Uncertainty in numerical weather prediction (NWP) arises due to the initial state not being fully known and physical processes not being perfectly represented within the models. Precipitation is challenging to predict because it is non-linear with complex drivers from the atmosphere and so varies quickly even on a local scale. This means even advanced NWP models struggle to predict precipitation with the correct intensity at the right time or location. This study aims to explore whether machine learning (ML) can r…