AbstractThe selection of a reliable long‐term rainfall dataset is deemed appropriate for hydroclimatic assessments, especially in regions with limited distribution of rain gauge stations like Sudan. The study presents an initial investigation for gridded‐based rainfall products and satellite‐based products over Sudan using standardized statistical methods. Overall, the monthly evaluation revealed reasonable statistical agreement with in situ observations. Seasonal analysis shows that summer rainfall is detected more accurately than yearly rainfall, especially in mountainous areas across the country. Generally, underestimation was observed in all products over most regions on an annual, seasonal, and monthly scale, respectively. Results for the Taylor skill score (TSS) indicated relatively low skills for ECMWF Reanalysis 5th Generation (ERA5), moderate to strong skills for Climate Research Unit (CRU) and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), against the reference rain gauges among the regions. The regional comparison using TSS when considering monthly and seasonal timescales showed CHIRPS and CRU had the highest performance with an average percentage of 89.6 and 92% in the west (Nyala, Al Geniena, and Al Fasher), 89 and 84.6% at the central part (Khartoum, Wad Madani, and Al Obied), and 92.5 and 86.5% in the south (Al Damazine and Kadogli). At 95% confidence level, a significant increasing trend was observed over the highlands at the centre (Al Obied) and western areas (Al Geniena and Nyala), while most stations showed positive trends. Further analysis on temporal correlation with Atlantic Multidecadal Oscillation (AMO) demonstrated a strong correlation between the AMO PC1 and JJAS rainfall PC1 (82%). The west recorded the highest response to AMO (90%), while the east had the lowest response (74%), with the north, central, and south obtaining 77, 76, and 76%, respectively. Our findings provide useful information about rainfall in Sudan, suggesting CHIRPS data for monitoring rainfall variability and extreme events which should encourage its use in areas with scarce stations.