Evaluating Satellite-Derived Precipitation Products for Drought Monitoring in Morocco

Meteorological drought poses significant challenges in Morocco, underscoring the need for accurate precipitation data to monitor and assess drought characteristics, particularly given the limited availability of ground-based measurements. This study evaluates the utility of two Satellite Precipitation Products (SPPs) for drought monitoring across Morocco: the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). The assessment utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) at multiple spatial and temporal scales. Ground-based monthly precipitation data from 27 stations spanning 1987 to 2017 served as the reference for evaluating the satellite-derived products. SPEIs derived from the SPPs and reanalysis data were compared with those based on ground observations to analyze drought trends and characteristics across Morocco. Performance metrics, including correlation coefficient (CC), mean error (ME), root mean square error (RMSE), relative bias, and mean absolute error (MAE), were used for evaluation. The findings show a strong correlation between satellite-derived and observed precipitation data, with low estimation errors overall, though RMSE values indicate some dispersion, particularly in mountainous regions. Both CHIRPS and PERSIANN-CDR effectively capture drought occurrences and characteristics across Morocco, albeit with slight discrepancies compared to ground-based data. PERSIANN-CDR exhibits particularly high accuracy in simulating drought events, and both products effectively illustrate the progression and trends of droughts, providing valuable tools for drought monitoring and management in Morocco.