A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data

Abstract

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σVV0 retrieved from new PR models as well as σHH0 is in good agreement with σVV0 extracted from SAR images directly.

Intelligent Wind Retrieval from Chinese Gaofen-3 SAR Imagery in Quad Polarization

“…Therefore, we divided each image into a number of subscenes with a spatial coverage of about 4 km 2 . In addition, we interpolated the ECMWF winds over the temporal scale to 1 h using a cubic spline (Wang et al 2018). Hence, the time difference between GF-3 SAR imaging and the ECMWF winds was within 30 min.…”

“…Recently, several studies have proposed empirical wind retrieval algorithms using cross-polarization (VH and HV) SAR NRCS (Hwang et al 2015;Wang et al 2018), because the cross-polarization NRCS has a linear growth relationship with wind speed and is less sensitive to wind direction (Vachon and Wolfe 2011;Ren et al 2017). The SAR backscattering signal at crosspolarization channel does not easily encounter a saturation problem at strong winds (probably greater than 25 m s 21 ) (Hwang et al 2010;Voronovich and Zavorotny 2014;Zhang and Perrie 2012;Shao et al 2017).…”

“…To date, the accuracy of retrieval wind using existing algorithms for various SAR at copolarization (Yang et al 2011;Shao et al 2014;Monaldo et al 2016) and crosspolarization (Wang et al 2018;Vachon and Wolfe 2011;Huang et al 2017) channels has been well studied, indicating a 2 m s 21 error of wind speed. Hence, a quad-polarization backscattering signal should include additional sea surface information, which is expected to improve the wind retrieval performance (Fois et al 2015).…”

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

“…The time difference between SAR images and ECMWF winds was within 30 minutes. This methodology was fully described by Wang et al (2018) for the development of wind retrieval using GF-3 SAR data. This method is applied only when the difference between the ECMWF samples and GF-3 SAR acquisitions is smaller than a few hours.…”

“…The accuracy of wind retrieval using copolarization GF-3 SAR images has been assessed in several studies (Shao et al, 2017b;Ren et al, 2017;Wang et al, 2018;Shao et al, 2019). A simple wind retrieval algorithm for VH GF-3 SAR underwent preliminary tuning without consideration for the radar incidence angle (Ren et al, 2017;Wang et al, 2018), showing the effectiveness of retrieving sea surface wind speed from GF-3 SAR images using cross-polarization channels because operational wind monitoring is an important aspect of using SAR data. In this work, we studied the dependence of the cross-polarization NRCS of GF-3 SAR on wind vector and incidence angle.…”