CSCARY: A New Algorithm Combining Observables of ASCAT and CyGNSS for More Accurate Ocean Surface Wind Speed Retrieval

This letter presents a new ocean surface wind speed (OSWS) retrieval algorithm called Combined SCAtterometry ReflectometrY (CSCARY). The algorithm uses the maximum-likelihood estimator (MLE) and geophysical model functions (GMFs) to combine backward and forward observables from the advanced scatterometer (ASCAT) and the cyclone global navigation satellite system (CyGNSS) to achieve more accurate wind speed retrieval. To verify the efficacy of the CSCARY algorithm, a case study is conducted on part of the South China Sea. Results showed that the algorithm improved wind speed accuracy by 28.22% for low-medium wind speeds (2–10 m/s) and 25.33% for medium-high wind speeds (6–16 m/s) compared to the operational ASCAT algorithm. Additionally, the most significant improvement is observed at medium wind speeds, with an increase of 23.6%. These findings suggest that combining scatterometer and global navigation satellite system-reflectometry (GNSS-R) could lead to better OSWS retrieval.