A Spatial‐Temporal Extreme Precipitation Database from GPM IMERG. Issue 19 (15th October 2019)

• Record Type: Journal Article
• Authors: Zhou, Yaping; Nelson, Kevin; Mohr, Karen I.; Huffman, George J.; Levy, Robert; Grecu, Mircea
• Is Part Of: Journal of geophysical research. Volume 124:Issue 19(2019)
• Page Start: 10344
• Page End: 10363
• Publication Date: 2019-10-15
• Subjects: Extreme precipitation -- event -- climate -- IMERG -- CONUS; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2019JD030449
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Extreme precipitation events (EPEs) have the potential to create catastrophic flooding, landslides, and infrastructure damage. We diagnose the spatial and temporal characteristics of EPEs by using the Integrated Multi‐SatellitE Retrievals for Global Precipitation Measurement mission (GPM; IMERG) precipitation estimates to construct spatial‐temporal ( xy‐t ) EPEs that depict both the spatial extent and temporal evolution of precipitation systems. EPEs were constructed using a recursive‐fractal approach to classify the precipitating grids across space and time as belonging to the same system, thus identifying events. This classification enables the accurate depiction of duration, areal coverage, total volume, and propagation of each EPE over its entire life cycle. Results from 4 years of IMERG statistics over the contiguous United States show that the most frequent EPEs have duration between 3 and 6 hr, an affected area of 10 3 –5 × 10 4 km 2, and a total precipitation volume of 10 6 –10 8 m 3 . Spatially, EPEs occur most frequently in the northwest and northeast in the winter and spring and the southwest and southeast in summer. Fall has the least number of EPEs, and summer exhibits some of the heaviest and largest precipitation events. The diurnal cycle in frequency and precipitation volume is most prominent in summer, weaker in spring and fall, and is not discernible in winter, especially for events lasting fewer than 6 hr. The event propagation speeds indicate the influence of large‐scale circulations as winter events tend to move faster than those in the other seasons. Key Points: A spatial‐temporal extreme precipitation event (EPE) database is generated from high‐resolution IMERG data The database allows analyses of many event‐based precipitation characteristics that conventional data sets are unable to provide Results from CONUS show spatial/seasonal distributions of EPEs, as well as many other characteristics over different seasons