Editing IPCC:AR6/SROCC/Chapter-1 (section)

==== 1.8.1.3 Model Simulation Data ====

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Models are numerical approximations of the Earth system that allow hypotheses about the mechanisms of ocean and cryosphere change to be tested, support attribution of observed changes to specific forcings (Section 1.3), and are the best available information for assessing future change (Figure 1.3). General Circulation Models (GCMs) typically simulate the atmosphere, ocean, sea ice, and land surface, and sometimes also incorporate terrestrial and marine ecosystems. Earth System Models (ESM) are climate models that explicitly include the carbon cycle and may include additional components (e.g., atmospheric chemistry, ice sheets, dynamic vegetation, nitrogen cycle, but also urban or crop models). The systematic set of global-scale model experiments (Taylor et al., 2012 <sup>[[#fn:r414|414]]</sup> ) used in SROCC were produced by CMIP5 (Cross-Chapter Box 1 in Chapter 1), including both GCMs and ESMs.

Models may differ in their spatial resolution, and in the extent to which processes are explicitly represented or approximated (parameterised). Model output can be biased due to uncertainties in their physical equations or parameterisations, specification of initial conditions, knowledge of external forcing factors, and unaccounted processes and feedbacks (Hawkins and Sutton, 2009 <sup>[[#fn:r415|415]]</sup> ; Deser et al., 2012 <sup>[[#fn:r416|416]]</sup> ; Gupta et al., 2013 <sup>[[#fn:r417|417]]</sup> ; Lin et al., 2016 <sup>[[#fn:r418|418]]</sup> ). Since AR5 there have been advances in modelling the dynamical processes of the Greenland and Antarctica ice sheets, leading to better representation of the range of potential future sea level rise scenarios (Sections 4.2.3). Downscaling, including the use of regional models, makes it possible to improve the spatial resolution of model output in order to better resolve past and future climate change in specific areas, such as high mountains and coastal seas (e.g., Sections 2.2.2, 3.2.3, 3.5.4, 4.2.2, 6.3.1). For biological processes, such as nutrient levels and organic matter production, model uncertainty at regional scales is the main issue limiting confidence in future projections (Sections 5.3, 5.7). While model projections of range shifts for fishes agree with theory and observations, at a regional scale there are known deficiencies in the ways models represent the impacts of ocean variables such as temperature and productivity (Sections 5.2.3, 5.7).

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'''Figure 1.3'''

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'''Figure 1.3 | Illustrative examples of the availability of ocean and cryosphere data relative to the major time periods assessed in the Special Report on the Oceans and Cryosphere in a Changing Climate (SROCC). Upper panel; observed (Keeling et al., 1976) and reconstructed (Bereiter et al., 2015) atmospheric CO2 concentrations, as well as the Representative […]'''
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Figure 1.3 | Illustrative examples of the availability of ocean and cryosphere data relative to the major time periods assessed in the Special Report on the Oceans and Cryosphere in a Changing Climate (SROCC). Upper panel; observed (Keeling et al., 1976 <sup>[[#fn:r425|425]]</sup> ) and reconstructed (Bereiter et al., 2015 <sup>[[#fn:r426|426]]</sup> ) atmospheric CO2 concentrations, as well as the Representative Concentration Pathways (RCPs) of CO2 for low (RCP2.6) and high (RCP8.5) future emission scenarios (van Vuuren et al., 2011a <sup>[[#fn:r427|427]]</sup> ; Cross-Chapter Box 1 in Chapter 1). Lower panel; illustrative examples of data availability for the ocean and cryosphere (Section 1.8.1; Taylor et al., 2012 <sup>[[#fn:r428|428]]</sup> ; Boyer et al., 2013 <sup>[[#fn:r429|429]]</sup> ; Dowell et al., 2013 <sup>[[#fn:r430|430]]</sup> ; McQuatters-Gollop et al., 2015 <sup>[[#fn:r431|431]]</sup> ; Raup et al., 2015 <sup>[[#fn:r432|432]]</sup> ; Olsen et al., 2016 <sup>[[#fn:r433|433]]</sup> ; PSMSL, 2016; PAGES2K Consortium, 2017 <sup>[[#fn:r434|434]]</sup> ; WGMS, 2017 <sup>[[#fn:r435|435]]</sup> ). The amount of data available through time is shown by the heights of the time series for observational data, palaeoclimate data and model simulations, expressed relative to the maximum annual data availability (maximum values given on plot; M = million, k = thousand). Spatial coverage of data across the globe or the relevant domain is shown by colour scale. See SM1.4 for further details.

| Illustrative examples of the availability of ocean and cryosphere data relative to the major time periods assessed in the Special Report on the Oceans and Cryosphere in a Changing Climate (SROCC). Upper panel; observed (Keeling et al., 1976) and reconstructed (Bereiter et al., 2015) atmospheric CO2 concentrations, as well as the Representative Concentration Pathways (RCPs) of CO2 for low (RCP2.6) and high (RCP8.5) future emission scenarios (van Vuuren et al., 2011a; Cross-Chapter Box 1 in Chapter 1). Lower panel; illustrative examples of data availability for the ocean and cryosphere (Section 1.8.1; Taylor et al., 2012; Boyer et al., 2013; Dowell et al., 2013; McQuatters-Gollop et al., 2015; Raup et al., 2015; Olsen et al., 2016; PSMSL, 2016; PAGES2K Consortium, 2017; WGMS, 2017). The amount of data available through time is shown by the heights of the time series for observational data, palaeoclimate data and model simulations, expressed relative to the maximum annual data availability (maximum values given on plot; M = million, k = thousand). Spatial coverage of data across the globe or the relevant domain is shown by colour scale. See SM1.4 for further details.

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