Name
Abstract | ||
|---|---|---|
Extreme precipitation events (EPE) often cause catastrophic floods accompanied by serious economic losses and casualties. The latest version (V06) of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) provides global satellite precipitation data from 2000 at a higher spatiotemporal resolution with improved quality. It is scientifically and practically important to assess the accuracy of the IMERG V06 in capturing extreme precipitation. This study evaluates the two widely used products of IMERG during 2000-2018, i.e., IMERG late run (IMERG-L) and IMERG final run (IMERG-F), in the densely populated and flood-prone North China Plain. The accuracy of the IMERG V06 is evaluated with ground measurements from rain gauge stations at multiple scales (hourly, daily, and seasonally). A novel target tracking method is introduced to extract three-dimensional (3D) extreme precipitation events, and the near-real-time uncalibrated PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System) and GSMAP (Global Satellite Mapping of Precipitation) satellite data are added to further evaluate IMERG's performance during extreme precipitation. Finally, for flash flood events induced by extreme rainfall in the Hebei Province from 15 to 23 July 2016, the accuracy of capturing the event with IMERG-F and IMERG-L was verified. Results reveal that IMERG-F is better than IMERG-L at all investigated scales (hourly, daily, and seasonally), but the difference between the two products is less at higher time resolutions. Both products manifest decreased performance when capturing 3D extreme precipitation events, and comparatively, IMERG-F performs better than IMERG-L. IMERG-F exhibits a distinct discontinuity in extreme precipitation thresholds between land and ocean, which is a limitation of IMERG-F not documented in previous studies. Moreover, IMERG-L and IMERG-F are comparable at an hourly scale for some metrics, which is beyond the expectation that IMERG-F is notably better than IMERG-L. This study provides a scientific basis for the performance of satellite precipitation products and contributes to guiding users when applying global precipitation products. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.3390/rs14040928 | REMOTE SENSING |
Keywords | DocType | Volume |
IMERG, object tracking, extreme precipitation, North China Plain | Journal | 14 |
Issue | Citations | PageRank |
4 | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dasheng Zhang | 1 | 0 | 0.34 |
| Mingxiang Yang | 2 | 0 | 1.35 |
| Meihong Ma | 3 | 2 | 1.09 |
| Guoqiang Tang | 4 | 0 | 0.34 |
| Tsechun Wang | 5 | 0 | 1.01 |
| Xun Zhao | 6 | 0 | 0.34 |
| Suying Ma | 7 | 0 | 0.34 |
| Jin Wu | 8 | 0 | 0.34 |
| Wei Wang | 9 | 0 | 0.34 |