Assessment of GPM-Era Satellite Products’ (IMERG and GSMaP) Ability to Detect Precipitation Extremes over Mountainous Country Nepal

Bikash Nepal,Nitesh Shrestha,Deepak Aryal,Shankar Sharma,Dibas Shrestha,Mandira Singh Shrestha

doi:10.3390/atmos12020254

Abstract

The reliability of satellite precipitation products is important in climatic and hydro-meteorological studies, which is especially true in mountainous regions because of the lack of observations in these areas. Two recent satellite rainfall estimates (SREs) from Global Precipitation Measurement (GPM)-era—Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG-V06) and gauge calibrated Global Satellite Mapping of Precipitation (GSMaP-V07) are evaluated for their spatiotemporal accuracy and ability to capture extreme precipitation events using 279 gauge stations from southern slope of central Himalaya, Nepal, between 2014 and 2019. The overall result suggests that both SREs can capture the spatiotemporal precipitation variability, although they both underestimated the observed precipitation amount. Between the two, the IMERG product shows a more consistent performance with a higher correlation coefficient (0.52) and smaller bias (−2.49 mm/day) than the GSMaP product. It is worth mentioning that the monthly gauge-calibrated IMERG product yields better detection capability (higher probability of detection (POD) values) of daily precipitation events than the daily gauge calibrated GSMaP product; however, they both show similar performance in terms of false alarm ratio (FAR) and critical success index (CSI). Assessment based on extreme precipitation indices revealed that the IMERG product outperforms GSMaP in capturing daily precipitation extremes (RX1Day and RX5Day). In contrast, the GSMaP product tends to be more consistent in capturing the duration and threshold-based precipitation extremes (consecutive dry days (CDD), consecutive wet days (CWD), number of heavy precipitation days (R10mm), and number of extreme precipitation days (R25mm)). Therefore, it is suggested that the IMERG product can be a good alternative for monitoring daily extremes; meanwhile, GSMaP could be a better option for duration-based extremes in the mountainous region.

Highlights

The orographic/non-orographic precipitation classification scheme is not applied in the IMERG algorithm [80], it shows heavy precipitation around 27.7◦ N, 84.5◦ E area (Figure 3b), which is not present in GSMaPGauge (Figure 3c)
Nepal is characterized by complex topography and the inherent north–south and east–west heterogeneity of the precipitation distribution
This study assesses the spatiotemporal performance of two Global Precipitation Measurement (GPM)-era satellite rainfall estimates (SREs)

Summary

Introduction

Precipitation is the result of the complex interaction between various atmospheric components at multiple levels and scales [1]. It is highly variable in both space and time because of its discrete nature. High resolution gridded precipitation datasets aid to better understand the hydro-meteorological cycle [3]. The importance of such gridded datasets is even higher in the mountainous region where accurate measurement of precipitation is more challenging due to the inherent limitations of complex topography

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Conclusion