Fused Geophysical–Contrastive Learning Model for CYGNSS-Based Sea Surface Wind Speed Retrieval in Typhoon Regions

Global Navigation Satellite System Reflectometry (GNSS-R) provides a vital means for sea surface wind speed retrieval, yet its application under extreme typhoon conditions remains challenging. Conventional geophysical models (GMFs) saturate in high wind speed regimes (>20 m/s), and deep learning mod...

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Detalles Bibliográficos

Principais autores:	Yun Zhang, Zelong Teng, Shuhu Yang, Qingjing Shi, Jiaying Li, Fei Guo, Bo Peng, Yanling Han, Zhonghua Hong
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2026-01-01
Series:	Journal of Marine Science and Engineering
Assuntos:	CYGNSS typhoon GMF comparative learning model
Acceso en liña:	https://www.mdpi.com/2077-1312/14/2/208
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