar resource from 15 min through 168 hours. It leverages surface and satellite observations in building both physically-based as well artificial intelligence nowcasting models. also employs numerical weather prediction models, including an enhanced version Weather Research model, WRF-Solar. This paper compares techniques describes how they are integrated provide a seamless probabilistic...