Data for the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). When using the datasets from this collection please use the citation indicated on each individual specific dataset, rather than the citation for the entire collection. Figure datasets related to this collection: - data for Figure SPM.1 - data for Figure SPM.2 - data for Figure SPM.3 - data for Figure SPM.4 - data for Figure SPM.5 - data for Figure SPM.6 - data for Figure SPM.7 - data for Figure SPM.8 - data for Figure SPM.9 - data for Figure SPM.10

Data for Figure 3.37 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.37 shows observed and simulated seasonality of ENSO. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels. All the data are provided in enso_seasonality.nc. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains - Climatological standard deviation of the ENSO index - A seasonality metric of the ENSO index in observations, CMIP5 historical-RCP4.5 and CMIP6 historical simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - stdv_enso_obs; black curves . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - stdv_enso_cmip5: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP5 models blue curve and shading - stdv_enso_cmip6: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP6 models; red curve and shading . ACCESS-CM2: ens_cmip6 = 1 - 3 . ACCESS-ESM1-5: ens_cmip6 = 4 - 23 . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28 . AWI-ESM-1-1-LR: ens_cmip6 = 29 . BCC-CSM2-MR: ens_cmip6 = 30 - 32 . BCC-ESM1: ens_cmip6 = 33 - 35 . CAMS-CSM1-0: ens_cmip6 = 36-38 . CanESM5-CanOE: ens_cmip6 = 39 - 41 . CanESM5: ens_cmip6 = 42 - 106 . CESM2-FV2: ens_cmip6 = 107 - 109 . CESM2: ens_cmip6 = 110 - 120 . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123 . CESM2-WACCM: ens_cmip6 = 124 - 126 . CIESM: ens_cmip6 = 127 - 129 . CMCC-CM2-HR4: ens_cmip6 = 130 . CMCC-CM2-SR5: ens_cmip6 = 131 . CMCC-ESM2: ens_cmip6 = 132 . CNRM-CM6-1-HR: ens_cmip6 = 133 . CNRM-CM6-1: ens_cmip6 = 134 - 162 . CNRM-ESM2-1: ens_cmip6 = 163 - 172 . E3SM-1-0: ens_cmip6 = 173 - 177 . E3SM-1-1-ECA: ens_cmip6 = 178 . E3SM-1-1: ens_cmip6 = 179 . EC-Earth3-AerChem: ens_cmip6 = 180, 181 . EC-Earth3-CC: ens_cmip6 = 182 . EC-Earth3: ens_cmip6 = 183 - 204 . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207 . EC-Earth3-Veg: ens_cmip6 = 208 - 215 . FGOALS-f3-L: ens_cmip6 = 216 - 218 . FGOALS-g3: ens_cmip6 = 219 - 224 . FIO-ESM-2-0: ens_cmip6 = 225 - 227 . GFDL-CM4: ens_cmip6 = 228 . GFDL-ESM4: ens_cmip6 = 229 - 231 . GISS-E2-1-G-CC: ens_cmip6 = 232 . GISS-E2-1-G: ens_cmip6 = 233 - 278 . GISS-E2-1-H: ens_cmip6 = 279 - 302 . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306 . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310 . IITM-ESM: ens_cmip6 = 311 . INM-CM4-8: ens_cmip6 = 312 . INM-CM5-0: ens_cmip6 = 313 - 322 . IPSL-CM5A2-INCA: ens_cmip6 = 323 . IPSL-CM6A-LR: ens_cmip6 = 324 - 355 . KACE-1-0-G: ens_cmip6 = 356-358 . KIOST-ESM: ens_cmip6 = 359 . MCM-UA-1-0: ens_cmip6 = 360, 361 . MIROC6: ens_cmip6 = 362 - 411 . MIROC-ES2L: ens_cmip6 = 412 - 421 . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424 . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434 . MPI-ESM1-2-LR: ens_cmip6 = 435 -  444 . MRI-ESM2-0: ens_cmip6 = 445 - 450 . NESM3: ens_cmip6 = 451 - 455 . NorCPM1: ens_cmip6 = 456 - 485 . NorESM2-LM: ens_cmip6 = 486 - 488 . NorESM2-MM: ens_cmip6 = 489 - 490 . SAM0-UNICON: ens_cmip6 = 491 . TaiESM1: ens_cmip6 = 492 . UKESM1-0-LL: ens_cmip6 = 493 - 510 Panel b: - seasonality_enso_obs; black vertical lines and numbers in the top right box . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - seasonality_enso_cmip5; Seasonality metric in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box - seasonality_enso_cmip6; Seasonality metric in each ensemble member of CMIP6 models; red dots, with their multimodal ensemble mean and percentiles for the red box-whisker and number in the top right box . ACCESS-CM2: ens_cmip6 = 1 - 3 . ACCESS-ESM1-5: ens_cmip6 = 4 - 23 . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28 . AWI-ESM-1-1-LR: ens_cmip6 = 29 . BCC-CSM2-MR: ens_cmip6 = 30 - 32 . BCC-ESM1: ens_cmip6 = 33 - 35 . CAMS-CSM1-0: ens_cmip6 = 36-38 . CanESM5-CanOE: ens_cmip6 = 39 - 41 . CanESM5: ens_cmip6 = 42 - 106 . CESM2-FV2: ens_cmip6 = 107 - 109 . CESM2: ens_cmip6 = 110 - 120 . