<p>Monitoring precipitation trends and anomalies is essential for hydrological planning and risk management, particularly in vulnerable regions with sparse rain gauge networks, such as the Pindaré River Watershed (PRW) in the Northeastern Amazon biome. This study evaluates five satellite-based precipitation products to identify the most suitable dataset for precipitation analyses, applies clustering techniques to define homogeneous climatic regions, and examines precipitation anomalies and trends at multiple temporal scales. Among the satellite products assessed, CHIRPS demonstrated the highest performance compared to rain gauge data, confirming its reliability for climate studies in data-scarce regions. Consequently, CHIRPS was selected for climatic assessment, focusing on the 1981–2023 period. The clustering analysis delineated three homogeneous climatic regions, revealing significant spatial variability, with the southern PRW experiencing lower and more irregular rainfall. The Standardized Precipitation Index (SPI-6) identified strong associations between precipitation anomalies and the El Niño-Southern Oscillation (ENSO), whereby El Niño (EN) phases increased drought probabilities, while La Niña (LN) phases were linked to above-average precipitation. However, EN and LN impacts on PRW precipitation are not entirely symmetrical. Additionally, a 3-to-5-month lag was observed between ENSO events and their effects, particularly in the southern PRW. The Mann-Kendall trend analysis detected no significant annual or seasonal precipitation trends, but August and September showed a declining trend, particularly in southern regions, potentially intensifying dry season conditions and wildfire risks. These findings underscore the importance of high-resolution remote sensing products for climate monitoring and adaptive water resource management to mitigate climate variability impacts in the PRW.</p> Graphical Abstract <p>This graphical abstract provides the methodological flow and major findings of a study investigating precipitation trends and ENSO-related variability in the under-monitored Pindaré River Watershed (PRW), located in the Northeastern Amazon biome The first panel presents the study area’s location, highlighting its ecological transition between the Amazon and Cerrado biomes, low rain gauge density (1 station per 2,376&#xa0;km²), and the strategic presence of infrastructure such as the Carajás Railway. The second section compares satellite-based precipitation datasets against 17 ground-based stations using statistical metrics, including Willmott’s index (d) and mean absolute error (MAE). CHIRPS emerged as the most accurate product at both monthly and annual scales. The third section illustrates the applied data analysis phase conducted with CHIRPS dataset: clustering techniques identified three homogeneous climatic regions, and an adapted Thiessen polygon method was used for spatial delineation. Time series of the Standardized Precipitation Index (SPI-6) and Oceanic Niño Index (ONI) were jointly analyzed, revealing that El Niño events led to increased drought probabilities, while La Niña events were generally associated with above-average rainfall. However, the impacts were not symmetrical, and a lag of approximately 3 to 5 months was observed between ENSO phases and their effects on regional precipitation, especially in the southern PRW. This lag suggests delayed atmospheric responses to oceanic forcing. Finally, the Mann-Kendall trend analysis showed no significant changes in annual or seasonal rainfall, but statistically significant negative trends were detected in August and September, particularly in the southern region. These months mark the late dry season, and the observed drying tendency may intensify water scarcity and fire risk. Overall, the graphical abstract provides a concise synthesis of data sources, methodological steps, and core conclusions, offering a rapid understanding of the region hydroclimatic behavior and its sensitivity to large-scale climatic drivers.</p>