As a result of climate change in recent past and unsustainable land management, drought became one of the most impacting disasters and, with the projected global warming, it is expected to progressively cause more damages by the end of the 21st century. This study investigates changes in drought occurrence, frequency, and severity in Europe in the next decades. A combined indicator based on the predominance of the drought signal over normal/wet conditions has been used. The indicator, which combines the standardized precipitation index (SPI, which accounts for anomalous low rainfall), the standardized precipitation evapotranspiration index (SPEI, which accounts for high temperatures and scarce precipitations), and the reconnaissance drought indicator (RDI, similar to SPEI but more affected by extreme events), has been computed at 3‐ and 12‐month accumulation scales to characterize trends in seasonal and annual events from 1981 to 2100. Climate data from 11 bias‐adjusted high‐resolution (0.11°) simulations from the EURO‐CORDEX (coordinated regional climate downscaling experiment) have been used in the analyses. For each simulation, the frequency and severity of drought and extreme drought events for 1981–2010, 2041–2070, and 2071–2100 have been analysed. Under the moderate emission scenario (RCP4.5), droughts are projected to become increasingly more frequent and severe in the Mediterranean area, western Europe, and Northern Scandinavia, whereas the whole European continent, with the exception of Iceland, will be affected by more frequent and severe extreme droughts under the most severe emission scenario (RCP8.5), especially after 2070. Seasonally, drought frequency is projected to increase everywhere in Europe for both scenarios in spring and summer, especially over southern Europe, and less intensely in autumn; on the contrary, winter shows a decrease in drought frequency over northern Europe.

An extreme heat wave occurred in Russia in the summer of 2010. It had serious impacts on humans and natural ecosystems, it was the strongest recorded globally in recent decades and exceeded in amplitude and spatial extent the previous hottest European summer in 2003. Earlier studies have not succeeded in comparing the magnitude of heat waves across continents and in time. This study introduces a new Heat Wave Magnitude Index that can be compared over space and time. The index is based on the analysis of daily maximum temperature in order to classify the strongest heat waves that occurred worldwide during the three study periods 1980–1990, 1991–2001, and 2002–2012. In addition, multimodel ensemble outputs from the Coupled Model Intercomparison Project Phase 5 are used to project future occurrence and severity of heat waves, under different Representative Concentration Pathways, adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). Results show that the percentage of global area affected by heat waves has increased in recent decades. Moreover, model predictions reveal an increase in the probability of occurrence of extreme and very extreme heat waves in the coming years, in particular, by the end of this century, under the most severe IPCC AR5 scenario, events of the same severity as that in Russia in the summer of 2010 will become the norm and are projected to occur as often as every 2 years for regions such as southern Europe, North America, South America, Africa, and Indonesia.

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas.

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.

In this work we present the results of the application of the consortium for small-scale modeling (COSMO) regional climate model (COSMO-CLM, hereafter, CCLM) over Africa in the context of the coordinated regional climate downscaling experiment. An ensemble of climate change projections has been created by downscaling the simulations of four global climate models (GCM), namely: MPI-ESM-LR, HadGEM2-ES, CNRM-CM5, and EC-Earth. Here we compare the results of CCLM to those of the driving GCMs over the present climate, in order to investigate whether RCMs are effectively able to add value, at regional scale, to the performances of GCMs. It is found that, in general, the geographical distribution of mean sea level pressure, surface temperature and seasonal precipitation is strongly affected by the boundary conditions (i.e. driving GCMs), and seasonal statistics are not always improved by the downscaling. However, CCLM is generally able to better represent the annual cycle of precipitation, in particular over Southern Africa and the West Africa monsoon (WAM) area. By performing a singular spectrum analysis it is found that CCLM is able to reproduce satisfactorily the annual and sub-annual principal components of the precipitation time series over the Guinea Gulf, whereas the GCMs are in general not able to simulate the bimodal distribution due to the passage of the WAM and show a unimodal precipitation annual cycle. Furthermore, it is shown that CCLM is able to better reproduce the probability distribution function of precipitation and some impact-relevant indices such as the number of consecutive wet and dry days, and the frequency of heavy rain events.