Editing IPCC:AR6/WGI/Chapter-Atlas (section)

=== Atlas.8.4 Assessment and Synthesis of Projections ===

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Simulations from CMIP5 and CMIP6 indicate pronounced geographical patterns and scenario dependence of the projections of mean temperature and precipitation. Global warming projected under SSP5-8.5 emissions in CMIP6 exceeds the warming projected by RCP8.5 emissions in CMIP5 ( [[IPCC:Wg1:Chapter:Chapter-4#4.3|Section 4.3]] ; [[#Forster--2020|Forster et al., 2020]] ). In selected regions in Europe CMIP6 also projects a systematically higher mean temperature than CMIP5 ( [[#Seneviratne--2020|Seneviratne and Hauser, 2020]] ). The annual mean projections from CMIP5, CMIP6 and 0.11° resolution EURO-CORDEX contained in the Interactive Atlas are shown for the four European regions in Figure Atlas.24. For each region and season a warming offset between the pre-industrial (1850–1900) and the recent past (1995–2014) baselines is also shown. The results confirm higher CMIP6 long-term annual mean warming rates for WCE, EEU and MED and a larger inter-model spread for each region. For given GWLs, regional annual mean temperature change in CMIP5 and CMIP6 are largely consistent and higher than the global average, most prominently in EEU. For high warming levels the CMIP5 subset of eight GCMs used to drive the EURO-CORDEX simulations show a lower annual mean temperature change than the full CMIP5 ensemble in each of the European sub-regions. This illustrates the large inter-model spread and implications for subsampling a relatively small subset from the full ensemble. Regional warming is strongest in continental EEU away from the Atlantic and in MED during summer ( [[#Lionello--2018|Lionello and Scarascia, 2018]] ). The assessment of EURO-CORDEX projections for levels of global warming of 1.5°C and 2.0°C indicate enhanced local warming even at relatively low global warming levels, particularly towards the north in winter ( [[#Schaller--2016|Schaller et al., 2016]] ; [[#Dosio--2018|Dosio and Fischer, 2018]] ; [[#Kjellström--2018|Kjellström et al., 2018]] ; [[#Teichmann--2018|Teichmann et al., 2018]] ).

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[[File:2d52a26cd191d9b715797c12594aba3b IPCC_AR6_WGI_Atlas_Figure_24.png]]

'''Figure Atlas.24''' '''|''' '''Regional changes over land in annual mean surface air temperature and precipitation relative to the 1995–2014 baseline for the reference regions in Europe (warming since the 1850–1900 pre-industrial baseline is also provided as an offset).''' Bar plots in the left panel of each region triplet show the median (dots) and 10th–90th percentile range (bars) across each model ensemble for annual mean temperature changes for four datasets (CMIP5 in intermediate colours; a subset of CMIP5 used to drive CORDEX in light colours; CORDEX overlying the CMIP5 subset with dashed bars; and CMIP6 in solid colours); the first six groups of bars represent the regional warming over two time periods (near-term 2021–2040 and long-term 2081–2100) for three scenarios (SSP1-2.6/RCP2.6, SSP2-4.5/RCP4.5 and SSP5-8.5/RCP8.5), and the remaining bars correspond to four global warming levels (GWLs: 1.5°C, 2°C, 3°C and 4°C). The scatter diagrams of temperature against precipitation changes display the median (dots) and 10th–90th percentile ranges for the above four warming levels for December–January–February (DJF; middle panel) and June–July–August (JJA; right panel), respectively; for the CMIP5 subset only the percentile range of temperature is shown, and only for 3°C and 4°C GWLs. Changes are absolute for temperature (in °C) and relative (as %) for precipitation. See [[#Atlas.1.3|Atlas.1.3]] for more details on reference regions ( [[#Iturbide--2020|Iturbide et al., 2020]] ) and [[#Atlas.1.4|Atlas.1.4]] for details on model data selection and processing. The script used to generate this figure is available online ( [[#Iturbide--2021|Iturbide et al., 2021]] ) and similar results can be generated in the Interactive Atlas for flexibly defined seasonal periods. Further details on data sources and processing are available in the chapter data table (Table Atlas.SM.15).

Some signatures of climate change projected by GCMs are modified by RCMs and CPRCMs. Projections of temperature, precipitation and wind in RCMs may deviate from GCM signals dependent on the dominant atmospheric circulation ( [[#Kjellström--2018|Kjellström et al., 2018]] ). In many areas RCMs produce lower warming rates and higher precipitation (less drying) in summer ( [[#Fernández--2019|Fernández et al., 2019]] ; [[#Boé--2020a|Boé et al., 2020a]] ). Also, for mean surface shortwave radiation, systematic differences between GCM and RCM outputs are found ( [[#Bartók--2017|Bartók et al., 2017]] ; [[#Gutiérrez--2020|Gutiérrez et al., 2020]] ). Although RCMs generally have a smaller bias for the present climate ( [[#Sørland--2018|Sørland et al., 2018]] ) and better cloud representation ( [[#Bartók--2017|Bartók et al., 2017]] ), the representation of aerosol forcing ( [[#Boé--2020a|Boé et al., 2020a]] ; [[#Gutiérrez--2020|Gutiérrez et al., 2020]] ), air-sea coupling ( [[#Boé--2020a|Boé et al., 2020a]] ) or vegetation response to elevated atmospheric CO <sub>2</sub> ( [[#Schwingshackl--2019|Schwingshackl et al., 2019]] ) give rise to systematic biases in RCM projections. The comparison between EURO-CORDEX and the CMIP5 subset shown in Figure Atlas.24 illustrates that the RCMs primarily modify the climate change warming signal from the driving GCMs for MED and WCE in summer ( [[#Boé--2020a|Boé et al., 2020a]] ).

