Quantifying signals and uncertainties in climate models is essential for climate change detection, attribution, prediction and projection [1][2][3] . Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain 4 , leading to low confidence in regional projections especially for precipitation over the coming decades 5, 6 . Furthermore, model simulations with tiny differences in initial conditions suggest that uncertainties may be largely irreducible due to the chaotic nature of the climate system 7-9 . However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate predictions of the last six decades project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Economía y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Skĺodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours

The tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern

The impact of climate change on Sahel precipitation suffers from large uncertainties and is strongly model-dependent. In this study, we analyse sources of inter-model spread in Sahel precipitation change by decomposing precipitation into its dynamic and thermodynamic terms, using a large set of climate model simulations. Results highlight that model uncertainty is mostly related to the response of the atmospheric circulation to climate change (dynamic changes), while thermodynamic changes are less uncertain among climate models. Uncertainties arise mainly because the models simulate different shifts in atmospheric circulation over West Africa in a warmer climate. We linked the changes in atmospheric circulation to the changes in Sea Surface Temperature, emphasising that the Northern hemispheric temperature gradient is primary to explain uncertainties in Sahel precipitation change. Sources of Sahel precipitation uncertainties are shown to be the same in the new generation of climate models (CMIP6) as in the previous generation of models (CMIP5).