High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study

Abstract. The use of satellite sensors to infer rainfall measurements has become a widely used practice in recent years, but their spatial resolution usually exceeds 10 km, due technological limitations. This poses an important constraint on its for applications such as water resource management, index insurance evaluation or hydrological models, which require more and detailed information. In this work, the algorithm SM2RAIN (Soil Moisture Rain) estimation is applied two soil moisture products over Po River basin: high-resolution product derived from Sentinel-1, named S1-RT1, characterized by 1 km (500 m spacing), 25 (12.5 spacing) ASCAT, resampled same grid S1-RT1. order overcome need calibration allow global application, parameterized version was adopted along with standard one. capabilities estimating each obtained were then compared, assess both performances added value Sentinel-1 high resolution. results show that good estimates are obtainable when considering aggregation time steps greater than d, since low temporal sensor (from 1.5 4 d Europe) prevents application daily rainfall. On average, ASCAT-derived performs better even if equally 30 accumulated considered (resulting mean Pearson correlation 0.74 0.73, respectively). Notwithstanding this, outperform those ASCAT specific areas, like valleys inside mountain regions most plains, confirming high-spatial-resolution information obtaining spatially Finally, similar calibrated algorithm, reliability area fostering possibility apply worldwide, without availability benchmark product.