Abstract. The COordinated Regional Downscaling EXperiment (CORDEX) is a diagnostic model intercomparison project (MIP) in CMIP6. CORDEX builds on a foundation of previous downscaling intercomparison projects to provide a common framework for downscaling activities around the world. The CORDEX Regional Challenges provide a focus for downscaling research and a basis for making use of CMIP6 global climate model (GCM) output to produce downscaled projected changes in regional climates and assess sources of uncertainties in the projections, all of which can potentially be distilled into climate change information for vulnerability, impacts and adaptation studies. CORDEX Flagship Pilot Studies advance regional downscaling by targeting one or more of the CORDEX Regional Challenges. A CORDEX-CORE framework is planned that will produce a baseline set of homogeneous high-resolution, downscaled projections for regions worldwide. In CMIP6, CORDEX coordinates with ScenarioMIP and is structured to allow cross comparisons with HighResMIP and interaction with the CMIP6 VIACS Advisory Board.

This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

There is a general lack of information about the potential effects of 1.5, 2 or more degrees of global warming on the regional climates within Africa, and most studies that address this use data from coarse resolution global models. Using a large ensemble of CORDEX Africa simulations, we present a pan-African overview of the effects of 1.5 and 2 • C global warming levels (GWLs) on the African climate. The CORDEX simulations, consistent with their driving global models, show a robust regional warming exceeding the mean global one over most of Africa. The highest increase in annual mean temperature is found over the subtropics and the smallest one over many coastal regions. Projected changes in annual mean precipitation have a tendency to wetter conditions in some parts of Africa (e.g. central/eastern Sahel and eastern Africa) at both GWLs, but models' agreement on the sign of change is low. In contrast to mean precipitation, there is a consistent increase in daily precipitation intensity of wet days over a large fraction of tropical Africa emerging already at 1.5 • C GWL and strengthening at 2 • C. A consistent difference between 2 • C and 1.5 • C warmings is also found for projected changes in annual mean temperature and daily precipitation intensity. Our study indicates that a 0.5 • C further warming (from 1.5 • C-2 • C) can indeed produce a robust change in some aspects of the African climate and its extremes.

We employ a large ensemble of Regional Climate Models (RCMs) from the COordinated Regional-climate Downscaling EXperiment to explore two questions: (1) what can we know about the future precipitation characteristics over Africa? and (2) does this information differ from that derived from the driving Global Climate Models (GCMs)? By taking into account both the statistical significance of the change and the models' agreement on its sign, we identify regions where the projected climate change signal is robust, suggesting confidence that the precipitation characteristics will change, and those where changes in the precipitation statistics are non-significant. Results show that, when spatially averaged, the RCMs median change is usually in agreement with that of the GCMs ensemble: even though the change in seasonal mean precipitation may differ, in some cases, other precipitation characteristics (e.g., intensity, frequency, and duration of dry and wet spells) show the same tendency. When the robust change (i.e., the value of the change averaged only over the land points where it is robust) is compared between the GCMs and RCMs, similarities are striking, indicating that, although with some uncertainty on the geographical extent, GCMs and RCMs project a consistent future. Potential added value of downscaling future climate projections (i.e., non-negligible fine-scale information that is absent in the lower resolution simulations) is found for instance over the Ethiopian highlands, where the RCM ensemble shows a robust decrease in mean precipitation in contrast with the GCMs results. This discrepancy may be associated with the better representation of topographical details that are missing in the large scale GCMs. The impact of the heterogeneity of the GCM-RCM matrix on the results has been also investigated; we found that, for most regions and indices, where results are robust or non-significant, they are so independently on the choice of the RCM or GCM. However, there are cases, especially over Central Africa and parts of West Africa, where results are uncertain, i.e. most of the RCMs project a statistically significant change but they do not agree on its sign. In these cases, especially where results are clearly clustered according to the RCM, there is not a simple way of subsampling the model ensemble in order to reduce the uncertainty or to infer a more robust result.

