Enhancing rainfall monitoring in Nigeria: a multi-scale performance evaluation of satellite-based precipitation estimates across eco-climatic zones (1981–2019)

This study evaluates the performance of satellite-based precipitation estimates (SPEs) across Nigeria’s six eco-climatic zones, emphasizing their role in agriculture, water resource managementand ecosystem health. Due to the limitations of traditional rain gauges, remote sensing provides a viable alternative. Using daily to annual rainfall data (1981–2019) from 48 weather stations and 11 SPEs, the study combined Global Summary of the Day (GSOD) data and Inverse Distance Weighting (IDW) methods. Statistical analyses, including correlation, error metrics and compromise programming (CP), were used to evaluate SPEs performance. Results showed SPEs correlate positively with ground observations, with the strongest correlations (r = 0.96–0.99) in the Montane, Sudan and Guinea Savanna regions. CMORPH overestimated rainfall by 1.65 mm in the Tropical Wet region, while CHIRPS showed the lowest Root Mean Square Error (RMSE). GPCC, CHIRPS and PERSIANN-CDR ranked as top-performing products. These findings enhance understanding of rainfall variability in Nigeria, supporting sustainable development and climate resilience.