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                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Box TS4, Figure 1 (v20220817)",
                "abstract": "Data for Box TS4 from Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nBox TS4, Figure 1 shows global mean sea level change on different time scales and under different scenarios.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nArias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\nWhen citing the SSP-based sea-level projections, please also include the following citation:\r\nGarner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Global Mean Sea-Level Rise Projections. Version 20210809. https://doi.org/10.5281/zenodo.5914710.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has three panels. Panel a shows global mean sea level (GMSL) change from 1900 to 2150, observed (1900–2018) and projected under the Shared Socioeconomic Pathway (SSP) scenarios (2000–2150). Panel b shows GMSL change on 100-, 2,000-, and 10,000-year time scales as a function of global surface temperature. Panel c shows timing of exceedance of different GMSL thresholds under different SSPs. \r\n\r\nFinal data is only available for panel c. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\nGlobal mean sea level change time-series from 1901-2150 for:\r\n- Observed global mean sea level change (1901-2018).\r\n- Projected global mean sea level change (2005-2150).\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Box TS4, Figure 1:\r\n\r\nSSP-based global mean sea level projections are archived as\r\n\r\nGarner, G. G., Hermans, T., Kopp, R. E., Slangen, A. B. A., Edwards, T. L., Levermann, A., Nowicki, S., Palmer, M. D., Smith, C., Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Krinner, G., Mix, A., … Pearson, B. (2021). IPCC AR6 Sea Level Projections (Version 20210809) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5914710\r\n\r\nPanel c:\r\n\r\n- FigTS4-1c-milestone_ssp119_data.nc\r\n- FigTS4-1c-milestone_ssp126_data.nc\r\n- FigTS4-1c-milestone_ssp126_data.nc\r\n- FigTS4-1c-milestone_ssp126_data.nc\r\n- FigTS4-1c-milestone_ssp126_data.nc\r\n\r\nSee sections 9.6.3.2 and 9.6.3.3 for detailed information on the SSP-based global mean sea level projections and their production.\r\n\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanel c data were plotted using standard open-source R software - code is available via the link in the documentation.\r\n\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n- Link to the code for the figure, archived on Zenodo.\r\n- Link to the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report, archived on Zenodo."
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                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Box TS4, Figure 1 (v20220817)",
                "abstract": "Input Data for Box TS4 from Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nBox TS4, Figure 1 shows global mean sea level change on different time scales and under different scenarios.\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nArias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\nWhen citing the SSP-based sea-level projections, please also include the following citation:\r\nGarner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Global Mean Sea-Level Rise Projections. Version 20210809. https://doi.org/10.5281/zenodo.5914710.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has three panels. Panel a shows global mean sea level (GMSL) change from 1900 to 2150, observed (1900–2018) and projected under the Shared Socioeconomic Pathway (SSP) scenarios (2000–2150). Panel b shows GMSL change on 100-, 2,000-, and 10,000-year time scales as a function of global surface temperature. Panel c shows timing of exceedance of different GMSL thresholds under different SSPs. \r\n\r\nInput data is only available for panel a and c. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\nGlobal mean sea level change time-series from 1901-2150 for:\r\n- Observed global mean sea level change (1901-2018).\r\n- Projected global mean sea level change (2005-2150).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Box TS4, Figure 1:\r\n\r\nSSP-based global mean sea level projections are archived as\r\n\r\nGarner, G. G., Hermans, T., Kopp, R. E., Slangen, A. B. A., Edwards, T. L., Levermann, A., Nowicki, S., Palmer, M. D., Smith, C., Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Krinner, G., Mix, A., … Pearson, B. (2021). IPCC AR6 Sea Level Projections (Version 20210809) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5914710\r\n\r\nPanel a:\r\n\r\nConsensus observational GMSL curve: gmsl_altimeter+TG_ensemble_28012021.mat\r\nThis file is not provided but a link to the Chapter 9 GitHub repository which contains this file is provided.\r\n\r\nSSP-based GMSL projections through 2100, medium confidence:\r\n- pbox1e_total_ssp119_globalsl_figuredata.nc\r\n- pbox1e_total_ssp126_globalsl_figuredata.nc\r\n- pbox1e_total_ssp245_globalsl_figuredata.nc\r\n- pbox1e_total_ssp370_globalsl_figuredata.nc\r\n- pbox1e_total_ssp585_globalsl_figuredata.nc\r\n\r\nSSP-based GMSL projections after 2100, medium confidence:\r\n- pbox1f_total_ssp119_globalsl_figuredata.nc\r\n- pbox1f_total_ssp126_globalsl_figuredata.nc\r\n- pbox1f_total_ssp245_globalsl_figuredata.nc\r\n- pbox1f_total_ssp370_globalsl_figuredata.nc\r\n- pbox1f_total_ssp585_globalsl_figuredata.nc\r\n\r\nSSP-based GMSL projections through 2100, low confidence:\r\n- pbox2e_total_ssp126_globalsl_figuredata.nc\r\n- pbox2e_total_ssp585_globalsl_figuredata.nc\r\n\r\nSSP-based GMSL projections after 2100, low confidence:\r\n- pbox2f_total_ssp126_globalsl_figuredata.nc\r\n- pbox2f_total_ssp245_globalsl_figuredata.nc\r\n- pbox2f_total_ssp585_globalsl_figuredata.nc\r\n\r\nPanel c:\r\n\r\nThreshold exceedance timing under different SSPs, medium confidence, with parametric emulator for Antarctic ice sheet:\r\n- wf_1f_ssp119_milestone_figuredata.nc\r\n- wf_1f_ssp126_milestone_figuredata.nc\r\n- wf_1f_ssp245_milestone_figuredata.nc\r\n- wf_1f_ssp370_milestone_figuredata.nc\r\n- wf_1f_ssp585_milestone_figuredata.nc\r\n\r\nThreshold exceedance timing under different SSPs, medium confidence, with LARMIP-2 emulator for Antarctic ice sheet:\r\n- wf_2f_ssp119_milestone_figuredata.nc\r\n- wf_2f_ssp126_milestone_figuredata.nc\r\n- wf_2f_ssp245_milestone_figuredata.nc\r\n- wf_2f_ssp370_milestone_figuredata.nc\r\n- wf_2f_ssp585_milestone_figuredata.nc\r\n\r\nThreshold exceedance timing under different SSPs, low confidence, with DeConto et al. 2021-based Antarctic ice sheet projections incorporating Marine Ice Cliff Instability:\r\n- wf_3f_ssp126_milestone_figuredata.nc\r\n- wf_3f_ssp585_milestone_figuredata.nc\r\n\r\nThreshold exceedance timing under different SSPs, low confidence, with Bamber et al. 2019-based structured expert judgement ice sheet projections:\r\n- wf_4_ssp126_milestone_figuredata.nc\r\n- wf_4_ssp585_milestone_figuredata.nc\r\n\r\nSee sections 9.6.3.2 and 9.6.3.3 for detailed information on the SSP-based global mean sea level projections and their production.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanel a data were plotted using standard matplotlib software and a Linux shell script,  - code is available via the link in the documentation. The code requires the input data provided here and the additional gmsl_altimeter+TG_ensemble_28012021.mat file from Figure 9.27. The link to this file from the Chapter 9 GitHub is provided. \r\n\r\nPanel c data were plotted using standard open-source R software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n- Link to the code for the figure, archived on Zenodo.\r\n- Link to the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report, archived on Zenodo.\r\n - Link to figure data in matlab format on github"
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                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.11 (v20220712)",
                "abstract": "Data for Figure 9.11 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.11 shows simulated barotropic streamfunction, surface speed and major current transport in CMIP5 and CMIP6. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 6 subpanels, with data provided for all panels in one central directory in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a) Mean barotropic streamfunction (unit: 109 kgs–1; 1995–2014)\r\n- (b) Projected barotropic streamfunction change (109 kgs–1; 2018–2100 vs 1995–2014) under SSP5-8.5. \r\n- (d) Mean surface (0–100 m) speed (m s–1)\r\n- (e) Projected surface speed change (m s–1, 2081–2100) versus 1995–2014 under SSP5-8.5.\r\n- (c, f) Median and likely range of 1995–2014 and 2081–2100 transport of three currents with the largest transport change and four with the largest fractional change (Sen Gupta et al., 2016). (c) Deep currents: Agulhas Extension (ACx), Gulf Stream (GS), Gulf Stream Extension (GSx), Tasman Leakage (TASL), East Australia Current Extension (EACx), Indonesian Throughflow (ITF), and Brazil Current (BC). (f) Shallow currents: as for deep but with New Guinea Current (NGC), and without ACx. \r\n\r\n\r\nNo overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). Further details on data sources and processing are available in the chapter data table (Table 9.SM.9). \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.11\r\n \r\n - Data file: Fig9-11a_data.nc:\r\n - Data file: Fig9-11b_data.nc:\r\n - Data file: Fig9-11d_data.nc:\r\n - Data file: Fig9-11e_data.nc:\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nSpeed maps, stream function maps and transport panels were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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        {
            "ob_id": 38017,
            "uuid": "434049d2923a447badafb54da7882b86",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig03/v20220721",
            "numberOfFiles": 34,
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            "observation": {
                "ob_id": 37714,
                "uuid": "ef7b615816cb432088d02c97836ca9fa",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.3 (v20220721)",
                "abstract": "Data for Figure 9.3 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 9.3 shows sea surface temperature (SST) and its changes with time. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has 12 panels labelled (a)-(j). Data is provided provided for panels using this lettering system.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Time series of global mean SST anomaly relative to 1950–1980 climatology. Shown are paleoclimate reconstructions and PMIP models, observational reanalyses (HadISST) and multi-model means from the Coupled Model Intercomparison Project (CMIP) historical simulations, CMIP projections, and HighResMIP experiment. \r\n\r\n- Map of observed SST (1995–2014 climatology HadISST). \r\n\r\n- Historical SST changes from observations. \r\n\r\n- CMIP 2005–2100 SST change rate. (e) Bias of CMIP. (f) CMIP change rate. \r\n\r\n- 2005–2050 change rate for SSP5-8.5 for the CMIP ensemble. \r\n\r\n- Bias of HighResMIP (bottom left) over 1995–2014. \r\n\r\n- HighResMIP change rate for 1950–2014. \r\n\r\n- 2005–2050 change rate for SSP5-8.5 for the HighResMIP ensemble. No overlay indicates regions with high model agreement, where ≥80% of models agree on sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on sign of change (see Cross-Chapter Box Atlas.1 for more information). Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.3\r\n \r\n - Data file: Fig9-3a_data_CMIPlikelybounds.nc: \r\n - Data file: Fig9-3a_data_CMIPmean.nc: \r\n - Data file: Fig9-3a_data_HighResMIPlikelybounds.nc: \r\n - Data file: Fig9-3a_data_HighResMIPmean.nc: \r\n - Data file: Fig9-3a_data_Observedmean.nc: \r\n - Data file: Fig9-3a_data_paleo.nc: \r\n - Data file: Fig9-3a_data_ssp126likelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp126likelybounds_extended.nc: \r\n - Data file: Fig9-3a_data_ssp126mean.nc: \r\n - Data file: Fig9-3a_data_ssp126mean_extended.nc: \r\n - Data file: Fig9-3a_data_ssp126verylikelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp245likelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp245mean.nc: \r\n - Data file: Fig9-3a_data_ssp245verylikelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp370likelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp370mean.nc: \r\n - Data file: Fig9-3a_data_ssp370verylikelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp585likelybounds.nc: \r\n - Data file: Fig9-3a_data_ssp585likelybounds_extended.nc: \r\n - Data file: Fig9-3a_data_ssp585mean.nc: \r\n - Data file: Fig9-3a_data_ssp585mean_extended.nc: \r\n - Data file: Fig9-3a_data_ssp585verylikelybounds.nc: \r\n - Data file: Fig9-3b_data.nc: \r\n - Data file: Fig9-3c_data.nc: \r\n - Data file: Fig9-3d_data.nc: \r\n - Data file: Fig9-3e_data.nc: \r\n - Data file: Fig9-3f_data.nc: \r\n - Data file: Fig9-3g_data.nc: \r\n - Data file: Fig9-3h_data.nc: \r\n - Data file: Fig9-3i_data.nc: \r\n - Data file: Fig9-3j_data.nc: \r\n\r\nPMIP is the Paleoclimate Modelling Intercomparison Project. \r\nHadISST stands for Hadley Centre Sea Ice and Sea Surface Temperature.\r\nCMIP is the Coupled Model Intercomparison Project.\r\nHighResMIP is the High Resolution Model Intercomparison Project.\r\nSST stands for Sea Surface Temperature.\r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP stands for Representative Concentration Pathway.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n GMSST and SST maps were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\nThe plotting code is designed to use pre-processed CMIP data, rather than the provided netcdf files. To reproduce these figures form the metadata please modify the example code linked in the Related Documents section of this catalogue record.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to example code on GitHub\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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        {
            "ob_id": 38018,
            "uuid": "99b556ed377c4f5985488597eaacd9f5",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig04/v20220721",
            "numberOfFiles": 14,
            "volume": 7083026,
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            "observation": {
                "ob_id": 37722,
                "uuid": "fdfeb81d2ffd42c3ba2bbb00b681317c",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.4 (v20220721)",
                "abstract": "Data for Figure 9.4 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.4 shows global maps of observed mean fluxes, the observed trends in these fluxes, and the projected rate of change in these fluxes from SSP5-8.5, for freshwater, net heat, and wind stress magnitude (momentum).\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has 9 panels labelled (a)-(i), with data provided for all panels using this lettering system in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Freshwater flux (a–c), net heat flux (d–f), and momentum flux or wind stress magnitude (g–i).\r\n- Means and observed trends between 1995–2014 (freshwater and wind stress) or 2001–2014 (heat). \r\n- SSP5-8.5 projected rates between 1995–2100 using 20-year averages at each end of the time period. - - Objective interpolation from CERES, EBAF v4 (Kato et al., 2018), OAFlux-HR (Yu, 2019) and GPCP (Adler et al., 2003) of fluxes and flux trends (b, e, h). \r\n\r\nObserved trends with no overlay indicate regions where the trends are significant at p = 0.34 level. Crosses indicate regions where trends are not significant. For (c, f, i) projections, no overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9). \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.4\r\n \r\n - Data file: Fig9-4a_data.nc: \r\n - Data file: Fig9-4b_data.nc: \r\n - Data file: Fig9-4c_data.nc: \r\n - Data file: Fig9-4d_data.nc: \r\n - Data file: Fig9-4e_data.nc: \r\n - Data file: Fig9-4f_data.nc: \r\n - Data file: Fig9-4g_data.nc: \r\n - Data file: Fig9-4g_data_tauu.nc: \r\n - Data file: Fig9-4g_data_tauv.nc: \r\n - Data file: Fig9-4h_data.nc: \r\n - Data file: Fig9-4i_data.nc: \r\n\r\nCERES stands for Clouds and the Earth’s Radiant Energy System.\r\nEBAF stands for Energy Balanced And Filled. \r\nOAFlux-HR stands for Objectively Analyzed air–sea Fluxes-High Resolution.\r\nGPCP is the Global Precipitation Climatology Project.\r\nSSP stands for Shared Socio-Economic Pathway. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nFlux maps were plotted using standard matplotlib software, code is available via the link in the documentation.\r\n\r\nSome of the plotting code is designed to use pre-processed CMIP data, rather than the provided netcdf files. To reproduce these figures form the metadata please modify the example code linked in the Related Documents section of this catalogue record.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to example code on GitHub\r\n- Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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        {
            "ob_id": 38019,
            "uuid": "03d4952fd65a4e719e6026f25dabc18d",
            "short_code": "result",
            "curationCategory": "A",
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            "observation": {
                "ob_id": 37721,
                "uuid": "8d9719be04d148d88d5ed8edd0426cf2",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.5 (v20220721)",
                "abstract": "Data for Figure 9.5 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.5 shows mixed-layer depth in winter and summer. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has 8 panels labelled (a)-(h), with data provided for all panels using this lettering system in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Mixed-layer depth in (a–d) winter and (e–h) summer (a, e).\r\n- Observed climatological mean mixed-layer depth (based on density threshold) from the Argo Mixed Layer Depth Climatology (Holte et al., 2017) using observations for 2000–2019 (b, f).\r\n- Bias between the observation-based estimate (2000–2019) and  the 1995–2014 CMIP6 climatological mean mixed-layer depth (c, d, g, h) .\r\n- Projected mixed-layer depth (MLD) change from 1995–2014 to 2081–2100 under (c, g) SSP1-2.6 and (d, h) SSP5-8.5 scenarios. \r\n\r\nThe (a–d) winter row shows December–January–February (DJF) in the Northern Hemisphere and June–July–August (JJA) in the Southern Hemisphere; the (e–h) summer row shows JJA in the Northern Hemisphere and DJF in the Southern Hemisphere. The mixed-layer depth is the depth where the potential density is 0.03 kg m–3 denser than at 10 m. \r\n\r\nNo overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9). \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.5\r\n \r\n- Data file: Fig9-5a_data.nc: \r\n- Data file: Fig9-5b_data.nc: \r\n- Data file: Fig9-5c_data.nc: \r\n- Data file: Fig9-5d_data.nc: \r\n- Data file: Fig9-5e_data.nc: \r\n- Data file: Fig9-5f_data.nc: \r\n- Data file: Fig9-5g_data.nc: \r\n- Data file: Fig9-5h_data.nc: \r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP stands for Shared Socioeconomic Pathway. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nMixed layer depth maps were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
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                "ob_id": 37720,
                "uuid": "439ccb0b0eb04c17b5c6897fb9cb550b",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.6 (v20220721)",
