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

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.

Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales

“…High FAR value can also contribute to the high overestimation of the IMERG data compared to the rain gauge [42]. However, for extreme rain events, which are especially associated with short-term and limited spatial extent events (few km 2 ), IMERG underestimates rainfall [43,47]. IMERG current spatial resolution (10 × 10 km 2 ) will tend to smooth out extreme values of rainfall at short time scales.…”

“…Higher accuracy was observed in the season with lower rainfall, namely in JJA, and lower accuracy in the rainy season, namely DJF. One of the possible reasons is that extreme rainfall occurred more frequently in IMC during the wet season and that IMERG is less accurate in observing extreme rainfall in the tropics [37], espescially in IMC [43,47]. In addition, low CC can also be related to the high FAR value in the rainy season.…”

“…However, Wicaksana et al [45] showed that rainfall observations from AWS and MRG were in excellent agreement, with a correlation coefficient of 0.98. AWS and MRG data have been used in several studies in Indonesia [6,17,47]. A rigorous quality control procedure was carried out to ascertain the suitability of the rain gauge data used for validating GPM-IMERG.…”

“…A rigorous quality control procedure was carried out to ascertain the suitability of the rain gauge data used for validating GPM-IMERG. The validation process carried out is the same as that conducted by Ramadhan et al [47]. Missing data or outliers were not included as IMERG validation data.…”

Can GPM IMERG Capture Extreme Precipitation in North China Plain?

“…Compared to TRMM products, IMERG products have higher temporal (half-hourly) and spatial resolution (0.1 • ) and improved capability for monitoring extreme precipitation [14][15][16]. Since the release of IMERG precipitation products in 2014, many studies evaluating different versions of IMERG precipitation products have been conducted at various spatial (e.g., watersheds, countries, continents, and the globe) and temporal scales (e.g., half-hourly, hourly, daily, and monthly) [17][18][19][20][21][22][23][24][25][26].…”