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  • Data for Figure 3.2 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.2 shows changes in surface temperature for different paleoclimates. --------------------------------------------------- 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 three subpanels, the data provided for all panels in subdirectories named panel_a, panel_b, panel_c --------------------------------------------------- List of data provided --------------------------------------------------- For panel (a): - PMIP3 global temperature anomalies over continents and oceans reconstruction sites - PMIP4 CMIP6 global temperature anomalies over continents and oceans reconstruction sites - PMIP4 non-CMIP6 global temperature anomalies over continents and oceans reconstruction sites - Tierney 2020 reconstructions of marine temperature - Cleator 2020 reconstructions of continental temperature For panel (b): - CMIP5 temperature data for paleoclimate periods - CMIP6 temperature data for paleoclimate periods - non-CMIP temperature data for paleoclimate periods - Instrumental observational and observations from reconstructions For panel (c): - Volcanic forcing from TS17, CU12, GRA08 - CMIP6 GMST anomaly with respect to 1850-1900 modelled with TS17 volcanic forcing - CMIP5 GMST anomaly with respect to 1850-1900 modelled with CU12 volcanic forcing - CMIP5 GMST anomaly with respect to 1850-1900 modelled with GRA08 volcanic forcing --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/temperature_anomalies_scatter_points.csv relates to the scatter points and their standard deviation for panel (a) - For panel (b) the datasets are stored as following panel_b/temperature_{color}_{marker}_{period}_{model_group}_{additional_info}.csv and relates to the scatter points for panel (b). - For panel (c) the data is stored in panel_c/gmst_changes_paleo_volcanic_forcings.csv and relates to red, green, blue and black lines on the panel as well as grey shadings. Additional information about data provided in relation to figure in files headers. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. PMIP4 is the Paleoclimate Modelling Intercomparison Project phase 4 PMIP3 is the Paleoclimate Modelling Intercomparison Project phase 3 --------------------------------------------------- Temporal Range of Paleoclimate Data --------------------------------------------------- This dataset covers a paleoclimate timespan from 3.3Ma to 6ka (3.3 million years ago to 6 thousand years ago). --------------------------------------------------- Notes on reproducing the figure from the provided data. --------------------------------------------------- For panel (a) the error bar should be plotted as anomalies from columns 2/4 +/- standard deviation. --------------------------------------------------- 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 FAQ 3.2, 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 3.2, Figure 1 shows annual, decadal and multi-decadal variations in average global surface temperature.  --------------------------------------------------- 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 technically has three panels, but they are not labelled. So the datasets are stored just in the main figure folder.  --------------------------------------------------- List of data provided --------------------------------------------------- Dataset contains modelled GSAT anomalies from MPI-ESM grand ensemble (1950-2019): - On annual scale - On decadal scale - On multi-decadal scale --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - annual_gsat_anomalies_mpi_esm_grand_ens.csv has data for the left panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble (black, light green, light marsh green, light dark green lines) - decadal_gsat_anomalies_mpi_esm_grand_ens.csv  has data for the middle panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble  (black, light green, light marsh green, light dark green lines) - multi_decadal_gsat_anomalies_mpi_esm_grand_ens.csv has data for the right panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble  (black, light green, light marsh green, light dark green lines) GSAT stands for Global Surface Air Temperature. MPI-ESM is a comprehensive Earth-System Model, consisting of component models for the ocean, the atmosphere and the land surface. --------------------------------------------------- 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 3.38 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.38 shows model evaluation of ENSO teleconnection for 2m-temperature and precipitation in boreal winter (December-January-February). --------------------------------------------------- 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 --------------------------------------------------- Data provided for all panels in one single directory --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains observed global