                "abstract": "Data for Figure 9.6 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.6 shows ocean heat content (OHC) and its changes with time. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has 8 panels labelled (a)-(g), with data provided for all panels using this lettering system in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n-  (a) Time series of global OHC anomaly relative to a 2005–2014 climatology in the upper 2000 m of the ocean, combining observations (Ishii et al., 2017; Baggenstos et al., 2019; Shackleton et al., 2020), model-observation hybrids (Cheng et al., 2019; Zanna et al., 2019), and multi-model means from CMIP6, historical (29 models) and SSP scenarios. \r\n\r\n- Maps of OHC from CMIP6 ensemble bias and observed (Ishii et al., 2017) trends of OHC for 0–700 m for the period 1971–2014 (b, c)\r\n\r\n-  Maps of OHC from CMIP6 ensemble bias and observed (Ishii et al., 2017) trends of OHC for 0–2000 m for the period 2005–2017 (e, f). \r\n\r\n- Projected rate of change 2015–2100 for (d) SSP5-8.5 and (g) SSP1-2.6 scenarios from CMIP6 ensemble means. \r\n\r\n- Projected change in 0–700 m OHC for (d) SSP1-2.6 and (g) SSP5-8.5 in the CMIP6 ensembles, for the period 2091–2100 versus 2005–2014.\r\n\r\nLabel subscripts in (a) indicate number of models per SSP. \r\nNo overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.6\r\n \r\n - Data file: Fig9-6a_data_CMIPlikelybounds.nc:\r\n - Data file: Fig9-6a_data_CMIPmean.nc:\r\n - Data file: Fig9-6a_data_HybridChengmean.nc:\r\n - Data file: Fig9-6a_data_HybridZannamean.nc:\r\n - Data file: Fig9-6a_data_Observedlikelybounds.nc:\r\n - Data file: Fig9-6a_data_Observedmean.nc:\r\n - Data file: Fig9-6a_data_paleo.nc:\r\n - Data file: Fig9-6a_data_ssp126likelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp126mean.nc:\r\n - Data file: Fig9-6a_data_ssp126verylikelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp245likelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp245mean.nc:\r\n - Data file: Fig9-6a_data_ssp245verylikelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp370likelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp370mean.nc: \r\n - Data file: Fig9-6a_data_ssp370verylikelybounds.nc: \r\n - Data file: Fig9-6a_data_ssp585likelybounds.nc:\r\n - Data file: Fig9-6a_data_ssp585mean.nc:\r\n - Data file: Fig9-6a_data_ssp585verylikelybounds.nc:\r\n - Data file: Fig9-6b_data.nc:\r\n - Data file: Fig9-6c_data.nc:\r\n - Data file: Fig9-6d_data.nc:\r\n - Data file: Fig9-6e_data.nc:\r\n - Data file: Fig9-6f_data.nc:\r\n - Data file: Fig9-6g_data.nc:\r\n\r\nOHC stands for Ocean Heat Content.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n OHC maps and OHC timeseries were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\nThe plotting code is designed to use pre-processed CMIP data, rather than the provided netcdf files. To reproduce these figures form the metadata please modify the example code given here: https://github.com/BrodiePearson/IPCC_AR6_Chapter9_Figures/blob/main/Plotting_code_and_data/Fig9_03_SST/Plot_Figure/Example_plotting_from_metadata.m\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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            "ob_id": 38021,
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            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig07/v20220721",
            "numberOfFiles": 19,
            "volume": 8424797,
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            "observation": {
                "ob_id": 37719,
                "uuid": "e2d7ec1924b04bebbb4044982e2be0ff",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.7 (v20220721)",
                "abstract": "Data for Figure 9.7 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.7 shows meridional-depth profiles of zonal-mean potential temperature in the ocean and its rate of change in the upper 2000 m of the Global, Pacific, Atlantic and Indian oceans. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 8 panels labelled (a)-(h), with data provided for all panels using this lettering system in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains: \r\n\r\n- Observed temperatures from Argo climatology 2005–2014 (a, e, i, m)\r\n- Bias of CMIP6 ensemble over same period 2005-2014 (b, f, j, n)\r\n- Future changes under SSP1-2.6 (c, g, k, o) and SSP5-8.5 (d, h, l, p), 1995-2100. \r\n\r\nNo overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where <80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.7\r\n \r\n - Data file: Fig9-7a_data.nc:\r\n - Data file: Fig9-7b_data.nc:\r\n - Data file: Fig9-7c_data.nc:\r\n - Data file: Fig9-7d_data.nc:\r\n - Data file: Fig9-7e_data.nc:\r\n - Data file: Fig9-7f_data.nc:\r\n - Data file: Fig9-7g_data.nc:\r\n - Data file: Fig9-7h_data.nc:\r\n - Data file: Fig9-7i_data.nc:\r\n - Data file: Fig9-7j_data.nc:\r\n - Data file: Fig9-7k_data.nc: \r\n - Data file: Fig9-7l_data.nc:\r\n - Data file: Fig9-7m_data.nc:\r\n- Data file: Fig9-7n_data.nc:\r\n- Data file: Fig9-7o_data.nc:\r\n- Data file: Fig9-7p_data.nc:\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP stands for Shared Socioeconomic Pathway. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Zonal transects were calculated and plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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        },
        {
            "ob_id": 38022,
            "uuid": "3d8b4827a75d43ccb966f5f68e6984b5",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig09/v20220721",
            "numberOfFiles": 21,
            "volume": 1400385,
            "fileFormat": "NetCDF, txt",
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            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37717,
                "uuid": "b35923b0641944178d0c9e17ce7dc9cb",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.9 (v20220721)",
                "abstract": "Data for Figure 9.9 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.9 shows long-term trends of ocean heat content (OHC) and surface temperature. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has 4 panels with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Ice-core rare gas estimates of past mean OHC (units = ZJ), scaled to global mean ocean temperature (°C), and to steric global mean sea level (GMSL) (m) per CCB-2 (red dashed line), compared to surface temperatures (black solid line, gold solid line; °C rightmost axis). \r\n- Southern Ocean sea surface temperature (SST) from multiple proxies in 11 sediment cores and from ice core deuterium excess (Uemura et  al., 2018). \r\n(a) Penultimate glacial interval to last interglacial, 150,000–100,000 yr B2K (before 2000) (Shackleton et al., 2020). First panel.\r\n(b) Last glacial interval to modern interglacial, 40,000–0 yr B2K (Baggenstos et al., 2019; Shackleton et al., 2019). Second panel.\r\n(c) Long-term projected (2000 to 12000 CE) changes of OHC (dashed lines) in response to four greenhouse gas emissions scenarios (Clark et al., 2016) scale similarly to large-scale paleo changes but lag projected global mean SST (solid lines). Third panel.\r\n(d) Model simulated 1500–1999 OHC (Gregory et al., 2006) and 1955–2019 observations (Levitus et al., 2012) updated by NOAA NODC. Fourth panel.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.9\r\n \r\n - Data file: Fig9-9_data_Baggenstoslikely_Deglacial.nc\r\n - Data file: Fig9-9_data_Baggenstosmean_Deglacial.nc\r\n - Data file: Fig9-9_data_GlobalMeanSST_Deglacial.nc\r\n - Data file: Fig9-9_data_GlobalMeanSST_LIG.nc\r\n - Data file: Fig9-9_data_HadCM3_Modern.nc\r\n - Data file: Fig9-9_data_Levitus_Modern.nc\r\n - Data file: Fig9-9_data_SST_to_OHC_Conversion_Factor.nc\r\n - Data file: Fig9-9_data_Shackletonlikely_Deglacial.nc\r\n - Data file: Fig9-9_data_Shackletonlikely_LIG.nc\r\n - Data file: Fig9-9_data_Shackletonmean_Deglacial.nc\r\n - Data file: Fig9-9_data_Shackletonmean_LIG.nc\r\n - Data file: Fig9-9_data_SouthernOceanSST_Deglacial.nc\r\n - Data file: Fig9-9_data_SouthernOceanSST_LIG.nc\r\n - Data file: Fig9-9_data_Uemera_Modern.nc\r\n - Data file: Fig9-9_data_ohc_1280Gt.nc\r\n - Data file: Fig9-9_data_ohc_2560Gt.nc\r\n - Data file: Fig9-9_data_ohc_3840Gt.nc\r\n - Data file: Fig9-9_data_ohc_5120Gt.nc\r\n\r\nChanges in OHC (dashed lines) track changes in Southern Ocean SST (solid lines). \r\nAll data expressed as anomalies relative to pre-industrial time. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\nOHC stands for Ocean Heat Content.\r\nGMSL stands for Global Mean Sea Level.\r\nNOAA NODC is the National Oceanic and Atmospheric Administration's National Oceanographic Data Center.\r\n\r\n---------------------------------------------------\r\nTemporal Range of Paleoclimate Data\r\n---------------------------------------------------\r\nThis dataset covers a paleoclimate timespan from -150kyr (150 thousand years ago) to 14000 CE (long-term future projection).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nOHC and SST time series were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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        {
            "ob_id": 38023,
            "uuid": "4feba0ce7dfa428e8bf184690a782205",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig12/v20220721",
            "numberOfFiles": 12,
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            "observation": {
                "ob_id": 37727,
                "uuid": "b37501409dd641219dd7c57174acdc35",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.12 (v20220721)",
                "abstract": "Data for Figure 9.12 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.12 shows CMIP6 multi-model mean projected change contributions to relative sea level change in steric sea level anomaly, thermosteric sea level anomaly, and halosteric sea level anomaly between 1995–2014 and 2081–2100.\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 9 subpanels, with data provided for all panels. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a, d) CMIP6 multi-model mean projected change contributions to relative sea level change in steric sea level anomaly between 1995-2014 and 2081-2100..\r\n- (b, e) CMIP6 multi-model mean projected change contributions to relative sea level change in thermosteric sea level anomaly between 1995-2014 and 2081-2100.\r\n- (c, f) CMIP6 multi-model mean projected change contributions to relative sea level change in halosteric sea level anomaly between 1995-2014 and 2081-2100.\r\n- (g–i) Standard deviation of ocean dynamic sea level change from (g) Aviso observations (10-day high-pass filter); (h) five-day mean of high-resolution Ocean Model Intercomparison Project phase 2 (OMIP-2) models forced with observed fluxes; and (i) five-day mean of low-resolution OMIP-2 models which are comparable in resolution to the models in (a–f).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.12\r\n \r\n - Data file: Fig9-12a_data.nc\r\n - Data file: Fig9-12b_data.nc\r\n - Data file: Fig9-12c_data.nc\r\n - Data file: Fig9-12d_data.nc\r\n - Data file: Fig9-12e_data.nc\r\n - Data file: Fig9-12f_data.nc\r\n - Data file: Fig9-12g_data.nc\r\n - Data file: Fig9-12h_data.nc\r\n - Data file: Fig9-12i_data.nc\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nOMIP-2 is the Ocean Model Intercomparison Project phase 2.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the output data for this figure, contained in a dedicated GitHub repository along with code to plot the figure."
            },
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        {
            "ob_id": 38024,
            "uuid": "3cc67b8324d94379bc293bad9272c5bc",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig13/v20220721",
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            "observation": {
                "ob_id": 37726,
                "uuid": "6f6697fff85e42fdb87156ad34e4a24e",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.13 (v20220721)",
                "abstract": "Data for Figure 9.13 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.13 shows Arctic sea ice historical records and CMIP6 projections. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n- (Left panel) Absolute anomaly of monthly-mean Arctic sea ice area during the period 1979 to 2019 relative to the average monthly-mean Arctic sea ice area during the period 1979 to 2008. \r\n- (Right panel) Sea ice concentration in the Arctic for March and September, which usually are the months of maximum and minimum sea ice area, respectively. \r\n\r\nFirst column: Satellite-retrieved mean sea ice concentration during the decade 1979–1988. Second column: Satellite-retrieved mean sea ice concentration during the decade 2010-2019. \r\nThird column: Absolute change in sea ice concentration between these two decades, with grid lines indicating non-significant differences. \r\nFourth column: Number of available CMIP6 models that simulate a mean sea ice concentration above 15 % for the decade 2045–2054. \r\n\r\nThe average observational record of sea ice area is derived from the UHH sea ice area product (Doerr et al., 2021), based on the average sea ice concentration of OSISAF/CCI (OSI-450 for 1979–2015, OSI-430b for 2016–2019) (Lavergne et al., 2019), NASA Team (version 1, 1979–2019) (Cavalieri et al., 1996) and Bootstrap (version 3, 1979–2019) (Comiso, 2017) that is also used for the figure panels showing observed sea ice concentration. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.13\r\n \r\n - Data file: NSIDC_polehole_big.nc\r\n - Data file: NSIDC_polehole_small.nc\r\n - Data file: SeaIceArea__NorthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: SeaIceArea__SouthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: cryo_div.txt\r\n - Data file: cryo_seq.txt\r\n\r\nDatafile  'mapplot_data.npz' included in the 'Plotted Data' folder of the dedicated GitHub repository is not archived here but on Zenodo at the link provided in the Related Documents section of this catalogue record.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nNSIDC is the National Snow and Ice Data Center.\r\nUHH is the University of Hamburg (Universtität Hamburg).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nBoth panels were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the output data and scripts for this figure, contained in a dedicated GitHub repository."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38025,
            "uuid": "61220c66d0f14d3db25c2c75be9f7dab",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig14/v20220721",
            "numberOfFiles": 17,
            "volume": 41147764,
            "fileFormat": "Data are net-CDF and csv formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37725,
                "uuid": "e25c3cffd4ae4abc8b2ff9b755fce164",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.14 (v20220721)",
                "abstract": "Data for Figure 9.14 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.14 shows monthly mean March and September sea ice area as a function of global surface air temperature (GSAT) anomaly; cumulative anthropogenic CO2 emissions; year in CMIP6 model simulations and in observations. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 8 subpanels, with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a) Monthly mean March sea ice area as a function of global surface air temperature (GSAT) anomaly.\r\n- (b) Monthly mean March sea ice area as a function of cumulative anthropogenic CO2 emissions.\r\n- (c) Monthly mean March sea ice area as a function of year in CMIP6 model simulations and observations.\r\n- (d) Sensitivity of March sea ice loss to anthropogenic CO2 emissions as a function of modelled sensitivity of GSAT to anthropogenic CO2 emissions.\r\n- (e) Monthly mean September sea ice area as a function of global surface air temperature (GSAT) anomaly. \r\n- (f) Monthly mean September sea ice area as a function of cumulative anthropogenic CO2 emissions.\r\n- (g) Monthly mean September sea ice area as a function of year in CMIP6 model simulations and observations\r\n- (h) Sensitivity of September sea ice loss to anthropogenic CO2 emissions as a function of modelled sensitivity of GSAT to anthropogenic CO2 emissions.\r\n\r\nCO2 emissions are shown as CMIP6 model simulations (shading, ensemble mean as bold line) and observations (black dots).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.14\r\n \r\n - Data file: CMIP3_sensitivity_nh.nc\r\n - Data file: CMIP5_sensitivity_nh.nc\r\n - Data file: CMIP6_historical_nh.nc\r\n - Data file: CMIP6_sensitivity_nh.nc\r\n - Data file: CMIP6_ssp119_nh.nc\r\n - Data file: CMIP6_ssp126_nh.nc\r\n - Data file: CMIP6_ssp245_nh.nc\r\n - Data file: CMIP6_ssp585_nh.nc\r\n - Data file: CO2_CMIP6.nc\r\n - Data file: IPCC_GSAT.csv: Provisional time series for use in GSAT calculations. \r\n - Data file: SeaIceArea__NorthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: SeaIceArea__SouthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: obs_sensitivity_nh.nc\r\n\r\nCMIP3 is the third phase of the Coupled Model Intercomparison Project.\r\nCMIP5 is the fifth phase of Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nGSAT stands for Global Surface Air Temperature. \r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nUHH is the University of Hamburg (Universität Hamburg).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nSections of the figure in the report were plotted using standard matplotlib software - code is available via the link in the documentation. Some data has been converted to net-CDF format for archival, original .mat files used in the plotting script are archived on Zenodo at the link provided in the Related Document section of this catalogue record.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38027,
            "uuid": "81e2e3d49f6b43619c96953516a37b40",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig15/v20220721",
            "numberOfFiles": 9,
            "volume": 4975832,
            "fileFormat": "NetCDF, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37724,
                "uuid": "65c832a5eeda4ed7a9b0a8af6cf5058d",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.15 (v20220712)",
                "abstract": "Data for Figure 9.15 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.15 shows Antarctic sea ice historical records and CMIP6 projections. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (Left panel) Absolute anomaly of observed monthly mean Antarctic sea ice area during the period 1979–2019 relative to the average monthly mean Antarctic sea ice area during the period 1979–2008. \r\n- (Right panel) Sea ice coverage in the Antarctic as given by the average of the three most widely used satellite-based estimates for September and February, which usually are the months of maximum and minimum sea ice coverage, respectively. \r\n\r\nFirst column: Mean sea ice coverage during the decade 1979–1988. \r\nSecond column: Mean sea ice coverage during the decade 2010–2019. \r\nThird column: Absolute change in sea ice concentration between these two decades, with grid lines indicating non-significant differences. \r\nFourth column: Number of available CMIP6 models that simulate a mean sea ice concentration above 15% for the decade 2045–2054. \r\n\r\nThe average observational record of sea ice area is derived from the UHH sea ice area product (Doerr et al., 2021), based on the average sea ice concentration of OSISAF/CCI (OSI-450 for 1979–2015, OSI-430b for 2016–2019) (Lavergne et al., 2019), NASA Team (version 1, 1979–2019) (Cavalieri et al., 1996) and Bootstrap (version 3, 1979–2019) (Comiso, 2017) that is also used for the figure panels showing observed sea ice concentration. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.15\r\n \r\n - Data file: NSIDC_polehole_big.nc\r\n - Data file: NSIDC_polehole_small.nc\r\n - Data file: SeaIceArea__NorthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: SeaIceArea__SouthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: cryo_div.txt\r\n - Data file: cryo_seq.txt\r\n\r\nDatafile  'mapplot_data.npz' included in the 'Plotted Data' folder of the GitHub repository is not archived here but on Zenodo at the link provided in the Related Documents section of this catalogue record.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nNSIDC is the National Snow and Ice Data Center.\r\nUHH is the University of Hamburg (Universität Hamburg).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nBoth panels were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the code and output data for this figure, contained in a dedicated GitHub repository."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38028,
            "uuid": "a13aea49e98d43d7b3b118a85aacb46b",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig22/v20220721",
            "numberOfFiles": 6,
            "volume": 5175,
            "fileFormat": "txt",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37736,
                "uuid": "80475295b32f4df6879ad7d2a23a88c1",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.22 (v20220721)",