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123 . CESM2-WACCM: ens_cmip6 = 124 - 126 . CIESM: ens_cmip6 = 127 - 129 . CMCC-CM2-HR4: ens_cmip6 = 130 . CMCC-CM2-SR5: ens_cmip6 = 131 . CMCC-ESM2: ens_cmip6 = 132 . CNRM-CM6-1-HR: ens_cmip6 = 133 . CNRM-CM6-1: ens_cmip6 = 134 - 162 . CNRM-ESM2-1: ens_cmip6 = 163 - 172 . E3SM-1-0: ens_cmip6 = 173 - 177 . E3SM-1-1-ECA: ens_cmip6 = 178 . E3SM-1-1: ens_cmip6 = 179 . EC-Earth3-AerChem: ens_cmip6 = 180, 181 . EC-Earth3-CC: ens_cmip6 = 182 . EC-Earth3: ens_cmip6 = 183 - 204 . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207 . EC-Earth3-Veg: ens_cmip6 = 208 - 215 . FGOALS-f3-L: ens_cmip6 = 216 - 218 . FGOALS-g3: ens_cmip6 = 219 - 224 . FIO-ESM-2-0: ens_cmip6 = 225 - 227 . GFDL-CM4: ens_cmip6 = 228 . GFDL-ESM4: ens_cmip6 = 229 - 231 . GISS-E2-1-G-CC: ens_cmip6 = 232 . GISS-E2-1-G: ens_cmip6 = 233 - 278 . GISS-E2-1-H: ens_cmip6 = 279 - 302 . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306 . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310 . IITM-ESM: ens_cmip6 = 311 . INM-CM4-8: ens_cmip6 = 312 . INM-CM5-0: ens_cmip6 = 313 - 322 . IPSL-CM5A2-INCA: ens_cmip6 = 323 . IPSL-CM6A-LR: ens_cmip6 = 324 - 355 . KACE-1-0-G: ens_cmip6 = 356-358 . KIOST-ESM: ens_cmip6 = 359 . MCM-UA-1-0: ens_cmip6 = 360, 361 . MIROC6: ens_cmip6 = 362 - 411 . MIROC-ES2L: ens_cmip6 = 412 - 421 . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424 . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434 . MPI-ESM1-2-LR: ens_cmip6 = 435 -  444 . MRI-ESM2-0: ens_cmip6 = 445 - 450 . NESM3: ens_cmip6 = 451 - 455 . NorCPM1: ens_cmip6 = 456 - 485 . NorESM2-LM: ens_cmip6 = 486 - 488 . NorESM2-MM: ens_cmip6 = 489 - 490 . SAM0-UNICON: ens_cmip6 = 491 . TaiESM1: ens_cmip6 = 492 . UKESM1-0-LL: ens_cmip6 = 493 - 510 Acronyms - ENSO - El Niño–Southern Oscillation, CMIP - Coupled Model Intercomparison Project, RCP - Representative Concentration Pathway, ERSST - Extended Reconstructed Sea Surface Temperature, HadISST - Hadley Centre Sea Ice and Sea Surface Temperature, ACCESS- CM2 – Australian Community Climate and Earth System Simulator coupled climate model, ACCESS- ESM – Australian Community Climate and Earth System Simulator Earth system model, AWI - Alfred Wegener Institute, BCC-CSM - Beijing Climate Center Climate System Model, CAMS - Chinese Academy of Meteorological Sciences, CanOE - Canadian Ocean Ecosystem, CESM2 - Community Earth System Model, WACCM - Whole Atmosphere Community Climate Model, CIESM - Community Integrated Earth System Model, CNCC - Centro Euro-Mediterraneo per I Cambiamenti Climatici, CNRM - Centre National de Recherches Météorologiques, E3SM - Energy Exascale Earth System Model, FGOALS - Flexible Global Ocean-Atmosphere-Land System Model, FIO-ESM - First Institute of Oceanography Earth System Model, GFDL - Geophysical Fluid Dynamics Laboratory, GISS - Goddard Institute for Space Studies, IITM - Indian Institute of Tropical Meteorology, INM - Institute for Numerical Mathematics, IPSL - Institut Pierre-Simon Laplace, KIOST-ESM - Korea Institute of Ocean Science & Technology Earth System, MIROC - Model for Interdisciplinary Research on Climate, MPI - Max-Planck-Institut für Meteorologie, NESM - Nanjing University of Information Science and Technology Earth System Model, NorCPM - Norwegian Climate Prediction Model, SAM0-UNICON - Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0-UNICON), TaiESM1 - Taiwan Earth System Model version 1, UKESM - The UK Earth System Modelling project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means and percentiles are calculated after weighting individual members with the inverse of the ensemble size of the same model. The weight is provided as the weight attribute of ens_cmip5 and ens_cmip6. If X(i) is the array, and w(i) the corresponding weight. - Mean shoud be suｍ_i(X(i) * w(i)) / sum_i(w(i)) - For percentile values, 1. Sort X and w so that X is in the ascending order 2. Accumulate w until i = j so that accumulated(w)/sum_i(w(i)) equals or exceeds the specified percentile level (e.g. 0.05) 3. Use X(j) or (X(j) + X(j - 1))/2 as the percentile value --------------------------------------------------- Sources of additional information --------------------------------------------------- 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 - Link to the figure on the IPCC AR6 website

