Abstract
In the framework of the coordinated regional climate downscaling experiment (CORDEX), an ensemble of climate change projections for Africa has been created by downscaling the simulations of four global climate models (GCMs) by means of the consortium for small-scale modeling (COSMO) regional climate model (RCM) (COSMO-CLM, hereafter, CCLM). Differences between the projected temperature and precipitation simulated by CCLM and the driving GCMs are analyzed and discussed. The projected increase of seasonal temperature is found to be relatively similar between GCMs and RCM, although large differences (more than 1 °C) exist locally. Differences are also found for extreme-event related quantities, such as the spread of the upper end of the maximum temperature probability distribution function and, in turn, the duration of heat waves. Larger uncertainties are found in the future precipitation changes; this is partly a consequence of the inter-model (GCMs) variability over some areas (e.g. Sahel). However, over other regions (e.g. Central Africa) the rainfall trends simulated by CCLM and the GCMs show opposite signs, with CCLM showing a significant reduction in precipitation at the end of the century. This uncertain and sometimes contrasting behaviour is further investigated by analyzing the different models’ response to the land–atmosphere interaction and feedback. Given the large uncertainty associated with inter-model variability across GCMs and the reduced spread in the results when a single RCM is used for downscaling, we strongly emphasize the importance of exploiting fully the CORDEX-Africa multi-GCM/multi-RCM ensemble in order to assess the robustness of the climate change signal and, possibly, to identify and quantify the many sources of uncertainty that still remain.
Highlights
As one of the most vulnerable regions to weather and climate variability (IPCC 2007), Africa was selected as the first target region for the World Climate Research Programme CORDEX (Giorgi et al 2009), which aims to foster international collaboration to generate an ensemble of high-resolution historical and future climate projections at regional scale, by downscaling the global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) (Taylor et al 2012).In order to properly simulate the climate of such a large and heterogeneous continent, models need to replicate correctly the many physical processes and their complex feedback over multiple temporal and spatial scales
Mariotti et al (2014) suggested that GCMs and regional climate model (RCM) discrepancies may arise from the difference in the representation of the large-scale circulation (e.g. African Easterly Waves), other studies showed that the different climate sensitivity between GCMs and RCMs is related to local processes, rather than being the effect of the boundary conditions; in particular, local processes linked to land–atmosphere interaction and parameterization play a relevant role in the simulation of e.g. the precipitation trend under global warming
In order to analyze the relationship between soil moisture and precipitation anomalies, and the different models’ response, we focus on three regions where: (a) COSMO-CLM RCM (CCLM) and GCM show a consistent and unambiguous precipitation trend (SA_E in JAS, see Table 2); (b) CCLM and the GCMs show a markedly different sign of the precipitation climate change signal (CA_SH in JFM); (c) both CCLM and GCMs show large uncertainties in the sign of the precipitation signal (WA_N in JAS)
Summary
As one of the most vulnerable regions to weather and climate variability (IPCC 2007), Africa was selected as the first target region for the World Climate Research Programme CORDEX (coordinated regional climate downscaling experiment) (Giorgi et al 2009), which aims to foster international collaboration to generate an ensemble of high-resolution historical and future climate projections at regional scale, by downscaling the global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) (Taylor et al 2012). Mariotti et al (2014) suggested that GCMs and RCMs discrepancies may arise from the difference in the representation of the large-scale circulation (e.g. African Easterly Waves), other studies showed that the different climate sensitivity between GCMs and RCMs is related to local processes, rather than being the effect of the boundary conditions; in particular, local processes linked to land–atmosphere interaction and parameterization play a relevant role in the simulation of e.g. the precipitation trend under global warming. This aspect will be analyzed in detail.
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