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.

An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

“…In fact, it is well-known that it is directly related to the NRCS of an SAR image. Hence, retrieval schemes based on semi-empirical geophysical model functions (GMFs) have been proposed to deal with co-polarization (vertical-vertical or horizontal-horizontal, VV or HH) imagery collected under moderate wind conditions [23][24][25][26][27]. When dealing with extreme weather conditions, co-polarized backscattering saturates, limiting the applicability of co-polarized GMFs.…”

On C-Band Quad-Polarized Synthetic Aperture Radar Properties of Ocean Surface Currents

“…In Figure 1, periodic bright/dark signatures are well expressed in HH and PR = σ hh 0 /σ vv 0 images. This case, which is only VV, has previously been considered [33] in the context of developing an improved C-band SAR GMF for ocean surface wind speed retrieval. It was reported that the observed periodic features are caused by near-surface wind oscillations induced by atmospheric gravity waves.…”

“…The case shown in Figure 1 provides quad-polarized SAR signatures of wind speed oscillations induced by atmospheric gravity waves. This case had been used [33] to test the capability of a new C_SARMOD2 GMF to retrieve wind speed variability from VV-polarized SAR data. In our present case, the full set of quad-polarized SAR images, and their companions, PD, NP, CPwb, and PR = HH/VV, are used.…”

US East Coast synthetic aperture radar wind atlas for offshore wind energy

“…SAR-derived wind speeds should correctly represent the wind conditions compared to in situ observations, but validation of SAR-derived wind speeds routinely leads to biases that are not consistent between studies (Christiansen et al, 2006;Horstmann et al, 2002;Lu et al, 2018;Takeyama et al, 2013). Deviations between studies can partially be explained by (Hasager et al, 2015;Karagali et al, 2018).…”