Data and trained models — Deep-learning statistical downscaling of daily precipitation over West Africa

Supporting data and trained model weights for the study on deep-learning statistical downscaling of daily precipitation over West Africa (ERA5 0.25° → IMERG 0.1°, factor 2.5×), submitted to Environmental Data Science (Cambridge University Press). Files: arrays_01deg.npz — cached model outputs and IMERG observations on the 0.1° evaluation grid (7 configurations + observations), allowing reproduction of all figures and metric tables without re-running the networks. weights.zip — the six trained PyTorch models (U-Net Simple/SE/CBAM and their cGAN-fine-tuned variants). The replication code is available on GitHub: github.com/sagna1/downscaling-westafrica-eds. Raw predictors (ERA5) and target (IMERG Final Run V06) are openly available from the C3S Climate Data Store and NASA GES DISC respectively.