patterns for: - temperature from the Berkeley Earth dataset over land - temperature from ERSSTv5 over ocean - precipitation from GPCC over land (shading, mm day–1) - precipitation from GPCP worldwide (contours, period: 1979-2014) and distributions of regression coefficients in IPCC regions for: - temperature - precipitation --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- maps: - reg_tas_NINO34_BEST_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over land) - reg_sst_NINO34_ERSSTv5_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over ocean) - reg_precip_NINO34_GPCP_ERSST5_1979_2018_DJF.nc (var = 'rc', lower map, contours) - reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc (var = 'rc', lower map, shading) histograms: - tas_enso_regression_pdf_v4_no_cosweight_DJF.nc . upper grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - tas_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dashed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for temperature: 'EAU/RFE/RAR/NWN/NCA/ENA/NSA/MED/NWS/ESAF' (see variable region_info with attributes making the association between the region index and the acronym/name). - pr_enso_regression_pdf_v4_no_cosweight_DJF.nc . lower grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - pr_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dahsed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for precipitation: 'EAS/SEA/EAU/WNA/NCA/SES/NSA/ESAF/SEAF/MED' (see variable info_region with attributes making the association between the region index and the acronym/name). ENSO is the El Niño Southern Oscillation. GPCC is the Global Precipitation Climatology Centre. GPCP is the Global Precipitation Climatology Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Data provided in reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc are in mm/month. Values should be divided by 30 for plotting in mm/day. --------------------------------------------------- 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 figure on the IPCC AR6 website

  • Data for Cross-Chapter Box 3.1, Figure 1 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Cross-Chapter Box 3.1, Figure 1 shows 15-year trends of surface global warming for 1998-2012 and 2012-2026. --------------------------------------------------- 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 panels a and b in a subdirectory named panel_ab, and for panels c and d in subdirectories named panel_c and panel_d respectively. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains:  - Observed and modelled global annual mean surface temperature and surface air temperature trends for 1998-2012 - Modelled global annual mean surface air temperature trends for 2012-2026 - Observed annual mean surface temperature trends for 1998-2012 - Composite of modelled annual mean surface air temperature trends for 1998-2012 --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - gmst_trend_1998-2012 in panel_ab/GMST_trend.csv; HadCRUT5 for histogram, ensemble mean of HadCRUT5 and other observations for open triangles at the top, and multimodel ensemble means of CMIP5 and CMIP6 for open diamonds at the top - gsat_trend_1998-2012 in panel_ab/GSAT_trend.csv; CMIP5 and CMIP6 ensembles for histograms, ERA5 for the top filled triangle, and multimodel ensemble means of CMIP5 and CMIP6 for filled diamonds at the top Panel b: - gmst_trend_2012-2026 in panel_ab/GMST_trend.csv; multimodel ensemble means of CMIP5 and CMIP6 for open diamonds at the top - gsat_trend_2012-2026 in panel_ab/GSAT_trend.csv; CMIP5 and CMIP6 ensembles for histograms, and multimodel ensemble means of CMIP5 and CMIP6 for filled diamonds at the top Panel c: - tas in panel_c/TrendPattern_HadCRUT5_mean.nc; shading, with the sig attribute for cross markers Panel d: - tas in panel_d/TrendPattern_composite.nc: shading CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. HadCRUT5 is a gridded dataset of global historical near-surface air temperature anomalies since the year 1850. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means and histograms are calculated after weighting each ensemble member with the inverse of the ensemble size of the same model. The values for panels c and d are stored with the K/year unit but scaled to the K/decade, therefore they need to be multiplied by a factor of 10 in order to be consistent with the plotted values. --------------------------------------------------- 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 3.36 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.36 shows observed and simulated life cycle of El Niño and La Niña events. --------------------------------------------------- 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. All the data are provided in enso_lifecycle.nc file. