Capability of GPM IMERG Products for Extreme Precipitation Analysis over the Indonesian Maritime Continent

Ravidho Ramadhan,Marzuki Marzuki,Robi Muharsyah,Alessandro Battaglia,Wiwit Suryanto,Helmi Yusnaini,Hiroyuki Hashiguchi,Mutya Vonnisa,Sholihun Sholihun

doi:10.3390/rs14020412

Abstract

Integrated Multi-satellite Retrievals for GPM (IMERG) data have been widely used to analyze extreme precipitation, but the data have never been validated for the Indonesian Maritime Continent (IMC). This study evaluated the capability of IMERG Early (E), Late (L), and Final (F) data to observe extreme rain in the IMC using the rain gauge data within five years (2016–2020). The capability of IMERG in the observation of the extreme rain index was evaluated using Kling–Gupta efficiency (KGE) matrices. The IMERG well captured climatologic characteristics of the index of annual total precipitation (PRCPTOT), number of wet days (R85p), number of very wet days (R95p), number of rainy days (R1mm), number of heavy rain days (R10mm), number of very heavy rain days (R20mm), consecutive dry days (CDD), and max 5-day precipitation (RX5day), indicated by KGE value >0.4. Moderate performance (KGE = 0–0.4) was shown in the index of the amount of very extremely wet days (R99p), the number of extremely heavy precipitation days (R50mm), max 1-day precipitation (RX1day), and Simple Daily Intensity Index (SDII). Furthermore, low performance of IMERG (KGE < 0) was observed in the consecutive wet days (CWDs) index. Of the 13 extreme rain indices evaluated, IMERG underestimated and overestimated precipitation of nine and four indexes, respectively. IMERG tends to overestimate precipitation of indexes related to low rainfall intensity (e.g., R1mm). The highest overestimation was observed in the CWD index, related to the overestimation of light rainfall and the high false alarm ratio (FAR) from the daily data. For all indices of extreme rain, IMERG showed good capability to observe extreme rain variability in the IMC. Overall, IMERG-L showed a better capability than IMERG-E and -F but with an insignificant difference. Thus, the data of IMERG-E and IMERG-L, with a more rapid latency than IMERG-F, have great potential to be used for extreme rain observation and flood modeling in the IMC.

Highlights

This article is an open access articleSince the last decades, Earth’s extreme climate events have been exacerbated by the continuous increase of temperatures [1]
rain gauge (RG) observation showed that a large PRCPTOT of 4500 mm year−1 was observed in the western Sumatra and Kalimantan and a low PRCPTOT was observed in Bali and Nusa Tenggara (Figure 3a)
A very good capability was found in the extreme rain index, with results worsening when moving from the R85p to the R95p, the R1mm, the R10mm, and the R20mm index, whereas worse skills were observed for the extreme rain index with high rainfall intensity (R99p, R50mm, RX1day)

Summary

Introduction

Earth’s extreme climate events have been exacerbated by the continuous increase of temperatures [1]. The increasing trend of extreme rain is one aspect of extreme climate [2] and is expected to continue in all parts of the world for the following decades as projected by climate models [2,3]. The increase in both the intensity and the frequency of the extreme rain shows distinctive patterns in different regions around the distributed under the terms and conditions of the Creative Commons. The increase of the extreme rain intensity is more prevalent in comparison to the increase of the extreme rain frequency [5], with trends in the increase of the extreme rain intensity driven by the total amount of precipitation in a given region.

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