Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Evaluation of GPM IMERG Early, Late, and Final Run in Precipitation Estimation and their Capability in Representing Extreme Rainfall Indices in Southwestern Iran

Version 1 : Received: 17 June 2024 / Approved: 17 June 2024 / Online: 17 June 2024 (15:46:10 CEST)

A peer-reviewed article of this Preprint also exists.

Keikhosravi-Kiany, M.S.; Balling, R.C., Jr. Evaluation of GPM IMERG Early, Late, and Final Run in Representing Extreme Rainfall Indices in Southwestern Iran. Remote Sens. 2024, 16, 2779. Keikhosravi-Kiany, M.S.; Balling, R.C., Jr. Evaluation of GPM IMERG Early, Late, and Final Run in Representing Extreme Rainfall Indices in Southwestern Iran. Remote Sens. 2024, 16, 2779.

Abstract

The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM-IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Run Final (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001-2020. The Asfezari gridded precipitation data which are developed using a dense of ground-based observation were utilized as the reference dataset. The findings indicate that the IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All the three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggest that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region.

Keywords

Precipitation estimation; Extreme precipitation indices; Southwestern Iran; GPM IMERG

Subject

Environmental and Earth Sciences, Remote Sensing

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