Ocean Surface Wind Wave Signatures in Single-Look Complex SAR Data

Spaceborne synthetic aperture radar (SAR) provides high-resolution sea surface observations to characterize oceanic and atmospheric variability at submesoscales. Despite significant progress in retrieving wind fields from SAR images, challenges remain particularly for single-antenna measurements where wind speed inversion often requires an external wind direction input. This study introduces and evaluates the use of directional features derived from SAR image sublook cross-spectra to improve wind retrieval. Specifically, we explore the imaginary part of SAR mean cross-spectra (IMACS) and its differential counterpart, $\Delta $ IMACS, which capture directional signatures of range-traveling intermediate wind waves. Using systematically collocated Sentinel-1A wave mode SAR images and model winds, we demonstrate that IMACS exhibits a cosine-like dependence on wind direction at given wind speeds at two incidence angles, while $\Delta $ IMACS reveals unique sensitivities that complement radar backscattering and can resolve wind direction ambiguities. A novel cost function combining radar backscattering, IMACS, and $\Delta $ IMACS is proposed to retrieve wind vectors directly from SAR data without external wind direction inputs. The proposed scheme is evaluated through comparisons with independent model outputs and buoy measurements, showing improved performance. These findings highlight the potential of IMACS and $\Delta $ IMACS to enhance self-sufficient wind inversion, offering a promising pathway for single-polarized SAR wind retrieval.