Data for Figure SPM.1 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure SPM.1 shows global temperature history and causes of recent warming. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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: IPCC, 2021: Summary for Policymakers. 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. In Press. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels, with data provided for all panels in subdirectories named panel_a and panel_b. --------------------------------------------------- List of data provided --------------------------------------------------- Panel a The dataset contains: - Estimated temperature during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago (4500 BCE), multi-centennial average, from AR6 WGI Chapter 2 - Global surface temperature change time series relative to 1850-1900 for 1-2020 from: • 1-2000 CE reconstruction from paleoclimate archives, decadal smoothed, from PAGES2k Consortium (2019, DOI: 10.1038/s41561-019-0400-0) • 1850-2020 CE, observations, decadal smoothed, from AR6 WGI Chapter 2 assessed mean Panel b: The dataset contains global surface temperature change time series relative to 1850-1900 for 1850-2020 from simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and observations: - CMIP6 historical+ssp245 simulations (simulations with human and natural forcing, 1850-2019) - CMIP6 hist-nat simulations (simulations with natural forcing, 1850-2019) - Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - panel_a/SPM1_1-2000_recon.txt, 1-2000 time series, decadal smoothed, for years centered on 5-1996 CE [column 1 grey line, columns 2 and 3 grey shading] - panel_a/SPM1_1850-2020_obs.txt, 1850-2020 time series, decadal smoothed, for years centered on 1855-2016 CE [black line] - panel_a/SPM1_6500_recon.txt, bar for the warmest multi-century period in more than 100,000 years (around 6500 years ago: 4500 BCE) [grey bar] Panel b: - panel_b/gmst_changes_model_and_obs.csv. Global surface temperature change time series relative to 1850-1900 for 1850-2020 from: • CMIP6 historical+ssp245 simulations (1850-2019) [mean, brown line] • CMIP6 historical+ssp245 simulations (1850-2019) [5% range, brown shading, bottom] • CMIP6 historical+ssp245 simulations (1850-2019) [95% range, brown shading, top] • CMIP6 hist-nat simulations (1850-2019) [mean, green line] • CMIP6 hist-nat simulations (1850-2019) [5% range, green shading, bottom] • CMIP6 hist-nat simulations (1850-2019) [95% range, green shading, top] • Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020) [black line] --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report webpage, which includes the report component containing the figure (Summary for Policymakers), the Technical Summary (Cross-Section Box TS.1, Figure 1a) and the Supplementary Material for Chapters 2 and 3, which contains details on the input data used in Tables 2.SM.1 (Figure 2.11a) and 3.SM.1 (Figure 3.2c; FAQ 3.1, Figure 1). - Link to related publication for input data

