Representation of Extreme Precipitation in High-Resolution, Long-Period-of-Record Precipitation Datasets over the Continental United States
Journal Article
Overview
abstract
Abstract; Extreme precipitation is a highly impactful phenomena, the observation and prediction of which underpin many pressing societal planning and response needs. Rigorous, confident understanding of extreme precipitation and its risks, hazards, and potential impacts (e.g., floods, landslides) requires precipitation data with high resolution and a sufficiently long period of record. Many applications also require low-latency data with global coverage. We examine six precipitation datasets to characterize the representation of extreme precipitation over the continental United States. The Analysis of Record for Calibration (AORC), version 1.1, Stage IV, and CONUS404 provide 4-km hourly precipitation estimates over the CONUS only, while Integrated Multi-satellitE Retrievals for GPM (IMERG) V07 (both early and final) and Multisource Weighted-Ensemble Precipitation, version 2.8 (MSWEP), are 10-km resolution global datasets with 30-min and 3-h time steps, respectively. The global precipitation products struggle to capture extreme precipitation, especially that produced by warm-season convection; IMERG also exhibited spurious events with much higher precipitation than any other dataset, often during West Coast atmospheric rivers. Stage IV and AORC were generally similar to one another, although Stage IV also revealed artifacts in the western United States due to poor radar coverage and missing hourly data. CONUS404 is the only nonobservational dataset included in this study, and while it seems to capture the climatology of extreme precipitation over the CONUS fairly well, it does not reproduce the observed spatial representation of many individual events. This work provides an important foundation from which to further contextualize the representation of extreme precipitation in contemporary, frequently used datasets.; ; Significance Statement; Many U.S. agencies are producing or improving products related to extreme precipitation and its impacts, which require precipitation information with high spatiotemporal resolution and long periods of record. This study examines the representation of extreme precipitation in six datasets meeting these criteria, including the climatological spatial distribution of precipitation extremes, upper quantiles of the precipitation distribution, and case studies. This work provides a critical foundation for a better understanding of our confidence in extreme precipitation estimates as functions of region, season, and/or storm type. Improving how extreme precipitation estimates are understood and used by scientists and stakeholders translates to better forecasts, preparation, and resilience.;