We examine the ability of an ensemble of 10 Regional Climate Models (RCMs), driven by ERA-Interim reanalysis, in skillfully reproducing key features of present-day precipitation and temperature (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) over West Africa. We explore a wide range of time scales spanning seasonal climatologies, annual cycles and interannual variability, and a number of spatial scales covering the Sahel, the Gulf of Guinea and the entire West Africa. We find that the RCMs show acceptable performance in simulating the spatial distribution of the main precipitation and temperature features. The occurrence of the West African Monsoon jump, the intensification and northward shift of the Saharan Heat Low (SHL), during the course of the year, are shown to be realistic in most RCMs. They also capture the mean annual cycle of precipitation and temperature, including, single and double-peaked rainy seasons, in terms of timing and amplitude over the homogeneous sub-regions. However, we should emphasize that the RCMs exhibit some biases, which vary considerably in both magnitude and spatial extent from model to model. The interannual variability of seasonal anomalies is best reproduced in temperature rather than precipitation. The ensemble mean considerably improves the skill of most of the individual RCMs. This highlights the importance of performing multi-model assessment in properly estimating the response of the West African climate to global warming at seasonal, annual and interannual time scales.

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Results from an 25 regional climate model simulations from the Coordinated Regional Downscaling Experiment Africa initiative are used to assess the projected changes in temperature and precipitation over southern Africa at two global warming levels (GWLs), namely 1.5 • C and 2.0 • C, relative to pre-industrial values, under the Representative Concentration Pathway 8.5. The results show a robust increase in temperature compared to the control period ranging from 0.5 • C-1.5 • C for the 1.5 • C GWL and from 1.5 • C-2.5 • C, for the 2.0 • C GWL. Areas in the south-western region of the subcontinent, covering South Africa and parts of Namibia and Botswana are projected to experience the largest increase in temperature, which are greater than the global mean warming, particularly during the September-October-November season. On the other hand, under 1.5 • C GWL, models exhibit a robust reduction in precipitation of up to 0.4 mm day −1 (roughly 20% of the climatological values) over the Limpopo Basin and smaller areas of the Zambezi Basin in Zambia, and also parts of Western Cape, South Africa. Models project precipitation increase of up to 0.1 mm day −1 over central and western South Africa and in southern Namibia. Under 2.0 • C GWL, a larger fraction of land is projected to face robust decreases between 0.2 and 0.4 mm day −1 (around 10%-20% of the climatological values) over most of the central subcontinent and parts of western South Africa and northern Mozambique. Decreases in precipitation are accompanied by increases in the number of consecutive dry days and decreases in consecutive wet days over the region. The importance of achieving the Paris Agreement is imperative for southern Africa as the projected changes under both the 1.5 • C, and more so, 2.0 • C GWL imply significant potential risks to agricultural and economic productivity, human and ecological systems health and water resources with implied increase in regional water stresses.

We analyze the potential effect of global warming levels (GWLs) of 1.5 • C and 2 • C above pre-industrial levels (1861−1890) on mean temperature and precipitation as well as intra-seasonal precipitation extremes over the Greater Horn of Africa. We used a large, 25-member regional climate model ensemble from the Coordinated Regional Downscaling Experiment and show that, compared to the control period of 1971−2000, annual mean near-surface temperature is projected to increase by more than 1 • C and 1.5 • C over most parts of the Greater Horn of Africa, under GWLs of 1.5 • C and 2 • C respectively. The highest temperature increases are projected in the northern region, covering most parts of Sudan and northern parts of Ethiopia, and the lowest temperature increases are projected over the coastal belt of Tanzania. However, the projected mean surface temperature difference between 2 • C and 1. 5 • C GWLs is higher than 0.5 • C over nearly all land points, reaching 0.8 • C over Sudan and northern Ethiopia. This implies that the Greater Horn of Africa will warm faster than the global mean.While projected changes in precipitation are mostly uncertain across the Greater Horn of Africa, there is a substantial decrease over the central and northern parts of Ethiopia. Additionally, the length of dry and wet spells is projected to increase and decrease respectively. The combined effect of a reduction in rainfall and the changes in the wet and dry spells will likely impact negatively on the livelihoods of people within the coastal cities, lake regions, highlands as well as arid and semi-arid lands of Kenya, Tanzania, Somalia, Ethiopia and Sudan. The probable impacts of these changes on key sectors such as agriculture, water, energy and health sectors, will likely call for formulation of actionable policies geared towards adaptation and mitigation of the impacts of 1.5 • C and 2 • C warming.