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Climate change, impacts and vulnerability in Europe ... - MemoFin.fr

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Changes <strong>in</strong> the climate systemBox 2.1General circulation models (GCMs) <strong>and</strong> regional climate models (RCMs)General circulation models (GCMs) are numerical models that represent key physical <strong>and</strong> chemical processes <strong>in</strong>all components of the global climate system (see Figure 2.1). GCMs are the most advanced tools for simulat<strong>in</strong>gthe response of the global climate system to different emissions scenarios for GHGs <strong>and</strong> aerosols. GCMs depictthe climate us<strong>in</strong>g a three-dimensional (3D) grid over the globe. The GCMs used <strong>in</strong> the IPCC AR4 typically simulateatmospheric processes at a horizontal resolution of between 100 <strong>and</strong> 300 km, with 20 to 60 vertical layers. Oceanprocesses were simulated at a horizontal resolution of between 20 <strong>and</strong> 200 km, with up to 30 vertical layers.Some more recent GCMs have a somewhat f<strong>in</strong>er horizontal resolution but their resolution is still quite coarserelative to the scale of exposure units <strong>in</strong> most climate impact assessments.Regional climate models (RCMs) can be used to bridge the coarse-resolution outputs <strong>fr</strong>om GCMs with thehigh‐resolution climate data needs of regional impact assessments. RCMs cover a limited area of <strong>in</strong>terest, such as<strong>Europe</strong> or an <strong>in</strong>dividual country (see Figure 2.3). They are embedded <strong>in</strong>to GCMs, which prescribe the large-scaleclimate features. RCMs typically have a horizontal resolution of between 5 <strong>and</strong> 50 km. Their higher resolutionallows for a better representation of topographic features (e.g. mounta<strong>in</strong> ranges) <strong>and</strong> of regional-scale climatephenomena. As a result they can provide better projections of <strong>change</strong>s <strong>in</strong> regional precipitation patterns <strong>and</strong> <strong>in</strong>certa<strong>in</strong> weather extremes. RCMs have been used to relate future climate <strong>change</strong> <strong>in</strong> specific locations to the currentvariability of climate with<strong>in</strong> <strong>Europe</strong>. For example, simulations with two RCMs have suggested that the climate ofthe city of London at the end of the 21st century under a high emissions scenario (SRES A2) would be similar tothe current climate <strong>in</strong> south-west France or northern Portugal, respectively (Kopf et al., 2008).Global <strong>and</strong> regional climate models have recognised weaknesses. Their simulations of past <strong>and</strong> current climateshow some deviation <strong>fr</strong>om the observed climate. Furthermore, different models provide somewhat differentclimate projections when forced with the same emissions scenario (see Section 2.1.4). Nevertheless, the scientificcommunity is confident that climate models provide credible quantitative estimates of future climate <strong>change</strong> s<strong>in</strong>cethese models are based on fundamental physical laws <strong>and</strong> are able to reproduce the key features of observedclimate <strong>change</strong>.Figure 2.3Components needed for modell<strong>in</strong>g climate <strong>change</strong> <strong>and</strong> its <strong>impacts</strong>GCMRCMGHG emission <strong>and</strong>concentration scenarios. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .<strong>Climate</strong>modelsImpactmodelsWaterAOGCM projectionsRegionalisationImpactsEnergyFoodEcosystemsHealthSource: Blaz Kurnik (EEA).Downscal<strong>in</strong>g of climate projections may be obta<strong>in</strong>ed by RCMs <strong>and</strong> the empirical-statistical downscal<strong>in</strong>g modell<strong>in</strong>g(ESDM). ESDM can effectively correct or ref<strong>in</strong>e climate variable projections provided by GCMs or RCMs <strong>and</strong> reducethe spread of projections given by a GCM/RCM ensemble. Application of ESDM is particularly beneficial to supportlocal-scale climate projections <strong>and</strong> adaptation <strong>in</strong> mounta<strong>in</strong> regions where many different precipitation regimes mayexist with<strong>in</strong> a GCM/RCM grid cell.52 <strong>Climate</strong> <strong>change</strong>, <strong>impacts</strong> <strong>and</strong> <strong>vulnerability</strong> <strong>in</strong> <strong>Europe</strong> 2012

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