Abstract
The monitoring of extreme precipitation events is an important task in environmental research, but the ability of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) precipitation products to monitor extreme precipitation events remains poorly understood. In this study, three precipitation products for IMERG version 6, early-, late-, and final-run products (IMERG-E, IMERG-L, and IMERG-F, respectively), were used to capture extreme precipitation, and their applicability to monitor extreme precipitation events over Hubei province in China was evaluated. We found that the accuracy of the three IMERG precipitation products is inconsistent in areas of complex and less complex topography. Compared with gauge-based precipitation data, the results reveal the following: (1) All products can accurately capture the spatiotemporal variation patterns in precipitation during extreme precipitation events. (2) The ability of IMERG-F was good in areas of complex topography, followed by IMERG-E and IMERG-L. In areas of less complex topography, IMERG-E and IMERG-L produced outcomes that were consistent with those of IMERG-F. (3) The three IMERG precipitation products can capture the actual hourly precipitation tendencies of extreme precipitation events. (4) In areas of complex topography, the rainfall intensity estimation ability of IMERG-F is better than those of IMERG-E and IMERG-L.
Highlights
We evaluate the effectiveness of the three Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) precipitation products to monitor extreme precipitation events over
This section sought to evaluate the ability of the three IMERG precipitation products to (1) estimate the spatial distribution of precipitation on the daily scale and the temporal variation of precipitation the three IMERG precipitation products to monitor extreme precipitation events over Hu6 of 22 bei province at the hourly and daily time scales
This section sought to evaluate the ability of the three IMERG precipitation products to 1) estimate the spatial distribution of precipitation on the daily scale and the temporal variation of precipitation on the hourly scale in extreme precipitation events and 2) detect different precipitation intenon the hourly scale in extreme precipitation events and (2) detect different precipitation sity levels
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Precipitation is one of the most important meteorological variables used for investigations in the hydrological cycle context [1]. The Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) stated that extreme precipitation events over most mid-latitude land masses are becoming increasingly intense and frequent as the global mean surface temperature increases [2]. Extreme precipitation events can exert considerable social, economic, and environmental impacts. In this context, monitoring extreme precipitation events is of great significance for flood forecasting and disaster mitigation
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