Spatio-Temporal Evaluation of GPM-IMERGV6.0 Final Run Precipitation Product in Capturing Extreme Precipitation Events across Iran

Abstract

Extreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning.

Evaluation of GPM IMERG Early, Late, and Final Run in Precipitation Estimation and their Capability in Representing Extreme Rainfall Indices in Southwestern Iran

“…As with the other two non-threshold indices, IMERG-F values appeared to match the observational data quite well (Figures 15i and l). Similarly, Bakhtar et al [33] have shown that IMERG-F can successfully capture PRCPTOT over the Zagros Mountains and eastern Alborz regions in Iran. The scatterplots for PRCPTOT (Figures 16g-i) clearly show that the IMERG-F product is far better in replicating the Asfezari observational data for PRCPTOT given a much higher correlation and considerably lower bias and RMSE.…”

“…In terms of fixed threshold indices, it is clear that IMERG-F is the best of the three products tested in our study in reproducing the patterns in the Asfezari data for the fixed threshold extreme precipitation indices. The findings of Bakhtar et al [33] also suggest that IMERG-F shows a reasonable capability in capturing CDD over arid, semi-arid, and hyper-arid regions in Iran. Not surprisingly, the good performance of IMERG-F compared to other products is due to the incorporation of GPCC data for bias correction [50].…”

“…The results suggest that the IMERG product was better at detecting one-day precipitation extremes, whereas GSMaP-Gauge showed a better performance in detecting duration-based and threshold extreme precipitation indices. Bakhtar et al [33] examined the capabilities of IMERG Final Run in estimating extreme rainfall indices within Iran from 2007-2016 using daily values from a total of 281 stations. They found that the satellite product had the highest accuracy in capturing extreme precipitations in the western highlands.…”

Prioritizing Water Resources for Conservation in a Land of Water Crisis: The Case of Protected Areas of Iran

“…Previous studies emphasize the importance of protecting water resources in PAs to preserve biodiversity and their services, such as drinking water supplies [17]. On the other hand, water resources are one of the most important requirements for agricultural production [18] and food security [19] in human livelihood. However, due to increasing human demand and overexploitation, the water crisis has become one of the most important global issues, with about a quarter of the world's population facing water deficits [20,21].…”

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

“…Each of these has its strengths and weaknesses. Gauges provide the most accurate measurements, but they are geographically sparse, especially in remote areas, inaccessible topographies, and harsh climates (Akbari et al., 2022; Bakhtar et al., 2022; Ghajarnia et al., 2014; Sun et al., 2018). Moreover, gauge observations suffer from sampling errors and undercatch issues (Ehsani & Behrangi, 2021; Kidd et al., 2017; Panahi & Behrangi, 2019; Saemian et al., 2022; Song et al., 2021).…”