                "abstract": "Data for Figure 9.22 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.22 shows simulated versus observed permafrost extent and volume change by warming level. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels in one central directory.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a) Diagnosed Northern Hemisphere permafrost extent (area with perennially frozen ground at 15 m depth, or at the deepest model soil level if this is above 15 m) for 1979–1998, for available CMIP5 and CMIP6 models, from the first ensemble member of the historical coupled run, and for CMIP6 AMIP (atmosphere+land surface, prescribed ocean) and land-hist (land only, prescribed atmospheric forcing) runs. \r\n\r\n- (b) Simulated global permafrost volume change between the surface and 3 m depth as a function of the simulated global surface air temperature (GSAT) change, from the first ensemble members of a selection of scenarios, for available CMIP6 models. \r\n\r\nEstimates of current permafrost extents based on physical evidence and reanalyses are indicated as black symbols – triangle: Obu et al. (2018); star: Zhang et al. (1999); circle: central value and associated range from Gruber (2012). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.22\r\n \r\n- Data file: pf15m_CMIP5historical_NH_1979-1998.txt\r\n- Data file: pf15m_amip_NH_1979-1998.txt\r\n- Data file: pf15m_historical_NH_1979-1998.txt\r\n- Data file: pf15m_land-hist_NH_1979-1998.txt\r\n- Data file: pfv_ACCESS-CM2_historical_ssp126.nc\r\n- Data file: pfv_ACCESS-CM2_historical_ssp245.nc\r\n- Data file: pfv_ACCESS-CM2_historical_ssp370.nc\r\n- Data file: pfv_ACCESS-CM2_historical_ssp585.nc\r\n- Data file: pfv_ACCESS-ESM1-5_historical_ssp126.nc\r\n- Data file: pfv_ACCESS-ESM1-5_historical_ssp245.nc\r\n- Data file: pfv_ACCESS-ESM1-5_historical_ssp370.nc\r\n- Data file: pfv_ACCESS-ESM1-5_historical_ssp585.nc\r\n- Data file: pfv_BCC-CSM2-MR_historical_ssp126.nc\r\n- Data file: pfv_BCC-CSM2-MR_historical_ssp245.nc\r\n- Data file: pfv_BCC-CSM2-MR_historical_ssp370.nc\r\n- Data file: pfv_BCC-CSM2-MR_historical_ssp585.nc\r\n- Data file: pfv_CAMS-CSM1-0_historical_ssp126.nc\r\n- Data file: pfv_CAMS-CSM1-0_historical_ssp245.nc\r\n- Data file: pfv_CAMS-CSM1-0_historical_ssp370.nc\r\n- Data file: pfv_CAMS-CSM1-0_historical_ssp585.nc\r\n- Data file: pfv_CESM2-WACCM_historical_ssp126.nc\r\n- Data file: pfv_CESM2-WACCM_historical_ssp245.nc\r\n- Data file: pfv_CESM2-WACCM_historical_ssp370.nc\r\n- Data file: pfv_CESM2-WACCM_historical_ssp585.nc\r\n- Data file: pfv_CESM2_historical_ssp126.nc\r\n- Data file: pfv_CESM2_historical_ssp245.nc\r\n- Data file: pfv_CESM2_historical_ssp370.nc\r\n- Data file: pfv_CESM2_historical_ssp585.nc\r\n- Data file: pfv_CNRM-CM6-1-HR_historical_ssp126.nc\r\n- Data file: pfv_CNRM-CM6-1-HR_historical_ssp245.nc\r\n- Data file: pfv_CNRM-CM6-1-HR_historical_ssp370.nc\r\n- Data file: pfv_CNRM-CM6-1-HR_historical_ssp585.nc\r\n- Data file: pfv_CNRM-CM6-1_historical_ssp126.nc\r\n- Data file: pfv_CNRM-CM6-1_historical_ssp245.nc\r\n- Data file: pfv_CNRM-CM6-1_historical_ssp370.nc\r\n- Data file: pfv_CNRM-CM6-1_historical_ssp585.nc\r\n- Data file: pfv_CNRM-ESM2-1_historical_ssp126.nc\r\n- Data file: pfv_CNRM-ESM2-1_historical_ssp245.nc\r\n- Data file: pfv_CNRM-ESM2-1_historical_ssp370.nc\r\n- Data file: pfv_CNRM-ESM2-1_historical_ssp585.nc\r\n- Data file: pfv_CanESM5-CanOE_historical_ssp126.nc\r\n- Data file: pfv_CanESM5-CanOE_historical_ssp245.nc\r\n- Data file: pfv_CanESM5-CanOE_historical_ssp370.nc\r\n- Data file: pfv_CanESM5-CanOE_historical_ssp585.nc\r\n- Data file: pfv_CanESM5_historical_ssp126.nc\r\n- Data file: pfv_CanESM5_historical_ssp245.nc\r\n- Data file: pfv_CanESM5_historical_ssp370.nc\r\n- Data file: pfv_CanESM5_historical_ssp585.nc\r\n- Data file: pfv_EC-Earth3_historical_ssp126.nc\r\n- Data file: pfv_EC-Earth3_historical_ssp245.nc\r\n- Data file: pfv_EC-Earth3_historical_ssp370.nc\r\n- Data file: pfv_EC-Earth3_historical_ssp585.nc\r\n- Data file: pfv_FGOALS-g3_historical_ssp126.nc\r\n- Data file: pfv_FGOALS-g3_historical_ssp245.nc\r\n- Data file: pfv_FGOALS-g3_historical_ssp370.nc\r\n- Data file: pfv_FGOALS-g3_historical_ssp585.nc\r\n- Data file: pfv_GFDL-CM4_historical_ssp245.nc\r\n- Data file: pfv_GFDL-CM4_historical_ssp585.nc\r\n- Data file: pfv_GFDL-ESM4_historical_ssp126.nc\r\n- Data file: pfv_GFDL-ESM4_historical_ssp245.nc\r\n- Data file: pfv_GFDL-ESM4_historical_ssp370.nc\r\n- Data file: pfv_GFDL-ESM4_historical_ssp585.nc\r\n- Data file: pfv_GISS-E2-1-G_historical_ssp126.nc\r\n- Data file: pfv_GISS-E2-1-G_historical_ssp245.nc\r\n- Data file: pfv_GISS-E2-1-G_historical_ssp370.nc\r\n- Data file: pfv_GISS-E2-1-G_historical_ssp585.nc\r\n- Data file: pfv_HadGEM3-GC31-LL_historical_ssp126.nc\r\n- Data file: pfv_HadGEM3-GC31-LL_historical_ssp245.nc\r\n- Data file: pfv_HadGEM3-GC31-LL_historical_ssp585.nc\r\n- Data file: pfv_IPSL-CM6A-LR_historical_ssp126.nc\r\n- Data file: pfv_IPSL-CM6A-LR_historical_ssp245.nc\r\n- Data file: pfv_IPSL-CM6A-LR_historical_ssp370.nc\r\n- Data file: pfv_IPSL-CM6A-LR_historical_ssp585.nc\r\n- Data file: pfv_KACE-1-0-G_historical_ssp126.nc\r\n- Data file: pfv_KACE-1-0-G_historical_ssp245.nc\r\n- Data file: pfv_KACE-1-0-G_historical_ssp370.nc\r\n- Data file: pfv_KACE-1-0-G_historical_ssp585.nc\r\n- Data file: pfv_MIROC-ES2L_historical_ssp126.nc\r\n- Data file: pfv_MIROC-ES2L_historical_ssp245.nc\r\n- Data file: pfv_MIROC-ES2L_historical_ssp370.nc\r\n- Data file: pfv_MIROC-ES2L_historical_ssp585.nc\r\n- Data file: pfv_MIROC6_historical_ssp126.nc\r\n- Data file: pfv_MIROC6_historical_ssp245.nc\r\n- Data file: pfv_MIROC6_historical_ssp370.nc\r\n- Data file: pfv_MIROC6_historical_ssp585.nc\r\n- Data file: pfv_MPI-ESM1-2-HR_historical_ssp126.nc\r\n- Data file: pfv_MPI-ESM1-2-HR_historical_ssp245.nc\r\n- Data file: pfv_MPI-ESM1-2-HR_historical_ssp370.nc\r\n- Data file: pfv_MPI-ESM1-2-HR_historical_ssp585.nc\r\n- Data file: pfv_MPI-ESM1-2-LR_historical_ssp126.nc\r\n- Data file: pfv_MPI-ESM1-2-LR_historical_ssp245.nc\r\n- Data file: pfv_MPI-ESM1-2-LR_historical_ssp370.nc\r\n- Data file: pfv_MPI-ESM1-2-LR_historical_ssp585.nc\r\n- Data file: pfv_MRI-ESM2-0_historical_ssp126.nc\r\n- Data file: pfv_MRI-ESM2-0_historical_ssp245.nc\r\n- Data file: pfv_MRI-ESM2-0_historical_ssp370.nc\r\n- Data file: pfv_MRI-ESM2-0_historical_ssp585.nc\r\n- Data file: pfv_NorESM2-LM_historical_ssp126.nc\r\n- Data file: pfv_NorESM2-LM_historical_ssp245.nc\r\n- Data file: pfv_NorESM2-LM_historical_ssp370.nc\r\n- Data file: pfv_NorESM2-LM_historical_ssp585.nc\r\n- Data file: pfv_NorESM2-MM_historical_ssp126.nc\r\n- Data file: pfv_NorESM2-MM_historical_ssp245.nc\r\n- Data file: pfv_NorESM2-MM_historical_ssp370.nc\r\n- Data file: pfv_NorESM2-MM_historical_ssp585.nc\r\n- Data file: pfv_UKESM1-0-LL_historical_ssp126.nc\r\n- Data file: pfv_UKESM1-0-LL_historical_ssp245.nc\r\n- Data file: pfv_UKESM1-0-LL_historical_ssp370.nc\r\n- Data file: pfv_UKESM1-0-LL_historical_ssp585.nc\r\n\r\nIn the GitHub repository the filenames differ from that listed above, the final underscore is replaced with a '+'.\r\nFor example, ' pfv_ACCESS-CM2_historical_ssp126.nc' in the repository is called ' pfv_ACCESS-CM2_historical+ssp126.nc'\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nAMIP is the Atmospheric Modelling Intercomparison Project.\r\nGSAT stands for Global Surface Air Temperature.\r\nACCESS-CM2 is the Australian Community Climate and Earth System Simulator coupled climate model.\r\nACCESS-ESM1-5 is the Australian Community Climate and Earth System Simulator Earth system model version designed to participate in CMIP6 simulations.\r\nBCC-CSM2-MR is one of the Beijing Climate Center Climate System Models designed for use in CMIP6 simulations.\r\nCAMS-CSM1-0 is the Chinese Academy of Meteorological Sciences Climate System Model version 1.\r\nCESM is the Community Earth System Model. \r\nCESM2-WACCM is the Community System Model - Whole Atmosphere Community Climate Model.\r\nCNRM-CM6-1 is the Centre National de Recherches Météorologiques Climate Model for CMIP6.\r\nCNRM-CM6-1-HR is the Centre National de Recherches Météorologiques Climate Model for CMIP6 - altered Horizontal Resolution.\r\nCNRM-ESM2-1 is the Centre National de Recherches Météorologiques Earth System Model, derived from CNRM-CM6-1.\r\nCanESM5 is the Canadian Earth System Model version 5.\r\nCanESM5-CanOE is the Canadian Earth System Model version 5 - Canadian Ocean Ecosystem.\r\nEC-Earth3 is the European Community Earth-system model version 3.\r\nFGOALS-g3 is the Flexible Global Ocean-Atmosphere-Land System Model, Grid-point Version 3\r\nGFDL-ESM4 is the Geophysical Fluid Dynamics Laboratory - Earth System Model version 4.\r\nGISS-E2-1-G is the Goddard Institute for Space Studies - chemistry-climate model version E2.1, using the GISS Ocean v1 (G01) model.\r\nHadGEM3-GC31-LL is the Met Offfice Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N96/ORCA1.\r\nIPSL-CM6A-LR is the Institut Pierre-Simon Laplace Climate Model for CMIP6 - Low Resolution.\r\nKACE-1-0-G is the Korean Advanced Community Earth system model. \r\nMIROC-ES2L is the Model for Interdisciplinary Research on Climate - Earth System version 2 for Long-term simulations.\r\nMIROC6 is the Model for Interdisciplinary Research on Climate - version 6.\r\nMPI-ESM1-2-HR is the Max Planck Institute Earth System Model - version 2 - altered Horizontal Resolution.\r\nMPI-ESM1-2-LR is the Max Planck Institute Earth System Model - version 2 - Low Resolution.\r\nMRI-ESM2-0 is the Meteorological Research Institute Earth System Model version 2.0.\r\nNorESM2-LM is the Norwegian Earth System Model version 2 - 2 degree resolution for atmosphere and land components, 1 degree resolution for ocean and sea-ice components.\r\nNorESM2-MM is the Norwegian Earth System Model version 2 - 1 degree resolution for all model components.\r\nUKESM1-0-LL is the United Kingdom Earth System Modelling project - version 1 - 2 degree resolution for all model components.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nThe panels were plotted using Python and shell scripts (BASH files) - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the code and output data for this figure, contained in a dedicated GitHub repository."
            },
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            "ob_id": 38029,
            "uuid": "a8aeed1b64c94640ada20760220803ba",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig32/v20220721",
            "numberOfFiles": 9,
            "volume": 431159,
            "fileFormat": "NetCDF, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37730,
                "uuid": "6b33327d0d0d4bcca872b431279086db",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.32 (v20220721)",
                "abstract": "Data for Figure 9.32 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.32 shows projected median frequency amplification factors for the 1% average annual probability extreme still water level in 2050 and 2100. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 6 subpanels, with data provided for panels a-f.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Projected median frequency amplification factors for 1% average annual probability extreme still water level in 2050 (a, c, e) and 2100 (b, d, f).\r\n- Regional projections for these under:\r\n(a, b) SSP5-85.\r\n(c, d) SSP2-45.\r\n(e, f) SSP1-26.\r\n\r\n1% average annual probability extreme still water level is defined as the 99th percentile of daily observed water levels over 1995–2014. Based on a peak-over-threshold (99.7%) method applied to the historical extreme still water levels of Global Extreme Sea Level Analysis version 2 (GESLA2) following Special Report on Ocean and Cryosphere in a Changing Climate (SROCC) and additionally fitting a Gumbel distribution between Mean Higher High Water (MHHW) and the threshold following Buchanan et al. (2016), using the regional sea level projections of Section 9.6.3.3 for (a-f).\r\n\r\n Further details on data sources and processing are available in the chapter data table \r\n(Table 9.SM.9).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.32\r\n \r\n - Data file: Fig9-32a_facts_esl_af_allow_ssp585_2050.nc\r\n - Data file: Fig9-32b_facts_esl_af_allow_ssp585_2100.nc\r\n - Data file: Fig9-32c_facts_esl_af_allow_ssp245_2050.nc\r\n - Data file: Fig9-32d_facts_esl_af_allow_ssp245_2100.nc\r\n - Data file: Fig9-32e_facts_esl_af_allow_ssp126_2050.nc\r\n - Data file: Fig9-32f_facts_esl_af_allow_ssp126_2100.nc\r\n\r\nPython file 'facts_esl_output_to_NetCDF.py' included in the 'Plotted Data' folder of the dedicated GitHub repository is not archived here but on Zenodo at the link provided in the Related Documents section of this catalogue record. This is a script converting ESL results in CSV format to NetCDF.\r\n\r\nSSP stands for Shared Socioeconomic Pathway. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nGESLA2 is the Global Extreme Sea Level Analysis version 2.\r\nSROCC stands for Ocean and Cryosphere in a Changing Climate. \r\nMHHW stands for Mean Higher High Water.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nMap and figure plots were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n - Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n - Link to the code and output data for this figure, contained in a dedicated GitHub repository."
            },
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            "uuid": "b1561339d839436f905c3128717bfd35",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig26/v20220721",
            "numberOfFiles": 24,
            "volume": 6045920,
            "fileFormat": "Data are net-CDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "onlineresource_set": []
        },
        {
            "ob_id": 38031,
            "uuid": "45714eeaacde46b6a1d0de97f35e51d8",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig24/v20221114",
            "numberOfFiles": 101,
            "volume": 999763,
            "fileFormat": "NetCDF, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37735,
                "uuid": "5806683122b74f4ca60e0d6c546583f9",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.24 (v20221114)",
                "abstract": "Data for Figure 9.24 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.24 shows simulated CMIP6 and observed snow cover extent (SCE). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels in one central directory in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a) Simulated CMIP6 and observed (Mudryk et al., 2020) SCE (in millions of km2) for 1981–2014.\r\n- (b) Spring (March to May) Northern Hemisphere SCE against global surface air temperature (GSAT) (relative to the 1995–2014 average) for the CMIP6 Tier 1 scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5), with linear regressions. \r\n\r\n(a) Boxes and whiskers with outliers represent monthly mean values for the individual CMIP6 models averaged over 1981–2014, with the red bar indicating the median of the CMIP6 multi-model ensemble for that period. The observed interannual distribution over the period is represented in green, with the yellow bar indicating the median.\r\n\r\n(b) Each data point is the mean for one CMIP6 simulation (first ensemble member for each available model) in the corresponding temperature bin. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.24\r\n \r\n - Data file: Mudryk_scf_1981-2014.txt\r\n - Data file: snc_clim_CMIP6_historical_1981-2014.txt\r\n - Data file: sncbin_BCC-CSM2-MR_historical_ssp126.nc\r\n - Data file: sncbin_BCC-CSM2-MR_historical_ssp245.nc\r\n - Data file: sncbin_BCC-CSM2-MR_historical_ssp370.nc\r\n - Data file: sncbin_BCC-CSM2-MR_historical_ssp585.nc\r\n - Data file: sncbin_CanESM5_historical_ssp119.nc\r\n - Data file: sncbin_CanESM5_historical_ssp126.nc\r\n - Data file: sncbin_CanESM5_historical_ssp245.nc\r\n - Data file: sncbin_CanESM5_historical_ssp370.nc\r\n - Data file: sncbin_CanESM5_historical_ssp585.nc\r\n - Data file: sncbin_CESM2_historical_ssp126.nc\r\n - Data file: sncbin_CESM2_historical_ssp245.nc\r\n - Data file: sncbin_CESM2_historical_ssp370.nc\r\n - Data file: sncbin_CESM2_historical_ssp585.nc\r\n - Data file: sncbin_CESM2-WACCM_historical_ssp126.nc\r\n - Data file: sncbin_CESM2-WACCM_historical_ssp245.nc\r\n - Data file: sncbin_CESM2-WACCM_historical_ssp370.nc\r\n - Data file: sncbin_CESM2-WACCM_historical_ssp585.nc\r\n - Data file: sncbin_CIESM_historical_ssp126.nc\r\n - Data file: sncbin_CIESM_historical_ssp245.nc\r\n - Data file: sncbin_CIESM_historical_ssp585.nc\r\n - Data file: sncbin_CMCC-CM2-SR5_historical_ssp126.nc\r\n - Data file: sncbin_CNRM-CM6-1_historical_ssp126.nc\r\n - Data file: sncbin_CNRM-CM6-1_historical_ssp245.nc\r\n - Data file: sncbin_CNRM-CM6-1_historical_ssp370.nc\r\n - Data file: sncbin_CNRM-CM6-1_historical_ssp585.nc\r\n - Data file: sncbin_CNRM-CM6-1-HR_historical_ssp126.nc\r\n - Data file: sncbin_CNRM-CM6-1-HR_historical_ssp245.nc\r\n - Data file: sncbin_CNRM-CM6-1-HR_historical_ssp370.nc\r\n - Data file: sncbin_CNRM-CM6-1-HR_historical_ssp585.nc\r\n - Data file: sncbin_CNRM-ESM2-1_historical_ssp119.nc\r\n - Data file: sncbin_CNRM-ESM2-1_historical_ssp126.nc\r\n - Data file: sncbin_CNRM-ESM2-1_historical_ssp245.nc\r\n - Data file: sncbin_CNRM-ESM2-1_historical_ssp370.nc\r\n - Data file: sncbin_CNRM-ESM2-1_historical_ssp585.nc\r\n - Data file: sncbin_EC-Earth3_historical_ssp126.nc\r\n - Data file: sncbin_EC-Earth3_historical_ssp245.nc\r\n - Data file: sncbin_EC-Earth3_historical_ssp370.nc\r\n - Data file: sncbin_EC-Earth3_historical_ssp585.nc\r\n - Data file: sncbin_EC-Earth3-Veg_historical_ssp126.nc\r\n - Data file: sncbin_EC-Earth3-Veg_historical_ssp245.nc\r\n - Data file: sncbin_EC-Earth3-Veg_historical_ssp370.nc\r\n - Data file: sncbin_EC-Earth3-Veg_historical_ssp585.nc\r\n - Data file: sncbin_FGOALS-f3-L_historical_ssp126.nc\r\n - Data file: sncbin_FGOALS-f3-L_historical_ssp245.nc\r\n - Data file: sncbin_FGOALS-f3-L_historical_ssp370.nc\r\n - Data file: sncbin_FGOALS-f3-L_historical_ssp585.nc\r\n - Data file: sncbin_GFDL-CM4_historical_ssp245.nc\r\n - Data file: sncbin_GFDL-CM4_historical_ssp585.nc\r\n - Data file: sncbin_GFDL-ESM4_historical_ssp126.nc\r\n - Data file: sncbin_GFDL-ESM4_historical_ssp245.nc\r\n - Data file: sncbin_GFDL-ESM4_historical_ssp370.nc\r\n - Data file: sncbin_GFDL-ESM4_historical_ssp585.nc\r\n - Data file: sncbin_GISS-E2-1-G_historical_ssp119.nc\r\n - Data file: sncbin_GISS-E2-1-G_historical_ssp126.nc\r\n - Data file: sncbin_GISS-E2-1-G_historical_ssp245.nc\r\n - Data file: sncbin_GISS-E2-1-G_historical_ssp370.nc\r\n - Data file: sncbin_GISS-E2-1-G_historical_ssp585.nc\r\n - Data file: sncbin_HadGEM3-GC31-LL_historical_ssp126.nc\r\n - Data file: sncbin_HadGEM3-GC31-LL_historical_ssp245.nc\r\n - Data file: sncbin_HadGEM3-GC31-LL_historical_ssp585.nc\r\n - Data file: sncbin_IPSL-CM6A-LR_historical_ssp119.nc\r\n - Data file: sncbin_IPSL-CM6A-LR_historical_ssp126.nc\r\n - Data file: sncbin_IPSL-CM6A-LR_historical_ssp245.nc\r\n - Data file: sncbin_IPSL-CM6A-LR_historical_ssp370.nc\r\n - Data file: sncbin_IPSL-CM6A-LR_historical_ssp585.nc\r\n - Data file: sncbin_MIROC6_historical_ssp119.nc\r\n - Data file: sncbin_MIROC6_historical_ssp126.nc\r\n - Data file: sncbin_MIROC6_historical_ssp245.nc\r\n - Data file: sncbin_MIROC6_historical_ssp370.nc\r\n - Data file: sncbin_MIROC6_historical_ssp585.nc\r\n - Data file: sncbin_MIROC-ES2L_historical_ssp119.nc\r\n - Data file: sncbin_MIROC-ES2L_historical_ssp126.nc\r\n - Data file: sncbin_MIROC-ES2L_historical_ssp245.nc\r\n - Data file: sncbin_MIROC-ES2L_historical_ssp370.nc\r\n - Data file: sncbin_MIROC-ES2L_historical_ssp585.nc\r\n - Data file: sncbin_MPI-ESM1-2-HR_historical_ssp126.nc\r\n - Data file: sncbin_MPI-ESM1-2-HR_historical_ssp245.nc\r\n - Data file: sncbin_MPI-ESM1-2-HR_historical_ssp370.nc\r\n - Data file: sncbin_MPI-ESM1-2-HR_historical_ssp585.nc\r\n - Data file: sncbin_MRI-ESM2-0_historical_ssp119.nc\r\n - Data file: sncbin_MRI-ESM2-0_historical_ssp126.nc\r\n - Data file: sncbin_MRI-ESM2-0_historical_ssp245.nc\r\n - Data file: sncbin_MRI-ESM2-0_historical_ssp370.nc\r\n - Data file: sncbin_MRI-ESM2-0_historical_ssp585.nc\r\n - Data file: sncbin_NorESM2-LM_historical_ssp126.nc\r\n - Data file: sncbin_NorESM2-LM_historical_ssp245.nc\r\n - Data file: sncbin_NorESM2-LM_historical_ssp370.nc\r\n - Data file: sncbin_NorESM2-LM_historical_ssp585.nc\r\n - Data file: sncbin_NorESM2-MM_historical_ssp126.nc\r\n - Data file: sncbin_NorESM2-MM_historical_ssp245.nc\r\n - Data file: sncbin_NorESM2-MM_historical_ssp370.nc\r\n - Data file: sncbin_NorESM2-MM_historical_ssp585.nc\r\n - Data file: sncbin_UKESM1-0-LL_historical_ssp119.nc\r\n - Data file: sncbin_UKESM1-0-LL_historical_ssp126.nc\r\n - Data file: sncbin_UKESM1-0-LL_historical_ssp245.nc\r\n - Data file: sncbin_UKESM1-0-LL_historical_ssp370.nc\r\n - Data file: sncbin_UKESM1-0-LL_historical_ssp585.nc\r\n\r\nIn the linked GitHub repository the filename convention differs slightly from the above, the final underscore is replaced with a '+'. \r\nFor example, 'sncbin_UKESM1-0-LL_historical_ssp585.nc' in the repository is called 'sncbin_UKESM1-0-LL_historical+ssp585.nc' in the GitHub repository.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP370 is the Shared Socioeonomic Pathway which represents the upper-middle range of radiative forcing and development scenarios, consistent with RCP6.0.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels (a) and (b) were plotted using standard Python software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the output data for this figure, contained in a dedicated GitHub repository. Note the difference in filenames mentioned above in the Data provided section."
            },
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        {
            "ob_id": 38032,
            "uuid": "62649b8e31f345a380a1d9c2ed24a192",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig26/v20220721",
            "numberOfFiles": 25,
            "volume": 6048943,
            "fileFormat": "Data are net-CDF formatted",
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            "observation": {
                "ob_id": 37734,
                "uuid": "64fa14764534431f805e747249786f88",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.26 (v20220721)",
                "abstract": "Data for Figure 9.26 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.26 shows median global mean and regional relative sea level projections (m) by contribution for the SSP1-2.6 and SSP5-8.5 scenarios. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 3 subpanels, with data provided for all panels in one central directory in the GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Upper time series: Global mean contributions to sea level change as a function of time, relative to 1995–2014. \r\n\r\n- Lower maps: Regional projections of the sea level contributions in 2100 relative to 1995–2014 for SSP5-8.5 and SSP1-2.6. Vertical land motion is common to both SSPs.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.26\r\n\r\n - Data file: Fig9-26_2100likelyranges.nc\r\n - Data file: Fig9-26_data_landmotion_map.nc\r\n - Data file: Fig9-26_data_ssp126_Antarctic_timeseries.nc\r\n - Data file: Fig9-26_data_ssp126_Greenland_map.nc\r\n - Data file: Fig9-26_data_ssp126_Greenland_timeseries.nc\r\n - Data file: Fig9-26_data_ssp126_glacier_map.nc\r\n - Data file: Fig9-26_data_ssp126_glacier_timeseries.nc\r\n - Data file: Fig9-26_data_ssp126_landwater_map.nc\r\n - Data file: Fig9-26_data_ssp126_landwater_timeseries.nc\r\n - Data file: Fig9-26_data_ssp126_oceandynamics_map.nc\r\n - Data file: Fig9-26_data_ssp126_thermalexpansion_timeseries.nc\r\n - Data file: Fig9-26_data_ssp585_Antarctic_map.nc\r\n - Data file: Fig9-26_data_ssp585_Antarctic_timeseries.nc\r\n - Data file: Fig9-26_data_ssp585_Greenland_map.nc\r\n - Data file: Fig9-26_data_ssp585_Greenland_timeseries.nc\r\n - Data file: Fig9-26_data_ssp585_glacier_map.nc\r\n - Data file: Fig9-26_data_ssp585_glacier_timeseries.nc\r\n - Data file: Fig9-26_data_ssp585_landwater_map.nc\r\n - Data file: Fig9-26_data_ssp585_landwater_timeseries.nc\r\n - Data file: Fig9-26_data_ssp585_oceandynamics_map.nc\r\n - Data file: Fig9-26_data_ssp585_thermalexpansion_timeseries.nc\r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9).\r\n\r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nContribution maps and timeseries were plotted using standard matplotlib software - code is available via the link in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the output data for this figure, contained in a dedicated GitHub repository."
            },
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            "ob_id": 38033,
            "uuid": "829423a12a7342a48e58d57bc8c024d7",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig28/v20220721",
            "numberOfFiles": 9,
            "volume": 3229576,
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            "observation": {
                "ob_id": 37733,
                "uuid": "7f9c951b59ae44aeb6d745ed702c56dd",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.28 (v20220721)",
                "abstract": "Data for Figure 9.28 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.28 shows regional sea level change at 2100 for different scenarios (with respect to 1995–2014). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 6 subpanels, with data provided for panels a-f. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Median regional relative sea level change from 1995–2014 up to 2100 for: (a) SSP1-1.9; (b) SSP1-2.6; (c) SSP2-4.5; (d) SSP3-7.0; (e) SSP5-8.5; and (f) width of the likely range for SSP3-7.0. \r\n\r\nThe high uncertainty in projections around Alaska and the Aleutian Islands arises from the tectonic contribution to vertical land motion, which varies greatly over short distances in this region. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.28\r\n \r\n - Data file: Fig9-28a_data.nc\r\n - Data file: Fig9-28b_data.nc\r\n - Data file: Fig9-28c_data.nc\r\n - Data file: Fig9-28d_data.nc\r\n - Data file: Fig9-28e_data.nc\r\n - Data file: Fig9-28f_data.nc\r\n\r\nSSP119 is the Shared Socioeconomic Pathway which represents the lowest scenario of radiative forcing and development scenarios, consistent with RCP1.9.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP370 is the Shared Socioeconomic Pathway which represents the upper-middle range of radiative forcing and development scenarios, consistent with RCP6.0.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\r\n------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nRSL scenarios were plotted using standard matplotlib software - code is available via the link in the documentation. Input data for each SSP scenario (.nc files in data/pb_1e) also provided.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the code and output data for this figure, contained in a dedicated GitHub repository."
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            "uuid": "90eaefa051d84a2fbc39b4e5714a73bd",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/ch6_fig12/v20220815",
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            "observation": {
                "ob_id": 37887,
                "uuid": "8855e410adf547b4afd039a5b88487f4",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 6.12 (v20220815)",
                "abstract": "Data for Figure 6.12 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.12 shows contribution to effective radiative forcing (ERF) and global mean surface air temperature (GSAT) change from component emissions between 1750 to 2019 based on CMIP6 models. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Contribution to effective radiative forcing (ERF) (a) and global mean surface air temperature (GSAT) change (b) from component emissions between 1750 to 2019 based on CMIP6 models\r\n\r\nERFs for the direct effect of well-mixed greenhouse gases (WMGHGs) are from the analytical formulae in section 7.3.2, H2O (strat) is from Table 7.8. ERFs for other components are multi-model means from Thornhill et al. (2021b) and are based on ESM simulations in which emissions of one species at a time are increased from 1850 to 2014 levels. The derived emissions-based ERFs are rescaled to match the concentration-based ERFs in Figure 7.6.\r\n\r\nError bars are 5–95% and for the ERF account for uncertainty in radiative efficiencies and multi-model error in the means. ERFs due to aerosol–radiation (ERFari) and cloud effects are calculated from separate radiation calls for clear-sky and aerosol-free conditions (Ghan, 2013; Thornhill et al., 2021b). \r\n\r\n‘Cloud’ includes cloud adjustments (semi-direct effect) and ERF from indirect aerosol-cloud to –0.22 W m–2 for ERFari and –0.84 W m–2 interactions (ERFaci). The aerosol components (SO2, organic carbon and black carbon) are scaled to sum to –0.22 W m–2 for ERFari and –0.84 W m–2 for ‘cloud’ (Section 7.3.3). \r\n\r\nFor GSAT estimates, time series (1750–2019) for the ERFs have been estimated by scaling with concentrations for WMGHGs and with historical emissions for SLCFs. The time variation of ERFaci for aerosols is from Chapter 7. The global mean temperature response is calculated from the ERF time series using an impulse response function (Cross-Chapter Box 7.1) with a climate feedback parameter of –1.31 W m–2 °C–1. \r\n\r\nContributions to ERF and GSAT change from contrails and light-absorbing particles on snow and ice are not represented, but their estimates can be seen on Figure 7.6 and 7.7, respectively. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 6.12:\r\n \r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_ERF.csv\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_ERF_uncertainty.csv\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_dT.csv\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_dT_uncertainty.csv\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nERFari stands for Effective Radiative Forcing of aerosol-radiation interactions.\r\nERFaci stands for Effective Radiative Forcing of aerosol-cloud interactions. \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n- Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with this figure.\r\n- Link to the code for the figure, archived on Zenodo."
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                "uuid": "288d2cfa740f4e60a369b5778064bd5a",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 6.22 (v20220815)",
                "abstract": "Data for Figure 6.22 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.22 shows time evolution of the effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs). \r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with data provided for this panel.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Effects of net aerosols, methane, tropospheric ozone and hydrofluorocarbons (HFCs; with lifetimes <50years), and the sum of these, relative to the year 2019 and to the year 1750. \r\n\r\nThe GSAT changes are based on the assessed historic and future evolution of effective radiative forcing (ERF; Section 7.3.5). The temperature responses to the ERFs are calculated with an impulse response function with an equilibrium climate sensitivity of 3.0°C for a doubling of atmospheric CO2 (feedback parameter of –1.31 W m–2 °C–1, see Cross-Chapter Box 7.1). The vertical bars to the right in each panel show the uncertainties (5–95% ranges) for the GSAT change between 2019 and 2100. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3).\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 6.22:\r\n \r\n - Data file: fig_timeseries_dT_p95-p50_HFCs_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_p95-p50_Sum_SLCF_Aerosols_Methane_Ozone_HFCs_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_p95-p50_aerosol-total-with_bc-snow_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_p95-p50_ch4_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_p95-p50_o3_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_recommendation_HFCs_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_recommendation_Sum_SLCF_Aerosols_Methane_Ozone_HFCs_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_recommendation_aerosol-total-with_bc-snow_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_recommendation_ch4_2019-2100_refyear2019.csv\r\n - Data file: fig_timeseries_dT_recommendation_o3_2019-2100_refyear2019.csv\r\n\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\r\n\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n- Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with this figure.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38038,
            "uuid": "5771863dd11f4d0581b1f791a75456a3",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/ch6_fig24/v20220815",
            "numberOfFiles": 9,
            "volume": 13863,
            "fileFormat": "Data are csv formatted",
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            "observation": {
                "ob_id": 37888,
                "uuid": "ca4127fb1be14ea68fefd5643fe3677f",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 6.24 (v20220815)",
                "abstract": "Data for Figure 6.24 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.24 shows effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Effects of net aerosols, methane, tropospheric ozone and hydrofluorocarbons (HFCs; with lifetimes <50years) compared with those of total anthropogenic forcing for 2040 and 2100 relative to the year 2019. \r\n\r\nThe GSAT changes are based on the assessed historic and future evolution of effective radiative forcing (ERF; Section 7.3.5). The temperature responses to the ERFs are calculated with an impulse response function with an equilibrium climate sensitivity of 3.0°C for a doubling of atmospheric CO2 (feedback parameter of –1.31 W m–2 °C–1; Cross-Chapter Box 7.1). Uncertainties are 5–95% ranges. The scenario total (grey bar) includes all anthropogenic forcings (long- and short-lived climate forcers, and land-use changes) whereas the white diamonds and bars show the net effects of SLCFs and HFCs and their uncertainties. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 6.24:\r\n \r\n - Data file: fig_dT_2040_2100_stacked_bar_5th-50th__2020-2040_refyear2020.csv\r\n - Data file: fig_dT_2040_2100_stacked_bar_5th-50th__2020-2100_refyear2020.csv\r\n - Data file: fig_dT_2040_2100_stacked_bar_95th-50th__2020-2040_refyear2020.csv\r\n - Data file: fig_dT_2040_2100_stacked_bar_95th-50th__2020-2100_refyear2020.csv\r\n - Data file: fig_dT_2040_2100_stacked_bar_mean__2019-2040_refyear2019.csv\r\n - Data file: fig_dT_2040_2100_stacked_bar_mean__2019-2100_refyear2019.csv\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n- Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with this figure.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38039,
            "uuid": "ae828262da704ae794e525fbf4c1f82c",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/inputdata_ch6_fig12/v20220824",
            "numberOfFiles": 58,
            "volume": 168322757,
            "fileFormat": "CSV, XLSX, txt, net-CDF",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 38002,
                "uuid": "c6b366dabf9b4536b5500e5f1f7a7235",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 6.12 (v20220824)",
                "abstract": "Input Data for Figure 6.12 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.12 shows contribution to effective radiative forcing (ERF) and global mean surface air temperature (GSAT) change from component emissions between 1750 to 2019 based on CMIP6 models. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Contribution to effective radiative forcing (ERF) (a) and global mean surface air temperature (GSAT) change (b) from component emissions between 1750 to 2019 based on CMIP6 models\r\n\r\nERFs for the direct effect of well-mixed greenhouse gases (WMGHGs) are from the analytical formulae in section 7.3.2, H2O (strat) is from Table 7.8. ERFs for other components are multi-model means from Thornhill et al. (2021b) and are based on ESM simulations in which emissions of one species at a time are increased from 1850 to 2014 levels. The derived emissions-based ERFs are rescaled to match the concentration-based ERFs in Figure 7.6.\r\n\r\nError bars are 5–95% and for the ERF account for uncertainty in radiative efficiencies and multi-model error in the means. ERFs due to aerosol–radiation (ERFari) and cloud effects are calculated from separate radiation calls for clear-sky and aerosol-free conditions (Ghan, 2013; Thornhill et al., 2021b). \r\n\r\n‘Cloud’ includes cloud adjustments (semi-direct effect) and ERF from indirect aerosol-cloud to –0.22 W m–2 for ERFari and –0.84 W m–2 interactions (ERFaci). The aerosol components (SO2, organic carbon and black carbon) are scaled to sum to –0.22 W m–2 for ERFari and –0.84 W m–2 for ‘cloud’ (Section 7.3.3). \r\n\r\nFor GSAT estimates, time series (1750–2019) for the ERFs have been estimated by scaling with concentrations for WMGHGs and with historical emissions for SLCFs. The time variation of ERFaci for aerosols is from Chapter 7. The global mean temperature response is calculated from the ERF time series using an impulse response function (Cross-Chapter Box 7.1) with a climate feedback parameter of –1.31 W m–2 °C–1. \r\n\r\nContributions to ERF and GSAT change from contrails and light-absorbing particles on snow and ice are not represented, but their estimates can be seen on Figure 7.6 and 7.7, respectively. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3)\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nERFari stands for Effective Radiative Forcing of aerosol-radiation interactions.\r\nERFaci stands for Effective Radiative Forcing of aerosol-cloud interactions. \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 6.12:\r\n \r\n - Data file: hodnebrog_tab3.csv: Radiative forcing for HFCs from Hodnebrog et al (2020)\r\n - Data file: recommended_irf_from_2xCO2_2021_02_25_222758.csv: Impulse response function (IRF) from AR6\r\n - Data file: table2_thornhill2020.csv: ERF from Thornhill et al (2021)\r\n - Data file: attribution_input.csv\r\n - Data file: attribution_input_sd.csv\r\n\r\nThe folder: 'LLGHG_history_AR6_v9_updated' - contains csv files for each sheet in excel file 'LLGHG_history_AR6_v9_updated.xlsx' which gives historical concentrations from AR6.\r\n\r\nThe folder CEDS_v2021-02-05_emissions (historical emissions of SLCFs from CEDS) contains the following file formats:\r\n\r\n${component}$_${region}$_CEDS_emissions_by${category}$_${type}$_2021_02_05.csv, with:\r\n\r\n- ${component}: BC, CH4, CO2, CO, N2O, NH3, NMVOC, NOx, OC, SO2\r\n- ${region}: blank, or 'global'\r\n- ${category}: sector, country, sector and country\r\n- ${type}: blank, or 'fuel'\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n - Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with this figure.\r\n - Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38040,
            "uuid": "93d8f943955c434585e1c286ac5c5ca1",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/inputdata_ch6_fig22/v20220824",
            "numberOfFiles": 82,
            "volume": 5507225,
            "fileFormat": "CSV, txt",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 38003,
                "uuid": "0ca27ce794324ec086d6a6c60d5567ac",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 6.22 and Figure 6.24 (v20220824)",
                "abstract": "Input data for figures 6.22 and 6.24 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.22 shows time evolution of the effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs). \r\n\r\nFigure 6.24 shows effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs).\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nFigure 6.22 has 1 panel, with input data provided for this panel.\r\n\r\nFigure 6.24 has 2 subpanels, with input data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Effects of net aerosols, methane, tropospheric ozone and hydrofluorocarbons (HFCs; with lifetimes <50years), and the sum of these, relative to the year 2019 and to the year 1750. \r\n\r\n- The GSAT changes are based on the assessed historic and future evolution of effective radiative forcing (ERF; Section 7.3.5). The temperature responses to the ERFs are calculated with an impulse response function with an equilibrium climate sensitivity of 3.0°C for a doubling of atmospheric CO2 (feedback parameter of –1.31 W m–2 °C–1, see Cross-Chapter Box 7.1). The vertical bars to the right in each panel show the uncertainties (5–95% ranges) for the GSAT change between 2019 and 2100. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figures\r\n ---------------------------------------------------\r\n Data provided in relation to figures 6.22 and 6.24:\r\n \r\n - Data file: AR6_ERF_1750-2019.csv: ERF derived from FAiR\r\n - Data file: AR6_ERF_minorGHGs_1750-2019.csv: ERF derived from FAiR\r\n - Data file: recommended_irf_from_2xCO2_2021_02_25_222758.csv: Impulse response function (IRF) from AR6\r\n\r\nThe folder SSPs (SSP scenario ERF from FAIR) contains the following file formats:\r\n\r\nERF_${scenario}$_${component}$_1750-2500.csv, with:\r\n\r\n- $(scenario): the name of the scenario : ssp119, ssp126, ssp245, ssp334, ssp370, ssp370-low-nTCF-aerchemmip, ssp370-low-nTCF-gidden, ssp434, ssp460, ssp534-over, ssp585\r\n- $(component): blank, or 'minor GHGs'\r\n\r\nThe folder slcf_warming_ranges (uncertainties in dGSAT from FAIR) contains the following file formats:\r\n\r\nslcf_warming_ranges_${scenario)_$(uncertainty).csv, with:\r\n\r\n- ${scenario}: the name of the scenario : ssp119, ssp126, ssp245, ssp334, ssp370, ssp370-lowNTCF-aerchemmip, ssp370-lowNTCF-gidden, ssp434, ssp460, ssp534-over, ssp585\r\n- ${uncertainty}: percentiles of warming: p05, p16, p50, p84, p95\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figures from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to Figure 6.22 on the IPCC AR6 website\r\n - Link to Figure 6.24 on the IPCC AR6 website\r\n - Link to the report component containing the figures (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n - Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with these figures.\r\n - Link to the code for the figures, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38042,
            "uuid": "f605f04ee04e48798ab303539681421f",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_12/inputdata_ch12_fig05/v20220804",
            "numberOfFiles": 73,
            "volume": 15964042,
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            "observation": {
                "ob_id": 37849,
                "uuid": "91c218d3a80f4c43ac665d0bdf0ed5e7",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 12.5 (v20220804)",
                "abstract": "Input Data for Figure 12.5 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 12.5 shows projected changes in selected climatic impact-driver indices for Africa.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with general data provided in the central directory and specific data in 3 folders (Q100_CMIP5, Q100_CMIP6, Q1000_CORDEX-core).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - spatial field over Africa of mean change in 1-in-100 year river discharge per unit catchment area (Q100, m3 s-1 km-2) from CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5\r\n - Shoreline position change over Africa (pointwise) along sandy coasts by the year 2100 relative to 2010 (meters; negative values indicate shoreline retreat) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n - regional averages in Africa of Q100 (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n    - CMIP6 historical, ssp126 and ssp585\r\n    - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n    - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n    - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n - regional averages in Africa of CMIP5 based projections (mean change estimates and bars the 5th-95th percentile range of associated uncertainty) of shoreline position change along sandy coasts for 2050 and 2100 relative to 2010 for RCP8.5 and RCP4.5 from Vousdoukas et al. (2020)\r\n\r\nSAH, ARP, WAF, CAF, NEAF, SEAF, WSAF, ESAF, MDG, NEU, WCE and MED are domains used in the model. \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.5:\r\n\r\n Panel a:\r\n - Q100_map_panel_a_AFR_less_MED_divdra.nc: Field (colors plotted on the map) of changes of 1-in-100yr river discharge per unit catchment area between 2041-2060 (mid-term) and 1995-2015 (recent past) for CORDEX RCP8.5;  the data is from the AFR CORDEX domain, without the MED AR6 region\r\n - Q100_map_panel_a_MED_for_AFR_from_EUR_divdra.nc: same as previous file but for the MED AR6 region, taken from the EUR CORDEX domain\r\n\r\n Panel b:\r\n - CoastalRecession_AFRICA_RCP85_2100.json: pointwise values (color points on the map) for Africa of shoreline position mean changes between 2100 (long-term) and 2010 (recent past) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n\r\n Panel c:\r\n - txt files containing the median and 5th/95th percentiles of each ensemble of the 1-in-100yr river discharge per unit catchment area (Q100) regional averages of time slices: Q100_${ensemble}/Q100_${scenario}_${period}.nc_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${scenario}: the name of the scenario : ssp126, ssp585, rcp26, rcp85\r\n     - ${period}: the explicit period used to compute the temporal average: 1995-2014 (recent past), 2041-2060 (mid-term) and 2080-2099 (long term)\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n - txt files containing the Q100 regional averages of global warming levels: Q100_${ensemble}/${GWL}_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${GWL}: the Global Warming Level: 1.5, 2 and 4\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n\r\n Panel d:\r\n - globalErosionProjections_by_AR6_region_${scenario}_${horizon).json: regional averages of shoreline position changes for Africa, for the RCP4.5 and RCP8.5 scenarios (${scenario} = RCP45 and ${scenario} = RCP85 respectively) and the 2050 (mid-term, in blue) and 2100 (long-term, in red) future horizons (${horizon}=2050 and ${horizon}=2100 respectively) against the recent past period (2010); the file contains the median (dots in the subpanels) and the 5th (q5) and 95th (q95) uncertainty estimates (used to plot the vertical bars)\r\n\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\nCORDEX is Coordinated Regional Downscaling Experiment from the WCRP. \r\nWCRP is the World Climate Research Programme. SSP stands for Shared Socioeconomic Pathway. \r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\nRCP stands for Representative Concentration Pathway. \r\nRCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n For panel a, the plotting script ch12_fig12.5_plotting_code_Q100_AFR.py (see data tables and code on Github) draws the rivers and uses a subroutine (dranetwrite) to identify the rivers to plot them individually with lines, using the data from the Q100_map_panel_a_AFR_less_MED_divdra.nc and Q100_map_panel_a_MED_for_AFR_from_EUR_divdra.nc netcdf files; plotting the Q100 netcdf file will produce dots (and not rivers).\r\n\r\n For panel c, the recent past values are plotted as absolute values (left column on each regional subpanel) and the future changes are plotted as differences against the recent past values (differences are computed when plotting the values).\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n- Link to the Chapter 12 GitHub repository"