Changes in precipitation clearly show a seasonal signature and a meridional gradient over Europe. Mean precipitation increases by 4–5% per °C of global warming in NEU, EEU and WCE in DJF, and decreases in summer in WCE and MED (Figure Atlas.24; [[#Jacob--2018|Jacob et al., 2018]] ). CMIP5 projections of precipitation change in MED are strongest in DJF in the south, while changes in JJA are dominant in the northern (European) part of MED ( [[#Lionello--2018|Lionello and Scarascia, 2018]] ). The European north–south gradient in precipitation response is confirmed by the EURO-CORDEX experiment ( [[#Coppola--2021a|Coppola et al., 2021a]] ), but Figure Atlas.24 shows that the JJA precipitation reduction in WCE projected by CMIP5 and CMIP6 at higher warming levels has ''low confidence'' in the CORDEX simulations. Precipitation in JJA in EEU is reduced in CMIP6, while little change is shown in CMIP5. Quantitative estimations of climate change features from regional climate projections in Eastern Europe ( [[#Partasenok--2015|Partasenok et al., 2015]] ; [[#Kattsov--2017|Kattsov et al., 2017]] ) have ''low confidence'' due to the use of relatively small ensembles of GCMs and/or RCMs, and limited evaluation of model performance in the region.

Over specific geographic features such as high mountains, RCMs further modify the climate change signal of precipitation simulated by the low-resolution GCMs ( [[#Giorgi--2016|Giorgi et al., 2016]] ; [[#Torma--2020|Torma and Giorgi, 2020]] ). This is especially true for summer precipitation over the Alps where opposite signs of changes in mean and extreme precipitation are generated by the CMIP5 GCM ensemble and the 12-km Med-CORDEX and EURO-CORDEX RCM ensembles ( [[IPCC:Wg1:Chapter:Chapter-10#10.6.4.7|Section 10.6.4.7]] ; [[#Giorgi--2016|Giorgi et al., 2016]] ).

Regional warming is ''virtually certain'' to extend the observed downward trends in snow accumulation, snow water equivalent and length of the snow cover season in NEU and at low altitudes in mountainous areas in the Alps and Pyrenees ( ''very high confidence'' ). This is supported by regional and global multi-model and/or single-model ensemble projections including CMIP5, PRUDENCE, ENSEMBLES and EURO-CORDEX ( [[#Jylhä--2008|Jylhä et al., 2008]] ; [[#Steger--2013|Steger et al., 2013]] ; [[#Mankin--2015|Mankin and Diffenbaugh, 2015]] ; [[#Schmucki--2015|Schmucki et al., 2015]] ; [[#Marty--2017|Marty et al., 2017]] ; [[#Frei--2018|Frei et al., 2018]] ), and attributed to changes in the snowfall fraction of precipitation and to increased snowmelt. In mountain areas a strong dependence of projected snow trends on altitude is shown, with most pronounced effects below 1500 m ( [[#López-Moreno--2009|López-Moreno et al., 2009]] ). [[#Terzago--2017|Terzago et al. (2017)]] showed a large positive bias in the amplitude of the annual snow cycle of EURO-CORDEX 0.11° simulations driven by GCM projections, while reanalysis-driven RCMs showed good agreement with in situ observations.

Regional ocean warming in projections with RCSMs for the Baltic and North seas ( [[#Gröger--2015|Gröger et al., 2015]] ) and for the Mediterranean ( [[#Darmaraki--2019|Darmaraki et al., 2019]] ) is associated with increased intensity and frequency of marine heatwaves in the Mediterranean ( [[IPCC:Wg1:Chapter:Chapter-12#12.4.5.5|Section 12.4.5.5]] ), strong freshening in the Baltic, and, for some simulations, changes in the circulation in response to non-uniform changes in air-sea interaction ( [[#Dieterich--2019|Dieterich et al., 2019]] ). Med-CORDEX RCSM and CMIP5 GCM results agree well on the Mediterranean SST warming rate ( [[#Mariotti--2015|Mariotti et al., 2015]] ; [[#Darmaraki--2019|Darmaraki et al., 2019]] ); see also the Interactive Atlas.

Assessments of projected changes in meteorological extremes and CIDs are reported elsewhere in this report. Extreme precipitation and temperature often exhibit a different response to global warming than mean values. Increased intensity and frequency of extreme temperatures and heatwaves is assessed in Sections 11.3.5 and 12.4.5.1. Changes in the hydrological cycle include enhanced soil moisture decline in southern Europe, drying in summer and autumn in Central Europe, and spring drought due to early snowmelt in Northern Europe (Sections 8.4.1, 11.6.5 and 12.4.5.2). Changes in mean and extreme wind are very uncertain ( [[IPCC:Wg1:Chapter:Chapter-12#12.4.5.3|Section 12.4.5.3]] ), while sea level rise will increase the frequency of occurrence of extreme sea level at most European coasts ( [[IPCC:Wg1:Chapter:Chapter-12#12.4.5.5|Section 12.4.5.5]] ).

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