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September 12, 2025Journal of Marine Science and EngineeringOpen Access

Deep Learning-Based Wind Speed Retrieval from Sentinel-1 SAR Wave Mode Data

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Authors

RSRuixuan SunCWChen WangZJZhuhui Jiang

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Overview

This analysis demonstrates improved wind speed retrieval using deep learning on SAR data, indicating potential for enhanced operational forecasting.

Key Points

  • The CNN-based approach achieves lower root mean square error and bias in wind speed retrieval.
  • Using Sentinel-1 SAR data, the model shows regional variations in retrieval accuracy due to geophysical features.
  • Evaluation against both collocated wind vectors and independent datasets highlights the model's robustness.
  • The results support deep learning for operational marine wind forecasting, emphasizing data-driven advancements.

Cite This Study

Sun et al. (2025) studied this question.

synapsesocial.com/papers/68d44b3031b076d99fa54834https://doi.org/10.3390/jmse13091751
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