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Wind velocity estimates from wave observing platforms
Near-surface ocean wind measurements are important for weather forecasting, determining surface transports, and estimating air-sea interactions; however, in-situ wind observations are often limited. Previous studies indicate that the equilibrium range of the surface gravity wave spectrum can be used to estimate surface wind velocity. This approach is tested using spectral wave measurements from the Coastal Data Information Program (CDIP) buoy array off Monterey, California. Quality controlled wind vectors inferred from wave spectra are statistically compared to measurements from a nearby National Data Buoy Center (NDBC) buoy, demonstrating strong agreement with the control observations with root mean square errors for speed and direction of 1.8 m/s for all wind speeds and 13.2° for wind speeds greater than 7 m/s. We expand this estimation method to account for biofouling, which causes high-frequency damping of the wave spectrum, and the effects of form factor, which impact the platform’s dynamic response to high-frequency waves. The method produces wind-proxy measurements solely from wave spectra and wave-based drag parametrizations, making it useful for operational integration. This work demonstrates the ability to make robust wind velocity estimates using wave data from multiple sources, increasing the coverage of wind information over the coastal and open ocean.
Wind velocity estimates from wave observing platforms
Near-surface ocean wind measurements are important for weather forecasting, determining surface transports, and estimating air-sea interactions; however, in-situ wind observations are often limited. Previous studies indicate that the equilibrium range of the surface gravity wave spectrum can be used to estimate surface wind velocity. This approach is tested using spectral wave measurements from the Coastal Data Information Program (CDIP) buoy array off Monterey, California. Quality controlled wind vectors inferred from wave spectra are statistically compared to measurements from a nearby National Data Buoy Center (NDBC) buoy, demonstrating strong agreement with the control observations with root mean square errors for speed and direction of 1.8 m/s for all wind speeds and 13.2° for wind speeds greater than 7 m/s. We expand this estimation method to account for biofouling, which causes high-frequency damping of the wave spectrum, and the effects of form factor, which impact the platform’s dynamic response to high-frequency waves. The method produces wind-proxy measurements solely from wave spectra and wave-based drag parametrizations, making it useful for operational integration. This work demonstrates the ability to make robust wind velocity estimates using wave data from multiple sources, increasing the coverage of wind information over the coastal and open ocean.
Wind velocity estimates from wave observing platforms
Mudd, K. C. (Autor:in) / Ho, A. (Autor:in) / Amador, A. (Autor:in) / Lodise, J. (Autor:in) / Behrens, J. (Autor:in) / Merrifield, S. T. (Autor:in)
Coastal Engineering Journal ; 66 ; 479-491
02.07.2024
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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