Data for FAQ 3.3, Figure 1 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). FAQ 3.3 Figure 1 shows pattern correlations between models and observations for three different variables: surface air temperature, precipitation and sea level pressure. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains all correlation pattern values displayed in the figure. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- fig_FAQ_3_3.nc: - variable: 'cor' with two dimensions: . 'vars': variables on the x-axis (same order as in the figure) . 'models': name of each models (the attribute 'project' contains mapping to 'CMIP3', 'CMIP5' or 'CMIP6') CMIP3 is the third phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Var 'cor' contains the values. Coordinate 'var' is the x-axis. Coordinate 'models' is the y-axis. The attribute 'project' of the coordinate 'models' contains as string chain the mapping to CMIP3 (cyan), CMIP5 (blue) and CMIP6 (red). The multi-model mean is not part of the dataset. --------------------------------------------------- Sources of additional information --------------------------------------------------- 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.

Data for Figure 3.27 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.27 shows maps of multi-decadal salinity trends for the near-surface ocean. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- Technically there are two panels, they are named in the datasets as top and bottom, but the data is stored in the parent directory. Data provided for bottom panel. --------------------------------------------------- List of data provided --------------------------------------------------- ​​​​​​The dataset contains salinity data: - climatological mean from CMIP6 models (1950-2014) - simulated trend from CMIP6 models (1950-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - ocean_salinity_cmip6.nc: climatological salinity (1950-2014) from CMIP6 models (black contours) in a bottom panel - ocean_salinity_trends_cmip6.nc: salinity trends (1950-2014) from CMIP6 models (colored shades) in a bottom panel CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- The observational data from here (top panel) is taken from the file: DurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc. The field of interest are salinity_mean (shown as black contours) and salinity_change (shown in colourscale). The file was archived as input data for Figure 2.27. The link to this dataset is provided in the Related Documents section of this catalogue record. --------------------------------------------------- Sources of additional information --------------------------------------------------- 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 - Link to input data figure 2.27 - Link to the figure on the IPCC AR6 website

Data for Figure 3.35 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.35 shows Southern Annular Mode indices in the last millennium.   --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels, and all the data are provided in sam_millennium.nc.   --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Annual SAM reconstructions. - Annual-mean SAM index by CMIP5 and CMIP6 Last Millennium simulations extended by historical simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - sam_abram_runmean, sam_datwyler_runmean: thin blue and brown lines - sam_abram_lowpass, sam_datwyler_lowpass: thick blue and brown lines Panel b: - sam_cmip_runmean: thin lines . MIROC-ES2L: ensemble = 10 (violet) . MRI-ESM2-0: ensemble = 11 (green) . CMIP5: ensemble = 1, 2, 3, 4, 5, 6, 7, 8, 9 (grey) - sam_cmip_lowpass: thick lines . MIROC-ES2L: ensemble = 10 (violet) . MRI-ESM2-0: ensemble = 11 (green) . CMIP5: ensemble = 1, 2, 3, 4, 5, 6, 7, 8, 9 (grey) --------------------------------------------------- Sources of additional information --------------------------------------------------- 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 - Link to the figure on the IPCC AR6 website

