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.

Access to spatio-temporally consistent precipitation data is a key prerequisite for hydrological studies, especially in data-scarce regions. Different global precipitation products offer an alternative way to estimate precipitation over areas with inadequate gauge distributions. However, before use of the datasets, the accuracy of these global estimations must be carefully studied at local and regional scale. This study evaluated 14 global precipitation products against gauge observations 2003-2012 in Karun and Karkheh basins in southwest Iran. Different categorical and statistical indices, including Kling-Gupta Efficiency (KGE), bias, correlation coefficient, and variability ratio, at varying spatial and temporal resolution were used to evaluate the products. KGE results at both daily and monthly time steps suggested that TMPA-3B42V7.0 and MERRA-2 outperformed all other products, while CMORPH-BLDV1.0 and PERSIANN-CDR was the best-performing product at daily and monthly time steps, respectively. ERA5-Land showed the highest positive bias compared with in-situ observations, particularly for mountainous southeastern parts of Karun basin. Overall, bias-adjusted products obtained by merging ground-based observations in the estimations outperformed the unadjusted versions. The spatial distribution of statistical error metrics indicated that almost all products showed their greatest uncertainties for mountainous regions, due to complex precipitation processes in these regions. These results can significantly contribute to various horological and water resources planning measures in the study region, including early flood warning systems, drought monitoring, and optimal dam operations.

Reliable assessment of Mediterranean precipitation remains challenging because gridded datasets differ in their construction, observational constraints, and representation of strong spatial variability. Although station-based studies show that precipitation characteristics and trends vary across the region, widely used gridded products have not been consistently evaluated against extensive station-derived references. Here, we assess seven products for 1981–2020 against two complementary station-derived benchmarks using mean annual precipitation, interannual variability, long-term slope, and annual maximum 1-day precipitation. The benchmarks combine published statistics from more than 23 000 stations in 27 countries with extreme precipitation records from HYADES (Archive of Yearly Maxima of Daily Precipitation Records), a global archive of annual maximum daily precipitation (RX1DAY) derived from Global Historical Climatology Network-Daily observations. After aggregation, the reference network represents 2096 grid cells and covers 52% of nondesert land cells in the study domain. Multi-Source Weighted-Ensemble Precipitation (MSWEP), Multi-Source Weather (MSWX), and the Global Precipitation Climatology Centre (GPCC) product show the most consistent performance for mean precipitation, variability, and slope. Across matched grid cells, typical product-level root-mean-square errors against the station-derived references are 60–80 mm for mean annual precipitation, 25 mm for interannual variability, and 1.5 mm yr ⁻¹ for slope. For RX1DAY, the European daily high-resolution gridded dataset (E-OBS) performs best ( R ² = 0.57), whereas the other products reach 0.18–0.30 and generally underestimate the strongest extremes. A separate analysis for 2001–20 shows stronger product agreement for precipitation changes associated with wet-day frequency than with wet-day intensity. These findings support more informed dataset selection for Mediterranean drought, flood, and water resource assessments. Significance Statement: Global datasets are widely used to study changes in Mediterranean precipitation, but they do not describe precipitation equally well. We find that Multi-Source Weighted-Ensemble Precipitation (MSWEP), Multi-Source Weather (MSWX), and Global Precipitation Climatology Centre (GPCC) best represent average conditions and year-to-year variability across the region. European daily high-resolution gridded dataset (E-OBS) captures annual daily extremes more closely than the other products, although all datasets fail to capture the strongest events. Agreement is much weaker for long-term slopes, indicating greater interproduct uncertainty in estimated temporal changes than in mean-state precipitation characteristics. These differences mean that conclusions about drought risk, flood potential, and water availability can vary depending on the dataset used. Our results support more careful dataset selection in climate assessments and practical planning for water resources and related hazards across the Mediterranean region.