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

==== Atlas.1.4.3 Global Model Data (CMIP5 and CMIP6) ====

<div id="h3-7-siblings" class="h3-siblings"></div>

The Atlaschapter (and the Interactive Atlas) uses global model simulations from both CMIP5 and CMIP6, mainly historical and future projections performed under ScenarioMIP ( [[#O’Neill--2016|O’Neill et al., 2016]] ). This facilitates backwards comparability and thus the detection of new salient features and findings from recent science and the latest CMIP6 ensemble. The selection of the models is based on availability of scenario data for the variables assessed in the Atlas chapter and for those included in the Interactive Atlas ( [[#Atlas.2.2|Atlas.2.2]] ). In particular, in order to harmonize the results obtained from the different scenarios as much as possible, only models providing data for the historical scenario and at least two emissions scenarios, RCP2.6, RCP4.5 and/or RCP8.5 (for CMIP5), and SSP1-2.6, SSP2-4.5, SSP3-7.0 and/or SSP5-8.5 (for CMIP6), were chosen, resulting in 29 and 35 models, respectively (see Cross-Chapter Box 1.4 for a description of the scenarios). In the Atlas chapter (similarly to the regional Chapters 11 and 12) a single simulation is taken from each model (see [[#Atlas.12|Atlas.12]] for limitations of this choice). Since the RCP and SSP emissions scenarios are not directly comparable due to different regional forcing ( [[IPCC:Wg1:Chapter:Chapter-4#4.2.2|Section 4.2.2]] ), the Atlas includes GWLs as an alternative dimension of analysis (Cross-Chapter Box 11.1), which allows intercomparison of results from different scenarios as an alternative to the standard analysis based on time slices for particular scenarios ( [[#Atlas.1.3.1|Atlas.1.3.1]] ). This dimension allows for enhanced comparability of CMIP5 and CMIP6, since it constrains the regional patterns to the same global warming level for both datasets.

Building on this information, the Interactive Atlas displays a number of (mean and extreme) indices and climatic impact-drivers (CIDs), considering both atmospheric and oceanic variables ( [[#Atlas.2.2|Atlas.2.2]] ). Some of these indices have been selected in coordination with Chapters 11 and 12, in order to support and extend the assessment performed in these chapters (see [[IPCC:Wg1:Chapter:Annex-vi|Annex VI]] for details on the indices). In order to harmonize this information, the indices have been computed for each individual model on the original model grids and the results have been interpolated to a common 2° (for CMIP5) and 1° (CMIP6) horizontal resolution grids. In addition, for the sake of comparability with CMIP6 results (in particular when using baselines going beyond 2005), the historical period of the CMIP5 and CORDEX datasets has been extended to 2006–2014 using the first years of RCP8.5-driven transient projections ( [[#Atlas.1.3.1|Atlas.1.3.1]] ). Tables listing the CMIP5 and CMIP6 models used in the Atlas and in the Interactive Atlas for different scenarios and variables are included as Supplementary Material (Tables Atlas.SM.1 and Atlas.SM.2, respectively); moreover, full inventories including details on the specific Earth System Grid Federation (ESGF) versions are given in the Atlas GitHub repository ( [[#Iturbide--2021|Iturbide et al., 2021]] ).

[[IPCC:Wg1:Chapter:Chapter-3|Chapter 3]] and [[#Flato--2013|Flato et al. (2013)]] describe the evaluation of CMIP6 and CMIP5 models, respectively, assessing surface variables and large-scale indicators. [[IPCC:Wg1:Chapter:Chapter-10#10.3.3|Section 10.3.3]] assesses the general capability of GCMs to produce climate output for regions.

Information from the existing CMIP5 and CMIP6 datasets is supplemented with downscaled regional climate simulations from CORDEX. This facilitates an assessment of the effects from higher resolution, including whether this modifies the projected climate change signals compared to global models and adds any value, especially in terms of high-resolution features and extremes.

<div id="Atlas.1.4.4" class="h3-container"></div>

<span id="atlas.1.4.4-regional-model-data-cordex"></span>