Data for EUCLEIA consists of the following simulations that have been produced with HadGEM3-A (N216 L85): - two 15 member multi-decadal stochastic physics ensemble simulations (ALL and NAT) spanning the period 1960 – 2013 which form the basis for model evaluation assessments including forecast reliability and modelled statistics of extreme events. - two corresponding large ensemble simulations (ALL and NAT) spanning the period 2014 – 2015 to be used for attribution studies. ALL simulations include historical natural and anthropogenic climate forcings which include GHGs, ozone, aerosols and land use. NAT simulations include only historical natural forcings with GHG, aerosol and land use forcings fixed to 1850 levels. The aerosol prescription is essentially the same as for the HadGEM2-ES historical simulations for CMIP5 with post-2005 values being taken from the RCP4.5 scenario. Sea surface temperature (SST) and sea ice (SIC) lower boundary conditions are derived from the HadISST observational dataset which for the NAT simulations have the multi-model mean of a set of coupled model estimates of the anthropogenic contribution removed. Within each set of simulations ensemble members differ only through the operation of the stochastic physics scheme. The multi-decadal simulations share initialisation from ERA-40 reanalysis at 0000Z Dec 1st 1959. Large ensemble simulations are initialised from the atmospheric state of the corresponding multi-decadal experiment at 0000Z Dec 1st 2013.

The data provided here are the numerical simulation data for the historical natural-only forcings-only short experiment (2014 – 2015 inclusive) as a test case for the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are restricted to just historical natural variability of solar irradiance and volcanic aerosol optical depth. SST and SIC lower boundary conditions are provided from the HadISST observational dataset minus an estimate of the anthropogenic contribution derived from CMIP5 coupled model simulations. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. Ensemble members are initialised from dumps taken from 0000Z December 1st 2013 at the end of the corresponding multi-decadal validation experiment.

The data provided here are the numerical simulation data for the historical forcings-only short experiment (2014 – 2015 inclusive) as a test case for the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are historical natural variability of solar irradiance and volcanic aerosol optical depth as well as historical anthropogenic prescriptions of GHGs, ozone, aerosols and land use change. SST and SIC lower boundary conditions are provided from the HadISST observational dataset. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. Ensemble members are initialised from dumps taken from 0000Z December 1st 2013 at the end of the corresponding multi-decadal validation experiment.

The data provided here are the numerical simulation data for the natural forcings-only version of the EUCLEIA multi-decadal experiment (1960 – 2013 inclusive) for the validation of the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are restricted to just historical natural variability of solar irradiance and volcanic aerosol optical depth. SST and SIC lower boundary conditions are provided from the HadISST observational dataset minus an estimate of the anthropogenic contribution derived from CMIP5 coupled model simulations. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. All ensemble members share identical initialisation of the atmospheric state from ERA-40 reanalysis at 0000Z December 1st 1959. Atmospheric data are provided at temporal output resolutions of 3-hourly, 6-hourly, daily and monthly; land data are provided at daily and monthly resolutions.

The data provided here are the numerical simulation data for the multi-decadal experiment (1960 – 2013 inclusive) for the validation of the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are historical natural variability of solar irradiance and volcanic aerosol optical depth as well as historical anthropogenic prescriptions of GHGs, ozone, aerosols and land use change. SST and SIC lower boundary conditions are provided from the HadISST observational dataset. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. All ensemble members share identical initialisation of the atmospheric state from ERA-40 reanalysis at 0000Z December 1st 1959. Atmospheric data are provided at temporal output resolutions of 3-hourly, 6-hourly, daily and monthly; land data are provided at daily and monthly resolutions.

