A New Approach for Ocean Surface Wind Speed Retrieval Using Sentinel-1 Dual-Polarized Imagery

Abstract

A synthetic aperture radar (SAR) has the capability to observe ocean surface winds with a high spatial resolution, even under extreme conditions. The purpose of this work was to develop a new method for wind speed retrieval with the combination of SAR dual-polarized signals. In this study, we collected 28 tropical cyclone imageries observed using the Sentinel-1 dual-polarization mode. These imageries were collocated with radiometer wind speed measurements and reanalysis of wind vector products. In the new method, the wind speed was set as the output. VV-polarized (vertical transmitting–vertical receiving polarized) normalized radar cross section (NRCS), incident angle, VH-polarized (vertical transmitting–horizontal receiving polarized) NRCS, and wind direction were set as the inputs. Based on different output combinations, wind retrieval models were developed with multiple linear regression (MLR). According to the validation and comparison, the proposed models performed better than the traditional piecewise VH-polarization geophysical model functions (GMFs). The impact of thermal noise on the retrieval of low wind speeds (<10 m/s) could be partially reduced. The input of wind direction is unnecessary if the combination of VV- and VH-polarized imageries has been utilized. These results suggest that the use of MLR and the dual-polarization combination can improve SAR wind retrieval accuracy. Compared with SMAP measurements, our SAR retrievals can provide fine structures of TC wind fields.

Concept of Spaceborne Ocean Microwave Dual-Function Integrated Sensor for Wind and Wave Measurement

“…SAR retrieves the wind fields by measuring the Normalized Radar Cross-Section (NRCS) variation of the sea surface, and it is the only satellite-based system that can offer wind information with a sub-kilometer spatial resolution (ranging from a few to a few hundred meters) [15]. However, as SAR operates at a single azimuth angle, external wind direction information is required to resolve the 180-degree ambiguity of the wind direction, which leads to the inversion precision being highly dependent on the accuracy of the auxiliary data [16][17][18]. Beyond wind field retrieval, SAR images can also be employed to estimate wave directional spectra based on the nonlinear mapping relationship between them.…”