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                "ob_id": 37861,
                "uuid": "d46d733725d64f45afc1e70054f2f51d",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 12.6 (v20220804)",
                "abstract": "Input Data for Figure 12.6 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 12.6 shows projected changes in selected climatic impact-driver indices for Asia.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with general data provided in the central directory and specific data in 3 folders (Q100_CMIP5, Q100_CMIP6, Q1000_CORDEX-core).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - spatial field over Asia of mean change in 1-in-100 year river discharge per unit catchment area (Q100, m3 s-1 km-2) from CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5\r\n - Shoreline position change over Asia (pointwise) along sandy coasts by the year 2100 relative to 2010 (meters; negative values indicate shoreline retreat) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n - regional averages in Asia of Q100 (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n    - CMIP6 historical, ssp126 and ssp585\r\n    - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n    - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n    - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n - regional averages in Asia of CMIP5 based projections (mean change estimates and bars the 5th-95th percentile range of associated uncertainty) of shoreline position change along sandy coasts for 2050 and 2100 relative to 2010 for RCP8.5 and RCP4.5 from Vousdoukas et al. (2020)\r\n\r\nTIB, ECA, EAS, SEA, ARP and SAS are domains used in the model.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.6:\r\n \r\nPanel a:\r\n - Q100_map_panel_a_EAS_for_ASIA_divdra.nc: Field (colors plotted on the map) of changes of 1-in-100yr river discharge per unit catchment area between 2041-2060 (mid-term) and 1995-2015 (recent past) for CORDEX RCP8.5;  the file contains the data for the regions from the EAS CORDEX domain\r\n - Q100_map_panel_a_SEA_for_ASIA_divdra.nc: same as previous file for the regions from the SEA CORDEX domain\r\n - Q100_map_panel_a_WAS_for_ASIA_divdra.nc: same as previous file for the regions from the WAS CORDEX domain\r\n \r\nPanel b:\r\n - CoastalRecession_ASIA_RCP85_2100.json: pointwise values (color points on the map) for Asia of shoreline position mean changes between 2100 (long-term) and 2010 (recent past) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n\r\nPanel c:\r\n - txt files containing the median and 5th/95th percentiles of each ensemble of the 1-in-100yr river discharge per unit catchment area (Q100) regional averages of time slices: Q100_${ensemble}/Q100_${scenario}_${period}.nc_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${scenario}: the name of the scenario : ssp126, ssp585, rcp26, rcp85\r\n     - ${period}: the explicit period used to compute the temporal average: 1995-2014 (recent past), 2041-2060 (mid-term) and 2080-2099 (long term)\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n - txt files containing the Q100 regional averages of global warming levels: Q100_${ensemble}/${GWL}_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${GWL}: the Global Warming Level: 1.5, 2 and 4\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n \r\nPanel d:\r\n - globalErosionProjections_by_AR6_region_${scenario}_${horizon).json: regional averages of shoreline position changes for Africa, for the RCP4.5 and RCP8.5 scenarios (${scenario} = RCP45 and ${scenario} = RCP85 respectively) and the 2050 (mid-term, in blue) and 2100 (long-term, in red) future horizons (${horizon}=2050 and ${horizon}=2100 respectively) against the recent past period (2010); the file contains the median (dots in the subpanels) and the 5th (q5) and 95th (q95) uncertainty estimates (used to plot the vertical bars)\r\n\r\n\r\nCORDEX is The Coordinated Regional Downscaling Experiment from the WCRP. \r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\nSSP stands for Shared Socioeconomic Pathway. \r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\nRCP stands for Representative Concentration Pathway. \r\nRCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n For panel a, the plotting script (see data tables and code on Github) draws the rivers and uses a subroutine to identify the rivers to plot them individually with lines; plotting the Q100 netcdf file will produce dots (and not rivers).\r\n\r\n\r\nFor panel c, the recent past values are plotted as absolute values (left column on each regional subpanel) and the future changes are plotted as differences against the recent past values (differences are computed when plotting the values).\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo.\r\n- Link to the Chapter 12 GitHub repository"
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                "ob_id": 37852,
                "uuid": "537b22f0230448fdb9a4ec806ed54d84",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 12.7 (v20220804)",
                "abstract": "Input Data for Figure 12.7 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 12.7 shows projected changes in selected climatic impact-driver indices for Australasia.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with general data provided in the central directory and specific data in 3 folders (Q100_CMIP5, Q100_CMIP6, Q1000_CORDEX-core).\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - spatial field over Australasia of mean change in 1-in-100 year river discharge per unit catchment area (Q100, m3 s-1 km-2) from CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5\r\n - Shoreline position change over Australasia  (pointwise) along sandy coasts by the year 2100 relative to 2010 (meters; negative values indicate shoreline retreat) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n - regional averages in Australasia  of Q100 (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n    - CMIP6 historical, ssp126 and ssp585\r\n    - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n    - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n    - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n - regional averages in Australasia  of CMIP5 based projections (mean change estimates and bars the 5th-95th percentile range of associated uncertainty) of shoreline position change along sandy coasts for 2050 and 2100 relative to 2010 for RCP8.5 and RCP4.5 from Vousdoukas et al. (2020)\r\n\r\nNAU, CAU, EAU, SAU and NZ are domains used in the model.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.7:\r\n \r\nPanel a:\r\n - Q100_map_panel_a_AUS_divdra.nc: Field (colors plotted on the map) of changes of 1-in-100yr river discharge per unit catchment area between 2041-2060 (mid-term) and 1995-2015 (recent past) for CORDEX RCP8.5;  the file contains the data for the regions from the AUS CORDEX domain\r\n\r\nPanel b:\r\n - CoastalRecession_Australasia_RCP85_2100.json: pointwise values (color points on the map) for Australasia of shoreline position mean changes between 2100 (long-term) and 2010 (recent past) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n\r\nPanel c:\r\n - txt files containing the median and 5th/95th percentiles of each ensemble of the 1-in-100yr river discharge per unit catchment area (Q100) regional averages of time slices: Q100_${ensemble}/Q100_${scenario}_${period}.nc_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${scenario}: the name of the scenario : ssp126, ssp585, rcp26, rcp85\r\n     - ${period}: the explicit period used to compute the temporal average: 1995-2014 (recent past), 2041-2060 (mid-term) and 2080-2099 (long term)\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n - txt files containing the Q100 regional averages of global warming levels: Q100_${ensemble}/${GWL}_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${GWL}: the Global Warming Level: 1.5, 2 and 4\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n\r\nPanel d:\r\n - globalErosionProjections_by_AR6_region_${scenario}_${horizon).json: regional averages of shoreline position changes for Africa, for the RCP4.5 and RCP8.5 scenarios (${scenario} = RCP45 and ${scenario} = RCP85 respectively) and the 2050 (mid-term, in blue) and 2100 (long-term, in red) future horizons (${horizon}=2050 and ${horizon}=2100 respectively) against the recent past period (2010); the file contains the median (dots in the subpanels) and the 5th (q5) and 95th (q95) uncertainty estimates (used to plot the vertical bars)\r\n\r\n\r\nCORDEX is The Coordinated Regional Downscaling Experiment from the WCRP. \r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\nSSP stands for Shared Socioeconomic Pathway. \r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\nRCP stands for Representative Concentration Pathway. \r\nRCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n For panel a, the plotting script (see data tables and code on Github) draws the rivers and uses a subroutine to identify the rivers to plot them individually with lines; plotting the Q100 netcdf file will produce dots (and not rivers).\r\n\r\nFor panel c, the recent past values are plotted as absolute values (left column on each regional subpanel) and the future changes are plotted as differences against the recent past values (differences are computed when plotting the values).\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo.\r\n- Link to the Chapter 12 GitHub repository"
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                "ob_id": 37903,
                "uuid": "0b5c980aa58447508eccdda79554b2b7",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 12.8 (v20220804)",
                "abstract": "Input Data for Figure 12.8 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 12.8 shows projected changes in selected climatic impact-driver indices for Central and South America.\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with general data provided in the central directory and specific data in 3 folders (Q100_CMIP5, Q100_CMIP6, Q1000_CORDEX-core).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - spatial field over South-America and Central-America of mean change in 1-in-100 year river discharge per unit catchment area (Q100, m3 s-1 km-2) from CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5\r\n\r\n- Shoreline position change over South-America (pointwise) along sandy coasts by the year 2100 relative to 2010 (meters; negative values indicate shoreline retreat) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n\r\n- regional averages in South-America and Central-America of Q100 (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n- regional averages in South-America and Central-America of CMIP5 based projections (mean change estimates and bars the 5th-95th percentile range of associated uncertainty) of shoreline position change along sandy coasts for 2050 and 2100 relative to 2010 for RCP8.5 and RCP4.5 from Vousdoukas et al. (2020)\r\n\r\nNWS, NSA, SAM, NES, SWS, SES, SSA, CAR and SCA are domains used in the model. \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.8:\r\n\r\nPanel a:\r\n\r\n- Q100_map_panel_a_SAM_divdra.nc: Field (colors plotted on the map) of changes of 1-in-100yr river discharge per unit catchment area between 2041-2060 (mid-term) and 1995-2015 (recent past) for CORDEX RCP8.5;  the file contains the data for the regions from the SAM CORDEX domain\r\n\r\n- Q100_map_panel_a_CAM_for_SAM_divdra.nc: same as previous file for the regions from the CAM CORDEX domain\r\n\r\nPanel b:\r\n\r\n- CoastalRecession_SOUTH-AMERICA_RCP85_2100.json: pointwise values (color points on the map) for South-America and Central-America of shoreline position mean changes between 2100 (long-term) and 2010 (recent past) from the CMIP5 based data set presented by Vousdoukas et al. (2020)\r\n\r\nPanel c:\r\n\r\n- txt files containing the median and 5th/95th percentiles of each ensemble of the 1-in-100yr river discharge per unit catchment area (Q100) regional averages of time slices: Q100_${ensemble}/Q100_${scenario}_${period}.nc_${CORDEX_domain}.txt, with:\r\n    - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n    - ${scenario}: the name of the scenario : ssp126, ssp585, rcp26, rcp85\r\n    - ${period}: the explicit period used to compute the temporal average: 1995-2014 (recent past), 2041-2060 (mid-term) and 2081-2099 (long term)\r\n    - ${CORDEX_domain}: the CORDEX domain\r\n\r\n- txt files containing the Q100 regional averages of global warming levels: Q100_${ensemble}/${GWL}_${CORDEX_domain}.txt, with:\r\n    - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n    - ${GWL}: the Global Warming Level: 1.5, 2 and 4\r\n    - ${CORDEX_domain}: the CORDEX domain\r\n\r\nPanel d:\r\n\r\n- globalErosionProjections_by_AR6_region_${scenario}_${horizon).json: regional averages of shoreline position changes for Africa, for the RCP4.5 and RCP8.5 scenarios (${scenario} = RCP45 and ${scenario} = RCP85 respectively) and the 2050 (mid-term, in blue) and 2100 (long-term, in red) future horizons (${horizon}=2050 and ${horizon}=2100 respectively) against the recent past period (2010); the file contains the median (dots in the subpanels) and the 5th (q5) and 95th (q95) uncertainty estimates (used to plot the vertical bars)\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\nCORDEX is Coordinated Regional Downscaling Experiment from the WCRP. \r\nWCRP is the World Climate Research Programme. SSP stands for Shared Socioeconomic Pathway. \r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6. \r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\nRCP stands for Representative Concentration Pathway. \r\nRCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nFor panel a, the plotting script (see data tables and code on Github) draws the rivers and uses a subroutine to identify the rivers to plot them individually with lines; plotting the Q100 netcdf file will produce dots (and not rivers).\r\n\r\nFor panel c, the recent past values are plotted as absolute values (left column on each regional subpanel) and the future changes are plotted as differences against the recent past values (differences are computed when plotting the values).\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the Chapter 12GitHub repository"
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                "ob_id": 37855,
                "uuid": "7c2c37c3c5d14aac87377c7673e35a0b",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 12.9 (v20220804)",
                "abstract": "Input Data for Figure 12.9 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 12.9 shows projected changes in selected climatic impact-driver indices for Europe.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with general data provided in the central directory and specific data in 3 folders (Q100_CMIP5, Q100_CMIP6, Q1000_CORDEX-core).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - spatial field over Europe of mean change in 1-in-100 year river discharge per unit catchment area (Q100, m3 s-1 km-2) from CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5\r\n - spatial field of changes of number of days per year with snow water equivalent over 100mm (SWE100) from EURO-CORDEX models for 2041-2060 relative to 1995-2014 for RCP8.5; the grid points with less than 14 days per year with SWE100 during the reference (recent past) period are put to zero.\r\n - the associated mask showing the areas with more than 80% of model agreement in the sign of change\r\n - regional averages in Europe of Q100 (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n    - CMIP6 historical, ssp126 and ssp585\r\n    - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n    - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n    - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n - regional averages of number of days per year with snow water equivalent over 100mm (SWE100) in Europe for:\r\n    - CMIP6 historical, ssp126 and ssp585\r\n    - CMIP5 and EURO-CORDEX historical, RCP2.6 and RCP8.5\r\n    - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n    - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n The grid points with less than 14 days per year with SWE100 during the reference (recent past) period are put to zero.\r\n\r\nNEU, WCE and MED are domains used in the model. \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.9:\r\n \r\nPanel a:\r\n - Q100_map_panel_a_EUR_divdra.nc: Field (colors plotted on the map) of changes of 1-in-100yr river discharge per unit catchment area between 2041-2060 (mid-term) and 1995-2014 (recent past) for CORDEX RCP8.5;  the file contains the data for the regions from the EUR CORDEX domain\r\n\r\n Panel b:\r\n - SWE_panel_b_RCP85_mce_minus_baseline.nc: spatial field (colors) of changes of number of days per year with snow water equivalent over 100mm (SWE100) from EURO-CORDEX models for 2041-2060 relative to 1995-2014 for RCP8; the grid points with less than 14 days per year with SWE100 during the reference (recent past) period are put to zero\r\n - mask_80perc-agreement_SWE_panel_b_RCP85_mce_minus_baseline.nc: spatial mask (for hatching) showing where at least 80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: 1 where true, 0 where false\r\n \r\nPanel c:\r\n - txt files containing the median and 5th/95th percentiles of each ensemble of the 1-in-100yr river discharge per unit catchment area (Q100) regional averages of time slices: Q100_${ensemble}/Q100_${scenario}_${period}.nc_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${scenario}: the name of the scenario : ssp126, ssp585, rcp26, rcp85\r\n     - ${period}: the explicit period used to compute the temporal average: 1995-2014 (recent past), 2041-2060 (mid-term) and 2080-2099 (long term)\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n - txt files containing the Q100 regional averages of global warming levels: Q100_${ensemble}/${GWL}_${CORDEX_domain}.txt, with:\r\n     - ${ensemble}: CMIP5, CMIP6 or CORDEX-core\r\n     - ${GWL}: the Global Warming Level: 1.5, 2 or 4\r\n     - ${CORDEX_domain}: the CORDEX domain\r\n \r\nPanel d:\r\n - CMIP5_EUR-11_snw_mask14_AR6_regional_averages.json: regional averages for the CMIP5 multimodel ensemble of number of days per year with snow water equivalent over 100mm (SWE100) in Europe for recent past (1995-2014), mid-term (2041-2060) long-term (2081-2099) for RCP2.6 and RCP8.5, and for three global warming levels: 1.5, 2 and 4; the file contains the median (dots in the subpanels) and the 5th (q5) and 95th (q95) uncertainty estimates (used to plot the vertical bars)\r\n - EURO-CORDEX_SWE_mask14_AR6_regional_averages.json: same as previous file for the EURO-CORDEX multimodel ensemble\r\n - CMIP6_EUR-11_snw_mask14_AR6_regional_averages.json: same as previous file for CMIP6 (ssp126 instead of RCP2.6 and ssp585 instead of RCP8.5)\r\n\r\n\r\nCORDEX is The Coordinated Regional Downscaling Experiment from the WCRP. \r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project. \r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\n\r\nSSP stands for Shared Socioeconomic Pathway. \r\n\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6. \r\n\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n\r\nRCP stands for Representative Concentration Pathway. \r\n\r\nRCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n\r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n For panel a, the plotting script (see data tables and code on Github) draws the rivers and uses a subroutine to identify the rivers to plot them individually with lines; plotting the Q100 netcdf file will produce dots (and not rivers).\r\n\r\n\r\nFor panel c, the recent past values are plotted as absolute values (left column on each regional subpanel) and the future changes are plotted as differences against the recent past values (differences are computed when plotting the values).\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo."
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            "observation": {
                "ob_id": 37875,
                "uuid": "156e4a10ddfb418aa24aadf244fbadf6",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.1 (v20220808)",
                "abstract": "Data for Figure 12.SM.1 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.1 shows regional projections for the number of days per year with maximum temperature exceeding 35°C for different scenarios, time horizons and global warming levels. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThis figure has 43 subpanels (AR6 regions).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- regional averages over 43 AR6 regions of the number of days per year with maximum daily temperature exceeding 35°C (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.1:\r\n \r\nThe regional averages for all the subpanels (AR6 regions) are stored in three json files:\r\n\r\n-  CMIP5_tx35isimip_AR6_regional_averages.json: data for the CMIP5 multi-model ensemble\r\n\r\n-  CMIP6_tx35isimip_AR6_regional_averages.json: data for the CMIP6 multi-model ensemble\r\n\r\n-  CORDEX_tx35isimip_AR6_regional_averages.json: data for the CORDEX multi-model ensemble\r\n\r\nThe content of the files is organized as follows:\r\n\r\n - level 1 key:\r\n      - GWL: string: 1.5, 2, 3, 4\r\n      or\r\n      - name of the time slice: baseline or ${scenario}_${horizon}, with:\r\n           - ${scenario}: the scenario: ssp126 or ssp585 for CMIP6, rcp26 or rcp85 for CMIP5 and CORDEX\r\n           - ${horizon}: mid (mid-term) or far (long-term)\r\n - level 2 keys: name of the AR6 region\r\n - value: list with:\r\n      - first element: the multi-model ensemble 10th percentile (lower bounds of the vertical lines)\r\n      - second element: the multi-model ensemble median (the dots)\r\n      - third element: the multi-model ensemble 90th percentile (upper bounds of the vertical lines)\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n- Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n- Link to the code for the figure, archived on Zenodo."
