Rain Rate Retrieval Algorithm for Dual-Polarized Sentinel-1 SAR in Tropical Cyclone.

Heavy rain is associated with strong winds and extreme waves in a tropical cyclone (TC). In this letter, a practical algorithm for rain rate retrieval in TCs is proposed through 24 dual-polarized [vertical-vertical (VV) and vertical-horizontal (VH)] Sentinel-1 (S-1) synthetic aperture radar (SAR) images acquired in interferometric-wide (IW) swath mode, in which 13 images are collocated with the observations from stepped-frequency microwave radiometers (SFMRs). TC winds are directly obtained from VH-polarized images utilizing the geophysical model function (GMF) S-1 IW mode wind speed retrieval model after noise removal (S1IW.NR). The normalized radar cross section (NRCS) at VV-polarization channel is simulated using GMF CMOD5N and VH-polarized SAR wind. It is found that the difference between the simulated NRCSs and measurements from SAR is linearly related to the rain rate and oscillates with the incidence angle. Following this finding, an empirical algorithm for SAR rain rate retrieval is developed, denoted as CRAIN2_S1, which considers the influence of the radius of the maximum wind speed. The proposed algorithm is applied to 11 images in the dataset, and the validation of the rain rate (up to 35 mm/hr) against the products from global precipitation measurements (GPMs) has a root mean square error (RMSE) of 1.74 mm/hr, a correlation coefficient of 0.92 and a scatter index (SI) of 0.29. Collectively, it is concluded that the algorithm CRAIN2_S1 can be practically applied for dual-polarized SAR rain rate retrieval without any external information. [ABSTRACT FROM AUTHOR]