Wind Direction Extraction from SAR in Coastal Areas

Abstract

This paper aims to illustrate and test a method, based on the Two-Dimensional Continuous Wavelet Transform (2D-CWT), developed to extract the wind directions from the Synthetic Aperture Radar (SAR) images. The knowledge of the wind direction is essential to retrieve the wind speed by using the radar-backscatter versus wind speed algorithms. The method has been applied to 61 SAR images from different satellites (Envisat, COSMO-SkyMed, Radarsat-2 and Sentinel-1A,B), and the results have been compared with the analysis wind fields from the European Centre for Medium-range Weather Forecasts (ECMWF) model, with in situ reports and with scatterometer data when available. The 2D-CWT method provides satisfactory results, both in areas a few kilometres from the coast and offshore. It is reliable as it produces good direction estimates, no matter what the characteristics of the SAR are. Statistics reports a success in the SAR wind direction estimates in 95% of cases (in 83% of cases the SAR-ECMWF wind direction difference is < ±20 • , in 92% < ±30 • ) with a mean directional bias B θ < 7 • . The SAR derived wind directions cannot be said to be validated, as the data available at present cannot be really representative of the wind field in the coastal area. However, the figures given by SAR winds are highly valuable even not properly validated, providing an independent and unique view of the spatial variability of the wind over the sea, which is possible by using the 2D-CWT method to derive the wind directions.

An assessment of marine atmospheric boundary layer roll detection using Sentinel-1 SAR data

“…This provides an opportunity for rigorous evaluation of C-band SAR detection and imaging of MABL rolls for varied wind speeds and radar viewing geometries. These characteristics have received limited attention in most previous SAR-based MABL roll investigations (Alpers and Brümmer, 1994;Young, 2000;Sikora and Ufermann, 2004;Li et al, 2013;Zhao et al, 2016), and in ocean SAR studies where the surface wind direction is inferred from roll imprint analyses (Gerling, 1986;Koch, 2004;Christiansen et al, 2006;Lin et al, 2008;Li and Lehner, 2014;Zecchetto, 2018). Alpers and Brümmer (1994) proposed that SAR backscatter due to the roll-induced wave-roughening can be interpreted using the empirical geophysical model functions (GMFs) that relate 20-40 km scale radar scatterometer measurements to surface wind speed and radar viewing geometry.…”

Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

“…However, the NRCS, instead of SAR-derived wind speed, is chosen here as the input for our proposed empirical model. The reason is that the wind speed retrieval from co-polarized NRCS usually needs prior information of wind direction i.e., [32,48], and the wind speed estimation accuracy depends on the selection of different GMFs [16][17][18]. Thus, by including NRCS, we propose our SWH empirical model which could be implemented without using SAR-derived wind speeds.…”

Surface Currents Derived from SAR Doppler Processing: An Analysis over the Naples Coastal Region in South Italy

“…The results presented in this paper suggest that this well known issue [53,54] could be partly overcome. The coarse spatial resolution of external data could indeed be refined by wind/Doppler approach that highlights changes in wind direction, as shown in this paper.…”