Data for Figure 3.22 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.22 shows time series of Northern Hemisphere March-April mean snow cover extent (SCE) from observations, CMIP5 and CMIP6 simulations. --------------------------------------------------- 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 --------------------------------------------------- There are technically two panels top and bottom (CMIP5 and CMIP6), however, the data is stored in the parent directory. --------------------------------------------------- List of data provided --------------------------------------------------- The data is for the Northern Hemisphere snow cover extent anomalies (SCEA) from models and observations: - The SCEA observational data from GLDAS-NOAH (1948-2012), Brown-NOAA (1923-2017), Mudryk et al 2020 (1968-2017) - The SCEA modelled by CMIP5 historical-rcp45 experiment (1923-2017) - The SCEA modelled by CMIP5 historicalNat experiment (1923-2012) - The SCEA modelled by CMIP6 historical-ssp245 experiment (1923-2017) - The SCEA modelled by CMIP6 hist-nat experiment (1923-2017) - The SCEA modelled by CMIP5 and CMIP6 piControl experiments --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- snow_cover_extent_cmip5_obs.csv is the data for the green and brown lines and shadings in the upper panel and grey lines (1923-2017) snow_cover_extent_cmip6_obs.csv is the data for the green and brown lines and shadings in the lower panel and grey lines (1923-2017) snow_cover_extent_piControl.csv for the blue error bars in the both panels Additional details of data provided in relation to figure in the file header (BADC-CSV file) CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. 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 SPM.4 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.4 panel a shows global emissions projections for CO2 and a set of key non-CO2 climate drivers, for the core set of five IPCC AR6 scenarios. Figure SPM.4 panel b shows attributed warming in 2081-2100 relative to 1850-1900 for total anthropogenic, CO2, other greenhouse gases, and other anthropogenic forcings for five Shared Socio-economic Pathway (SSP) scenarios. --------------------------------------------------- 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, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001. --------------------------------------------------- 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 --------------------------------------------------- This dataset contains: - Projected emissions from 2015 to 2100 for the five scenarios of the AR6 WGI core scenario set (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) - Projected warming for all anthropogenic forcers, CO2 only, non-CO2 greenhouse gases (GHGs) only, and other anthropogenic components for 2081-2100 relative to 1850-1900, for SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. The five illustrative SSP (Shared Socio-economic Pathway) scenarios are described in Box SPM.1 of the Summary for Policymakers and Section 1.6.1.1 of Chapter 1. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: The first column includes the years, while the next columns include the data per scenario and per climate forcer for the line graphs. - Data file: Carbon_dioxide_Gt_CO2_yr.csv. relates to Carbon dioxide emissions panel - Data file: Methane_Mt_CO2_yr.csv. relates to Methane emissions panel - Data file: Nitrous_oxide_Mt N2O_yr.csv. relates to Nitrous oxide emissions panel - Data file: Sulfur_dioxide_Mt SO2_yr.csv. relates to Sulfur dioxide emissions panel Panel b: - Data file: ts_warming_ranges_1850-1900_base_panel_b.csv. [Rows 2 to 5 relate to the first bar chart (cyan). Rows 6 to 9 relate to the second bar chart (blue). Rows 10 to 13 relate to the third bar chart (orange). Rows 14 to 17 relate to the fourth bar chart (red). Rows 18 to 21 relate to the fifth bar chart (brown).]. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblink 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) and the Supplementary Material for Chapter 1, which contains details on the input data used in Table 1.SM.1..(Cross-Chapter Box 1.4, Figure 2). - Link to related publication for input data used in panel a.

Data for Figure 3.41 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.41 is a summary figure showing simulated and observed changes in key large-scale indicators of climate change across the climate system, for continental, ocean basin and larger scales.  --------------------------------------------------- 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 data of each panel is provided in a single file. --------------------------------------------------- List of data provided --------------------------------------------------- This datasets contains global and regional anomaly time-series for: - near-surface air temperature (1850-2020) - precipitation (1950-2014) - sea ice extent (1979-2014) - ocean heat content (1850-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- near-surface air temperature (tas) -fig_3_41_tas_global.nc, fig_3_41_tas_land.nc, fig_3_41_tas_north_america.nc, fig_3_41_tas_central_south_america.nc, fig_3_41_tas_europe_north_africa.nc, fig_3_41_tas_africa.nc, fig_3_41_tas_asia.nc, fig_3_41_tas_australasia.nc, fig_3_41_tas_antarctic.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 4, stat = 0 (mean) ocean heat content (ohc) -fig_3_41_ohc_global.nc: brown line: ncl5 = 0, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile) green line: ncl5 = 1, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile) black line: ncl5 = 2, ncl6 = 0 (mean) precipitation (pr) -fig_3_41_pr_60N_90N.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 2, stat = 0 (mean) sea ice extent (siconc) -fig_3_41_siconc_nh.nc, fig_3_41_siconc_sh.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 2, stat = 0 (mean) The ensemble spread (shaded regions) of CMIP6 data shown in figure 3.41 are the mean, 5th and 95th percentiles. The in-file metadata labels the same ensemble spread with mean, min and max. --------------------------------------------------- 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.2 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.2 relates to assessed contributions to observed 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, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has three panels, with data provided for all panels in subdirectories named panel_a, panel_b and panel_c. --------------------------------------------------- List of data provided --------------------------------------------------- This data set contains: - Observed warming (2010-2019 relative to 1850-1900) - Aggregated contributions to 2010-2019 warming relative 1850 -1900, assessed from attribution studies - Contributions to 2010-2019 warming relative to 1850-1900, assessed from radiative studies --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - Data file: panel_a/SPM2a.csv (Observed warming). Mean value is used for the bar plot and top and bottom values are used for the error bars and they represent borders of the very likely range. Panel b: - Data file: panel_b/SPM2b.csv (Aggregated contributions assessed from attribution studies). Mean values are used for the bar plot and top and bottom values are used for the error bars and represent the borders of the very likely range Panel c: - Data file: panel_c/SPM2c_data.csv (Contributions assessed from radiative studies). Total global surface air temperature (GSAT) effect values are used for the bar plots and 5% and 95% very likely limit values are used for the error bars. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblink is 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) and the Supplementary Material for Chapters 3, 6 and 7, which contain details on the input data used in Tables 3.SM.1 (Figure 3.8), 6.SM.1 (Figure 6.12) and 7.SM.14 (Figure 7.7).