Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco

Abstract Internal variability, multiple emission scenarios, and different model responses to anthropogenic forcing are ultimately behind a wide range of uncertainties that arise in climate change projections. Model weighting approaches generally used reduce the uncertainty related choice model. This study compares three multi-model combination approaches: simple arithmetic mean two recently developed weighting-based alternatives. One method takes into account models’ performance only other accounts for independence. The effect these is assessed projected changes precipitation temperature as well four extreme indices over northern Morocco. We analyze widely high-resolution ensembles issued from statistical (NEXGDDP) dynamical (Euro-CORDEX bias-adjusted Euro-CORDEX) downscaling. For latter, we also investigate potential added value bias adjustment may have raw simulations. Results show can significantly spread future projections increasing their reliability. Nearly all project significant warming studied region (more intense inland than near coasts), together with longer more severe dry periods. In most cases, methods lead almost identical spatial patterns change, indicating due strategy nearly negligible.