An Analysis of a Commercial GNSS-R Ocean Wind Speed Dataset

An analysis of Level-2 (L2) ocean wind speed retrievals from 1st May, 2021 to 1st June, 2024 derived from Spire, Inc.’s Global Navigation Satellite System Reflectometry observatories is presented. Comparisons of retrieved ocean surface wind speeds with European Center for Medium-Range Weather Forecasts Reanalysis v5 estimates show correlations on the order of 73<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and unbiased rms error (uRMSE) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 2.4 m/s over all wind speeds using the latest v2.07 data version. Colocated observations with advanced scatterometer (ASCAT) B, ASCAT C, advanced microwave scanning radiometer 2, soil moisture active passive, and Cyclone Global Navigation Satellite System winds also show correlations up to 86<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and overall uRMSE values ranging between 1.45–2.03 m/s, with “triple colocation” analyses yielding similar results. Errors are found to increase significantly for wind speeds exceeding 12–15 m/s, likely due to the relatively low signal-to-noise ratio of such measurements for Spire's receivers. A sensitivity of ocean wind speed retrievals to storm structure is nevertheless demonstrated that highlights an ability to capture large scale features in a manner commensurate with reference model data.

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Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/jstars.2025.3555820
Citations
2
Primary Topic
Oceanographic and Atmospheric Processes
Type
article
Field-Weighted Citation Impact
3.59
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article

An Analysis of a Commercial GNSS-R Ocean Wind Speed Dataset

Joel T. Johnson, Darren McKague, Dorina Twigg, Mohammad M. Al-Khaldi et al.
2 citations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Oceanographic and Atmospheric Processes
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article

An Analysis of a Commercial GNSS-R Ocean Wind Speed Dataset

Joel T. Johnson, Darren McKague, Dorina Twigg, Mohammad M. Al-Khaldi, Anthony Russel, F. Policelli
article en
2 citations

Abstract

An analysis of Level-2 (L2) ocean wind speed retrievals from 1st May, 2021 to 1st June, 2024 derived from Spire, Inc.’s Global Navigation Satellite System Reflectometry observatories is presented. Comparisons of retrieved ocean surface wind speeds with European Center for Medium-Range Weather Forecasts Reanalysis v5 estimates show correlations on the order of 73<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and unbiased rms error (uRMSE) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 2.4 m/s over all wind speeds using the latest v2.07 data version. Colocated observations with advanced scatterometer (ASCAT) B, ASCAT C, advanced microwave scanning radiometer 2, soil moisture active passive, and Cyclone Global Navigation Satellite System winds also show correlations up to 86<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and overall uRMSE values ranging between 1.45–2.03 m/s, with “triple colocation” analyses yielding similar results. Errors are found to increase significantly for wind speeds exceeding 12–15 m/s, likely due to the relatively low signal-to-noise ratio of such measurements for Spire's receivers. A sensitivity of ocean wind speed retrievals to storm structure is nevertheless demonstrated that highlights an ability to capture large scale features in a manner commensurate with reference model data.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
Goddard Space Flight Center (US), University of Michigan (US), The Ohio State University (US)
Life below water
Openalex Percentile: Top 10%
Oceanographic and Atmospheric Processes
3.59
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