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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.

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.

Discriminating climate impacts between 1.5 °C and 2 °C warming levels is particularly important for Central Africa, a vulnerable region where multiple biophysical, political, and socioeconomic stresses interact to constrain the region's adaptive capacity. This study uses an ensemble of 25 transient Regional Climate Model (RCM) simulations from the CORDEX initiative, forced with the Representative Concentration Pathway (RCP) 8.5, to investigate the potential temperature and precipitation changes in Central Africa corresponding to 1.5 °C and 2 °C global warming levels. Global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to drive the RCMs and determine timing of the targeted global warming levels. The regional warming differs over Central Africa between 1.5 °C and 2 °C global warming levels. Whilst there are large uncertainties associated with projections at 1.5 °C and 2 °C, the 0.5 °C increase in global temperature is associated with larger regional warming response. Compared to changes in temperature, changes in precipitation are more heterogeneous and climate model simulations indicate a lack of consensus across the region, though there is a tendency towards decreasing seasonal precipitation in March-May, and a reduction of consecutive wet days. As a drought indicator, a significant increase in consecutive dry days was found. Consistent changes of maximum 5 day rainfall are also detected between 1.5 °C vs. 2 °C global warming levels.

We examine the impact of +1.5 °C and +2 °C global warming levels above pre-industrial levels on consecutive dry days (CDD) and consecutive wet days (CWD), two key indicators for extreme precipitation and seasonal drought. This is done using climate projections from a multi-model ensemble of 25 regional climate model (RCM) simulations. The RCMs take boundary conditions from ten global climate models (GCMs) under the RCP8.5 scenario. We define CDD as the maximum number of consecutive days with rainfall amount less than 1 mm and CWD as the maximum number of consecutive days with rainfall amount more than 1 mm. The differences in model representations of the change in CDD and CWD, at 1.5 °C and 2 °C global warming, and based on the control period 1971−2000 are reported. The models agree on a noticeable response to both 1.5 °C and 2 °C warming for each index. Enhanced warming results in a reduction in mean rainfall across the region. More than 80% of ensemble members agree that CDD will increase over the Guinea Coast, in tandem with a projected decrease in CWD at both 1.5 °C and 2 °C global warming levels. These projected changes may influence already fragile ecosystems and agriculture in the region, both of which are strongly affected by mean rainfall and the length of wet and dry periods.

The study focuses on the analysis of extreme precipitation events of the present and future climate over southern Africa. Parametric and non-parametric approaches are used to identify and analyse these extreme events in data from the Coordinated Regional Climate Downscaling Experiment (CORDEX) models. The performance of the global climate model (GCM) forced regional climate model (RCM) simulations shows that the models are able to capture the observed climatological spatial patterns of the extreme precipitation. It is also shown that the downscaling of the present climate are able to add value to the performance of GCMs over some areas depending on the metric used. The added value over GCMs justifies the additional computational effort of RCM simulation for the generation of relevant climate information for regional application. In the climate projections for the end of twenty-first Century (2069–2098) relative to the reference period (1976–2005), annual total precipitation is projected to decrease while the maximum number of consecutive dry days increases. Maximum 5-day precipitation amounts and 95th percentile of precipitation are also projected to increase significantly in the tropical and sub-tropical regions of southern Africa and decrease in the extra-tropical region. There are indications that rainfall intensity is likely to increase. This does not equate to an increase in total rainfall, but suggests that when it does rain, the intensity is likely to be greater. These changes are magnified under the RCP8.5 when compared with the RCP4.5 and are consistent with previous studies based on GCMs over the region.

We assess the daily characteristics of recent past precipitation over Africa by means of a large ensemble of observational products, including reanalysis, gauge‐based, and satellite‐based products. The spatial distribution of seasonal mean precipitation varies considerably amongst products especially over areas where gauge networks are sparse. Large uncertainties in the annual precipitation cycle are visible in particular over the Ethiopian Highlands, the eastern Sahel, the coasts of the Gulf of Guinea, and the Horn of Africa. Interannual variability shows large differences especially amongst reanalysis data sets whereas satellite and gauge‐based products usually show more consistent results. Plain Language Summary Southern Africa and the Atlas region show the largest agreement amongst different products for most of the precipitation characteristics, including annual time series and trends, spatial and temporal correlations, and indices of mean and extreme events. Over other regions, discrepancies amongst different products are larger, especially for indices based on short time scales, in particular, over the regions affected by the monsoon (the Sahel, the coasts of the Gulf of Guinea, and Central Africa). Observed precipitation characteristics have been compared to the results of state‐of‐the‐art regional climate models (RCMs). Given the impossibility to select a single “best” observation data set for a realistic representation of all precipitation characteristics, our results show that comparing model results to a very limited set of observations is not only pointless, but it can be even misleading. When similarly large ensembles of model results and observations are compared, our findings show that RCMs are able to reproduce daily precipitation characteristics as well as the observations. Key Points Precipitation over Africa is assessed by means of a large ensemble of reanalysis, gauge‐based, and satellite‐based products Southern Africa and the Atlas region show the largest agreement amongst different products for most of the precipitation characteristics Similarly large ensembles of regional models are able to reproduce daily precipitation characteristics as well as the observations

