Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

Abstract

We provide an assessment of future daily characteristics of African precipitation by explicitly comparing the results of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models, specifically highlighting the similarities and inconsistencies between them. Results for seasonal mean precipitation are not always consistent amongst ensembles: in particular, global models tend to project a wetter future compared to regional models, especially over the Eastern Sahel, Central and East Africa. However, results for other precipitation characteristics are more consistent. In general, all ensembles project an increase in maximum precipitation intensity during the wet season over all regions and emission scenarios (except the West Sahel for CORE) and a decrease in precipitation frequency (under the Representative Concentration Pathways RCP8.5) especially over the West Sahel, the Atlas region, southern central Africa, East Africa and southern Africa. Depending on the season, the length of dry spells is projected to increase consistently by all ensembles and for most (if not all) models over southern Africa, the Ethiopian highlands and the Atlas region. Discrepancies exist between global and regional models on the projected change in precipitation characteristics over specific regions and seasons. For instance, over the Eastern Sahel in July–August most global models show an increase in precipitation frequency but regional models project a robust decrease. Global and regional models also project an opposite sign in the change of the length of dry spells. CORE results show a marked drying over the regions affected by the West Africa monsoon throughout the year, accompanied by a decrease in mean precipitation intensity between May and July that is not present in the other ensembles. This enhanced drying may be related to specific physical mechanisms that are better resolved by the higher resolution models and highlights the importance of a process-based evaluation of the mechanisms controlling precipitation over the region.

Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

“…Thus, this study equally utilizes the MME in examining the future changes in local precipitation extremes. Numerous studies (e.g., [69,70]) have employed the six indices (listed above) to examine changes in precipitation across various regions.…”

Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations

“…Ethiopian highlands). Additionally, even between contiguous subregions, substantial differences in observed (Dosio et al 2021a) and projected (Dosio et al 2021b) precipitation indices exist.…”

“…Nikulin et al 2012;Panitz et al 2014;Kim et al 2014;Akinsanola et al 2015;Shongwe et al 2015;Sarr et al 2015;Klutse et al 2016;Favre et al 2016;Kisembe et al 2019;Careto et al 2018;Warnatzsch andReay 2019, Tamoffo et al 2021), as well as GCM-driven ones (e.g. Laprise et al 2013;Teichmann et al 2013;Endris et al 2016Endris et al , 2019Dosio 2017;Pinto et al 2018;Dosio et al 2019Dosio et al , 2020Dosio et al , 2021bTamoffo et al 2019;Ayugi et al, 2020a, b;Mengistu et al, 2021). In particular, the ability of RCMs to add value (i.e.…”

On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems on the Simulated Summer Potential Evapotranspiration of Tropical Africa Using RegCM4

“…To facilitate the comparison between the model and observation, CRU gridded-observation and SRB reanalysis products were bi-linearly interpolated on the RegCM4-CLM45 horizontal grid. This bi-linear interpolation already used in some previous studies (Diallo et al 2013;Li et al 2015;Jia et al 2019;Libanda and Nkolola 2019;Krishnan and Bhaskaran 2020;Anwar and Diallo 2021c, d;Almazroui et al 2021;Dosio et al 2021) has been chosen since it does not impose a significant impact on the spatial distribution of climatology, trends, or biases (Wang et al 2021).…”