TY - JOUR
T1 - Two-decades of GPM IMERG early and final run products intercomparison
T2 - Similarity and difference in climatology, rates, and extremes
AU - Li, Zhi
AU - Tang, Guoqiang
AU - Hong, Zhen
AU - Chen, Mengye
AU - Gao, Shang
AU - Kirstetter, Pierre
AU - Gourley, Jonathan J.
AU - Wen, Yixin
AU - Yami, Teshome
AU - Nabih, Soumaya
AU - Hong, Yang
N1 - Publisher Copyright:
© 2021
PY - 2021/3
Y1 - 2021/3
N2 - Precipitation is an essential climate and forcing variable for modeling the global water cycle. Particularly, the recent Integrated Multi-satellite Retrievals for GPM (IMERG) product retrospectively provides an unprecedented two decades of high-resolution satellite precipitation estimates. The primary goal of this study is to examine the similarities and differences between the two latest and also arguably the most popular, GPM IMERG Early and Final Run (ER and FR) products across the globe. The results reveal that: (1) ER systematically estimates 12.0% higher annual rainfall than FR, particularly over land (16.7%); (2) ER and FR show significant differences in instantaneous rates (Root Mean Squared Difference: RMSD = 2.38 mm h−1 and normalized RMSD: RMSD_norm = 1.09), especially in Africa (RMSD = 2.40 mm h−1) and hot, arid regions (RMSD_norm = 1.11), but less so in Europe (RMSD = 2.16 mm h−1) and cold areas (RMSD_norm = 0.87); and (3) ER measures 33.0% higher extreme rainfall rates than FR over the globe. The exploration of their similarities and differences provides a first-order global assessment of various hydrological utilities: FR is designed to be more suitable for retrospective hydroclimatology and water resource applications, while the earliest available ER product, though not bias-corrected by rain gauges, still shows potential utility for operational modeling of rainfall-triggered hazards. The findings of this study can provide an assessment to product developers and broader data users and practitioners to address the inherent issues in hardware limitations, retrieval algorithms, and uncertainty quantification for research and applications.
AB - Precipitation is an essential climate and forcing variable for modeling the global water cycle. Particularly, the recent Integrated Multi-satellite Retrievals for GPM (IMERG) product retrospectively provides an unprecedented two decades of high-resolution satellite precipitation estimates. The primary goal of this study is to examine the similarities and differences between the two latest and also arguably the most popular, GPM IMERG Early and Final Run (ER and FR) products across the globe. The results reveal that: (1) ER systematically estimates 12.0% higher annual rainfall than FR, particularly over land (16.7%); (2) ER and FR show significant differences in instantaneous rates (Root Mean Squared Difference: RMSD = 2.38 mm h−1 and normalized RMSD: RMSD_norm = 1.09), especially in Africa (RMSD = 2.40 mm h−1) and hot, arid regions (RMSD_norm = 1.11), but less so in Europe (RMSD = 2.16 mm h−1) and cold areas (RMSD_norm = 0.87); and (3) ER measures 33.0% higher extreme rainfall rates than FR over the globe. The exploration of their similarities and differences provides a first-order global assessment of various hydrological utilities: FR is designed to be more suitable for retrospective hydroclimatology and water resource applications, while the earliest available ER product, though not bias-corrected by rain gauges, still shows potential utility for operational modeling of rainfall-triggered hazards. The findings of this study can provide an assessment to product developers and broader data users and practitioners to address the inherent issues in hardware limitations, retrieval algorithms, and uncertainty quantification for research and applications.
KW - Climatology
KW - Early run
KW - Extremes
KW - Final run
KW - GPM IMERG
KW - Satellite
UR - https://www.scopus.com/pages/publications/85100219474
U2 - 10.1016/j.jhydrol.2021.125975
DO - 10.1016/j.jhydrol.2021.125975
M3 - Article
AN - SCOPUS:85100219474
SN - 0022-1694
VL - 594
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 125975
ER -