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  • An ensemble of simulations made using the Unified Model version 6.6 (HadGEM2) in AMIP (atmosphere only) configuration for the SAPRISE (South Asian PRecIpitation: A SEamless assessment) project. The simulations are used to investigate the impacts of aerosols on the South Asian Monsoon. The four-member ensemble of simulations are forced with anthropogenic-only aerosols i.e. sulphur dioxide, black carbon and biomass burning aerosols. The simulations cover the period from 1850-2000. Since aerosol-only simulation is not compulsory in CMIP5, these four runs are complements to other CMIP5 simulations conducted by Met Office using the HadGEM2-ES (vn 6.6).

  • This dataset contains model data for CCMI-2022 experiment refD1 produced by the ACCESS-CM2-Chem chemistry-climate model run by the modelling team at the CSIRO (Commonwealth Scientific and Industrial Research Organisation) ARCCSS (Australian Research Council Centre of Excellence for Climate System Science). The refD1 experiment is a hindcast of the atmospheric state, using a prescribed evolution of sea surface temperature and sea ice from observations along with forcings for the extra-terrestrial solar flux, long-lived greenhouse gases and ozone depleting substances, stratospheric aerosols and an imposed quasi-biennial oscillation that approximate the observed variations over the historical period to the fullest extent possible. The CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models. ------------------------------------------ Sources of additional information ------------------------------------------ The following web links are provided in the Details/Docs section of this catalogue record: - Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI) - A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30

  • Data for Figure 3.17 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.17 shows observed and simulated global monsoon domain, intensity, and circulation.  --------------------------------------------------- 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 a single file.   --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains - Observed and simulated global monsoon domain and summer minus winter precipitation and 850hPa wind velocity - Global land monsoon precipitation index and Northern Hemisphere summer monsoon circulation index. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- All data are given in global_monsoon.nc file. Panel a: - uRef & vRef: vector - prRef: shading - domainRef: domain (1 = monsoon, 0 = not monsoon) Panel b: - uMME & vMME: vector - prMME: shading - domainMME: monsoon domain (1 = monsoon, 0 = not monsoon) Panel c: - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip6: red curve and shading - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip5: blue curve and shading - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_amip: yellow curve and shading - GMprecip_CMAP: black dotted curve - GMprecip_CRU-TS: black solid curve - GMprecip_GPCC: black dashed-dotted curve - GMprecip_GPCP-SG: black dashed curve Panel d: - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip6: red curve and shading - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip5: blue curve and shading - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_amip: yellow curve and shading - Max-min range of NHMcirc_20CRv3: grey hatching - NHMcirc_ERA-20C: black dash-dotted curve - NHMcirc_ERA5: black solid curve - NHMcirc_JRA-55: dashed curve - NHMcirc_MERRA2: dotted curve --------------------------------------------------- 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, which is given as the weight attribute of each variable. --------------------------------------------------- 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 supporting information on the figure in Section and details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.

