A C-band Geophysical Model Function for Determining Coastal Wind Speed Using Synthetic Aperture Radar

Abstract

A new geophysical model function (GMF), called C_SARMOD2, has been developed to relate highresolution C-band normalized radar cross section (NRCS), acquired in VV polarization over the ocean, to the 10-m height wind speed. A total of 3078 RADARSAT-2 and Sentinel-1A VV-polarized synthetic aperture radar (SAR) images, acquired under different wind speed conditions, were collocated with in situ buoy measurements. The paired dataset was used to derive transfer functions and coefficients of C_SARMOD2, and then to validate the wind speed retrievals. The comparison between SAR-retrieved wind speeds and buoy measurements show almost no bias and a root mean square error of 1.84 m/s. Two representative quad-and dual-polarization SAR images, acquired from coastal regions, are used as case studies to examine C_SARMOD2 performances. The case study and statistical validation results suggest that the proposed C_SARMOD2 has the potential to measure coastal wind speeds at subkilometer resolutions. Although derived from low resolution NRCS measurements, this study also confirms the great robustness of CMOD5.N and recent CMOD7 when applied to SAR data. In addition, it shows that with the new generation of SAR satellite-borne sensors, it is no longer mandatory to rely on scatterometers in order to build a GMF, which will be used for SAR applications. Such an approach is particularly important in view of the upcoming RADARSAT Constellation Mission with new polarization configurations. Moreover, it also opens new perspectives on the derivation of GMFs in HH-polarization. However, these results also suggest that for coastal areas, the increase of the resolution to define the GMF is less important than adding other geophysical parameters to improve wind retrieval performance. This advocates for the necessity of revisiting the methodologies for ocean surface wind speed measurements in coastal areas.

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

“…The accuracy of retrieved scatterometer winds using such GMFs is about m/s (Vogelzang et al, 2011). As reported in numerous studies (Lehner et al, 1996;Yang et al, 2011;Shao et al, 2014;Monaldo et al, 2016;Lu et al, 2018;Corcione et al, 2018), the root mean square error (RMSE) of SAR-derived wind speed retrievals with respect to reliable validation sources is within 2 m/s. The applicability of GMF, however, relies on prior wind direction.…”

Extreme Wind Speeds Retrieval Using Sentinel-1 IW Mode SAR Data

“…According to the influence of wind vector and incident angle on NRCS, several empirical GMFs have been developed for C-band co-polarization scatterometer and SAR data such as CMOD5.N [1], CMOD7 [2], C_SARMOD [3], and C_SARMOD2 [4]. Polarization ratio function is often used when a VV-polarization GMF is applied for HH-polarization data [3].…”

On Modeling of Quad‐Polarization Radar Scattering From the Ocean Surface With Breaking Waves

“…Except theoretical EM scattering models, empirical geophysical model functions (GMFs) can also be used to estimate copolarized and cross‐pol radar backscatters, with given incidence angles, wind speeds, and wind directions (Hwang et al, 2015; Lu et al, 2018; A. Mouche et al, 2017; Mouche & Chapron, 2015; Vachon & Wolfe, 2011; Zhang et al, 2014, 2019; Zhang & Perrie, 2012). These GMFs are derived from C‐band SAR‐measured radar backscatters and collocated winds from buoys or scatterometers or radiometers.…”