A Geophysical Model Function for Wind Speed Retrieval From C-Band HH-Polarized Synthetic Aperture Radar

Abstract

Synthetic aperture radar (SAR) imagery is routinely acquired at HH-polarization in high latitude areas for measuring surface wind over the ocean. However, in the contrary of VV-polarization, there is no HHpolarization geophysical model function (GMF) exists to directly retrieve wind speed from SAR images. In general, HH-polarized Normalized Radar Cross Section (NRCS) is thus converted into VV-polarization and then conventional CMOD functions are used with auxiliary wind direction information for wind speed retrieval. In this letter, we propose a new GMF for SAR ocean surface wind speed retrieval, called CMODH, which relates the C-band NRCS acquired at HH-polarization over the ocean, to the 10-m height wind speed, incident angle and relative wind direction. We first use more than 220,000 ENVISAT ASAR radar backscatter measurements collocated with ASCAT winds to derive the CMODH coefficients. Subsequently, 1459 RADARSAT-2 (RS-2) and 428 Sentinel-1A/B (Sl-1A/B) HH-polarized SAR acquisitions under different wind speeds are matched to in situ buoy observations to validate CMODH. The statistical comparisons between SAR-observed and simulated NRCS show a bias of -0.07 dB and a root mean square error of 1.62 dB for RS-2, and -0.01 dB and 2.48 dB for S1-1A/B. These results suggest that the proposed CMODH has the potential to directly retrieve ocean surface wind speeds using C-band SAR images acquired at HH-polarization, with no need for NRCS transformation by using various empirical and theoretical polarization ratio models.

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

“…Observed RS‐2 quad‐pol SAR measurements are illustrated using blue plus signs (+) in Figure 4. Moreover, we also estimate HH‐, VV‐, and HV‐pol NRCS with three empirical GMFs, namely, CMODH (Zhang et al, 2019), CMOD5.N (Hersbach, 2010), and MS1A (A. Mouche et al, 2017), and calculations are shown as the orange circle lines, yellow diamond lines, and purple square lines, in Figure 4. Thus, we compare RS‐2 observations and GMF estimates with CB and SSA‐2 simulations.…”

“…Moreover, we also estimate HH-, VV-, and HV-pol NRCS with three empirical GMFs, namely, CMODH (Zhang et al, 2019), CMOD5.N (Hersbach, 2010), and MS1A (A. Mouche et al, 2017), and calculations are shown as the orange circle lines, yellow diamond lines, and purple square lines, in Figure 4.…”

“…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.…”

Retrieval of Sea Surface Wind Speed from Spaceborne SAR over the Arctic Marginal Ice Zone with a Neural Network

“…The comparison with buoy measurements has a bias of 0.12 m/s and an RMSE of 1.42 m/s. A recent study [29]shows that the retrieval of by S1 HH-polarized data using the CMODH [12] has a bias of 0.49 m/s and an RMSE of 2.05 m/s compared with buoy measurements. This suggests that the proposed machine learning-type retrieval method can also yield accurate estimates of but avoids the complicatedly tuning of coefficients in the CMOD functions.…”

“…However, the dependence of PR is not only on incidence angle [7] - [9] but also on SSW conditions [8], [10]. While PR depends on various factors, one can also develop independent GMFs for HH-polarized spaceborne SAR data, e.g., as proposed by Monaldo et al [11] for the Radarsat data and by Zhang et al [12] for ENVISAT/ASAR data in HH polarization. This should be an optimized method to retrieve SSW by spaceborne SAR in HH polarization, as the PR may depend on various factors through nonlinear relations.…”