  • Data for Figure 3.32 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.32 shows relative change in the amplitude of the seasonal cycle of global land carbon uptake in the historical CMIP6 simulations from 1961-2014.  --------------------------------------------------- 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 --------------------------------------------------- - Observed seasonal cycle amplitude of global land carbon uptake - Simulated seasonal cycle amplitude of global land carbon uptake --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- fig_3_32_main.nc: - Multi-Model Mean: dim0 = 0, red solid line. [red shaded region: (dim0=0) +- (dim0=1))] - JMA-TRANSCOM: dim0 = 2, black dotted line. - CO2-MLO: dim0 = 3, black solid line. [black shaded region: (dim0=3) +- (dim0=4))] - CO2-GLOBAL: dim0 = 5, black dashed line. fig_3_32_inset.nc: - Multi-Model Mean for 1961-1970 (orange): dim0 = 0 (shaded region(dim0=0) +- (dim0=1)) - Multi-Model Mean for 2005-2014 (green): dim0 = 2 (shaded region(dim0=2) +- (dim0=3)) --------------------------------------------------- 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 3.3 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.3 shows the global annual-mean surface (2 m) air temperature (°C) and the model bias to ERA5. --------------------------------------------------- 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, with data provided for four panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Global modelled annual-mean surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 - Global bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 to reanalysis ERA5 - Global root mean square bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 to reanalysis ERA5 - Global bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP5 for the period 1985–2004 to reanalysis ERA5 CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. ERA5 is the fifth generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis of the global climate. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/tas_mean_cmip6.nc; global map - panel_b/tas_bias_cmip6.nc; global map - panel_c/tas_rms_bias_cmip6.nc; global map - panel_d/tas_bias_cmip5.nc; global map --------------------------------------------------- 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 3.31 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.31 shows evaluation of historical emission-driven CMIP6 simulations for 1850-2014. --------------------------------------------------- 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: - Observed and simulated change in global mean atmospheric CO2 concentration (1850-2014) - Observed and simulated air surface temperature anomaly (1850-2014) - Observed and simulated change in land carbon uptake (1850-2014) - Observed and simulated change in ocean carbon uptake (1850-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- panel_a/fig_3_31_panel_a.nc: - dim0 = 0: 'ACCESS-ESM1-5 ', (turquoise solid line), Australian Community Climate and Earth System Simulator - Earth System Model - dim0 = 1: 'CNRM-ESM2-1', (light green solid line), National Centre for Meteorological Research - dim0 = 2: 'CanESM5-CanOE ', (orange solid line), Canadian Earth System Model - Canadian Ocean Ecosystem model - dim0 = 3: 'CanESM5', (dark green solid line). - dim0 = 4: 'MIROC-ES2L', (light purple solid line), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and Centre for Climate System Research / National Institute for Environmental Studies, Japan. - dim0 = 5: 'MPI-ESM1-2-LR ', (teal solid line), Max Planck Institute Earth System Model - dim0 = 6: 'MRI-ESM2-0', (lime solid line), Meteorological Research Institute of the Japan Meteorological Agency - dim0 = 7: 'NorESM2-LM', (pink solid line), The Norwegian Earth System Model - dim0 = 8: 'UKESM1-0-LL', (dark purple solid line), UK Earth System Model - dim0 = 9: 'MultiModelMean', (red solid line). - dim0 = 10: 'ESRL' (OBS), (black solid line). panel_b/fig_3_31_panel_b.nc - dim0_0 = 0: 'ACCESS-ESM1-5', - dim0_0 = 1: 'ACCESS-ESM1-5_historical'. - dim0_0 = 2: 'CNRM-ESM2-1'. - dim0_0 = 3: 'CNRM-ESM2-1_historical'. - dim0_0 = 4: 'CanESM5-CanOE '. - dim0_0 = 5: 'CanESM5-CanOE_historical'. - dim0_0 = 6: 'CanESM5'. - dim0_0 = 7: 'CanESM5_historical'. - dim0_0 = 8: 'MIROC-ES2L'. - dim0_0 = 9: 'MIROC-ES2L_historical'. - dim0_0 = 10: 'MPI-ESM1-2-LR '. - dim0_0 = 11: 'MPI-ESM1-2-LR_historical '. - dim0_0 = 12: 'MRI-ESM2-0'. - dim0_0 = 13: 'MRI-ESM2-0_historical'. - dim0_0 = 14: 'NorESM2-LM'. - dim0_0 = 15: 'NorESM2-LM_historical'. - dim0_0 = 16: 'UKESM1-0-LL'. - dim0_0 = 17: 'UKESM1-0-LL_historical'. - dim0_0 = 18: 'HadCRUT5' (OBS), Met Office Hadley Centre panel_c/fig_3_31_panel_c.nc - dim0 = 0: 'ACCESS-ESM1-5 '. - dim0 = 1: 'CNRM-ESM2-1'. - dim0 = 2: 'CanESM5-CanOE '. - dim0 = 3: 'CanESM5'. - dim0 = 4: 'MIROC-ES2L'. - dim0 = 5: 'MPI-ESM1-2-LR '. - dim0 = 6: 'MRI-ESM2-0'. - dim0 = 7: 'NorESM2-LM'. - dim0 = 8: 'UKESM1-0-LL'. - dim0 = 9: 'MultiModelMean'. - dim0 = 10: 'GCP' (OBS), Global Carbon Project (GCP) panel_d/fig_3_31_panel_d.nc - dim0 = 0: 'ACCESS-ESM1-5 '. - dim0 = 1: 'CNRM-ESM2-1'. - dim0 = 2: 'CanESM5-CanOE '. - dim0 = 3: 'CanESM5'. - dim0 = 4: 'MIROC-ES2L'. - dim0 = 5: 'MPI-ESM1-2-LR '. - dim0 = 6: 'MRI-ESM2-0'. - dim0 = 7: 'NorESM2-LM'. - dim0 = 8: 'UKESM1-0-LL'. - dim0 = 9: 'MultiModelMean'. - dim0 = 10: 'GCP' (OBS). Labels and colors for all figures are the same as for panel a. Historical values in panel b are plotted with the same colors as the corresponding simulation, but using dotted lines. --------------------------------------------------- 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 3.33 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.33 shows observed and simulated Northern Annular Mode (NAM), North Atlantic Oscillation (NAO) and Southern Annular Mode (SAM) in boreal winter. --------------------------------------------------- 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 twelve panels, with data provided for panels (a), (d), (g) and (j) in the subdirectory named panel_adgj, panels (b), (e), (h) and (k) in the subdirectory named panel_behk, and panels (c), (f), (i) and (l) in the subdirectory named panel_cfil.   --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains:  - Observed sea level pressure anomalies associated with NAM. - Observed sea level pressure anomalies associated with NAO. - Observed sea level pressure anomalies associated with SAM. - Simulated sea level pressure anomalies associated with NAM. - Simulated sea level pressure anomalies associated with NAO. - Simulated sea level pressure anomalies associated with SAM. - Taylor statistics of sea level pressure anomalies associated with NAM. - Taylor statistics of sea level pressure anomalies associated with NAO. - Taylor statistics of sea level pressure anomalies associated with SAM. - 1958-2014 trends of the NAM index. - 1958-2014 trends of the NAO index. - 1979-2014 trends of the SAM index. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - nam_patterns(0, :, :) in panel_adgj/nam.obs.nc; shading - nam_pattern_significance in panel_adgj/nam.obs.nc; cross marker Panel b: - nao_patterns(0, :, :) in panel_behk/nao.obs.nc; shading - nao_pattern_significance in panel_behk/nao.obs.nc; cross marker Panel c: - sam_patterns(0, :, :) in panel_cfil/sam.obs.nc; shading - sam_pattern_significance in panel_cfil/sam.obs.nc; cross marker Panel d: - nam_patterns in panel_adgj/nam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching Panel e: - nao_patterns in panel_behk/nao.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching Panel f: - sam_patterns in panel_cfil/sam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching Panel g: - nam_tay_stat(:, 0:1) in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for the orange dot - nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot - nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot - nam_tay_stat(:, 0:1) in panel_adgj/nam.obs.nc: black dots Panel h: - nao_tay_stat(:, 0:1) in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for the orange dot - nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot - nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot - nao_tay_stat(:, 0:1) in panel_behk/nao.obs.nc: black dots Panel i: - sam_tay_stat(:, 0:1) in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for the orange dot - sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot - sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot - sam_tay_stat(:, 0:1) in panel_cfil/sam.obs.nc: black dots Panel j: - nam_pc_trends in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line - nam_pc_trends in panel_adgj/nam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line - nam_pc_trends in panel_adgj/nam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line - nam_pc_trends in panel_adgj/nam.obs.nc: black vertical lines Panel k: - nao_pc_trends in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for orange vertical line - nao_pc_trends in panel_behk/nao.hist.cmip5.nc: multimodel ensemble mean for blue vertical line - nao_pc_trends in panel_behk/nao.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line - nao_pc_trends in panel_behk/nao.obs.nc: black vertical lines Panel l: - sam_pc_trends in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line - sam_pc_trends in panel_cfil/sam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line - sam_pc_trends in panel_cfil/sam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line - sam_pc_trends in panel_cfil/sam.obs.nc: black vertical lines --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means and histograms are obtained 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. Multimodel ensemble mean of the pattern correlation in Taylor statistics is 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 supporting information on the figure in Section and 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

