Wind Speed Retrieval from Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data for Marine Application

Abstract

RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys on the West and East coasts of Canada. Wind speeds up to 18 m/s were included. CP and linear polarization parameters were related to the C-band model (CMOD) geophysical model functions CMOD-IFR2 and CMOD5n. These were evaluated for their wind retrieval potential in each RCM mode. The CP parameter Conformity was investigated to establish a data-quality threshold (>0.2), to ensure high-quality data for model validation. An accuracy analysis shows that the first Stokes vector (SV 0 ) and the right-transmit vertical-receive backscatter (RV) parameters were as good as the VV backscatter with CMOD inversion. SV 0 produced wind speed retrieval accuracies between 2.13 m/s and 2.22 m/s, depending on the RCM mode. The RCM Medium Resolution 50 m mode produced the best results. The Low Resolution 100 m and Low Noise modes provided similar results. The efficacy of SV 0 and RV imparts confidence in the continuity of robust wind speed retrieval with RCM CP data. Three image-based case studies illustrate the potential for the application of CP parameters and RCM modes in operational wind retrieval systems. The results of this study provide guidance to direct research objectives once RCM is launched. The results also provide guidance for operational RCM data implementation in Canada's National SAR winds system, which provides near-real-time wind speed estimates to operational marine forecasters and meteorologists within Environment and Climate Change Canada. the use of a polarization ratio (PR) [4,5]. The cross-polarized backscatter, i.e., horizontal-transmit vertical-receive (HV), was associated with wind speed, without wind direction or incidence angle input [5]. Models employing both co-and cross-polarized parameters (i.e., VV and VH), in addition to incidence angle and sensor noise, with or without wind direction, were associated with wind speed and are found to be comparable to or better than CMOD-IFR2 retrievals [6]. Using cross-polarized wind speed retrieval in concert with CMOD5n, [7] reported capabilities for SAR wind direction retrieval. Alternatively, azimuthal smearing due to surface motion was associated with wind speed via the SAR azimuth cutoff [8]. Geophysical model functions relating the azimuth cutoff to wind speed and significant wave height were described by [9]. The azimuth cutoff was explored further by [10], who also establish criteria for the optimal use of azimuth cutoff for wind speed retrieval.The development of the RADARSAT Constellation Mission (RCM) and Radar Imaging Satellite-1 (RISAT-1) necessitates an examination of C-band compact polarimetry (CP) SAR data for wind retrieval. CP data provides near-polarimetric SAR capabilities, but at much larger swath widths, making these data more operationally viable. However, while RCM and RISA...

Compact Polarimetry Synthetic Aperture Radar Ocean Wind Retrieval: Model Development and Validation

“…1a and 1b. Previous studies have reported that s 0 RR is more dependent on wind speed than s 0 RH , s 0 RV , and s 0 RL (Geldsetzer et al 2015;G. Zhang et al 2019); thus, we suggest that s 0 RR is appropriate for high wind speed retrieval.…”

“…Previous studies have demonstrated that wind speed can be estimated from the s 0 RR using a combination of CMOD5 and a linear model (Denbina and Collins 2016). Moreover, in terms of wind speed retrieval accuracy, right circular transmit, vertical receive (RV-pol) backscatter (s 0 RV ) was found to be comparable to VV-pol backscatter (s 0 VV ), with CMOD GMFs (Geldsetzer et al 2019). A simple CP wind speed retrieval model has been proposed, relating RR-pol backscatter and the wind speed (Fang et al 2019), which has been further refined by incorporating additional incidence angle dependency (G. Zhang et al 2019).…”

“…Prior to the RCM launch, great efforts were devoted to investigating the feasibility of CP SAR ocean wind retrieval. CP parameters were simulated from RS-2 quad-pol images using a RCM simulator (Charbonneau et al 2010), and used to examine the dependency of incidence angle and wind vector on these parameters (Geldsetzer et al 2015). Thus, it was found that right circular transmit, right circular receive (RR-pol) backscatter (s 0 RR ) data show a primary dependency on wind speed, and are also dependent on both incidence angle and wind direction; however, an analytic function and associated coefficients were not presented.…”

Introduction to Radar Scattering Application in Remote Sensing and Diagnostics: Review

“…When an electromagnetic wave passes from one medium to another, changing, therefore, refraction index, or when it strikes an object such as a radar target and it is reflected, it allows a polarization control to acquire knowledge of the characteristic information about the reflectivity, e.g., the orientation and shape of the reflecting object. In classical radars, i.e., amplitude-only radars, the information about a target is mainly obtained from the energy of the returned pulse; interferometric SAR exploits fully the phase and Doppler information, but not the polarization information of the electromagnetic vector wave-scatterer interrogation process [116][117][118][119].…”

The RADARSAT Constellation Mission Core Applications: First Results

“…In [9], the simulated CP data were related to C-band geophysical model function (CMOD) outputs, and their dependence on radar incidence angle, wind speed, and wind direction was examined. This study was further extended in [10] with a larger simulated RCM CP dataset. Results of [9,10] provided initial guidance to Canada's national SAR wind system for the potential of wind information retrieval using RCM.…”