Observational Insights of Nearshore Wind Stress and Parameterizations From Gaussian Process Regressions
Abstract The nearshore wind stress, u∗2, is examined using machine‐learning models for air‐ocean data collected via new flux buoys deployed across four experiments. Consistent with prior nearshore studies, existing open‐ocean models predict nearshore u∗2 with a large error of 0.0152 m2/s2. Gaussian...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Wiley
2024-10-01
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| Serie: | Geophysical Research Letters |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1029/2023GL106825 |
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