This project involved downloading and bias correcting Regional Climate Model (RCM) outputs from the EuroCordex ensemble. Firstly, RCM outputs were downloaded from the ESGF database and postprocessed to a standardised grid and time representation. Subsequently, bias correction was performed using a quantile mapping approach and ERA5-Land as the reference observational dataset. Finally, extreme variables were extracted from the dataset using the openly available CDO library to determine the effects of climate change on extreme precipitation related events (namely drought).

Morocco is a country with extremely arid areas and a complex topography. The majority of climate change related studies predict increases in temperature and generalised decreases in precipitation, however the outputs of these studies are limited in that the resolution of the climate models used is relatively low and therefore often does not pick up variation over areas of complex topography (in which much of the population live). This study therefore helps generate a higher resolution, bias corrected climate dataset. It is also important that trends in precipitation, and more importantly drought, are better understood as Morocco is highly vulnerable to water scarcity. This study therefore focuses on the impacts of climate change on extreme low precipitation, which is directly linked to water shortages and drought events. The study adds valuable new insights to climate change impact analysis in Morocco and is the first to use downscaled climate data to focus on sector wise impact. The data outputs will be located at a number of universities and government ministries in Morocco.