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            "observation": {
                "ob_id": 37873,
                "uuid": "660a0224eee04d0880b78f538510f416",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.2 (v20220808)",
                "abstract": "Data for Figure 12.SM.2 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.2 shows regional projections for the number of days per year with NOAA Heat Index exceeding 41°C for different scenarios, time horizons and global warming levels. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThis figure has 43 subpanels (AR6 regions).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- regional averages over 43 AR6 regions of the number of days per year with NOAA Heat Index exceeding 41°C (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.2\r\n \r\nThe regional averages for all the subpanels (AR6 regions) are stored in three json files:\r\n\r\n-  CMIP5_HI41_AR6_regional_averages.json: data for the CMIP5 multi-model ensemble\r\n\r\n-  CMIP6_HI41_AR6_regional_averages.json: data for the CMIP6 multi-model ensemble\r\n\r\n-  CORDEX_HI41_AR6_regional_averages.json: data for the CORDEX multi-model ensemble\r\n\r\nThe content of the files is organized as follows:\r\n\r\n - level 1 key:\r\n      - GWL: string: 1.5, 2, 3, 4\r\n      or\r\n      - name of the time slice: baseline or ${scenario}_${horizon}, with:\r\n           - ${scenario}: the scenario: ssp126 or ssp585 for CMIP6, rcp26 or rcp85 for CMIP5 and CORDEX\r\n           - ${horizon}: mid (mid-term) or far (long-term)\r\n - level 2 keys: name of the AR6 region\r\n - value: list with:\r\n      - first element: the multi-model ensemble 10th percentile (lower bounds of the vertical lines)\r\n      - second element: the multi-model ensemble median (the dots)\r\n      - third element: the multi-model ensemble 90th percentile (upper bounds of the vertical lines)\r\n\r\n NOAA is the National Oceanic and Atmospheric Administration.\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n - Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38050,
            "uuid": "3ce707fea7ac4f59b89ccbca9c1c0d3d",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_sm_03/v20220808",
            "numberOfFiles": 6,
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            "fileFormat": "json, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37872,
                "uuid": "e8975cc3195b487d9ec482cb8ef5f07d",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.3 (v20220808)",
                "abstract": "Data for Figure 12.SM.3 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.3 shows regional projections for the number of negative precipitation anomaly events per decade using the 6-month Standardised Precipitation Index for different scenarios, time horizons and global warming levels.. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThis figure has 43 subpanels (AR6 regions). \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- regional averages over 43 AR6 regions of the number of negative precipitation anomaly events per decade (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.3\r\n \r\nThe regional averages for all the subpanels (AR6 regions) are stored in three json files:\r\n\r\n-  CMIP5_DF6_AR6_regional_averages.json: data for the CMIP5 multi-model ensemble\r\n\r\n-  CMIP6_DF6_AR6_regional_averages.json: data for the CMIP6 multi-model ensemble\r\n\r\n-  CORDEX_DF6_AR6_regional_averages.json: data for the CORDEX multi-model ensemble\r\n\r\nThe content of the files is organized as follows:\r\n\r\n - level 1 key:\r\n      - GWL: string: 1.5, 2, 3, 4\r\n      or\r\n      - name of the time slice: baseline or ${scenario}_${horizon}, with:\r\n           - ${scenario}: the scenario: ssp126 or ssp585 for CMIP6, rcp26 or rcp85 for CMIP5 and CORDEX\r\n           - ${horizon}: mid (mid-term) or far (long-term)\r\n - level 2 keys: name of the AR6 region\r\n - value: list with:\r\n      - first element:  the multi-model ensemble 10th percentile (lower bounds of the vertical lines)\r\n      - second element: the multi-model ensemble median (the dots)\r\n      - third element: the multi-model ensemble 90th percentile (upper bounds of the vertical lines)\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n- Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38051,
            "uuid": "b883ab12b928494aa9525b172c37c5c0",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_sm_04/v20220808",
            "numberOfFiles": 6,
            "volume": 127417,
            "fileFormat": "CSV, json, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37871,
                "uuid": "8c58b12e8fd541428b1b25b0d572ce94",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.4 (v20220808)",
                "abstract": "Data for Figure 12.SM.4 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.4 shows regional projections for changes in soil moisture for different scenarios, time horizons and global warming levels. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n This figure has 41 subpanels (AR6 regions). \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\nThis figure has 41 subpanels (AR6 regions). \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.4\r\n \r\nThe regional averages of the changes in soil moisture in percentage of the recent past value for all the subpanels (AR6 regions) are stored in three json files:\r\n\r\n-  CMIP5_SM_diff_perc2020_AR6_regional_averages.json: data for the CMIP5 multi-model ensemble\r\n\r\n-  CMIP6_SM_diff_perc2020_AR6_regional_averages.json: data for the CMIP6 multi-model ensemble\r\n\r\n-  CORDEX_SM_diff_perc2020_AR6_regional_averages.json: data for the CORDEX multi-model ensemble\r\n\r\nThe content of the files is organized as follows:\r\n\r\n - level 1 key:\r\n      - GWL: string: 1.5, 2, 3, 4\r\n      or\r\n      - name of the time slice: baseline or ${scenario}_${horizon}, with:\r\n           - ${scenario}: the scenario: ssp126 or ssp585 for CMIP6, rcp26 or rcp85 for CMIP5 and CORDEX\r\n           - ${horizon}: mid (mid-term) or far (long-term)\r\n - level 2 keys: name of the AR6 region\r\n - value: list with:\r\n      - first element:  the multi-model ensemble 10th percentile (lower bounds of the vertical lines)\r\n      - second element: the multi-model ensemble median (the dots)\r\n      - third element: the multi-model ensemble 90th percentile (upper bounds of the vertical lines)\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n- Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38052,
            "uuid": "736b51d9aa674a5ba8be3aef714139f9",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_sm_05/v20220808",
            "numberOfFiles": 6,
            "volume": 131854,
            "fileFormat": "json",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37869,
                "uuid": "8418e1f0c9d64a758490a14daeb22574",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.5 (v20220808)",
                "abstract": "Data for Figure 12.SM.5 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.5 shows regional projections for changes in mean wind speed for different scenarios, time horizons and global warming levels. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThis figure has 43 subpanels (AR6 regions). \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- regional averages over 43 AR6 regions of the changes in mean wind speed in percentage of the recent past value (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.5\r\n \r\nThe regional averages of the changes in mean wind speed in percentage of the recent past value for all the subpanels (AR6 regions) are stored in three json files:\r\n\r\n-  CMIP5_sfcWind_diff-perc-baseline_AR6_regional_averages.json: data for the CMIP5 multi-model ensemble\r\n\r\n-  CMIP6_sfcWind_diff-perc-baseline_AR6_regional_averages.json: data for the CMIP6 multi-model ensemble\r\n\r\n-  CORDEX_sfcWind_diff-perc-baseline_AR6_regional_averages.json: data for the CORDEX multi-model ensemble\r\n\r\nThe content of the files is organized as follows:\r\n\r\n - level 1 key:\r\n      - GWL: string: 1.5, 2, 3, 4\r\n      or\r\n      - name of the time slice: baseline or ${scenario}_${horizon}, with:\r\n           - ${scenario}: the scenario: ssp126 or ssp585 for CMIP6, rcp26 or rcp85 for CMIP5 and CORDEX\r\n           - ${horizon}: mid (mid-term) or far (long-term)\r\n - level 2 keys: name of the AR6 region\r\n - value: list with:\r\n      - first element: the multi-model ensemble 10th percentile (lower bounds of the vertical lines)\r\n      - second element: the multi-model ensemble median (the dots)\r\n      - third element: the multi-model ensemble 90th percentile (upper bounds of the vertical lines)\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n- Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
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        {
            "ob_id": 38053,
            "uuid": "bb2df9ad208241639d25fef468a00a74",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_sm_06/v20220808",
            "numberOfFiles": 9,
            "volume": 70789,
            "fileFormat": "csv, json",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37868,
                "uuid": "38e7a3f35ced465283debd6cac1cae50",
                "short_code": "ob",
                "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.SM.6 (v20220808)",
                "abstract": "Data for Figure 12.SM.6 from Chapter 12 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 12.SM.6 shows regional projections of extreme sea level (1-in-100 year return period extreme total water level). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nRanasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment Supplementary Material. 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.)]. Available from https://www.ipcc.ch/\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThis figure has 39 subpanels (AR6 regions). \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- regional averages over 43 AR6 regions of the changes in mean wind speed in percentage of the recent past value (median value and the 10th-90th percentile range of model ensemble values across each model ensemble) over land areas for the WGI reference AR6 regions (defined in Chapter 1) for:\r\n\r\n   - CMIP6 historical, ssp126 and ssp585\r\n\r\n   - CMIP5 and CORDEX historical, RCP2.6 and RCP8.5\r\n\r\n   - for the ‘recent past’ (1995-2014), mid-term (2041-2060) and long-term (2081-2100) time periods\r\n\r\n   - and for three global warming levels (defined relative to the preindustrial period 1850-1900): 1.5°C, 2°C and 4°C\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 12.SM.6\r\n \r\nThe regional averages for all the subpanels (AR6 regions) are stored in four json files (Vousdoukas et al 2018 dataset) and one csv file (Kiresci et al 2020:\r\n\r\n- Vousdoukas_ETWL_by_AR6_region_${scenario}_${horizon}.json: contains the regional averages (median and 5th/95th percentiles uncertainty range) for the Vousdoukas et al 2018 dataset for the horizon ${horizon} (2050 or 2100) and the scenario ${scenario} (RCP45 or RCP85)\r\n\r\n- Vousdoukas_ETWL_by_AR6_region_modern.json contains the regional averages for the recent past period (median and 5th/95th percentiles uncertainty range) for the Vousdoukas et al 2018 dataset \r\n\r\n- Kirezci_ESL.csv contains the regional averages of the Kirezci et al (2020) dataset for future horizons and recent past (median and 5th/95th percentiles uncertainty range)\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project\r\n CORDEX is The Coordinated Regional Downscaling Experiment from the WCRP.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5. \r\n RCP2.6 is the Representative Concentration Pathway for 2.6 Wm-2 global warming by 2100. \r\n RCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nJupyter notebooks containing the data files and code used to plot this figure are stored in the 'scripts' GitHub repository linked in the documentation. \r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n- Link to the master GitHub repository containing the Juptyer notebooks to run the code for the figure, as well as the other figures in Chapter 12.\r\n- Link to the code for the figure, archived on Zenodo."
            },
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            "ob_id": 38054,
            "uuid": "baa5cb92f5a04f3598c23740f94c2b18",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/ch7_SM_1/v20220721",
            "numberOfFiles": 44,
            "volume": 12241439,
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            "observation": {
                "ob_id": 37828,
                "uuid": "f0f622f4e9d14f95949a5cc44451e8bb",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 7.SM.1 (v20220721)",
                "abstract": "Data for Figure 7.SM.1 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.SM.1 shows total effective radiative forcing from SSP scenarios with respect to 1750 for 2000-2500, 14 showing best estimate and 5–95% uncertainty range. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 13 subpanels, with data provided for all panels in the master GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Total effective radiative forcing from SSP scenarios with respect to 1750 for 2000-2500, 14 showing best estimate and 5–95% uncertainty range. \r\n- Graph (top panel) showing radiative forcing trajectories for (shaded regions):\r\n  - SSP5-8.5 (brown line)\r\n  - SSP3-7.0-lownNTCF (red dashed line)\r\n  - SSP3-7.0 (red line)\r\n  - SSP3-7.0-lowNTCFCH4 (red dotted line)\r\n  - SSP4-6.0 (orange line)\r\n  - SSP2-4.5 (yellow line)\r\n  - SSP5-3.4-over (early overshoot of purple line)\r\n  - SSP4-3.4 (light blue line)\r\n  - SSP1-2.6 (purple line)\r\n  - SSP1-1.9 (green line)\r\n- Radiative forcing component breakdowns (smaller subpanels):\r\n  - CO2 (carbon dioxide)\r\n  - CH4 (methane)\r\n  - N2O (nitrous oxide)\r\n  - Halogenated gases\r\n  - O3 (ozone)\r\n  - Strat H2O (stratospheric water)\r\n  - Contrails and aviation induced cirrus\r\n  - Aerosol-radiation interactions\r\n  - Aerosol-cloud interactions\r\n  - Light absorbing particles on snow and ice\r\n  - Land use\r\n  - Solar\r\n\r\nUncertainty ranges are not shown for SSP3-7.0-lowNTCF and SSP3-7.0-NTCFCH4 for visual clarity. Bottom matrix shows the best estimate ERF for each anthropogenic component, and solar (volcanic ERF is zero beyond 2024).\r\n\r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP119 is the Shared Socioeconomic Pathway which represents the lowest scenario of radiative forcing and development scenarios, consistent with RCP1.9.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP370 is the Shared Socioeconomic Pathway which represents the upper-middle range of radiative forcing and development scenarios, consistent with RCP6.0.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nNTCF stands for Near-Term Climate Forcer.\r\nERF stands for Effective Radiative Forcing.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.SM.1:\r\n\r\n - Data file: ERF_%_1750-2500.csv'\r\n - Data file: ERF_%_1750-2500_pc05.csv\r\n - Data file: ERF_%_1750-2500_pc95.csv\r\n - Data file: ERF_%_minorGHGs_1750-2500.csv\r\n\r\nEach % is substituted for one of the following scenarios:\r\nSSP119 - best estimate.\r\nSSP119 - 5th percentile.\r\nSSP119 - 95th percentile.\r\nSSP119 minor GHGs - best estimate.\r\n\r\nSSP126 - best estimate.\r\nSSP126 - 5th percentile.\r\nSSP126 - 95th percentile.\r\nSSP126 minor GHGs - best estimate. \r\n\r\nSSP245 - best estimate.\r\nSSP245 - 5th percentile.\r\nSSP245 - 95th percentile.\r\nSSP245 minor GHGs - best estimate.\r\n\r\nSSP334 - best estimate.\r\n\r\nSSP370 - best estimate.\r\nSSP370 - 5th percentile.\r\nSSP370 - 95th percentile.\r\nSSP370 minor GHGs - best estimate.\r\nSSP370 low NTCF - best estimate.\r\nSSP370 low NTCF - 5th percentile.\r\nSSP370 low NTCF - 95th percentile.\r\nSSP370 low NTCF minor GHGs - best estimate.\r\nSSP370 low NTCFCH4 - best estimate.\r\nSSP370 low NTCFCH4 - 5th percentile.\r\nSSP370 low NTCFCH4 - 95th percentile.\r\nSSP370 low NTCFCH4 minor GHGs - best estimate.\r\n\r\nSSP434 - best estimate.\r\nSSP434 - 5th percentile.\r\nSSP434 - 95th percentile.\r\nSSP434 minor GHGs - best estimate.\r\n\r\nSSP460 - best estimate.\r\nSSP460 - 5th percentile.\r\nSSP460 - 95th percentile.\r\nSSP460 minor GHGs - best estimate.\r\n\r\nSSP534 over - best estimate.\r\nSSP534 over - 5th percentile.\r\nSSP534 over - 95th percentile.\r\nSSP534 over minor GHGs - best estimate.\r\n\r\nSSP585 - best estimate.\r\nSSP585 - 5th percentile.\r\nSSP585 - 95th pecentile.\r\nSSP585 minor GHGs - best estimate.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided \"as-is\" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.\r\n\r\nWithin the processing chain, every notebook is prefixed by a number. To reproduce all results in the chapter, the notebooks should be run in numerical order, because some later things depend on earlier things (historical temperature attribution requires a constrained ensemble of the two layer climate model, which relies on the generation of the radiative forcing time series). This being said, most notebooks should run standalone, as input data is provided where the datasets are small enough (see the 'master;' GitHub page for these).\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n - Link to the Jupyter notebook for plotting the figure from the Chapter 7 GitHub repository\r\n - Link to the code for the figure, archived on Zenodo."
            },
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            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_faq3_fig1/v20220721",
            "numberOfFiles": 231,
            "volume": 8047857,
            "fileFormat": "XLSX, netCDF, txt",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37826,
                "uuid": "47586c6f52a9473ea0b1f909fb231bfc",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for FAQ 7.3, Figure 1 (v20220721)",
                "abstract": "Input Data for FAQ 7.3 Figure 1, from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFAQ 7.3 Figure 1 shows equilibrium climate sensitivity and future warming.\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\nWhen 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with input data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (left) Equilibrium climate sensitivities for the current generation (CMIP6) climate models, and the previous (CMIP5) generation. The assessed range in this Report (AR6) is also shown. \r\n\r\n- (right) Climate projections of CMIP5, CMIP6 and AR6 for the very high-emissions scenarios RCP8.5, and SSP5-8.5, respectively. \r\n\r\nThe thick horizontal lines represent the multi-model average and the thin horizontal lines represent the results of individual models. The boxes represent the model ranges for CMIP5 and CMIP6 and the range assessed in AR6.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to FAQ 7.3 Figure 1.\r\n \r\n - Data file: ecs_for_faq.csv\r\n - Data file: tcr_for_faq.csv\r\n - Data files: CMIP5_means/dtas_\"+model+\".nc\r\n - Data files: CMIP5_means/tas_\"+model+\"_rcp85.nc\r\n - Data files: CMIP5_means/tas_\"+model+\"_piControl.nc\r\n - Data files: CMIP6_means/dtas_\"+model+\".nc\r\n - Data files: CMIP6_means/tas_\"+model+\"_ssp585.nc\r\n - Data files: CMIP6_means/tas_\"+model+\"_piControl.nc\r\n\r\nModels to be substituted in file names where +model+ exists:\r\n- ACCESS-CM2\r\n- ACCESS-ESM1-5\r\n- AWI-CM-1-1-MR\r\n- BCC-CSM2-MR\r\n- CAMS-CSM1-0\r\n- CESM2-WACCM\r\n- CESM2\r\n- CIESM\r\n- CMCC-CM2-SR5\r\n- CNRM-CM6-1-HR\r\n- CNRM-CM6-1\r\n- CNRM-ESM2-1\r\n- CanESM5\r\n- EC-Earth3-Veg\r\n- FGOALS-f3-L\r\n- FGOALS-g3\r\n- FIO-ESM-2-0\r\n- GISS-E2-1-G\r\n- HadGEM3-GC31-LL\r\n- HadGEM3-GC31-MM\r\n- IITM-ESM\r\n- INM-CM4-8\r\n- INM-CM5-0\r\n- IPSL-CM6A-LR\r\n- KACE-1-0-G\r\n- MCM-UA-1-0\r\n- MIROC-ES2L\r\n- MIROC6\r\n- MPI-ESM1-2-HR\r\n- MPI-ESM1-2-LR\r\n- MRI-ESM2-0\r\n- NESM3\r\n- NorESM2-LM\r\n- NorESM2-MM\r\n- TaiESM1\r\n- UKESM1-0-LL\r\nThis means the _ssp585.nc and _piControl.nc files have 36 versions each, for both CMIP5 and CMIP6 (a total of 144 netCDF files).\r\n\r\nThe above files are from the 'contributed' folder on the 'master' GitHub repository, rather than in data_input or data_output. \r\n\r\nCMIP5 is the fifth stage of the Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth stage of the Coupled Model Intercomparison Project.\r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nACCESS-CM2 is the Australian Community Climate and Earth System Simulator coupled climate model.\r\nACCESS-ESM1-5 is the Australian Community Climate and Earth System Simulator Earth system model version designed to participate in CMIP6 simulations.\r\nAWI-CM-1-1-MR is the Alfred Wegener Institute Climate Model version 1.1 - Medium Resolution, with locally-increased horizontal resolution over energetically active ocean areas.\r\nBCC-CSM2-MR is the Beijing Climate Center Climate System Model version 2 - moderate vertical resolution.\r\nCAMS-CSM1-0 is the Chinese Academy of Meteorological Sciences Climate System Model version 1.\r\nCESM2-WACCM is the Community System Model version 2- Whole Atmosphere Community Climate Model.\r\nCESM2 is the Community Earth System Model version 2.\r\nCIESM is the Community Integrated Earth System Model.\r\nCMCC-CM2-SR5 is the Euro-Mediterranean Centre on Climate Change Coupled Climate Model version 2 - standard configuration.\r\nCNRM-CM6-1-HR is the Centre National de Recherches Météorologiques Climate Model for CMIP6 - altered Horizontal Resolution.\r\nCNRM-CM6-1 is the Centre National de Recherches Météorologiques Climate Model for CMIP6.\r\nCNRM-ESM2-1 is the Centre National de Recherches Météorologiques Earth System Model, derived from CNRM-CM6-1.\r\nCanESM5 is the Canadian Earth System Model version 5.\r\nEC-Earth3-Veg is the European Community Earth-system model version 3, with the Global Circulation Model (GCM) coupled to the dynamic vegetation model.\r\nFGOALS-f3-L is the Flexible Global Ocean-Atmosphere-Land System Model, Finite-volume version 3, low horizontal resolution. \r\nFGOALS-g3 is the Flexible Global Ocean-Atmosphere-Land System Model, Grid-point Version 3.\r\nFIO-ESM-2-0 is the First Institute of Oceanography Earth System Model version 2.0.\r\nGISS-E2-1-G is the Goddard Institute for Space Studies - chemistry-climate model version E2.1, using the GISS Ocean v1 (G01) model.\r\nHadGEM3-GC31-LL is the Met Offfice Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N96/ORCA1.\r\nHadGEM3-GC31-MM is the Met Offfice Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N216/ORCA025.\r\nIITM-ESM is the Indian Institute of Tropical Meteorology Earth System Model.\r\nINM-CM4-8 is the Institute for Numerical Mathematics Climate Model version 4.8. \r\nINM-CM5-0 is the Institute for Numerical Mathematics Climate Model version 5.0. \r\nIPSL-CM6A-LR is the Institut Pierre-Simon Laplace Climate Model for CMIP6 - Low Resolution.\r\nKACE-1-0-G is the Korean Advanced Community Earth system model. \r\nMCM-UA-1-0 is the Manabe Climate Climate - University of Arizona - version 1.0. \r\nMIROC-ES2L is the Model for Interdisciplinary Research on Climate - Earth System version 2 for Long-term simulations.\r\nMIROC6 is the Model for Interdisciplinary Research on Climate version 6.\r\nMPI-ESM1-2-HR is the Max Planck Institute Earth System Model - version 2 - altered Horizontal Resolution.\r\nMPI-ESM1-2-LR is the Max Planck Institute Earth System Model - version 2 - Low Resolution.\r\nMRI-ESM2-0 is the Meteorological Research Institute Earth System Model version 2.0.\r\nNESM3 is the Nanjing University of Information Science and Technology Earth System Model version 3.\r\nNorESM2-LM is the Norwegian Earth System Model version 2 - 2 degree resolution for atmosphere and land components, 1 degree resolution for ocean and sea-ice components.\r\nNorESM2-MM is the Norwegian Earth System Model version 2 - 1 degree resolution for all model components.\r\nTaiESM1 is theTaiwan Earth System Model version 1.\r\nUKESM1-0-LL is the The UK Earth System Model - version 1 - 2 degree resolution for all model components.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided \"as-is\" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.\r\n\r\nThe notebook used to plot this figure is linked in the 'Related Documents' section. The output figure data is also archived at CEDA.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n - Link to the Jupyter notebook for plotting this figure from the Chapter 7 GitHub repository\r\n- Link to the code for the figure, archived on Zenodo."