  • Reference state data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis for the nudging experiments of the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. These reference states are used to nudge the stratosphere towards a specified evolution in the ensemble forecasts carried out by the SNAPSI project. The data contain: (a) lightly processed horizontal winds and temperatures from ERA5 spanning three case studies of sudden stratospheric warmings from 2018 to 2019 and (b) climatological horizontal winds and temperatures.

  • Data for Figure 3.5 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.5 shows the standard deviation of annually averaged zonal-mean near-surface air 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. --------------------------------------------------- List of data provided --------------------------------------------------- - Simulated (CMIP6) standard deviation of near-surface air temperature - Observed standard deviation of near-surface air temperature CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Datafile: fig_3_5.nc, black lines: - HadCRUT5: model = 62 - BerkleyEarth: model = 61 - NOAAGlobalTemp-Interim: model = 60 - Kadow: model = 59 - colored lines: model = 0, 1, ..., 58 Where HadCRUT5, BerkleyEarth, NOAAGlobalTemp-Interim, and Kadow are gridded datasets of global historical surface temperature. --------------------------------------------------- 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.

  • The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. Snowf or snowfall is the snowfall rate based on the GPCC bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Snowf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this snowfall dataset is available from the EIDC. These snowfall datasets contain snowfall data only and need to be combined with the respective WFD rainfall datasets to obtain precipitation data.