On the range of future Sahel precipitation projections and the selection of a sub-sample of CMIP5 models for impact studies
The future evolution of the West African Monsoon is studied by analyzing 32 CMIP5 models under the rcp8.5 emission scenario. A hierarchical clustering method based on the simulated pattern of precipitation changes is used to classify the models. Four groups, which do not agree on the simple sign of future Sahel precipitation change, are obtained. We find that the inter-group differences are mainly associated with the large spread in (1) temperature increase over the Sahara and North Atlantic and in (2) the strengthening of low and mid-level winds. A wetter Sahel is associated with a strong increase in temperature over the Sahara (>6 °C), a northward shift of the monsoon system and a weakening of the African Easterly jet. A dryer Sahel is associated with subsidence anomalies, a strengthening of the 600 hPa wind speed, and a weaker warming over the Northern Hemisphere. Moreover, the western (central) Sahel is projected to become dryer (wetter) during the first months (last months) of the rainy season in a majority of models. We propose several methods to select a sub-sample of models that captures both the ensemble mean pattern and/or the spread of precipitation changes from the full ensemble. This methodology is useful in all the situations for which it is not possible to deal with a large ensemble of models, and in particular most impact studies. We show that no relationship exists between the climatological mean biases in precipitation and temperature and the future changes in the monsoon intensity. This indicates that the mean bias is therefore not a reliable metric for the model selection. For this reason, we propose several methodologies, based on the projected precipitation changes: The “diversity” method, which consists in the selection of one model from each group is the most appropriate to capture the spread in precipitation change. The “pattern selection” method, which consists in the selection of models in a single group allows to select models for the study of a specific pattern of precipitation change, for example the one that is the most representative of the full ensemble.