            },
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_BOX2_fig1/v20220817",
            "numberOfFiles": 10,
            "volume": 190006,
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            "observation": {
                "ob_id": 37892,
                "uuid": "568fb4b2e6464a50a30c7140bb88a497",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Box 7.2, Figure 1. (v20220817)",
                "abstract": "Input Data for Box 7.2, Figure 1 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nBox 7.2, Figure 1 shows estimates of the net cumulative energy change (ZJ = 1021 Joules) for the period 1971–2018 associated with: (a) observations of changes in the Global Energy Inventory (b) Integrated Radiative Forcing; (c) Integrated Radiative Response. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 6 subpanels, with input data provided for panels a-f.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Estimates of the net cumulative energy change (ZJ = 1021 Joules) for the period 1971–2018 associated with: \r\n(a) observations of changes in the Global Energy Inventory \r\n(b) Integrated Radiative Forcing; \r\n(c) Integrated Radiative Response.\r\n\r\nBlack dotted lines indicate the central estimate with likely and very likely ranges as indicated in the legend. The grey dotted lines indicate the energy change associated with an estimated pre-industrial Earth energy imbalance of 0.2 W m–2 (a), and an illustration of an assumed pattern effect of –0.5 W m–2 °C–1 (c). \r\n\r\nBackground grey lines indicate equivalent heating rates in W m–2 per unit area of Earth’s surface. \r\nPanels (d) and (e) show the breakdown of components, as indicated in the legend, for the global energy inventory and integrated radiative forcing, respectively. Panel (f) shows the global energy budget assessed for the period 1971–2018, that is, the consistency between the change in the global energy inventory relative to pre-industrial and the implied energy change from integrated radiative forcing plus integrated radiative response under a number of different assumptions, as indicated in the legend, including assumptions of correlated and uncorrelated uncertainties in forcing plus response. \r\n\r\nShading represents the very likely range for observed energy change relative to pre-industrial levels and likely range for all other quantities. \r\nForcing and response time series are expressed relative to a baseline period of 1850–1900. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Box 7.2, Figure 1:\r\n \r\n - Data file: AR6_ERF_1750-2019.csv\r\n - Data file: AR6_energy_GMSL_timeseries_FGD_1971to2018_IMBIEupdate.csv\r\n - Data file: AR6_energy_GMSL_timeseries_FGD_1971to2018_corrigendum.csv\r\n - Data file: Box7.2_ERF_ZJ_percentiles_FGD_1971to2018.csv\r\n - Data file: Box7.2_Response_ZJ_percentiles_FGD_1971to2018.csv\r\n - Data file: Box7.2_ERFResp_uncorrelated_ZJ_percentiles_FGD_1971to2018.csv\r\n - Data file: Box7.2_ERFResp_correlated_ZJ_percentiles_FGD_1971to2018.csv\r\n\r\nData files are converted to csv from pickle format for archival. A link to the original files on GitHub is provided in the 'Related Documents' section.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided \"as-is\" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.\r\n\r\nThe data provided here is converted from pickle files which are used in the plotting script. The link to the original pickle files on GitHub is provided. To reproduce the figure from the input data provided, you will need to edit the filepaths within the notebook based on your local directory structure.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n - Link to the notebook to plot the figure on the Chapter 7 GitHub repository\r\n - Link to the original pickle files on GitHub\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to Cross-Chapter Box 9.1, Figure 1"
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            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig03/v20220721",
            "numberOfFiles": 6,
            "volume": 77658,
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            "observation": {
                "ob_id": 37820,
                "uuid": "6842c53c516746ea860e11512dc133c2",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.3 (v20220721)",
                "abstract": "Input Data for Figure 7.3 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.3 shows anomalies in global mean all-sky top-of-atmosphere (TOA) fluxes from CERES-EBAF Ed4.0 and various CMIP6 climate models in terms of reflected solar, emitted thermal and net TOA fluxes. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 3 subpanels, with input data provided for panels a-c. A link to the code to plot the figure archived on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Anomalies in global mean all-sky top-of-atmosphere (TOA) fluxes from CERES-EBAF Ed4.0 in terms of reflected solar, emitted thermal and net TOA fluxes. \r\n- Anomalies in various CMIP6 climate models in terms of reflected solar, emitted thermal and net TOA fluxes. \r\n\r\n(a) Global mean solar flux anomaly.\r\n(b) Global mean thermal flux anomaly.\r\n(c) Global mean net flux anomaly.\r\n\r\nAnomalies in global mean all-sky top-of-atmosphere (TOA) fluxes from CERES-EBAF Ed4.0 are depicted as solid black lines.\r\nAnomalies in CMIP6 climate models are depicted as coloured lines.\r\nThe multi-model means are additionally depicted as solid red lines. \r\n\r\nModel fluxes stem from simulations driven with prescribed sea surface temperatures (SSTs) and all known anthropogenic and natural forcings. Shown are anomalies of 12-month running means. All flux anomalies are defined as positive downwards, consistent with the sign convention used throughout this chapter. The correlations between the multi-model means (solid red lines) and the CERES records (solid black lines) for 12-month running means are: 0.85 for the global mean reflected solar; 0.73 for outgoing thermal radiation; and 0.81 for net TOA radiation. Figure adapted from Loeb et al. (2020). \r\n\r\nThe models from which the input data are derived are the following:\r\n- CERES\r\n- CESM2\r\n- CanESM5\r\n- EC-Earth3\r\n- ECHAM\r\n- GFDL\r\n- HadGEM3\r\n- IPSL\r\n- multimodel\r\n- EC-Earth3-Veg\r\n- ECHAM6.3\r\n- GFDL-AM4\r\n- IPSL-CM6A\r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nCERES stands for Clouds and the Earth's Radiant Energy System.\r\nCERES-EBAF Ed4.0 is the Clouds and the Earth's Radiant Energy System - Energy Balanced and Filled data product version 4.\r\nCESM2 is the Community Earth System Model version 2.\r\nCanESM5 is the Canadian Earth System Model version 5.\r\nEC-Earth3 is the European Community Earth-system model version 3.\r\nECHAM is an atmospheric General Circulation Model (GCM) from the MPI (Max Planck Institute for Meteorology).\r\nGFDL is the Geophysical Fluid Dynamics Laboratory.\r\nHadGEM3 is the Met Offfice Hadley Centre Global Environment Model version 3.\r\nIPSL is the Institut Pierre-Simon Laplace. \r\nEC-Earth3-Veg is the European Community Earth-system model version 3, with the Global Circulation Model (GCM) coupled to the dynamic vegetation model.\r\nECHAM6.3 is version 6.2 of the atmospheric General Circulation Model (GCM) ECHAM from the MPI (Max Planck Institute for Meteorology).\r\nGFDL-AM4 is the Geophysical Fluid Dynamics Laboratory Atmosphere and Land Model version 4.\r\nIPSL-CM6A is the Institut Pierre-Simon Laplace Climate Model for CMIP6.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.3:\r\n\r\n - Data file: Global_Net_Anomaly_Timeseries_12monthMean.txt\r\n - Data file: Global_SW_Anomaly_Timeseries_12monthMean.txt\r\n - Data file: Global_LW_Anomaly_Timeseries_12monthMean.txt\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository. The input data provided is used in the notebook to output figure 7.3. To reproduce the figure from the input data, you will need to edit the path 'datadir' in box 3 of the notebook based on your local directory structure.\r\n\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo\r\n- Link to the notebook for plotting the figure on the Chapter 7 GitHub repository"
            },
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        {
            "ob_id": 38059,
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig04/v20230517",
            "numberOfFiles": 4,
            "volume": 21705,
            "fileFormat": "CSV",
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            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37819,
                "uuid": "d32090ff8fe342788191683eb4416411",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.4 (v20230517)",
                "abstract": "Input Data for Figure 7.4 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.4 shows radiative adjustments at top of atmosphere for seven different climate drivers as a proportion of forcing. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with input data provided. A link to the code to plot the figure archived on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Radiative adjustment for tropospheric temperature (orange)\r\n- Radiative adjustment for stratospheric temperature (yellow)\r\n- Radiative adjustment for water vapour (blue)\r\n- Radiative adjustment for surface albedo (green)\r\n- Radiative adjustment for clouds (grey)\r\n- Total adjustment (black) \r\n\r\nFor the greenhouse gases (carbon dioxide, methane, nitrous oxide and CFC-12) the adjustments are expressed as a percentage of stratospheric-temperature-adjusted radiative forcing (SARF), whereas for aerosol, solar and volcanic forcing they are expressed as a percentage of instantaneous radiative forcing (IRF). Land surface temperature response (outline red bar) is shown, but included in the definition of forcing. Data from Smith et al. (2018b) for carbon dioxide and methane; Smith et al. (2018b) and Gray et al. (2009) for solar; Hodnebrog et al. (2020b) for nitrous oxide and CFC-12; Smith et al. (2020b) for aerosol, and Marshall et al. (2020) for volcanic. \r\nIRFs come from offline calculations by Chris and Gunnar (for CAM4)\r\n\r\ntas_SW, ta_trop_SW, ta_strat_SW. alb_LW are always set to zero.  Variables are included in netcdf anyways for consistency.\r\nWhen LW or SW IRFs is not available, The value is set to NaN in the netcdf.\r\nWhen the IRFs are NaN, the corresponding cloud adjustments are also set to NaN.\r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\nCanESM2 is the Canadian Earth System Model version 2.\r\nECHAM-HAM is the atmospheric General Circulation Model (GCM) from the MPI (Max Planck Institute for Meteorology) - Hamburg Aerosol Model.\r\nGISS-E2-R is the Goddard Institute for Space Studies coupled general circulation model (CGCM) - ocean configuration coupled to the Russell OGCM. \r\nHadGEM2 is the Met Offfice Hadley Centre Global Environment Model version 2.\r\nHadGEM3 is the Met Offfice Hadley Centre Global Environment Model version 3.\r\nIPSL-CM5A is the Institut Pierre-Simon Laplace Climate Model for CMIP5.\r\nMIROC-SPRINTARS is the Model for Interdisciplinary Research on Climate - Spectral Radiation-Transport Model for Aerosol Species.\r\nMPI-ESM is the Max Planck Institute Earth System Model.\r\nNCAR-CESM1-CAM4 is the National Center for Atmospheric Research - Community Earth System Model version 1 - Community Atmosphere Model version 4. \r\nNCAR-CESM1-CAM5 is the National Center for Atmospheric Research - Community Earth System Model version 1 - Community Atmosphere Model version 5. \r\nHadGEM2 is the Met Offfice Hadley Centre Global Environment Model version 2.\r\nGFDL is the Geophysical Fluid Dynamics Laboratory.\r\nBMRC is the Australian Bureau of Meteorology Research Centre.\r\nCCSM4 is the Community Climate System Model version 4.\r\nCESM is the Community Earth System Model.\r\nERF stands for Effective Radiative Forcing.\r\nIRF stands for Instantaneous Radiative Forcing. \r\nTAS stands for Temperature at Surface. \r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nThe CSV file used to plot Figure 7.4 is provided:\r\n\r\n- 'fig7.4.csv'\r\n\r\nThe github repository contains all input files to the plotting script for the figure except 'rcmip-concentrations-annual-means-v5-1-0.csv'. These are processed and combined in the code to create a single file 'fig7.4.csv' which is provided. The figure can be reproduced using just this file by running the notebook from box 22 by reading in the csv as variable 'adjustments_df'.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository linked in the Related Documents section. The github repository contains all input files to the notebook except 'rcmip-concentrations-annual-means-v5-1-0.csv'. These are processed and combined in the code to create a single file 'fig7.4.csv' which is provided. The figure can be reproduced using just this file by running the notebook from box 22 by reading in the csv as variable 'adjustments_df'.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo.\r\n- Link to the notebook for plotting the figure from the Chapter 7 GitHub repository which also contains input data files"
            },
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        {
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            "short_code": "result",
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            "dataPath": "/badc/ar6_wg1/data/ch_07/ch7_fig06/v20220721",
            "numberOfFiles": 6,
            "volume": 314172,
            "fileFormat": "Data are CSV formatted",
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            "observation": {
                "ob_id": 37817,
                "uuid": "0dd364e74c254b64bb5fddb5dceed364",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 7.6 (v20220721)",
                "abstract": "Data for Figure 7.6 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.6 shows the change in effective radiative forcing (ERF) from 1750 to 2019 by contributing forcing agents (carbon dioxide, other well-mixed greenhouse gases (WMGHGs), ozone, stratospheric water vapour, surface albedo, contrails and aviation-induced cirrus, aerosols, anthropogenic total, and solar). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with data provided for this panel. A link to the code to plot the figure archived on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\nChange in effective radiative forcing (ERF) from 1750 to 2019 by the following contributing forcing agents:\r\n   - Carbon dioxide\r\n   - Other well-mixed greenhouse gases (WMGHGs)\r\n   - Ozone\r\n   - Stratospheric water vapour\r\n   - Surface albedo\r\n   - Contrails and aviation-induced cirrus\r\n   - Aerosols\r\n   - Anthropogenic total\r\n   - Solar  \r\n\r\nSolid bars represent best estimates, and very likely (5–95%) ranges are given by error bars. \r\nNon-CO2 WMGHGs are further broken down into contributions from methane (CH4), nitrous oxide (N2O) and halogenated compounds. \r\nSurface albedo is broken down into land-use changes and light-absorbing particles on snow and ice. \r\nAerosols are broken down into contributions from aerosol–cloud interactions (ERFaci) and aerosol–radiation interactions (ERFari). For aerosols and solar, the 2019 single-year values are given (Table 7.8), which differ from the headline assessments in both cases. Volcanic forcing is not shown due to the episodic nature of volcanic eruptions. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.6:\r\n \r\n - Data file: AR6_ERF_1750-2019.csv\r\n - Data file: AR6_ERF_1750-2019_pc05.csv\r\n - Data file: AR6_ERF_1750-2019_pc95.csv\r\n\r\nERFaci stands for Effective Radiative Forcing of aerosol-cloud interaction.\r\nERFari stands for Effective Radiative Forcing of aerosol-radiation interaction.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nThe data for the bars in this figure correspond to the 2019 data in final line of the csv files provided.\r\n\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository, which is linked in the 'Related Documents' section. Within the processing chain, every notebook is prefixed by a number. To reproduce all results in the chapter, the notebooks should be run in numerical order.\r\n\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo.\r\n- Link to the Chapter 7 GitHub repository  \r\n- Link to the notebook for plotting figure"
            },
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            "short_code": "result",
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            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig07/v20220721",
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            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37906,
                "uuid": "3069833ab06a4968a90fa9f649b87ed7",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.7 (v20220721)",
                "abstract": "Input Data for Figure 7.7 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.7 shows the contribution of forcing agents to 2019 temperature change relative to 1750 produced using the two-layer emulator (Supplementary Material 7.SM.2), constrained to assessed ranges for key climate metrics described in Cross-Chapter Box 7.1.\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with data provided for this panel in the master GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Contribution of forcing agents to 2019 temperature change relative to 1750 produced using the two-layer emulator (Supplementary Material 7.SM.2), constrained to assessed ranges for key climate metrics described in Cross-Chapter Box 7.1. The forcing agents represented are the following:\r\n  - carbon dioxide\r\n  - other well-mixed greenhouse gases (WMGHGs)\r\n  - ozone\r\n  - stratospheric water vapour\r\n  - surface albedo\r\n  - contrails and aviation-induced cirrus\r\n  - aerosols\r\n  - solar\r\n  - volcanic\r\n  - total\r\n\r\nThe results are from a 2237-member ensemble. \r\nSolid bars represent best estimates, and very likely (5–95%) ranges are given by error bars. Dashed error bars show the contribution of forcing uncertainty alone, using best estimates of ECS (3.0°C), TCR (1.8°C) and two-layer model parameters representing the CMIP6 multi-model mean. \r\nSolid error bars show the combined effects of forcing and climate response uncertainty using the distribution of ECS and TCR from Tables 7.13 and 7.14, and the distribution of calibrated model parameters from 44 CMIP6 models. \r\nNon-CO2 WMGHGs are further broken down into contributions from methane (CH4), nitrous oxide (N2O) and halogenated compounds. \r\nSurface albedo is broken down into land-use changes and light-absorbing particles on snow and ice. \r\nAerosols are broken down into contributions from aerosol–cloud interactions (ERFaci) and aerosol–radiation interactions (ERFari). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.7:\r\n \r\n - Data file: AR6 FGD assessment time series - GMST and GSAT.xlsx\r\n\r\nECS stands for Equilibrium Climate Sensitivity.\r\nTCR stands for Transient Climate Response.\r\nERFaci stands for Effective Radiative Forcing of aerosol-cloud interaction.\r\nERFari stands for Effective Radiative Forcing of aerosol-radiation interaction.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided \"as-is\" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.\r\n\r\nWithin the processing chain, every notebook is prefixed by a number. To reproduce all results in the chapter, the notebooks should be run in numerical order, because some later things depend on earlier things (historical temperature attribution requires a constrained ensemble of the two layer climate model, which relies on the generation of the radiative forcing time series). This being said, most notebooks should run standalone, as input data is provided where the datasets are small enough (see the 'master;' GitHub page for these).\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38063,
            "uuid": "d2b9908825794f8980e1a03a84b39cae",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig10/v20220721",
            "numberOfFiles": 4,
            "volume": 22130,
            "fileFormat": "json",
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            "storageLocation": "internal",
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            "observation": {
                "ob_id": 37813,
                "uuid": "80380cfc0b10478b8b5821c0facdbdda",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.10 (v20220721)",
                "abstract": "Input Data for Figure 7.10 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.10 shows global mean climate feedbacks estimated in abrupt4xCO2 simulations of 29 CMIP5 models and 49 CMIP6 models, compared with those assessed in this Report. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with data provided for this panel in the master GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Global mean climate feedbacks estimated in abrupt4xCO2 simulations of 29 CMIP5 models and 49 CMIP6 models, compared with those assessed in AR6. The radiative kernels represented are the following:\r\n  - Water vapour & lapse rate\r\n  - Surface albedo\r\n  - Cloud\r\n  - Biogeophysical and non-CO2 biogeochemical\r\n  - Net feedback\r\n  - Planck response\r\n\r\nCMIP5 - light blue\r\nCMIP6 - orange\r\nThis Assessment Report - red\r\n\r\nIndividual feedbacks for CMIP models are averaged across six radiative kernels as computed in Zelinka et al. (2020). \r\nThe white line, black box and vertical line indicate the mean, 66% and 90% ranges, respectively. The shading represents the probability distribution across the full range of GCM/ESM values and for the 2.5–97.5 percentile range of the AR6 normal distribution. The unit is W m–2 °C–1. \r\nFeedbacks associated with biogeophysical and non-CO2 biogeochemical processes are assessed in AR6, but they are not explicitly estimated from general circulation models (GCMs)/Earth system models (ESMs) in CMIP5 and CMIP6. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.10:\r\n \r\n - Data file: cmip56_feedbacks_AR6.json\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository. The input json file provided is used in the notebook to output figure 7.10. To reproduce the figure from the input data, you will need to run the notebook from the same directory as the input data.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n - Link to the code for the figure, archived on Zenodo.\r\n - Link to the notebook for plotting the figure on GitHub\r\n - Link to Zelinka et al. (2020)"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38064,
            "uuid": "07f7ac6ec9124ec4b4b513fba44320f2",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig18/v20220721",
            "numberOfFiles": 7,
            "volume": 38366,
            "fileFormat": "XLSX, CSV",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37805,
                "uuid": "399a75d2538a471cb529d1f0fa01410e",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.18 (v20220721)",
