Dataset
Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.7 (v20220613)
Abstract
Data for Figure 3.7 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).
Figure 3.7 shows regression coefficients and corresponding attributable warming estimates for individual CMIP6 models.
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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:
Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. 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. 423–552, doi:10.1017/9781009157896.005.
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Figure subpanels
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The figure has four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d.
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List of data provided
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This dataset contains information on global temperature attributable warming (2010-2019 relative to 1850-1900) from CMIP6 models:
- Regression coefficients for two way regression (2010-2019 relative to 1850-1900)
- Regression coefficients for three way regression (2010-2019 relative to 1850-1900)
- Attributable warming for two way regression (2010-2019 relative to 1850-1900)
- Attributable warming for three way regression (2010-2019 relative to 1850-1900)
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Data provided in relation to figure
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- panel_a/regression_coeff_two_way_regression.csv has data for brown and green crosses
- panel_b/regression_coeff_three_way_regression.csv has data for grey, green and blue crosses
- panel_c/attributable_warming_two_way_regression.csv has data for brown and green crosses
- panel_d/attributable_warming_three_way_regression.csv has data for grey, green and blue crosses
Details about the data provided in relation to the figure in the header of every file.
CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.
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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 3)
- Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1
- Link to the code for the figure, archived on Zenodo.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://creativecommons.org/licenses/by/4.0/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI). |
| Data Quality: |
Data as provided by the IPCC
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| File Format: |
Data are netCDF formatted
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Related Documents
Process overview
| Title | Caption for Figure 3.7 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) |
| Abstract | Regression coefficients and corresponding attributable warming estimates for individual CMIP6 models. Upper panels show regression coefficients based on a two-way regression (left) and three-way regression (right), of observed five-year mean, globally averaged, masked and blended surface temperature (HadCRUT4) onto individual model response patterns, and a multi-model mean, labelled ‘Multi’. Anthropogenic, natural, greenhouse gas, and other anthropogenic (aerosols, ozone, land-use change) regression coefficients are shown. Regression coefficients are the scaling factors by which the model responses must be multiplied to best match observations. Regression coefficients consistent with one indicate a consistent magnitude response in observations and models, and regression coefficients inconsistent with zero indicate a detectable response to the forcing concerned. Lower panels show corresponding observationally-constrained estimates of attributable warming in globally-complete GSAT for the period 2010–2019, relative to 1850–1900, and the horizontal black line shows an estimate of observed warming in GSAT for this period. Figure is adapted from Gillett et al. (2021), their Extended Data Figure 3. Further details on data sources and processing are available in the chapter data table (Table 3.SM.1). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
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Co-ordinate Variables
Temporal Range
2010-01-01T12:00:00
2019-12-31T12:00:00
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |