The first African-led analysis of the highest resolution simulations of African climate change to date (Misiani et al 2020) show an improved simulation of the July-August (known locally as Kiremt in Ethiopia) rainfall of the South Sudan/Ethiopian region, and that global models are likely to underestimate increases in extreme rainfall under climate change.
The analysis was performed at ICPAC (IGAD Climate Prediction and Applications Centre), in collaboration with the University of Leeds, as part of the East Meets West add-on to the HyCRISTAL project. The research also found increases in wind speed at low levels in the Turkana Jet, an important feature of regional wind patterns that are already being exploited for renewable electricity.
Climate change is altering the intensity and frequency of occurrence of high-impact weather events with devastating impacts. Climate simulations show risks will continue to increase although, if rapid action to reduce emissions is taken, these risks can be minimised. Future changes will significantly impact economies across the globe, but especially in regions where critical activities are still vulnerable to climate shocks. For example, the above-normal rainfall received during the 2020 “long rains” (March-May) season extending into June – August season in the Horn of Africa region lead to extensive flooding in many countries (Somalia, Kenya, Ethiopia and South Sudan) resulting in displacement of people, disruption of transport services and left approximately 12.5 million people food insecure. Additionally, the above-normal wet conditions in the region resulted in improved breeding conditions for new dessert locust swarms which affected cropland and pasture availability.
It is therefore important to have skilful information on future climate change scenarios for adaptation and mitigation planning purposes. A major hindrance to putting in place concrete plans are the uncertainties associated with climate projections and lack of agreement amongst climate models, especially for rainfall simulations. One of the reasons for the observed biases in rainfall simulations is associated with the use of approximations (also known as convection parameterization schemes) to represent the convection processes that generate rainfall in the tropics, and which occur at scales less than the model resolution. One solution is to run the model at finer scales to enable convection to be modelled explicitly; an approach which is time-consuming and computationally intensive, but which has the prospects of increased accuracy in simulating various aspects of convection. This has only recently become computationally feasible for multi-year simulations over large domains.
The IMPALA (Improving Model Processes for African Climate) project, which is part of FCFA, made the first experimental simulations of climate change for Africa (CP4-Africa) using the convection-permitting approach. A detailed guide on how to access and use these datasets can be found in Senior, et al., 2020.
The research by Misiani, et al., 2020 uses these model runs to show how explicit convection improves the simulation of current and future climate. Other than extreme rainfall events, some of the areas where the added value was found if convection is allowed to develop explicitly includes the simulation of the number of wet days (defined as days with rainfall greater than 1mm) and in the diurnal propagation of convective features. Improvements in such characteristics of rainfall in current climate builds confidence in future climate simulations.
The CP4A simulations are from one model, run for one possible global future, with one possible future of greenhouse gas emissions: if the regional CP4A was nested inside a different global model we could see very different changes in regional rainfall accumulations in CP4A.
The results support the need for coordinated comparisons of Convection Permitting models, as is being started under the ELVIC (Climate Extremes in the Lake Victoria Basin) flagship project under CORDEX (Coordinated Regional Downscaling Experiment), and synthesis of knowledge of these models with global models such as those in the CMIP (Coupled Model Inter-Comparison Project). The resultant increased confidence in future climate simulations should inform adaptation and mitigation planning and funding for vulnerable regions.