In the period 2015-2017, the Western Cape region has suffered from three consecutive years of below average rainfall-leading to a prolonged drought and acute water shortages, most prominently in the city of Cape Town. After testing that the precipitation deficit is the primary driver behind the reduced surface water availability, we undertake a multi-method attribution analysis for the meteorological drought, defined in terms of a deficit in the 3 years running mean precipitation averaged over the Western Cape area. The exact estimate of the return time of the event is sensitive to the number of stations whose data is incorporated in the analysis but the rarity of the event is unquestionable, with a return time of more than a hundred years. Synthesising the results from five different large model ensembles as well as observed data gives a significant increase by a factor of three (95% confidence interval 1.5-6) of such a drought to occur because of anthropogenic climate change. All the model results further suggest that this trend will continue with future global warming. These results are in line with physical understanding of the effect of climate change at these latitudes and highlights that measures to improve Cape Town's resilience to future droughts are an adaptation priority.

Renewable energy is key for the development of African countries, and knowing the best location for the implementation of solar and wind energy projects is important within this context. The purpose of this study is to assess the impact of climate change on solar and wind energy potential over Africa under low end (RCP2.6) and high end (RCP8.5) emission scenarios using a set of new high resolution (25 km) simulations with the Regional Climate Model version 4 (RegCM4) produced as part of the CORDEX-CORE initiative. The projections focus on two periods: (i) the near future (2021-2040) and ii) the mid-century future (2041)(2042)(2043)(2044)(2045)(2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054)(2055)(2056)(2057)(2058)(2059)(2060). The performance of the RegCM4 ensemble mean (Rmean) in simulating relevant present climate variables (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) is first evaluated with respect to the ERA5 reanalysis and satellite-based data. The Rmean reproduces reasonably well the observed spatial patterns of solar irradiance, air temperature, total cloud cover, wind speed at 100 m above the ground level, photovoltaic power potential (PVP), concentrated solar power output (CSPOUT) and wind power density (WPD) over Africa, though some biases are still evident, especially for cloud-related variables. For the future climate, the sign of the changes is consistent in both scenarios but with more intense magnitude in the middle of the century RCP8.5 scenario. Considering the energy variables, the Rmean projects a general decrease in PVP, which is more pronounced in the mid-century future and under RCP8.5 (up to 2%). Similarly, a general increase in CSPOUT (up to 2%) is projected over the continent under both the RCP2.6 and RCP8.5 scenarios. The projection in WPD shows a similar change (predominant increase) in the near and mid-century future slices under both RCPs with a maximum increase of 20%. The present study suggests that the RCP2.6 emission scenario, in general, favours the implementation of renewable energy in Africa compared to the RCP8.5.

Anthropogenic warming is projected to increase the magnitude and frequency of extreme events, whose impacts are already being felt in vulnerable regions in sub‐Saharan Africa. Solar radiation management (SRM) has been proposed as an interim measure to offset warming while emissions are reduced; however, the impact of stratospheric SRM on regional climate extremes have not yet been explored, particularly in the Paris agreement context. We investigate the potential impact of SRM on temperature and rainfall means and extremes over sub‐Saharan Africa using simulations from the Geoengineering Large Ensemble. We found SRM significantly reduces temperature means and extremes; however, the effect on precipitation is not as linear. The results should be interpreted with caution as they are particular to this approach of SRM and this modelling experiment.