Data for Figure 3.40 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.40 shows the observed and simulated Atlantic Multidecadal Variability (AMV). --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has six panels. Files are not separated according to the panels. --------------------------------------------------- List of data provided --------------------------------------------------- amv.obs.nc contains - Observed SST anomalies associated with the AMV pattern - Observed AMV index time series (unfiltered) - Observed AMV index time series (low-pass filtered) - Taylor statistics of the observed AMV patterns amv.hist.cmip6.nc contains - Statistical significance of the observed SST anomalies associated with the AMV pattern - Simulated SST anomalies associated with the AMV pattern - Simulated AMV index time series (unfiltered) - Simulated AMV index time series (low-pass filtered) - Taylor statistics of the simulated AMV patterns based on CMIP6 historical simulations. amv.hist.cmip5.nc contains - Simulated SST anomalies associated with the AMV pattern - Simulated AMV index time series (unfiltered) - Simulated AMV index time series (low-pass filtered) - Taylor statistics of the simulated AMV patterns based on CMIP5 historical simulations. amv.piControl.cmip6.nc contains - Simulated SST anomalies associated with the AMV pattern - Simulated AMV index time series (unfiltered) - Simulated AMV index time series (low-pass filtered) - Taylor statistics of the simulated AMV patterns based on CMIP6 piControl simulations. amv.piControl.cmip5.nc contains - Simulated SST anomalies associated with the AMV pattern - Simulated AMV index time series (unfiltered) - Simulated AMV index time series (low-pass filtered) - Taylor statistics of the simulated AMV patterns based on CMIP5 piControl simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - amv_pattern_obs_ref in amv.obs.nc: shading - amv_pattern_obs_signif (dataset = 1) in amv.obs.nc: cross markers Panel b: - Multimodel ensemble mean of amv_pattern in amv.hist.cmip6.nc: shading, with their sign agreement for hatching Panel c: - tay_stats (stat = 0, 1) in amv.obs.nc: black dots - tay_stats (stat = 0, 1) in amv.hist.cmip6.nc: red crosses, and their multimodel ensemble mean for the red dot - tay_stats (stat = 0, 1) in amv.hist.cmip5.nc: blue crosses, and their multimodel ensemble mean for the blue dot Panel d: - Lag-1 autocorrelation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left - Lag-10 autocorrelation of amv_timeseries in amv.obs.nc: black horizontal lines in right . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right Panel e: - Standard deviation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left - Standard deviation of amv_timeseries in amv.obs.nc: black horizontal lines in right . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right Panel f: - amv_timeseries in amv.obs.nc: black curves . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - amv_timeseries in amv.hist.cmip6.nc: 5th-95th percentiles in red shading, multimodel ensemble mean and its 5-95% confidence interval for red curves - amv_timeseries in amv.hist.cmip5.nc: 5th-95th percentiles in blue shading, multimodel ensemble mean for blue curve CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. SST stands for Sea Surface Temperature. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means and percentiles of historical simulations of CMIP5 and CMIP6 are calculated after weighting individual members with the inverse of the ensemble size of the same model. ensemble_assign in each file provides the model number to which each ensemble member belongs. This weighting does not apply to the sign agreement calculation. piControl simulations from CMIP5 and CMIP6 consist of a single member from each model, so the weighting is not applied. Multimodel ensemble means of the pattern correlation in Taylor statistics in (c) and the autocorrelation of the index in (d) are calculated via Fisher z-transformation and back transformation. --------------------------------------------------- Sources of additional information --------------------------------------------------- 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 - Link to the figure on the IPCC AR6 website

Data for Figure 3.21 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.21 shows the seasonal evolution of observed and simulated Arctic and Antarctic sea ice area (SIA) over 1979-2017. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has several subplots, but they are unidentified, so the data is stored in the parent directory. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains Sea Ice Area anomalies over 1979-2017 relative to the 1979-2000 means from: - Observations (OSISAF, NASA Team, and Bootstrap) - Historical simulations from CMIP5 and CMIP6 multi-model means - Natural only simulations from CMIP5 and CMIP6 multi-model means --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - *_arctic_* files are used for the plots on the left side of the figure - *_antarctic_* files are used for the plots on the right side of the figure - *_OBS_NASATeam* files are used for the first row of the plot - *_OBS_Bootstrap* are used for the second row of the plot - *_OBS_OSISAF* are used for the third row of the plot - *_ALL_CMIP5* are used in the fourth row of the plot - *_ALL_CMIP6* are used in the fifth row of the plot - *_NAT_CMIP5* are used in the sixth row of the plot - *_NAT_CMIP6* are used in the seventh row of the plot --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- The significance are for the grey dots, it's nan or 1 values. The data has to be overplotted to colored squares. Grey dots indicate multi-model mean anomalies stronger than inter-model spread (beyond ± 1 standard deviation). The coordinates of the data are indices, but in global attributes 'comments' of each file there are relations of indices to months, since months are the y coordinate. --------------------------------------------------- Sources of additional information --------------------------------------------------- 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.

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. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- 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) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - 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. --------------------------------------------------- Sources of additional information --------------------------------------------------- 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.

Data for Figure 3.8 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.8 shows assessed contributions to observed warming, and supporting lines of evidence. --------------------------------------------------- How to cite this dataset --------------------------------------------------- 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. --------------------------------------------------- List of data provided --------------------------------------------------- The dataset contains the drivers of the attributable warming (2010-2019 relative to 1850-1900): - Observed global warming (2010-2019) - Global warming and its drivers reported in the literature sources  (2010-2019) - Global warming and its drivers calculated from CMIP6 models (2010-2019) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - drivers_observed_warming.csv has data for the shadings and markers in the figure. Additional details of data provided in relation to figure in the file header (BADC-CSV file). --------------------------------------------------- Sources of additional information --------------------------------------------------- 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.