Ground Validation of GPM IMERG-F Precipitation Products with the Point Rain Gauge Records on the Extreme Rainfall Over a Mountainous Area of Sumatra Island

Abstract

Accurate satellite precipitation estimates over areas of complex topography are still challenging, while such accuracy is of importance to the adoption of satellite data for hydrological applications. This study evaluated the ability of Integrated Multi-satellitE Retrievals for GPM -Final (IMERG) V06 product to observe the extreme rainfall over a mountainous area of Sumatra Island. Fifteen years of optical rain gauge (ORG) observation at Kototabang, West Sumatra, Indonesia (100.32°E, 0.20°S, 865 m above sea level), were used as reference surface measurement. The performance of IMERG-F was evaluated using 13 extreme rain indexes formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The IMERG-F overestimated the values of all precipitation amount-based indices (PRCPTOT, R85P, R95P, and R99P), three precipitation frequency-based indices (R1mm, R10mm, R20mm), one precipitation duration-based indices (CWD), and one precipitation intensity-based indices (RX5day). Furthermore, the IMERG-F underestimated the values of precipitation frequency-based indices (R50mm), one precipitation duration-based indices (CDD), one precipitation intensity-based indices (SDII). In terms of correlation, only five indexes have a correlation coefficient (R) > 0.5, consistent with Kling–Gupta Efficiency (KGE) value. These results confirm the need to improve the accuracy of the IMERG-F data in mountainous areas.

Statistical Comparison of IMERG Precipitation Products with Optical Rain Gauge Observations over Kototabang, Indonesia

“…The high overestimation of the IMERG-F data for annual rainfall is due to the overestimation of IMERG-F for light and medium rains. IMERG-F underestimates rainfall at very low intensity and extreme rainfall (Ramadhan et al, 2022). Such overestimation of annual rainfall by IMERG data was also found in Singapore (Tan & Duan, 2017).…”

“…The low correlation during the wet season may be due to higher rainfall in the tropics . The ability of IMERG to observe extreme rainfall is very low (underestimate), especially for rain > 50 mm/day (Liu et al, 2020;Ramadhan et al, 2022). Similar to CC, a lower error rate (smaller RMSE) was found during JJA (9.95 mm/day).…”

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.…”

“…Additionally, the temporal resolution of the data validated in the previous study was daily. IMERG V06 validation for one observation point in Sumatra has been carried out by Helmi et al [42] and Ramadhan et al [43]. Thus, the existing validation activities are not able to assess the overall IMERG performance for the IMC area; a comprehensive validation for the entire IMC area is timely.…”