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Improvements In NOAA Modeling and Data Assimilation To Improve Guidance For The Renewable Energy Industry


A strong requirement exists from the renewable energy (RE) industry for improved guidance for both wind and solar power generation potential. NOAA has some modest efforts in several key areas that will expand greatly in the next few years to meet this requirement, including more accurate boundary-layer modeling, especially under stable conditions, improved cloud parameterizations, and higher horizontal and vertical resolution. Also critical for improved RE forecast guidance are efforts toward improved data assimilation for cloud observations from satellites, METARs, radar, and lightning detection networks, and for use of high-frequency wind profile data from aircraft, profilers of various types, and satellite-based estimates. The goal of these efforts, which will be at least decade-long, will be much more accurate and precise forecasts updated hourly for durations of 1 hour to many days for 20-150 m wind forecasts, and direct and diffuse solar radiation incident at the surface. These efforts will also benefit NOAA forecast guidance for aviation, severe weather, fire weather, air quality, and hydrology. NOAA will be collaborating with many different organizations and laboratories in this effort to improve its operational guidance. These improved data assimilation and modeling capabilities will also benefit multi-decade reanalyses. NOAA will analyze some historic satellite and conventional data and reanalysis grids to understand the trend of solar and wind energy potential over the United States and the globe. Improved reanalysis and forecast guidance data will provide a resource for future solar and wind farm siting.

Article / Publication Data
Available Metadata
Fiscal Year
Published On
January 01, 2010

This publication was presented at the following:

First Conference on Weather, Climate, and the New Energy Economy 8th Users Forum on Weather and Clim
American Meteorological Society


Not available


Authors who have authored or contributed to this publication.

  • robert M. banta - Not Positioned Psl
    Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
    NOAA/Global Systems Laboratory