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We use a suite of quantitative precipitation estimates (QPEs) derived fromsatellite, radar, and surface observations to derive precipitationcharacteristics over the contiguous United States (CONUS) for the period 2002–2012. This comparison effortincludes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations.Remotely sensed precipitation data sets are compared with surfaceobservations from the Global Historical Climatology Network-Daily (GHCN-D) andfrom the PRISM (Parameter-elevation Regressions on Independent SlopesModel). The comparisons are performed at the annual, seasonal, and dailyscales over the River Forecast Centers (RFCs) for CONUS. Annual average rainrates present a satisfying agreement with GHCN-D for all products over CONUS(±6%). However, differences at the RFC are more important inparticular for near-real-time 3B42RT precipitation estimates (−33 to+49%). At annual and seasonal scales, the bias-adjusted 3B42 presentedimportant improvement when compared to its near-real-time counterpart3B42RT. However, large biases remained for 3B42 over the western USA forhigher average accumulation (≥ 5 mm day<sup>−1</sup>) with respect to GHCN-D surfaceobservations. At the daily scale, 3B42RT performed poorly in capturingextreme daily precipitation (> 4 in. day<sup>−1</sup>) over the PacificNorthwest. Furthermore, the conditional analysis and a contingency analysisconducted illustrated the challenge in retrieving extreme precipitation fromremote sensing estimates

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)