Towards a Physically - Informed Projection of East African Summer Rainfall Derived from ENSO Dynamics and Teleconnections

Abstract:

The agricultural economy of East Africa is highly vulnerable to disruptions caused by climate extremes, such as prolonged droughts. The region’s summer rainfall, occurring during the months of July-August-September, is crucial to maintain the flow of the Blue Nile river as it runs from the Ethiopian Highlands. The El Nino Southern Oscillation (ENSO) is the leading cause of interannual variability of rainfall in the region, and is linked to suppressed rainfall in the region during the warm phase (El Nino). Global Climate Models (GCMs) differ widely in their ability to capture this ENSO teleconnection to East African summer rainfall (EASR). We show that differences in GCM’s ability to capture the ENSO-EASR teleconnection can be attributed to models’ ability to capture EASR rainfall couplings with atmospheric jets. Since ENSO has such a strong impact on EASR, there is a need to account for the deep uncertainties in ENSO projections when projecting local climate change impacts. However, since GCMs do not offer consistent representation of the ENSO-EASR teleconnection, this uncertainty is not meaningfully captured by standard multi-model ensemble projections. Here, we address the question of whether it is possible to leverage GCMs that do capture ENSO-EASR teleconnections to construct projections that appropriately account for ENSO-based uncertainty. We first investigate future ENSO projections across those GCMs that have superior ENSO dynamics in their historical simulations. We then generate idealized ENSO time series that are simplified representations based on ENSO theory. Finally, we merge these representations with our understanding of accurate ENSO-EASR teleconnections in order to derive a more realistic range of EASR projections under RCP 8.5.