A new gridded offshore wind profile product for US coasts using machine learning and satellite observations

Frech, James; Saha, Korak; Lavin, Paige D.; Zhang, Huai-Min; Reagan, James; Fung, Brandon

doi:https://doi.org/10.5194/wes-10-1077-2025

Articles | Volume 10, issue 6

https://doi.org/10.5194/wes-10-1077-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-10-1077-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 6

Research article

|

12 Jun 2025

Research article |

| 12 Jun 2025

A new gridded offshore wind profile product for US coasts using machine learning and satellite observations

James Frech, Korak Saha, Paige D. Lavin, Huai-Min Zhang, James Reagan, and Brandon Fung

Data sets

NOAA/NCEI blended global sea surface winds K. Saha and H.-M. Zhang https://doi.org/10.25921/MXT4-B075

2023 National Offshore Wind data set (NOW-23) N. Bodini et al. https://doi.org/10.25984/1821404

ERA5 hourly data on single levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

Atlantic shores offshore wind, ASOW-4, winds profile Atlantic Shores Offshore Wind https://erddap.maracoos.org/erddap/tabledap/AtlanticShores_ASOW-4_wind.html

Atlantic shores offshore wind, ASOW-4, timeseries data Atlantic Shores Offshore Wind https://erddap.maracoos.org/erddap/tabledap/AtlanticShores_ASOW-4_timeseries.html

Atlantic shores offshore wind, ASOW-6, winds profile Atlantic Shores Offshore Wind https://erddap.maracoos.org/erddap/tabledap/AtlanticShores_ASOW-6_wind.html

Atlantic shores offshore wind, ASOW-6, timeseries data Atlantic Shores Offshore Wind https://erddap.maracoos.org/erddap/tabledap/AtlanticShores_ASOW-6_timeseries.html

Hudson North, Hudson South, and Hudson South West buoys New York State Energy Research and Development Authority https://data.ny.gov/Energy-Environment/Floating-LiDAR-BUOY-Data-Beginning-August-2019/xdq2-qf34/about_data

buoy/buoy.z06.b0 Wind Data Hub https://doi.org/10.21947/1959715

buoy/lidar.z06.a0 Wind Data Hub https://doi.org/10.21947/1959720

buoy/buoy.z05.a0 Wind Data Hub https://doi.org/10.21947/1959713

buoy/lidar.z05.a0 Wind Data Hub https://doi.org/10.21947/1959719

Short summary

A machine learning model is developed using lidar stations around US coasts to extrapolate wind speed profiles up to the hub heights of wind turbines from surface wind speeds. Independent validation shows that our model vastly outperforms traditional methods for vertical wind extrapolation. We produce a new long-term gridded dataset of wind speed profiles from 20 to 200 m at 0.25° and 6-hourly resolution from 1987 to the present by applying this model to the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Information (NCEI) Blended Seawinds product.