The results of a large ensemble of regional climate models lead to two contrasting but plausible scenarios for the precipitation change over West Africa, one where mean precipitation is projected to decrease significantly over the Gulf of Guinea in spring and the Sahel in summer, and the other where summer precipitation over both regions is projected to increase. Dry and wet models show similar patterns of the dynamic and thermodynamic terms of the moisture budget, although their magnitudes are larger in the dry models. The largest discrepancies are found in the strength of the land-atmosphere coupling, with dry models showing a marked decrease in soil moisture and evapotranspiration. Some changes in precipitation characteristics are consistent for both sets of models. In particular, precipitation frequency is projected to decrease in spring over the Gulf of Guinea and in summer over the Sahel, but precipitation is projected to become more intense.

The Benue River Basin (BRB) is a major tributary of the Niger River Basin (NRB) and the second-largest river in Cameroon. It serves many water resource functions including irrigation, hydroelectricity production and navigation. Previous research has indicated that recent climate change (CC) has had significant impacts on local and regional hydrological regimes of this watershed. In this study, CC scenarios were integrated with a hydrological model to evaluate the influence of CC on water resources in the BRB. Historical and projected scenarios of dynamically downscaled temperature and precipitation from the REMO regional climate model (RCM) forced by the boundary conditions data of the Europe-wide Consortium Earth System Model (EC-ESM) and the Max Planck Institute-Earth System Model (MPI-ESM) general circulation models (GCMs) were used. The historical runs of the REMO simulations were first evaluated after which downscaled temperature and precipitation data were used as input for the HBV-Light hydrological model to simulate water balance components. The mean climate and hydrological variables for the historical (1981–2005) and the two future periods (2041–2065 and 2071–2095) were compared to assess the potential impact of CC on water resources in the middle and late twenty-first century under three greenhouse gases (GHGs) concentration scenarios, the Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. Our results show that (a) the HBV-Light hydrological model could effectively simulate the streamflow change in the BRB; (b) annual precipitation will decrease between 1 and 10% while both annual temperature and potential evapotranspiration (PET) will increase between 8–18 and 6–30%, respectively, under both scenarios, models and future periods; c) the combination of reduced precipitation and increase of PET results in a significant decrease in streamflow in the BRB (up to 51%) and this will move the basin to a much drier environmental state. Therefore, CC adaptation strategies and future development planning in this region must consider these important decreases of discharge.

Anthropogenic forcing of the climate is estimated to have increased the likelihood of the 2015-2017 Western Cape drought, also called 'Day Zero' drought, by a factor of three, with a projected additional threefold increase of risk in a world with 2 °C warming. Here, we assess the potential for geoengineering using stratospheric aerosols injection (SAI) to offset the risk of 'Day Zero' level droughts in a high emission future climate using climate model simulations from the Stratospheric Aerosol Geoengineering Large Ensemble Project. Our findings suggest that keeping the global mean temperature at 2020 levels through SAI would offset the projected end century risk of 'Day Zero' level droughts by approximately 90%, keeping the risk of such droughts similar to today's level. Precipitation is maintained at present-day levels in the simulations analysed here, because SAI (i) keeps westerlies near the South Western Cape in the future, as in the present-day, and (ii) induces the reduction or reversal of the upward trend in southern annular mode. These results are, however, specific to the SAI design considered here because using different model, different SAI deployment experiments, or analysing a different location might lead to different conclusions.

This study examines the effects of 1.5 °C and 2 °C global warming levels (GWLs) on intra-seasonal rainfall characteristics over the Greater Horn of Africa. The impacts are analysed based on the outputs of a 25-member regional multi-model ensemble from the Coordinated Regional Climate Downscaling Experiment project. The regional climate models were driven by Coupled Model Intercomparison Project Phase 5 Global Climate Models for historical and future (RCP8.5) periods. We analyse the three major seasons over the region, namely March-May, June-September, and October-December. Results indicate widespread robust changes in the mean intra-seasonal rainfall characteristics at 1.5 °C and 2 °C GWLs especially for the June-September and October-December seasons. The March-May season is projected to shift for both GWL scenarios with the season starting and ending early. During the June-September season, there is a robust indication of delayed onset, reduction in consecutive wet days and shortening of the length of rainy season over parts of the northern sector under 2 °C GWL. During the October-December season, the region is projected to have late-onset, delayed cessation, reduced consecutive wet days and a longer season over most of the equatorial region under the 2 °C GWL. These results indicate that it is crucial to limit the GWL to below 1.5 °C as the differences between the 1.5 °C and 2 °C GWLs in some cases exacerbates changes in the intra-seasonal rainfall characteristics over the Greater Horn of Africa.