## 5 Conclusions  
Following a scatterometry-based approach, which allows retrieval of SSW speed from SAR data through a GMF inversion, an effective and simple operational methodology has been addressed to fully evaluate the corresponding uncertainty. One of the key points of the presented methodology is precisely to provide a spatial distribution of SAR SSW speed uncertainty, moving beyond the limitations of the traditional approach to report the accuracy of SAR SSW speed in terms of summary measures, such as RMSE, MBE, and R\({}^{2}\). This result has been achieved exploiting the capability of the MS LG-Mod algorithm [40] to provide a spatial distribution of SSW direction and its uncertainty, both inferred directly from wind-induced linear patterns onto SAR amplitudes. On the strength of this coupled approach, the estimation of the whole SSW field does not depend on any external wind data source, but only from SAR derived parameters. As a consequence, SAR SSW speed may be retrieved at the same high spatial resolution as well as at the same acquisition time of the SSW direction extracted from wind-driven SAR signatures. In case of wind rows visibility in SAR imagery, the use of low spatial resolution NWP models may be avoided, especially in complex coastal areas where they can show unpredictable errors [10]. This fact allows avoidance of temporal and spatial resampling of NWP model wind data, which is a further source of errors. Hence, results obtained could mark an important step ahead towards the assessment of the suitability of high-resolution SAR data to fully describe local wind field spatial variability, also providing the spatial variations of the related wind speed and direction accuracy. Both accuracy maps are required by end users for the assimilation of satellite products, not only for modelling purposes but also for decision-making. The sensitivity analysis of the GMF-inferred SSW speed uncertainty, which clearly depends on both the uncertainties and the mean values of the actual SAR NRCS, incidence angle and SSW direction, has been carried out at various WVC dimensions, i.e., 5 km, 10 km and 15 km. The more recent C-band VV-polarised GMFs, i.e., CMOD5.N and CMOD7, have been focused on always showing a better precision and accuracy of the latter model in the estimation of SSW speed and its uncertainty. A noteworthy decrease (bettering) of SAR SSW speed uncertainty has been evidenced for an increasing WVC dimension, which is in contrast with the desired requirement of using a small spatial resolution for wind retrievals. Nevertheless, whatever the chosen GMF and the fixed WVC size, the method is able to select only SSW speed estimates with an uncertainty that is lower than a suitable threshold of acceptance as defined by the user (e.g., 2 m/s). It follows that the user may also choose the smallest WVC dimension that guarantees a minimum desired percentage of SSW speed estimates with uncertainty lower than the fixed threshold. This is another strong point of the proposed methodology exploited in an operational context. Independently from the WVC dimension and the applied GMF, both the contributions derived from the uncertainty of the NRCS and the SSW direction always appeared to be taken into account in the estimation of SAR SSW speed uncertainty. The contribution that may be ignored, especially for smaller WVC dimensions, is the one from the incidence angle uncertainty. While considering the described limits of applicability of the approach, the resulting good correlation between the wind speed and direction uncertainties derived from SAR estimations and those from the comparison SAR vs. the global ECMWF, respectively, suggests that the proposed technique may be considered valid, although an under-estimation of the former estimates with respect to latter ones was observed.