A Nonparametric Statistical Technique for Modeling Overland TMI (2A12) Rainfall Retrieval Error

In this letter, we evaluate a nonparametric error model for Tropical Rainfall Measurement Mission (TRMM) passive microwave (PMW) rainfall (2A12) product over coverage in the southern continental United States, and assess the impact of surface soil moisture information on the model’s performance. Reference precipitation was based on high-resolution (5 min/1 km) rainfall fields derived from the NOAA/National Severe Storms Laboratory multiradar multisensor system. The error model was evaluated using a K-fold validation experiment using systematic and random error statistics of the model-adjusted TRMM Microwave Imager rainfall point estimates, and ensemble verification statistics of the corresponding prediction intervals. Results show better performance, particularly in the accuracy of the prediction intervals, when near-surface soil moisture was used as input parameter. The error model can be extended using the TRMM and Global Precipitation Measurement satellite missions’ precipitation radar rainfall and satellite soil moisture data sets to characterize globally the uncertainty of PMW products.

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