Development of Wind Speed Retrieval from Cross-Polarization Chinese Gaofen-3 Synthetic Aperture Radar in Typhoons

Abstract

The purpose of our work is to determine the feasibility and effectiveness of retrieving sea surface wind speeds from C-band cross-polarization (herein vertical-horizontal, VH) Chinese Gaofen-3 (GF-3) SAR images in typhoons. In this study, we have collected three GF-3 SAR images acquired in Global Observation (GLO) and Wide ScanSAR (WSC) mode during the summer of 2017 from the China Sea, which includes the typhoons Noru, Doksuri and Talim. These images were collocated with wind simulations at 0.12° grids from a numeric model, called the Regional Assimilation and Prediction System-Typhoon model (GRAPES-TYM). Recent research shows that GRAPES-TYM has a good performance for typhoon simulation in the China Sea. Based on the dataset, the dependence of wind speed and of radar incidence angle on normalized radar cross (NRCS) of VH-polarization GF-3 SAR have been investigated, after which an empirical algorithm for wind speed retrieval from VH-polarization GF-3 SAR was tuned. An additional four VH-polarization GF-3 SAR images in three typhoons, Noru, Hato and Talim, were investigated in order to validate the proposed algorithm. SAR-derived winds were compared with measurements from Windsat winds at 0.25° grids with wind speeds up to 40 m/s, showing a 5.5 m/s root mean square error (RMSE) of wind speed and an improved RMSE of 5.1 m/s wind speed was achieved compared with the retrieval results validated against GRAPES-TYM winds. It is concluded that the proposed algorithm is a promising potential technique for strong wind retrieval from cross-polarization GF-3 SAR images without encountering a signal saturation problem.

A Novel Wind Speed Estimation Based on the Integration of an Artificial Neural Network and a Particle Filter Using BeiDou GEO Reflectometry

“…It is highly effective for monitoring the Earth’s environments, measuring significant wave heights, wind speeds, soil moisture, and ice and snow thicknesses [ 2 , 3 , 4 , 5 ]. In particular, the characteristics of wind speed are an important factor for the observations of typhoon and hurricane events [ 6 , 7 ]. In 2003, Surrey Satellite Technology developed the first GPS-R receiver onboard the UK-Disaster Monitoring Constellation (UK-DMC) satellite in order to establish ocean and land surface conditions [ 8 ].…”

Tropical Cyclone Wind Speed Retrieval from Dual-Polarization Sentinel-1 EW Mode Products

“…Since 1978, synthetic aperture radar (SAR) images with advantages of high spatial resolution, large spatial coverage, and the capability of sensing through clouds at day and night have become available for studying, forecasting, and monitoring TCs (Li 2015;Yu et al 2017). With development of SAR technology, the TC wind speed retrieval by C-band SAR is widely studied from copolarization signals to cross-polarization (CP) signals (Zhang and Perrie 2014;Hwang 2016;Shao et al 2017).…”

“…Generally, TC sea surface wind speed can be retrieved either from normalized radar cross section (NRCS) directly (Zhang and Perrie 2014;Zhang et al 2017) or from the SAR-derived wave information indirectly (Hwang 2016;Shao et al 2017). For TC conditions, due to the saturation of the drag coefficient, aerodynamic roughness, and sea surface roughness (Donelan et al 2004;Bye and Jenkins 2006;Fujimura et al 2019), the copolarization NRCS starts to saturate and decreases as wind speed increases beyond marginal hurricane strength (Hwang et al 2010;Hwang and Fois 2015).…”

“…This overcomes the retrieval limitations of copolarization SAR images. Recently, several CP GMFs with respect to TC wind speed retrieval have been developed statistically for RadarSat-2 (Hwang et al 2010;Zhang and Perrie 2012;Van Zadelhoff et al 2013Zhang et al 2014;Horstmann et al 2015;Zhang et al 2017), Sentinel-1 (Mouche et al 2017;Gao et al 2019), and Gaofen-3 (Shao et al 2018). The wind speeds retrieved from CP SAR images have significantly better performance than copolarization at wind speeds above 20 m s 21 (Horstmann et al 2013;Mouche et al 2017).…”

Speckle Filtering of GF-3 Polarimetric SAR Data with Joint Restriction Principle

“…Yin et al [ 3 ] provided an analysis on the physical scattering mechanism of GF-3 polarimetric SAR data and showed that the data has great potential for target characterization. Shao et al [ 4 ] developed the method of strong wind retrieval from the cross-polarization GF-3 SAR data. Chang et al [ 5 ] had an experiment on the calibration of residual polarimetric distortion for channel imbalance and crosstalk of GF-3 polarimetric SAR images and improved the quality of image greatly.…”