Estimation of Significant Wave Height from Gaofen-3 SAR Wave Mode Data Based on Elastic Net Regression

The EN regression models are implemented for estimating significant wave height (SWH) from quad-polarization Gaofen-3 SAR wave mode data based on the collocated data set of ~11200 Gaofen-3 imagettes matched with SWH from ERA5 reanalysis. The importance of SAR features for SWH estimation from EN is analyzed. The model performance is evaluated through a comparison with observations from buoys and altimeters. The results show that the 20 EOF spectral parameters, NRCS, cvar, and θ are significant for EN to estimate SWH from Gaofen-3 SAR. The EN models achieve good performance with RMSEs smaller than 0.5 m. The co-polarization models show better performance at low sea states but worse performance at high sea states compared to the cross-polarization models.