资源环境科技发展态势分析平台

The assessment of precipitation over land is extremely important for a number of scientific purposes related to the mitigation of natural hazards, climate modelling and prediction, famine and disease monitoring, to cite a few. Due to the difficulties and the cost to maintain ground monitoring networks, i.e., raingauges and meteorological radars, remote sensing is receiving more and more attention in the recent decade(s). However, the accuracy of satellite observations of rainfall should be assessed with ground information as it is affected by a number of factors (topography, vegetation density, land-sea interface).

Calabria is a peninsular region in southern Italy characterized by complex topography, dense vegetation and a narrow North-South elongated shape, thus being a very challenging place for rainfall retrieval from remote sensing. In this study, we built a high-quality rainfall datasets from raingauges and meteorological radars for testing three remotely sensed rainfall products: 1) the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement product (IMERG), 2) the SM2RASC product obtained from the application of SM2RAIN (Soil Moisture TO RAIN) algorithm to the Advanced SCATterometer (ASCAT) derived satellite soil moisture data, and 3) a product derived from a simple combination of IMERG and SM2RASC. The assessment of the products is carried out at different rainfall time accumulation (e.g., from 0.5 to 24 h) for a similar to 2-year period from 10th March 2015, to 31st December 2016.

Results show that IMERG has good performance at time resolutions higher than 6 h. At daily time scale, IMERG and SM2RASC show similar results with median correlations, R, similar to 0.60, and root mean square error, RMSE, similar to 7.6 mm/day (BIAS is -0.85 and + 0.51 mm/day, respectively). The combined product outperforms the parent products (median R > 0.70, RMSE < 6.5 mm/day, BIAS -0.07 mm/day). Among the different factors affecting products quality, topographic complexity seems to play the more relevant role, particularly for SM2RASC but also for IMERG. Overall, this study shows that the investigated satellite-based products agree reasonably well with observations notwithstanding the challenging features of the region, and the combination of IMERG and SM2RASC provides a way to overcome their limitations and to produce a higher quality satellite rainfall product.