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains - Composite time series of the ENSO index for El Niño events - Composite time series of the ENSO index for La Niña events - Mean duration of El Niño events - Mean duration of La Niña events in observations, CMIP5 historical-RCP4.5 and and CMIP6 historical simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - ts_elnino_obs; black curves . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - ts_elnino_cmip5: The ENSO index time series in each ensemble member of CMIP5 models; blue curve and shading - ts_elnino_cmip6: The ENSO index time series in each ensemble member of CMIP6 models; red curve and shading Panel b: - ts_lanina_obs; black curves . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - ts_lanina_cmip5: The ENSO index time series in each ensemble member of CMIP5 models; blue curve and shading - ts_lanina_cmip6: The ENSO index time series in each ensemble member of CMIP6 models; red curve and shading Panel c: - duration_elnino_obs; black vertical lines and numbers in the top right box . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - duration_elnino_cmip5: El Nino duration in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box - duration_elnino_cmip6; El Nino duration in each ensemble member of CMIP6 models; red dots, 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 Panel d: - duration_lanina_obs; black vertical lines and numbers in the top right box . ERSSTv5, dashed lines: dataset = 1 . HadISST, solid lines: dataset = 2 - duration_lanina_cmip5; La Nina duration in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box - duration_lanina_cmip6; La Nina duration in each ensemble member of CMIP6 models; red dots, 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 3.28 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.28 shows long-term trends in halosteric and thermosteric sea level in CMIP6 models and observations. --------------------------------------------------- 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 panels (a), (b), (c), (d), (e), (f), with data provided for all panels in subdirectories named panel_a, panel_b, panel_c, panel_d, panel_e and panel_f. --------------------------------------------------- List of data provided --------------------------------------------------- The datasets contains:  - Atlantic and Pacific halosteric sea level trend from CMIP6 models (1950-2014) - Atlantic and Pacific halosteric sea level trend from Durack&Wijffels observations (1950-2019) - Atlantic and Pacific halosteric sea level trend from EN4 observations (1950-2019) - Atlantic and Pacific halosteric sea level trend from Ishii observations (1955-2019) - Atlantic and Pacific thermosteric sea level trend from CMIP6 models (1950-2014) - Atlantic and Pacific thermosteric sea level trend from Durack&Wijffels observations (1950-2019) - Atlantic and Pacific thermosteric sea level trend from EN4 observations (1950-2019) - Atlantic and Pacific thermosteric sea level trend from Ishii observations (1955-2019) - Global halosteric sea level trends from Durack&Wijffels observations (1950-2019) - Global halosteric sea level trends from EN4 observations (1950-2019) - Global halosteric sea level trends from Ishii observations (1955-2019) - Global halosteric sea level trends from CMIP6 multi-model mean (1950-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/halosteric_trends_hist-nat.csv has data for green and black markers. - panel_a/halosteric_trends_historical.csv has data for orange and black markers. - panel_b/thermosteric_trends_hist-nat.csv has data for green and black markers. - panel_b/thermosteric_trends_historical.csv has data for orange and black markers. - panel_c/halosteric_trends_map_DW.nc has data for filled colored contours. - panel_d/halosteric_trends_map_EN4.nc has data for filled colored contours. - panel_e/halosteric_trends_map_Ishii.nc has data for filled colored contours. - panel_f/halosteric_trends_map_cmip6.nc has data for filled colored contours. For panels a and b 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. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- The observational data from here (top right 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 input dataset for figure 3.28 - Link to the code for the figure, archived on Zenodo - Link to the figure on the IPCC AR6 website

