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The distribution of precipitation on the Tibetan Plateau (TiP) is not yet understood due to various factors. Satellite-based precipitation retrieval can provide comprehensive information in a high spatial-temporal resolution. The aim of this feasibility study is to retrieve precipitation rates over High Asia using multi-spectral data from the two geostationary (GEO) satellites Elektro-L2 and Insat-3D in a 30 minutes and 4 km resolution. The variety of spectral bands from both satellites provides an insight into the cloud properties which are associated with precipitation. In the first step, the precipitation area is delineated, and in a second step, the rates are retrieved. To this end, we use a machine learning approach (Random Forest, RF) and a precipitation product of the Global Precipitation Measurement Mission (GPM IMERG) as a reference. From this product, we use the best quality gauge calibrated microwave (MW) precipitation estimates. We validate our results with independent gauge calibrated MW precipitation. To improve the RF models, we tested various optimization schemes. The results of this study will provide information about the precipitation processes in High Asia.

Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 2: Precipitation Rates with Elektro-L2 and Insat-3D