Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Abstract Wind energy plays a crucial role in sustainable power generation, yet its full potential in the southeast United States (SEUS) remains underexplored. This study advances wind resource assessment in the SEUS using existing regional modeling and multisource observations. We find that terrain complexity, influenced by orography and forest canopy, significantly impacts the accuracy of modeled wind speed. While the High-Resolution Rapid Refresh (HRRR) model effectively simulates wind profiles over flat, nonforested terrain, larger errors are produced above forest canopies, and particularly for those stands in hilly and mountainous terrain where there are no observations aloft that could be used by HRRR’s data assimilation software. Seasonal variations, e.g., changes in the leaf area index, further complicate the relationship between terrain complexity and simulation errors. Our findings emphasize the critical need for comprehensive wind profile measurements, extending from below the canopy to height above the canopy and through the lower planetary boundary layer, to fully quantify model performance over and near forests, and for improving wind resource assessment, planning, and management. This study provides valuable insights not only for further model development but also for future field campaign deployment with the goal of further improving our understanding of wind resources in the region.

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Publication Details

Journal
Journal of Applied Meteorology and Climatology
Published
2025-06-30
DOI
https://doi.org/10.1175/jamc-d-24-0163.1
Citations
3
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
3.32
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article

Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Sha Feng, David D. Turner, Jerome D. Fast, Larry K. Berg et al.
3 citations
Journal of Applied Meteorology and Climatology
Atmospheric and Environmental Gas Dynamics
3.32
article

Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Sha Feng, David D. Turner, Jerome D. Fast, Larry K. Berg, Sonia Wharton, Robert S. Arthur, Ye Liu
article en
3 citations

Abstract

Abstract Wind energy plays a crucial role in sustainable power generation, yet its full potential in the southeast United States (SEUS) remains underexplored. This study advances wind resource assessment in the SEUS using existing regional modeling and multisource observations. We find that terrain complexity, influenced by orography and forest canopy, significantly impacts the accuracy of modeled wind speed. While the High-Resolution Rapid Refresh (HRRR) model effectively simulates wind profiles over flat, nonforested terrain, larger errors are produced above forest canopies, and particularly for those stands in hilly and mountainous terrain where there are no observations aloft that could be used by HRRR’s data assimilation software. Seasonal variations, e.g., changes in the leaf area index, further complicate the relationship between terrain complexity and simulation errors. Our findings emphasize the critical need for comprehensive wind profile measurements, extending from below the canopy to height above the canopy and through the lower planetary boundary layer, to fully quantify model performance over and near forests, and for improving wind resource assessment, planning, and management. This study provides valuable insights not only for further model development but also for future field campaign deployment with the goal of further improving our understanding of wind resources in the region.

Journal of Applied Meteorology and ClimatologyVol. 64(10)
Lawrence Livermore National Laboratory (US), National Oceanic and Atmospheric Administration (US), Pacific Northwest National Laboratory (US), NOAA Global Systems Laboratory, NOAA Earth System Research Laboratory (US)
Openalex Percentile: Top 8%
Atmospheric and Environmental Gas Dynamics
3.32
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