We present the follow-up of our previously published work, where we described a wavelet-based method to characterize the sea surface backscatter structures in Synthetic Aperture Radar (SAR) images. The method relies on the ability of the 2-D continuous wavelet technique to detect the spatial structure of the Marine Atmospheric Boundary Layer (MABL) and to isolate wind-related cells and features. The analysis of the cells’ geometry, molded by the radiometric characteristics of the sea surface, permits the identification of the wind direction inside the cells, due to the along-wind asymmetry of backscatter structures, and thus the computation of the wind speed through standard algorithms. Twenty-one SAR images (ERS-2 and Envisat ASAR Wide Swath) over the Mediterranean Sea have been analyzed, and the results are compared with satellite wind fields. The images cover a range of meteorological conditions from low to moderate winds. Comparison of the SAR-derived wind fields with those provided by satellite scatterometers indicates a good score of success (roughly 70%–80%). The developed methodology, once tested over an adequate number of images to derive statistically reliable results, could be routinely used to enrich SAR images with the wind field as well as to characterize the MABL in terms of size, distribution, and shape of the backscatter cells.

Synthetic aperture radar (SAR) images of the sea surface often show roll-vortex structures and other features which, in general, are spread out over several length scales and may present spatial periodicity as well as intermittence.  Standard techniques, such as two-dimensional (2-D)  Fourier analysis, are unsuitable both when it is of interest to detect intermittent phenomena and to analyze the spatial disposition of the backscatter structures inside the SAR images. For the above reasons, the 2-D continuous wavelet transform analysis has been applied to two European Remote Sensing mission SAR images over the Mediterranean Sea, showing wind rolls and atmospheric gravity waves. Through the evaluation of the wavelet variance map, which ideally corresponds to the 2-D Fourier spectrum, it has been possible to assess the presence of two main energy areas at large (from 7–28 km) and small (from 0.5–2 km) spatial scales. While the large-scale fluctuations may be ascribed to atmospheric gravity waves and other features induced by the surroundings, the small-scale fluctuations reveal the inner structure of the atmospheric wind rolls. The SAR-like maps, obtained by adding the wavelet coefficient maps pertaining to the small scales, have permitted to highlight the high- and low-intensity backscatter cells associated with the wind rolls. These cells have been statistically characterized by means of the frequency distributions of the size of the cells maximum and minimum axes, of the orientation of the maximum axis, and of their area. The results indicate that high- and low-intensity backscatter cells have similar characteristics in both cases studied: they appear of elliptic shape, with the major axis along the wind roll direction; the average axes ratio is 2.5:1. The frequency distributions of the cells area indicate a continuous distribution of sizes, without significant gaps.

The potential of active microwave satellite observations of sea surface height (radar altimetry) and of sea surface wind (radar scatterometry) has been exploited for storm surge modeling purposes. The altimetry observations were assimilated into a storm surge model (SSM) with a dual 4D-Var system, in order to obtain the best possible surge level field as initial condition to reforecast runs. The scatterometer wind data were instead used to improve the accuracy of the wind fields of a global atmospheric model used as forcing to the SSM through a procedure that has been proved to be able to reduce the differences between the model winds and the scatterometer observations. Hindcast experiments were performed to test the sensitivity of the SSM to the altimetry data assimilation and to the modified wind forcing.Remarkable improvements of the storm surge level hindcast have been obtained for what concerns the modified model wind forcing, while encouraging results have been obtained with the altimeter data assimilation.

This work deals with the spatial characteristics of the wind fields evaluated from synthetic aperture radar (SAR) images and simulated by the weather research and  forecasting (WRF) atmospheric model in the Gulf of  Oristano, a small coastal area about 10 km × 18 km wide in western coast of Sardinia (Western Mediterranean Sea). The SAR-derived wind fields have been obtained analyzing images of the COSMO-SkyMed, Radarsat-2, and Sentinel-1A satellites through a fully two-dimensional continuous wavelet transform (2-D-CWT) method. The analysis of the wind directions has shown that the model variability is limited if compared to that inferred by 2-D-CWT method, which mostly respects the variability evidenced by in situ data. As the use of model directions to compute the SAR wind fields is a standard in many studies, the impact on the SAR wind speed retrieval of using the model instead of the SAR-derived directions has been assessed: differences of wind speed greater than ±10% occur for about the 20% of data. The spatial variability of the SAR and model wind speed fields results quite different at both local and domain scales. The knowledge of the spatial variations of the surface wind fields can be very important for the oceanographic applications and constitutes the added value brought by SAR in the description of the coastal wind. For this reason, the SAR-derived wind fields should be taken as reference in many kind of applications.