Saildrone direct covariance wind stress in various wind and current regimes of the tropical Pacific
Saildrone direct covariance wind stress in various wind and current regimes of the tropical Pacific
dc.contributor.author | Reeves Eyre, J. E. Jack | |
dc.contributor.author | Cronin, Meghan F. | |
dc.contributor.author | Zhang, Dongxiao | |
dc.contributor.author | Thompson, Elizabeth J. | |
dc.contributor.author | Fairall, Christopher W. | |
dc.contributor.author | Edson, James B. | |
dc.date.accessioned | 2024-02-05T18:18:59Z | |
dc.date.available | 2024-02-05T18:18:59Z | |
dc.date.issued | 2023-04-01 | |
dc.description | Author Posting. © American Meteorological Society, 2023. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 40(4), (2023): 503-517, https://doi.org/10.1175/JTECH-D-22-0077.1. | |
dc.description.abstract | High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s −1 . The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction. Significance Statement We use data from Saildrone uncrewed oceanographic research vehicles to investigate the horizontal forces applied to the surface of the ocean by the action of the wind. We compare two methods to calculate the forces: one uses several simplifying assumptions, and the other makes fewer assumptions but is error prone if the data are incorrectly processed. The two methods agree well, suggesting that Saildrone vehicles are suitable for both methods and that the data processing methods work. Our results show that it is important to consider ocean currents, as well as winds, in order to achieve accurate magnitude and direction of the surface forces. | |
dc.description.sponsorship | This work was partially funded by the Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CIOCES) under NOAA Cooperative Agreement NA20OAR4320271, Contribution Number 2022-1199. This work was supported by NOAA’s Global Ocean Monitoring and Observing Program, NOAA’s Climate Program Office in the Climate Variability and Predictability Program as well as the Climate Observations and Monitoring Program, and NOAA’s Office of Marine and Aviation Operations. This is PMEL Contribution Number 5367. | |
dc.identifier.citation | Eyre, J. E. J. R., Cronin, M. F., Zhang, D., Thompson, E. J., Fairall, C. W., & Edson, J. B. (2023). Saildrone direct covariance wind stress in various wind and current regimes of the Tropical Pacific. Journal of Atmospheric and Oceanic Technology, 40(4) 503-517. | |
dc.identifier.doi | 10.1175/JTECH-D-22-0077.1 | |
dc.identifier.uri | https://hdl.handle.net/1912/67572 | |
dc.publisher | American Meteorological Society | |
dc.relation.uri | https://doi.org/10.1175/JTECH-D-22-0077.1 | |
dc.subject | Atmosphere-ocean interaction | |
dc.subject | Surface observations | |
dc.subject | Turbulence | |
dc.subject | Pacific Ocean | |
dc.subject | Parameterization | |
dc.title | Saildrone direct covariance wind stress in various wind and current regimes of the tropical Pacific | |
dc.type | Article | |
dspace.entity.type | Publication | |
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relation.isAuthorOfPublication.latestForDiscovery | 1e40e2cd-15d5-4963-b716-0e8e86528cbf |
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