Recent innovations in high-resolution precipitation products (HRPPs) based upon satellite observations allow unprecedented evaluations of rainfall variability over data-sparse regions. Climate assessment models driven by data from the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN), Climate Prediction Center's Morphing Method (CMORPH), and the Tropical Rainfall Measuring Mission's 3B-42 product (TRMM 3B-42) are inter-compared over regions that experienced historical extreme events to determine the robustness and skill of the HRPP-assessment pairing. Performance using high-resolution observation-based rainfall is established as a baseline for impact comparisons driven by regional, numerical weather prediction, and climate model output.