  • Data for Figure 3.30 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.30 shows observed and CMIP6 simulated AMOC mean state, variability and long-term trends. --------------------------------------------------- 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 6 subpanels with data provided for all panels in subdirectories named panel_a, panel_b, panel_c, panel_d, panel_e and panel_f. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains:  - AMOC streamfunction profiles from CMIP5 (1860-2004) and CMIP6 (1860-2014) historical simulations - AMOC mean maximum overturning depth from CMIP5 (1860-2004) and CMIP6 (1860-2014) historical simulations - AMOC mean maximum overturning depth from RAPID observational dataset (2004-2018) - AMOC mean maximum overturning streamfunction from CMIP5 (1860-2004) and CMIP6 (1860-2014) historical simulations - AMOC mean maximum overturning streamfunction from RAPID observational dataset (2004-2018) - AMOC 8-year trends from CMIP5 and CMIP6 simulations and RAPID observations (2004-2012) - Interannual AMOC changes from CMIP5 and CMIP6 simulations and RAPID observations (2008-2010) - Longterm AMOC trends (1850-2014) from CMIP6 simulations - Longterm AMOC trends (1940-1985) from CMIP6 simulations - Longterm AMOC trends (1985-2014) from CMIP6 simulations --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/amoc_mean_state_boxes.csv has the data for the grey observations lines and blue and red boxes with whiskers - panel_a/amoc_profiles_shadings.csv has data for the blue and red profile shadings. - panel_a/amoc_profile_cmip5.csv has data for the blue profile - panel_a/amoc_profile_cmip6.csv has data for the red profile - panel_b/amoc_trends_2004_2012.csv has data for boxes and whiskers and outlier dots - panel_b/amoc_trends_cmip5_cmip6_additional_outliers.csv has data for additional outlier dots for CMIP5 and CMIP6 - panel_c/interannual_variability_AMOC.csv has data for boxes and whiskers and outlier dots - panel_c/interannual_variability_AMOC_cmip5_cmip6_additional_outliers.csv has data for additional outlier dots for CMIP5 and CMIP6 - panel_d/amoc_longtern_trend_1850_2014.csv has data for grey, green, blue and orange boxes and whiskers - panel_e/amoc_longtern_trend_1940_1985.csv has data for grey, green, blue and orange boxes and whiskers - panel_f/amoc_longtern_trend_1985_2014.csv has data for grey, green, blue and orange boxes and whiskers CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. AMOC is the Atlantic Meridional Overturning Circulation. --------------------------------------------------- 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 FAQ 3.1, 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 3.1 Figure 1 shows that observed warming (1850-2018) is only reproduced in simulations including human influence. --------------------------------------------------- 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 global surface temperature changes timeseries relative to 1850-1900 for 1850-2019 from: - CMIP6 historical+ssp245 simulations (simulations with human and natural forcing) - CMIP6 hist-GHG simulations (simulations with anthropogenic green house gases forcing) - CMIP6 hist-aer simulations (simulation with anthropogenic aerosol forcing) - CMIP6 hist-nat simulations (simulation with natural forcing only) - Observations from Chapter 2 --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- gmst_anomalies_timeseries.csv. Global surface temperature changes timeseries relative to 1850-1900 for 1850-2019 from: - CMIP6 historical+ssp245 simulations (1850-2019) [mean, grey line] - CMIP6 historical+ssp245 simulations (1850-2019) [5% range, grey shading, bottom] - CMIP6 historical+ssp245 simulations (1850-2019) [95% range, grey shading, top] - CMIP6 hist-GHG simulations (1850-2019) [mean, red line] - CMIP6 hist-GHG simulations (1850-2019) [5% range, red shading, bottom] - CMIP6 hist-GHG simulations (1850-2019) [95% range, red shading, top] - CMIP6 hist-aer simulations (1850-2019) [mean, blue line] - CMIP6 hist-aer simulations (1850-2019) [5% range, blue shading, bottom] - CMIP6 hist-aer simulations (1850-2019) [95% range, blue 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] - Observations from Chapter 2 (1850-2019) [black line] 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 3.39 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.39 shows the observed and simulated Pacific Decadal Variability (PDV). --------------------------------------------------- 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 --------------------------------------------------- pdv.obs.nc contains - Observed SST anomalies associated with the PDV pattern - Observed PDV index time series (unfiltered) - Observed PDV index time series (low-pass filtered) - Taylor statistics of the observed PDV patterns - Statistical significance of the observed SST anomalies associated with the PDV pattern pdv.hist.cmip6.nc contains - Simulated SST anomalies associated with the PDV pattern - Simulated PDV index time series (unfiltered) - Simulated PDV index time series (low-pass filtered) - Taylor statistics of the simulated PDV patterns based on CMIP6 historical simulations. pdv.hist.cmip5.nc contains - Simulated SST anomalies associated with the PDV pattern - Simulated PDV index time series (unfiltered) - Simulated PDV index time series (low-pass filtered) - Taylor statistics of the simulated PDV patterns based on CMIP5 historical simulations. pdv.piControl.cmip6.nc contains - Simulated SST anomalies associated with the PDV pattern - Simulated PDV index time series (unfiltered) - Simulated PDV index time series (low-pass filtered) - Taylor statistics