# Automated Rain Detection by Dual-Polarization Sentinel-1 Data
## 5 Conclusions and Perspectives  
This study takes benefit of Sentinel-1 C-band SAR mission new capabilities that provides observations over the sea surface in both co- and cross-polarization and of the significant number of data now routinely acquired in coastal areas. Sentinel-1 images have been systematically collocated with high-resolution measurements from ground-based radar from US and Japanese networks. This unique dataset is used to document the rain impact on C-band co- and cross-polarization backscattered radar signals. We observe that in general, the radar backscattering increases with rain rate for light to moderate winds regime. However, this is not always the case for C-band, since the radar signature of rain can be positive as well as negative, i.e., it can have NRCS values, which are larger or smaller than the NRCS values of the surrounding rain--free area [14; 17; 40], explaining the variability around the mean trend (see Figure 7). This sensitivity of NRCS to rain rate is found to be more pronounced for higher incidence angles in the case of VV polarization and weak in the case of VH. For the strongest wind conditions analyzed here, the increase is found weaker, yielding to a negative contribution to the radar backscattering for co-polarization. We note that in the case of cross-polarization, the low signal-to-noise ratio observed for low wind speed regimes may have impacted our analysis. Improvements in future mission performance will certainly allow the refinement of this analysis. The filter as defined by [PERSON] [25] has been implemented on both co- and cross-polarization channels, for different resolutions. A threshold has been defined to maximize the rain detection based on the collocated dataset. We have obtained the result that the combination of the filters computed for each polarization channel at two different resolutions (VV: 400 m and VH: 800 m) improves the rain detection capability in comparison of using only co- or cross-polarization filters. The statistical analysis of NRCS behavior  
Figure 14: **(a,b)** show the S-1 maps at VV and VH at 21:08 UTC on 3 September 2019. **(c)** shows wind speed and direction from ECMWF. Rain rate provided by JMA are displayed on **(d)**. **(e)** the masks generated only by single-pol VV/VH and by our proposed algorithm. **(f)** shows NRCS along two transects inserted in SAR images. Two rectangles are overlaid on **(a,b,d)** to demonstrate the 2 area with heavy rain. **(g,h)** the masks generated only by single-pol VV/VH. **(i)** the dual-pol filter. under rain conditions has yielded the result that the detection performance is sensitive to sea-state background, rain rate, and incidence angle. This work also reveals promising results for rain detection in the cases of extreme events such as tropical cyclones. The dual-polarization filter is hopefully applied on other C-band satellite data, i.e., RADARSAT-2, yet the incidence angle differing from Sentinel-1 might gave slightly different performance. The encouraging performance of a dual-polarization filter to detect rain signatures in SAR images seems to be applicable also to other, non-rain-related features visible on SAR images, such as roll vortices [2]. Additionally, in the particular case of rain detection and segmentation, further work could be done to decipher between the various rain contributions (i.e., stratiform rain, convective rain) and the possible relationship of backscattered signal with lighting events by exploiting the full capability of SAR (for instance, by including phase information), including data from ground-based radars but also other ancillary products such as the Geostationary Global Lightning Mapper (GLM). All authors contributed to the study conception and design. Data preparation, Y.Z. ; methodology, N.L., A.M.; validation, Y.Z. ; writing--original draft preparation, Y.Z. ; writing--review and editing, N.L., A.M.; visualization, Y.Z.