Data for Figure 7.15 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).

Figure 7.15 shows the relationship between historical and abrupt4xCO2 net radiative feedbacks in ESMs.

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How to cite this dataset
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When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:
Forster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 923–1054, doi:10.1017/9781009157896.009.

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Figure subpanels
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The figure has 2 subpanels, with data provided for both panels in the master GitHub repository linked in the documentation.

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List of data provided
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This dataset contains:

- (a) Radiative feedbacks in CMIP6 ESMs estimated under historical forcing (values for GFDL CM4.0 and HadGEM3-CG3.1-LL from Winton et al. (2020) and Andrews et al. (2019), respectively);
- (b) Historical radiative feedbacks estimated from atmosphere-only ESMs with prescribed observed sea-surface temperature and sea-ice concentration changes (Andrews et al., 2018) based on a linear regression of global top-of-atmosphere (TOA) radiation against global near-surface air temperature over the period 1870–2010 (pattern of warming similar to Figure 7.14a) and compared with equilibrium feedbacks in abrupt4xCO2 simulations of coupled versions of the same ESMs (pattern of warming similar to Figure 7.14b).

In all cases, the equilibrium feedback magnitudes are estimated as CO2 ERF divided by ECS where ECS is derived from regression over years 1–150 of abrupt4xCO2 simulations (Box 7.1); similar results are found if the equilibrium feedback is estimated directly from the slope of the linear regression.

For (a), horizontal lines show the range across ensemble members. The other points show effective feedback values for 29 ESMs estimated using regression over the first 50 years of abrupt4xCO2 simulations as an analogue for historical warming (Dong et al., 2020).

Further details on data sources and processing are available in the chapter data table (Table 7.SM.14).

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Data provided in relation to figure
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Data provided in relation to Figure 7.15:

- Data file: :
- Data file: :

CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.
ESM stands for Earth System Model.
ECS stands for Equilibrium Climate Sensitivity.
GFDL-CM4 is the Geophysical Fluid Dynamics Laboratory - Climate Model 4.
HadGEM3-GC31-LL is the Met Offfice Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N96/ORCA1.

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Notes on reproducing the figure from the provided data
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Data and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided "as-is" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.

Within the processing chain, every notebook is prefixed by a number. To reproduce all results in the chapter, the notebooks should be run in numerical order, because some later things depend on earlier things (historical temperature attribution requires a constrained ensemble of the two layer climate model, which relies on the generation of the radiative forcing time series). This being said, most notebooks should run standalone, as input data is provided where the datasets are small enough (see the 'master;' GitHub page for these).

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Sources of additional information
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The following weblinks are provided in the Related Documents section of this catalogue record:
- Link to the report component containing the figure (Chapter 7)
- Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.
- Link to the code for the figure, archived on Zenodo.