A new approach for obtaining precipitation estimates with a finer spatial resolution on a daily scale based on TMPA V7 data over the Tibetan Plateau

Precipitation plays vital roles in the worldwide hydrological cycles. Gridded precipitation estimates with finer spatio-temporal resolutions are critical in various application fields. In this study, we focused on obtaining downscaled precipitation estimates (approximately1 km) at daily scale over the Tibetan Plateau (TP), which was considered as a great challenge in previous downscaling studies. To meet this challenge, a new approach, incorporating geographically ratio analysis (GRA) and spatially weighted moving window technique, was proposed. The performances of the downscaled results and those of TRMM Multisatellite Precipitation Analysis (TMPA) data were evaluated against point-based ground observations. The results indicated that: (1) the monthly downscaled results (R² around 0.70, bias around 10%) outperformed TMPA 3B43 data (R² around 0.55, bias around 25%) against ground observations; (2) the performances of the daily downscaled results (R² around 0.65, bias around 10%) were better than those of the TMPA 3B42 data (R² around 0.50, bias around 28%); and (3) the anomalies in the TMPA data did not exist in the downscaled results based on the proposed approach. Therefore, the proposed approach was suitable for obtaining both monthly and daily downscaled results based on TMPA data over the TP.