Multiscale evaluation of gridded precipitation and temperature in the High Atlas (Morocco)

ABSTRACT This study presents a multiscale evaluation of five gridded climate products, ERA5-Land, TerraClimate, CHIRPS, CHIRTS, and PERSIANN CCS-CDR, over the semiarid topographically complex High Atlas Mountains of Morocco. Using observations from nine ground stations, performance was assessed at daily, monthly, and annual scales through correlation coefficient, RMSE, bias, and MAE metrics. Results reveal substantial spatial and temporal variability in accuracy. ERA5-Land consistently achieved the highest agreement with observations (CC = 0.92–0.99 for temperature), attributed to its multisource data assimilation framework. TerraClimate also performed well, particularly for temperature and monthly precipitation, benefiting from hybrid downscaling and elevation correction. In contrast, satellite-based products exhibited pronounced systematic biases, including precipitation overestimation (+110% for CHIRPS), underestimation (−34% for PERSIANN CCS-CDR), and significant temperature biases for CHIRTS, especially at high-altitude stations. Spatial analysis confirmed a consistent decline in performance with increasing elevation, underscoring the limitations of both reanalysis and satellite-based estimation in mountainous terrain. These findings stress the importance of bias correction and careful dataset selection for hydrological, agricultural, and climate change applications. More broadly, this work offers a transferable evaluation framework for data-scarce, topographically complex regions, providing actionable guidance for researchers, water managers, and policymakers supporting climate adaptation strategies.