of the simulated PDV patterns based on CMIP6 piControl simulations. pdv.piControl.cmip5.nc contains - Simulated SST anomalies associated with the PDV pattern - Simulated PDV index time series (unfiltered) - Simulated PDV index time series (low-pass filtered) - Taylor statistics of the simulated PDV patterns based on CMIP5 piControl simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - ipo_pattern_obs_ref in pdv.obs.nc: shading - ipo_pattern_obs_signif (dataset = 1) in pdv.obs.nc: cross markers Panel b: - Multimodel ensemble mean of ipo_model_pattern in pdv.hist.cmip6.nc: shading, with their sign agreement for hatching Panel c: - tay_stats (stat = 0, 1) in pdv.obs.nc: black dots - tay_stats (stat = 0, 1) in pdv.hist.cmip6.nc: red crosses, and their multimodel ensemble mean for the red dot - tay_stats (stat = 0, 1) in pdv.hist.cmip5.nc: blue crosses, and their multimodel ensemble mean for the blue dot Panel d: - Lag-1 autocorrelation of tpi in pdv.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 tpi in pdv.piControl.cmip5.nc: blue open box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of tpi in pdv.piControl.cmip6.nc: red open box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of tpi in pdv.hist.cmip5.nc: blue filled box-whisker in the left - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of tpi in pdv.hist.cmip6.nc: red filled box-whisker in the left - Lag-10 autocorrelation of tpi_lp in pdv.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 tpi_lp in pdv.piControl.cmip5.nc: blue open box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of tpi_lp in pdv.piControl.cmip6.nc: red open box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of tpi_lp in pdv.hist.cmip5.nc: blue filled box-whisker in the right - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of tpi_lp in pdv.hist.cmip6.nc: red filled box-whisker in the right Panel e: - Standard deviation of tpi in pdv.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 tpi in pdv.piControl.cmip5.nc: blue open box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of tpi in pdv.piControl.cmip6.nc: red open box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of tpi in pdv.hist.cmip5.nc: blue filled box-whisker in the left - Multimodel ensemble mean and percentiles of standard deviation of tpi in pdv.hist.cmip6.nc: red filled box-whisker in the left - Standard deviation of tpi_lp in pdv.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 tpi_lp in pdv.piControl.cmip5.nc: blue open box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of tpi_lp in pdv.piControl.cmip6.nc: red open box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of tpi_lp in pdv.hist.cmip5.nc: blue filled box-whisker in the right - Multimodel ensemble mean and percentiles of standard deviation of tpi_lp in pdv.hist.cmip6.nc: red filled box-whisker in the right Panel f: - tpi_lp in pdv.obs.nc: black curves . ERSSTv5: dataset = 1 . HadISST: dataset = 2 . COBE-SST2: dataset = 3 - tpi_lp in pdv.hist.cmip6.nc: 5th-95th percentiles in red shading, multimodel ensemble mean and its 5-95% confidence interval for red curves - tpi_lp in pdv.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 5.33 from Chapter 5 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 5.33 shows carbon sink response in a scenario with net carbon dioxide (CO2) removal from the atmosphere.  --------------------------------------------------- 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: Canadell, J.G., P.M.S. Monteiro, M.H. Costa, L. Cotrim da Cunha, P.M. Cox, A.V. Eliseev, S. Henson, M. Ishii, S. Jaccard, C. Koven, A. Lohila, P.K. Patra, S. Piao, J. Rogelj, S. Syampungani, S. Zaehle, and K. Zickfeld, 2021: Global Carbon and other Biogeochemical Cycles and Feedbacks. 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. 673–816, doi:10.1017/9781009157896.007. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains data for 50-year periods during 2000-2300 for: - Atmospheric CO2 concentration - Net CO2 emissions (accumulated over 50 year periods) - Net land flux (accumulated over 50 year periods) - Net ocean flux (accumulated over 50 year periods) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Data file: Data_Figure_5_33.csv: - row 1: x-axis values. - row 2: light blue bars. - row 3: orange bars. - row 4: green bars. - row 5: blue bars - row 6: relates with the values written in black over the corresponding arrows (row 2 values plus values written in black) - row 7: Standard deviation over orange bars. - row 8: Standard deviation over green bars. - row 9: Standard deviation over blue bars. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- This figure was created in Excel and the error bars (standard deviation) were added in Adobe Illustrator. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Chapter 5) - Link to the Supplementary Material for Chapter 5, which contains details on the input data used in Table 5.SM.6