# Automated Rain Detection by Dual-Polarization Sentinel-1 Data
## 1 Introduction
However, areas associated with bright patches on the VV images are also visible as bright area on VH polarization channel and probably not due to Bragg scattering from ring waves but to enhanced roughness from splash products [17] or from scattering of hydrometeors in the melting layer [21]. These continuous studies have revealed that the complicated mechanisms of rain signatures at C-band SAR images. However, given the multiple factors intertwined on radar backscatter, it is quite challenging to figure out how strong the sensitivity of received radar backscatter to the rain rate. [PERSON] et al. [22] showed that the statistics of VV-pol NRCS significantly increases even under light rain by collocating ASCAT NRCS data with TRMM/TMI rain data and wind speed from an atmospheric model. This impact decreases with increasing wind speed. In particular, for wind speeds larger than 15 m/s and for rain rates considered in this study, the effect is found to be negligible. However, the 25-km resolution of ASCAT NRCS measurements does not allow the capture of the full complexity observed in the SAR data at high resolution [17; 23]. Recently, in a case study, [PERSON] et al. [24] compared an ENVISAT/ASAR image with weather radar data from a station in Taiwan. They found that the NRCS increases with base reflectivity up to 45 dBZ (\(\sim\)rain rate 24 mm/h) and then decreases gradually, showing a different trend from what is expected from scatterometer data. This case study, as well as the detailed study from [PERSON] et al. [23], point to the necessity of having collocated measurements with high-resolution ground-based weather radars and SARs to further investigate the relationship between NRCS and rain intensity. Apart from that, the radar backscatter under cross-polarization is not quantitatively compared to co-polarization. In this study, we take advantage of the Sentinel-1 that provides a large amount of data close to the coast in co- and cross-polarization collocated with operational weather radar stations. Based on this dataset, we aim to document the different behaviors of high-resolution co-/cross-pol NRCS in response to intensifying rain rate and wind speed. This high-resolution investigation would help to understand the wind-rain interaction and provide a reference to rain signature recognition. Moreover, according to the collocated dataset, we propose a dual-polarization filter to detect the rain signatures. The systematic detection of heterogeneity objects in SAR images not associated with meso-scale winds has been investigated by [PERSON] [25] only for single-polarization. Given the cross-pol contribution, the dual-polarization filter significantly improves the detection accuracy of rain signatures. The paper is organized as follows: In Section 2 the dataset is described. Section 3 characterizes the rain impact on SAR image with respect to rain rate, background wind speed as a function of polarization, and incidence angle. In Section 4, we propose a method to detect rain signatures based on the dual-polarization acquisitions. Section 5 presents our conclusions and perspectives.