Evaluation of SAR-based Sea State Parameters and Roughness Length Derivation over the Coastal Seas of the United States

This paper presents comprehensive validation of specific sea state parameters (SSPs) and SAR-derived wind speeds (u_SAR ). The paper introduces a novel approach to retrieving roughness length (z₀) based on wave steepness, following the retrieval of the short wavelengths necessary to estimate z₀. The Synthetic aperture radar (SAR) onboard the Sentinel-1 (S1) satellite was used specifically the Interferometric Wide Swath Mode (IW) data. The data was processed using the CWAVE_EX algorithm for SSPs and CMOD-5 for u_SAR CWAVE_EX was developed especially for coastal waters; the processing chain includes steps for SAR image denoising and eliminating image artifacts. SAR S-1 data inherently exhibits a substantial azimuthal cutoff length due to the data's high satellite altitude and SAR IW resolution. That complicates the retrieving of short wavelengths prevalent in coastal zones and needed to retrieve z₀ The research focuses on the coastal seas of the United States, benefiting from the presence of an extensive network of ocean buoys for validation purposes. The complete SAR S1 A/B archive from 2014 to 2022 was first processed to retrieve SSPs and u_SAR The validation for significant wave height (Z_s), second moment wave period(T_m2) and u_SAR was performed using in-situ measurements with about 6,000 collocations.H_s and T_m2 were compared against the corresponding parameters from hindcast spectral numerical model data with about 380,000 collocations. The comparisons between the retrieved H_s and T_m2 against the in-situ observations and hindcast wave model data yielded a root mean square error (RMSE) of 0.46-0.50 m and 0.9-1.1 sec. The RMSE of u_SAR against in-situ observation was about 2 m/s with a bias of 0.78 m/s. The estimated z₀ values from satellite-driven wave parameters were highly correlated with the z₀ estimated from the in-situ observations, with a RMSE of 0.04×10^-3 m and a bias of -0.01×10^-3 m. The study highlights the possibility of using SAR remote sensing data for global mapping of z₀, including coastal effects of local variability in sea state and wind field gustiness.