East African population exposure to precipitation extremes under 1.5 °C and 2.0 °C warming levels based on CMIP6 models. (1st April 2022) - Ayugi, Brian; Jiang, Zhihong; Iyakaremye, Vedaste; Ngoma, Hamida; Babaousmail, Hassen; Onyutha, Charles; Dike, Victor Nnamdi; Mumo, Richard; Ongoma, Victor
Abstract: Understanding population exposure to precipitation-related extreme events is important for effective climate change adaptation and mitigation measures. We analyze extreme precipitation using indices (EPIs), including consecutive dry days (CDD), annual total precipitation, simple daily intensity, and the number of extremely wet days, under the past and future climatic conditions over East Africa. The exposure of the East African population to these extreme events at 1.5 °C and 2.0 °C global warming levels (GWLs) is analyzed based on Climate Model Intercomparison Project phase 6 models. Exposure is computed from extremely wet and dry days (R95p and CDD, respectively). Under both GWLs, EPIs (except CDD) averaged over East Africa are projected to increase under the Shared Socio-economic Pathways (SSP)2-4.5 and SSP5-8.5 scenarios. The largest increase in wet events will likely occur in eastern and northern Kenya. The results also reveal an intensification of precipitation extremes over Burundi, Rwanda, and some parts of Uganda. However, small changes are expected over most parts of Kenya and Tanzania. Examination of population exposure to EPIs shows that the most prominent and net intense occurrence is over Burundi, Rwanda, and some parts of Uganda. In contrast, less change is noted to occur over vast parts of Kenya and Tanzania. Meanwhile, limiting the warming target to less than 1.5 °C but not more than 2.0 °C has 37% (44.2%) and 92% (4%) less impact on the occurrence of EPIs for R95p (CDD) under SSP2-4.5 (SSP5-8.5) scenarios, respectively. The study establishes that future exposure is predominantly driven by changes in population compared to other factors such as climate or concurrent changes in climate and population (the nonlinear interaction effect). For instance, climate effects are anticipated to contribute ∼10.6% (12.6%) of the total change in population exposure under 1.5 °C (2.0 °C) warming levels, while population and interaction effects are expected to contribute ∼77.4% (71.9%) and 12% (15.5%), respectively, under 1.5 °C (2.0 °C) scenarios. Interestingly, the projected changes in regional exposure due to the interaction effects under SSP2-4.5 are greater than the climate effect, while the reverse pattern is observed under SSP5-8.5. For example, under SSP5-8.5, climate effects for 1.5 °C and 2.0 °C are larger (after population effect) with ∼3.8 × 10 5 (15.7%) and ∼6.1 × 10 5 (17.5%) billion person-mm, respectively. The high exposure noted over East Africa calls for a shift in policies to instate suitable adaptation measures to cushion the already vulnerable population.