No abstract

At the 21st session of the United Nations Framework Convention on Climate Change Conference of the Parties (COP21) in Paris, an agreement to strengthen the effort to limit the global temperature increase well below 2°C was decided. However, even if global warming is limited, some regions might still be substantially affected by climate change, especially for continents like Africa where the socio‐economic conditions are strongly linked to the climatic conditions. In the paper we will discuss the analysis of indices assigned to the sectors health, agriculture, and infrastructure in a 1.5, 2, and 3°C global warming world for the African continent. For this analysis an ensemble of 10 different general circulation model‐regional climate model simulations conducted in the framework of the COordinated Downscaling EXperiment for Africa was investigated. The results show that the African continent, in particular the regions between 15°S and 15°N, has to expect an increase in hot nights and longer and more frequent heat waves even if the global temperature will be kept below 2°C. These effects intensify if the global mean temperature will exceed the 2°C threshold. Moreover, the daily rainfall intensity is expected to increase toward higher global warming scenarios and will affect especially the African Sub‐Saharan coastal regions.

It is well established that Africa is particularly exposed to climate extremes including heat waves, droughts, and intense rainfall events. How exposed Africa is to the co-occurrence of these events is however virtually unknown. This study provides the first analysis of projected changes in the co-occurrence of five such compound climate extremes in Africa, under a low (RCP2.6) and high (RCP8.5) emissions scenario. These changes are combined with population projections for a low (SSP1) and high (SSP3) population growth scenario, in order to provide estimates of the number of people that may be exposed to such events at the end of the 21st century. We make use of an ensemble of regional climate projections from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. This ensemble comprises five different Earth System Model/Regional Climate Model (ESM/RCM) combinations with three different ESMs and two RCMs. We show that all five compound climate extremes will increase in frequency, with changes being greater under RCP8.5 than RCP2.6. Moreover, populations exposed to these changes are greater under RCP8.5/SSP3, than RCP2.6/SSP1, increasing by 47-and 12-fold, respectively, compared to the present-day. Regions of Africa that are particularly exposed are West Africa, Central-East Africa, and Northeast and Southeast Africa. Increased exposure is mainly driven by the interaction between climate and population growth, and the effect of population alone. This has important policy implications in relation to climate mitigation and adaptation. Plain Language Summary It is well known that Africa is exposed to a range of different climate hazards including droughts, heat waves, and extreme rainfall events, which cause major social and economic suffering. It is, however, largely unknown how exposed the African population is to the co-occurrence of such climate hazards. This is important because compound events will likely increase the suffering far and above that caused by individual climate hazards. In this study, we provide an analysis of potential changes in five different compound events, and the exposure of the African population to them, at the end of this century. Combining exposure to all compound events, the results show that compared to the present-day, the exposure of the African population may increase by 12-and 47-fold in the best-and worst-case scenarios, respectively. The spatial distribution of changes shows that West Africa and central and eastern regions of Africa may be particularly exposed. Increased exposure is mainly caused by the interaction between climate and population growth, and the effect of population alone. These results imply that any policy response designed to reduce exposure needs to address both climatic and socioeconomic factors.

A new ensemble of climate and climate change simulations covering all major inhabited regions with a spatial resolution of about 25 km, from the WCRP CORDEX COmmon Regional Experiment (CORE) Framework, has been established in support of the growing demands for climate services. The main objective of this study is to assess the quality of the simulated climate and its fitness for climate change projections by REMO (REMO2015), a regional climate model of Climate Service Center Germany (GERICS) and one of the RCMs used in the CORDEX-CORE Framework. The CORDEX-CORE REMO2015 simulations were driven by the ECMWF ERA-Interim reanalysis and the simulations were evaluated in terms of biases and skill scores over ten CORDEX Domains against the Climatic Research Unit (CRU) TS version 4.02, from 1981 to 2010, according to the regions defined by the Köppen–Trewartha (K–T) Climate Classification types. The REMO simulations have a relatively low mean annual temperature bias (about ± 0.5 K) with low spatial standard deviation (about ± 1.5 K) in the European, African, North and Central American, and Southeast Asian domains. The relative mean annual precipitation biases of REMO are below ± 50 % in most domains; however, spatial standard deviation varies from ± 30 % to ± 200 %. The REMO results simulated most climate types relatively well with lowest biases and highest skill score found in the boreal, temperate, and subtropical regions. In dry and polar regions, the REMO results simulated a relatively high annual biases of precipitation and temperature and low skill. Biases were traced to: missing or misrepresented processes, observational uncertainty, and uncertainties due to input boundary forcing.

Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM) chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM) is modified by dynamic downscaling with the regional model REMO in different world regions. The historical specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming, although somewhat less so by the RCM for certain regions and climate types. A common feature in regions of tropical climate types is that REMO shows dryer climate conditions than forMax Planck Institute for Meteorology-Earth System Model (MPI-ESM) for RCP 4.5 and RCP 8.5, leading to an opposing sign in the climate change signal. With an increase in radiative forcing from RCP 2.6 to RCP 8.5 and towards the end of the 21st century, some of the detected differences between GCM and RCM are more pronounced.

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$ km (0.22$$^{\circ }$$ ∘ ) versus 50$$\,\mathrm {km}$$ km (0.44$$^{\circ }$$ ∘ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

No abstract

Abstract:We investigate the reasons for the opposite climate change signals in precipitation between the regional climate model REMO and its driving earth system model MPI-ESM over the greater Congo region. Three REMO simulations following three RCP scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) are conducted, and it is found that the opposite signals, with REMO showing a decrease and MPI-ESM an increase in the future precipitation, diverge strongly as we move from a less extreme to a more extreme scenario. It has been shown that REMO simulates a much higher number of extreme rainfall events than MPI-ESM. This results in higher surface runoff and thus less soil infiltration, which leads to lower amounts of soil moisture in REMO. This further leads to less moisture recycling via evapotranspiration, which in turn results in less precipitation over the region. In the presence of a strong radiative forcing, the hydrological cycle becomes less intense in REMO and a downward trend in hydrological variables is observed. Contrary to this, the higher amounts of soil-moisture due to the lack of extreme rainfall events in MPI-ESM enhance the hydrological cycle. In the presence of strong radiative forcing, higher amounts of soil moisture result in increased evapotranspiration which in turn results in the higher amount of precipitation. It is concluded that the land-atmosphere coupling over the Congo region is very sensitive to the change in soil moisture amounts, which is likely to play a major role in global warming conditions. Therefore, adequate and improved representation of soil processes in climate models is essential to study the effects of climate change. However, the better representation of extreme rainfall events in REMO compared to OPEN ACCESSAtmosphere 2013, 4 255 MPI-ESM can be regarded as an added value of the model.