An ensemble climate projection for Africa

Abstract

of the RCMs are often different than the driving GCMs and arguably more credible given the improved performance of the RCM. This also suggests that local climate forcing will be a significant driver of the regional response to climate change over Africa.

Projection of temperature and heat waves for Africa with an ensemble of CORDEX Regional Climate Models

“…Haensler et al 2013;Laprise et al 2013;Buontempo et al 2014;Giorgi et al 2014), they are not, to our knowledge, publicly available through the Earth System Grid Federation (ESGF) server, and, consequently, they are not used in this study.…”

“…When using Regional Climate Models (RCMs) to dynamically downscale the projections of the global models, the GCMs' simulation skills are not always improved, especially for the general characteristics of the mean climatology; however added value is found especially in the fine scales and in the ability of RCM to simulate extreme events (e.g. Kim et al 2002;Diallo et al 2012;Paeth and Mannig 2012;Diaconescu and Laprise 2013;Crétat et al 2013;Haensler et al 2013;Laprise et al 2013;Buontempo et al 2014;Giorgi et al 2014;.…”

“…Many works have since then focused on the analysis of present day climatology (e.g. Nikulin et al 2012;Endris et al 2013;Kalognomou et al 2013;Kim et al 2014;Krähenmann et al 2013;Gbobaniyi et al 2014; and future projections Teichmann et al 2013;Giorgi et al 2014;Buontempo et al 2014;Mariotti et al 2014;Pinto et al 2015;Diallo et al 2016). However, all these studies focused mainly on precipitation and mean temperature, and only Giorgi et al (2014) provided explicit projections of heat waves duration, although based on the results of a single RCM.…”

Multimodel ensemble simulations of present and future climates over West Africa: Impacts of vegetation dynamics

“…The models' disagreement remains unresolved in phase 5 of the coupled model intercomparison project (CMIP5) despite significant improvements of the models in many aspects [IPCC, 2013;Nicholson, 2013;Biasutti, 2013]. On the other hand, Regional Climate Models (RCMs) tend to produce more consistent projections for WA, in spite of the considerable disagreements among the driving GCMs [Patricola and Cook, 2010;Buontempo et al, 2015;Dosio and Panitz, 2016]. This is mainly attributed to the RCMs physics dominating over the signal imposed by large-scale forcing over WA, and to a lesser extent, the coarse representation of surface conditions in the GCMs being unable to capture the heterogeneous topography, land cover, and For RCM applications, the common approach of prescribing a static land cover is considered a major limitation.…”

The WASCAL high-resolution regional climate simulation ensemble for West Africa: concept, dissemination and assessment

“…They showed an annual mean temperature increase of around 1.3 • C in the Volta region, significantly exceeding the interannual variability, and a mean annual change in precipitation from −20 to +50 %. While an individual model run can provide a plausible representation of the future under a given climate change scenario, it does not allow an estimate of the range of outcomes expected for the assessment of risks and opportunities (Buontempo et al, 2015). Further, large uncertainties and errors are associated with the result of each model run as a consequence of imperfect initial conditions, with the model being an imperfect abstraction of reality, and from numerical errors and artifacts accumulating in long-term simulations (for example, Laprise, 2003;Park et al, 2014).…”