Impact of sub‐pixel rainfall variability on spaceborne precipitation estimation: evaluating the TRMM 2A25 product

Rain intensity spectra as seen by space sensors feed numerous applications at global scales ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. Rainfall variability at scales finer than what is resolved by current space sensors affects their detection capabilities, the characterization of rainfall types, as well as the quantification of rainfall rates. A high‐resolution surface rainfall product is used to evaluate the impact of rainfall variability within the field of view (FOV) of the Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The primary contribution of this study is to assess the impact of rainfall variability in terms of occurrence, types and rate at PR's pixel resolution on PR precipitation detection, classification and quantification. Several aspects of PR errors are revealed and quantified including sensitivity to non‐uniform beam filling. While the error structure of the PR is complicated because of the interaction of these factors, simple error models are developed to describe the PR performances. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors on board low Earth‐orbiting satellites such as microwave imagers and dual‐frequency radars such as with the Global Precipitation Measurement (GPM) mission.