                "abstract": "Input Data for Figure 7.18 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.18 shows a summary of the equilibrium climate sensitivity and transient climate response assessments using different lines of evidence. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with input data provided for both panels. A link to the code to plot the figure archived on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- (a) Equilibrium climate sensitivity (ECM) estimates. \r\n   Assessment methods:\r\n   - Process understanding\r\n   - Instrumental record\r\n   - Paleoclimates\r\n   - Emergent constraints\r\n   - Combined assessment\r\n   - CMIP6 ESMs\r\n\r\n- (b) Transient climate response (TCR) estimates. \r\n   Assessment methods:\r\n   - Process understanding\r\n   - Instrumental record\r\n   - Paleoclimates\r\n   - Emergent constraints\r\n   - Combined assessment\r\n   - CMIP6 ESMs\r\n\r\nAssessed ranges are taken from Tables 7.13 and 7.14 for ECS and TCR respectively. \r\nNote that for the ECS assessment based on both the instrumental record and paleoclimates, limits (i.e., one-sided distributions) are given, which have twice the probability of being outside the maximum/minimum value at a given end, compared to ranges (i.e., two-tailed distributions) which are given for the other lines of evidence. For example, the extremely likely limit of greater than 95% probability corresponds to one side of the very likely (5–95%) range. Best estimates are given as either a single number or by a range represented by a grey box. CMIP6 model values are not directly used as a line of evidence but presented on the Figure for comparison.\r\n \r\nECS values are taken from Schlund et al. (2020) and TCR values from Meehl et al. (2020); see Supplementary Material 7.SM.4. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.18:\r\n \r\n - Data file: ecs_for_faq.csv\r\n - Data file: tcr_for_faq.csv\r\n\r\nData is also provided in xlsx format, which is the format used by the plotting script linked in the Related Documents section.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nESM stands for Earth System Model. \r\nACCESS1-0 is the Australian Community Climate and Earth System Simulator coupled climate model version 1.0.\r\nACCESS1-3 is the Australian Community Climate and Earth System Simulator coupled climate model version 1.3.\r\nACCESS-CM2 is the Australian Community Climate and Earth System Simulator coupled climate model.\r\nACCESS-ESM1-5 is the Australian Community Climate and Earth System Simulator Earth system model version designed to participate in CMIP6 simulations.\r\nAWI-CM-1-1-MR is the Alfred Wegener Institute Climate Model version 1.1 - Medium Resolution, with locally-increased horizontal resolution over energetically active ocean areas.\r\nBCC-CSM1-1 is the Beijing Climate Center Climate System Model version 1.1.\r\nBCC-CSM1-1-M is the Beijing Climate Center Climate System Model version 1.1, with a moderate resolution.\r\nBCC-CSM2-MR is the Beijing Climate Center Climate System Model version 2 - moderate vertical resolution.\r\nBNU-ESM is the Beijing Normal University Earth System Model.\r\nBNU-ESM1 is the Beijing Normal University Earth System Model version 1.\r\nCAMS-CSM1-0 is the Chinese Academy of Meteorological Sciences Climate System Model version 1.\r\nCanESM5 is the Canadian Earth System Model version 5.\r\nCanESM2 is the Canadian Earth System Model version 2.\r\nCCSM3 is the Community Climate System Model version 3.\r\nCAS-ESM2-0 is the Chinese Academy of Sciences Earth System Model version 2.0.\r\nCESM2 is the Community Earth System Model version 2.\r\nCESM2-FV2 is the Community Earth System Model version 2 - Finite Volume with a 2 degree resolution. \r\nCESM2-WACCM is the Community System Model version 2 - Whole Atmosphere Community Climate Model.\r\nCMCC-CM2-SR5 is the Euro-Mediterranean Centre on Climate Change Coupled Climate Model version 2 - standard configuration.\r\nCNRM-CM5 is the Centre National de Recherches Météorologiques Climate Model for CMIP5.\r\nCNRM-CM5-2 is the Centre National de Recherches Météorologiques Climate Model for CMIP5, version 2.\r\nCNRM-CM6-1 is the Centre National de Recherches Météorologiques Climate Model for CMIP6.\r\nCNRM-CM6-1-HR is the Centre National de Recherches Météorologiques Climate Model for CMIP6 - altered Horizontal Resolution.\r\nCNRM-ESM2-1 is the Centre National de Recherches Météorologiques Earth System Model, derived from CNRM-CM6-1.\r\nCSIRO-Mk3-6-0 is the Commonwealth Scientific and Industrial Research Organisation Atmosphere Ocean Global Climate Model (GCM).\r\nE3SM-1-0 is the Energy Exascale Earth System Model version 1.0.\r\nEC-Earth3-Veg is the European Community Earth-system model version 3, with the Global Circulation Model (GCM) coupled to the dynamic vegetation model.\r\nFGOALS-f3-L is the Flexible Global Ocean-Atmosphere-Land System Model, Finite-volume version 3, low horizontal resolution. \r\nFGOALS-g2 is the Flexible Global Ocean-Atmosphere-Land System Model, Grid-point Version 2.\r\nFGOALS-g3 is the Flexible Global Ocean-Atmosphere-Land System Model, Grid-point Version 3.\r\nGFDL-CM3 is the Geophysical Fluid Dynamics Laboratory - Climate Model 3.\r\nGFDL-ESM2G is the Geophysical Fluid Dynamics Laboratory - Earth System Model version 2, multi-centennial warming.\r\nGFDL-ESM2M is the Geophysical Fluid Dynamics Laboratory - Earth System Model version 2, multi-centennial cooling. \r\nGISS-E2-1-G is the Goddard Institute for Space Studies - chemistry-climate model version E2.1, using the GISS Ocean v1 (G01) model.\r\nGISS-E2-H is the Goddard Institute for Space Studies coupled general circulation model (CGCM) - ocean configuration coupled to the \r\nHYCOM is the Hybrid Coordinate Ocean Model.\r\nGISS-E2-R is the Goddard Institute for Space Studies coupled general circulation model (CGCM) - ocean configuration coupled to the Russell OGCM.\r\nHadGEM2-ES is the Met Office Hadley Centre Global Environment Model version 2 - Earth System. \r\nHadGEM3-GC31-LL is the Met Office Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N96/ORCA1.\r\nHadGEM3-GC31-MM is the Met Office Hadley Centre Global Environment Model - Global Coupled configuration 3.1 - using an atmosphere/ocean resolution for historical simulation N216/ORCA025.\r\nHYCOM is the Hybrid Coordinate Ocean Model. \r\nINMCM4 is the Institute for Numerical Mathematics Climate Model version 4.0. \r\nINM-CM4-8 is the Institute for Numerical Mathematics Climate Model version 4.8.\r\nINM-CM5-0 is the Institute for Numerical Mathematics Climate Model version 5.0. \r\nIPSL-CM5A-LR is the Institut Pierre-Simon Laplace Climate Model for CMIP5 - Low Resolution, with re-parameterised cloud configuration.\r\nIPSL-CM5A-MR is the Institut Pierre-Simon Laplace Climate Model for CMIP5 - Mixed Resolution, with a higher horizontal atmospheric resolution.\r\nIPSL-CM5B-LR is the Institut Pierre-Simon Laplace Climate Model for CMIP5 - Low Resolution, with a LMDZ5B atmospheric component.\r\nIPSL-CM6A-LR is the Institut Pierre-Simon Laplace Climate Model for CMIP6 - Low Resolution.\r\nKACE-1-0-G is the Korean Advanced Community Earth system model. \r\nMCM-UA-1-0 is the Manabe Climate Model - University of Arizona - version 1.0. \r\nMIROC-ES2L is the Model for Interdisciplinary Research on Climate - Earth System version 2 for Long-term simulations.\r\nMIROC-ESM is the Model for Interdisciplinary Research on Climate - Earth System Model.\r\nMIROC5 is the Model for Interdisciplinary Research on Climate version 5.\r\nMIROC6 is the Model for Interdisciplinary Research on Climate version 6.\r\nMPI-ESM-1-2-HAM is the Max Planck Institute Earth System Model - version 2 - Hamburg Aerosol Model.\r\nMPI-ESM1-2-HR is the Max Planck Institute Earth System Model - version 2 - altered Horizontal Resolution.\r\nMPI-ESM1-2-LR is the Max Planck Institute Earth System Model - version 2 - Low Resolution.\r\nMPI-ESM-LR is the Max Planck Institute Earth System Model - Low Resolution.\r\nMPI-ESM-MR is the Max Planck Institute Earth System Model - Mixed Resolution.\r\nMPI-ESM-P is the Max Planck Institute Earth System Model - with reconfiguration of orbit and vegetation. \r\nMRI-CGCM3 is the Meteorological Research Institute - Coupled General Circulation Model version 3. \r\nMRI-ESM2-0 is the Meteorological Research Institute Earth System Model version 2.0.\r\nNESM3 is the Nanjing University of Information Science and Technology Earth System Model version 3.\r\nNorCPM1 is the Norwegian Climate Prediction Model version 1.\r\nNorESM1-LM is the Norwegian Earth System Model version 1 - 2 degree resolution for atmosphere and land components, 1 degree resolution for ocean and sea-ice components.\r\nNorESM2-LM is the Norwegian Earth System Model version 2 - 2 degree resolution for atmosphere and land components, 1 degree resolution for ocean and sea-ice components.\r\nNorESM2-MM is the Norwegian Earth System Model version 2 - 1 degree resolution for all model components.\r\nRussell OGCM is the Russell Ocean General Circulation Model. \r\nSAM0-UNICON is the Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme.\r\nTaiESM1 is the Taiwan Earth System Model version 1.\r\nUKESM1-0-LL is the UK Earth System Model - version 1 - 2 degree resolution for all model components.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository. The input data provided is used in the notebook to output figure 7.18. To reproduce the figure from the input data, you will need to edit the path 'datadir' in box 6 of the notebook based on your local directory structure. The notebook runs with data in .xlsx format but the data is also provided in .csv format here.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo.\r\n - Link to notebook for plotting figure from the Chapter 7 GitHub repository"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38065,
            "uuid": "73abda7cb8354799831651f71969c398",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig21/v20220721",
            "numberOfFiles": 4,
            "volume": 58873,
            "fileFormat": "CSV",
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            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 37824,
                "uuid": "f94821849dfb4ee2bd1a367a81a6b6f7",
                "short_code": "ob",
                "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.21 (v20220721)",
                "abstract": "Input Data for Figure 7.21 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.21 shows emissions metrics for two short-lived greenhouse gases: HFC-32 and methane (CH4; lifetimes of 5.4 and 11.8 years). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 4 subpanels, with data provided for panels a-d.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Emissions metrics for HFC-32 and methane (CH4):\r\n(a) Temperature response to a step change in short-lived greenhouse gas emissions. \r\n(b) Temperature response to a pulse CO2 emission. \r\n(c) Conventional GTP metrics (pulse vs pulse). \r\n(d) Combined GTP metric (step versus pulse). \r\n\r\nThe temperature response function comes from Supplementary Material 7.SM.5.2. Values for non-CO2 species include the carbon cycle response (Section 7.6.1.3). Results for HFC-32 have been divided by 100 to show on the same scale. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\nGTP stands for Global Temperature-change Potential.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.21:\r\n \r\n - Data file: cgtp.csv\r\n\r\nThe data in this files is identical to the original data in .npz format. Link to the orginal data in this format used with the code for reproducing the figure is provided in the 'Related Documents' section.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository. The link to the input .npz file provided is used in the notebook to output figure 7.21. To reproduce the figure from the input data, you will need to run the notebook from the same directory as the input data and adjust the path to the data in box 3.\r\n\r\n ---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n - Link to the original data in .npz format used in the code\r\n - Link to the code for the figure, archived on Zenodo.\r\n - Link to the notebook on the Chapter 7 GitHub repository for plotting the figure"
            },
            "onlineresource_set": []
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        {
            "ob_id": 38075,
            "uuid": "7b0bd35c55a9425f8748833a9cecd066",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-daily-rain-obs/dataset-version-202207/",
            "numberOfFiles": 51646,
            "volume": 1084616388,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38071,
                "uuid": "15deeb29cdcd4524b07560e5aad45ded",
                "short_code": "ob",
                "title": "MIDAS Open: UK daily rainfall data, v202207",
                "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2021. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202107) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Colmonell (Ayrshire, 1924-1960), Camps Reservoir (Lanarkshire, 1934-1960), and Greenock (Renfrewshire, 1910-1960).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38076,
            "uuid": "a61aa44ac6534481b790e01196ec4040",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-daily-weather-obs/dataset-version-202207/",
            "numberOfFiles": 47397,
            "volume": 3037385885,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38069,
                "uuid": "4b44cec2f9a846f39d5007983b7eaaab",
                "short_code": "ob",
                "title": "MIDAS Open: UK daily weather observation data, v202207",
                "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2021. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Sheffield (South Yorkshire, 1898-1935).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38077,
            "uuid": "b01c749180984a57ad205ec1d629ee1e",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-hourly-rain-obs/dataset-version-202207/",
            "numberOfFiles": 15675,
            "volume": 5143758435,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38072,
                "uuid": "64f5d7be890a4ac08cb2b4e78eb5fcc1",
                "short_code": "ob",
                "title": "MIDAS Open: UK hourly rainfall data, v202207",
                "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38078,
            "uuid": "96161295ca7a4bb6b27150c2c9f58dc1",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-daily-temperature-obs/dataset-version-202207/",
            "numberOfFiles": 62933,
            "volume": 2137232187,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38067,
                "uuid": "8bcf6925cddc4681b96f94d424537b9e",
                "short_code": "ob",
                "title": "MIDAS Open: UK daily temperature data, v202207",
                "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2021. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38079,
            "uuid": "f887a3cad6fc4cacaaba51813e22bbc8",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-hourly-weather-obs/dataset-version-202207/",
            "numberOfFiles": 51431,
            "volume": 31273999098,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38070,
                "uuid": "6180fb7ed76a442eb1b8f3f152fd08d7",
                "short_code": "ob",
                "title": "MIDAS Open: UK hourly weather observation data, v202207",
                "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Sheffield (South Yorkshire, 1882-1935).\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38080,
            "uuid": "98d95d600a0348c9b955c4758e801013",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-mean-wind-obs/dataset-version-202207/",
            "numberOfFiles": 14644,
            "volume": 7743361027,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38068,
                "uuid": "fa83484e57854d6fbde16ff945ff6dc0",
                "short_code": "ob",
                "title": "MIDAS Open: UK mean wind data, v202207",
                "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK,  section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38081,
            "uuid": "17fc0c6417fa4133b21bbe1403c5162c",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-soil-temperature-obs/dataset-version-202207/",
            "numberOfFiles": 23510,
            "volume": 4046211314,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38073,
                "uuid": "4ecbf3fa1b084c5a9080248433275124",
                "short_code": "ob",
                "title": "MIDAS Open: UK soil temperature data, v202207",
                "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38082,
            "uuid": "a6b708ae95af4648aef1a1db840ed137",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-midas-open/data/uk-radiation-obs/dataset-version-202207/",
            "numberOfFiles": 5369,
            "volume": 2844877616,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38074,
                "uuid": "e3a7f3336ff8464f9ae6534a8e8676e5",
                "short_code": "ob",
                "title": "MIDAS Open: UK hourly solar radiation data, v202207",
                "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38084,
            "uuid": "39669bf73c7643e7998e20c4c0757add",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/lgm_oscillations",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 38093,
            "uuid": "2b6e384527d6471a92a592bae49c744c",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/lgm_oscillations",
            "numberOfFiles": 107,
            "volume": 53536747877,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38092,
                "uuid": "aff921a9f2a34f008744342f0baaa9a5",
                "short_code": "ob",
                "title": "HadCM3 general circulation model forced simulations of oscillating last glacial maximum forced with deglacial meltwater",
                "abstract": "This dataset contains HadCM3 model global forced simulations of the last glacial maximum, inputs and outputs, as used in the publication Rome et al. 2022 (DOI:10.1002/essoar.10511015.1). Seven simulations outputs are included under the names XOUPA, TFGBD_XOUPD, XOUPH, TFGBR_XOUPL, TFGBI, XOUPF and TFGBJ. The simulations were created using the general circulation model HadCM3 over the entire globe under last glacial maximum (21,000 years ago) conditions and forced with snapshots of meltwater derived from the early deglaciation (21,500 to 17,800 years ago). The outputs consist of sea-ice concentration, ocean overturning circulation, mixed layer depth, sea surface salinity, sea surface temperature, precipitation and surface air temperature. For reproducibility,  the meltwater input files used for the forcing (lgm_inputs), the model input files (mw_inputs), the pre-industrial climatologies (pi_climate) and the crash diagnostics (crash_data) are included."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38100,
            "uuid": "7d00f4d4b37045a78f859267e669a9da",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/sasso_aus_wildfires_stratosphere",
            "numberOfFiles": 15,
            "volume": 1521084402,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38099,
                "uuid": "605bdfe77b0a4c7493c0477f5a95fc0a",
                "short_code": "ob",
                "title": "CALIOP and OMPS-LP satellite retrievals of the aerosol extinction coefficient for the Australian wildfires stratospheric impact study, Southern Hemisphere Data Set 2020",
                "abstract": "This dataset contains zonally averaged data from NASA's Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and NASA's Ozone Mapping and Profiler Suite -Limb Profiler (OMPS-LP) satellite retrievals of the aerosol extinction coefficient and ozone anomalies during 2020.  These data were used for the experiments of Damany-Pearce et al. in the publication \"Australian Wildfires cause the largest stratospheric warming since Pinatubo and extends the lifetime of the Antarctic ozone hole\" 2022.  \r\n\r\nThe ozone anomalies are given at monthly intervals, throughout all of 2020, at 1˚ latitude bands over the whole Southern Hemisphere, based on OMPS-LP retrievals. The aerosol extinction coefficient anomalies are given at weekly intervals, from 2020-12-29 through to the end of 2020, at 10˚ latitude bands from 20˚S to 70˚S. These are given as a combined dataset based off both CALIOP and OMPS-LP retrievals, the full details of how the retrievals were combined and all anomalies were calculated is outlined in Damany-Pearce et al., (2020). NetCDF files of the total uncertainty in both the CALIOP and OMPS-LP retrieved aerosol extinction coefficient anomalies are also included.\r\n\r\nThe dataset also includes 8 files that would be needed to reproduce the experiments of Damany-Pearce et al. (2022) on the (UK Earth System Model) UKESM1 platform, these are the satellite retrievals of aerosol extinction coefficient and ozone anomalies, that have been converted into the input required by UKESM1 and full descriptions of these are provided in the readme.txt file."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38104,
            "uuid": "95ca005c636442d7b334f9303e0e4d98",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/cru/data/cru_ts/cru_ts_4.06",
            "numberOfFiles": 409,
            "volume": 7033543050,
            "fileFormat": "Data are provided in ASCII and NetCDF formats.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38103,
                "uuid": "e0b4e1e56c1c4460b796073a31366980",
                "short_code": "ob",
                "title": "CRU TS4.06: Climatic Research Unit (CRU) Time-Series (TS) version 4.06 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2021)",
                "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.06 data are month-by-month variations in climate over the period 1901-2021, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.\r\n\r\nThe CRU TS4.06 variables are cloud cover, diurnal temperature range, frost day frequency, wet day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2021.\r\n\r\nThe CRU TS4.06 data were produced using angular-distance weighting (ADW) interpolation. All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.06 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38110,
            "uuid": "25c6a75de5e4458e8f135454babf7eca",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/Airborne_Imagery_Sabah_2020",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are tif images, shape files and lidar (.laz) formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 38112,
            "uuid": "31e6afd731fa486e83dd4016f25dac7a",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/Airborne_Imagery_Sabah_2020",
            "numberOfFiles": 9982,
            "volume": 1010598480479,
            "fileFormat": "Data are tif images, shape files and LASer (.las) formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38111,
                "uuid": "dd4d20c8626f4b9d99bc14358b1b50fe",
                "short_code": "ob",
                "title": "Airborne LiDAR and RGB imagery from Sepilok Reserve and Danum Valley in Malaysia in 2020",
                "abstract": "This dataset contains LiDAR and RedGreenBlue (RGB) Imagery data collected from a helicopter over two forest sites in Sabah, Malaysia in February 2020.\r\n\r\nPoint cloud data are included in LAS (LASer) format as well as RGB data summary rasters in .tif format. The raster images were processed with LAStools using default parameters.   Canopy Height Model (CHM), Digital Surface Model (DSM), Digital Terrain Model (DTM) and pulse density (pd) are also present. The RGB data are provided as jpgs and are organised by flight julian day (JD).  \r\n\r\nThe Sepilok Reserve was scanned in full between 15 February 2020 (julian day 46). This is a total area of 27 square kilometres. In Danum Valley the scanning was distributed into two contiguous areas, the protected area (20 square kilometres) and the reduced impact logging area (9 square kilometres) on the 19-22 February 2020 (julian day 50-53). Importantly, these areas were chosen because of the availability of prior airborne LiDAR data collected by NERC in 2014 and by Ground Data Solutions in 2013. \r\n\r\nThe helicopter flew at approximately 350 m altitude above the forest canopy and at a speed of approximately 100 km/hr. The data were georeferenced using ground control points and are provided in the UTM 50N coordinate system."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38129,
            "uuid": "40e03a21bd044233ba71e7f46820ef15",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/TS/ts_15/v20220916",
            "numberOfFiles": 9,
            "volume": 18403,
            "fileFormat": "Data are CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38128,
                "uuid": "1f359da21c4041b4ab0977d05c7d38f0",
                "short_code": "ob",
                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure TS.15 (v20220916)",
                "abstract": "Data for Figure TS.15 from the Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure TS.15 shows contribution to ERF and global surface temperature change from component emissions between 1750 to 2019 based on CMIP6 models, and net aerosol effective radiative forcing (ERF) from different lines of evidence.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Arias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has three panels with data provided for all panels in the underlying chapter figures (6.12 and 7.5).\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n Figure 6.12:\r\n - Contribution to effective radiative forcing (ERF) (a) and global mean surface air temperature (GSAT) change (b) from component emissions between 1750 to 2019 based on CMIP6 models\r\n\r\n\r\nFigure 7.5:\r\n - Net aerosol effective radiative forcing (ERF), in W m-2, from:\r\n - AR5 assessment\r\n - AR6 assessment comprising the following:\r\n (Energy balance constraints [–2 to 0 W m–2 with no best estimate])\r\n (Observational evidence from satellite retrievals of –1.4 [–2.2 to –0.6] W m–2)\r\n (Combined model-based evidence of –1.25 [–2.1 to –0.4] W m–2)\r\n\r\n\r\nDetails about the dataset in the catalogue records of the underlying chapter figures (6.12 and 7.5)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a and panel b:\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_ERF.csv.\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_ERF_uncertainty.csv.\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_dT.csv.\r\n - Data file: fig_em_based_ERF_GSAT_period_1750-2019_values_dT_uncertainty.csv.\r\n  \r\n Panel c:\r\n - Data file: table7.6.csv: input data for figure 7.5\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n ERFari stands for Effective Radiative Forcing of aerosol-radiation interaction.\r\n ERFaci stands for Effective Radiative Forcing of aerosol-cloud interaction.\r\n IRFari stands for Instantaneous Radiative Forcing of aerosol-radiation interaction.\r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Panel a and panel b are identical to panel a and panel b of figure 6.12. Panel c is identical to figure 7.5.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n - Link to the code for the figure, archived on Zenodo.\r\n - Link to underlying chapter figures from which the figure was generated (Figure 6.12, Figure 7.5)\r\n - Link to code used to produce figure 7.5 on the Chapter 7 GitHub repository."
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                "ob_id": 38209,
                "uuid": "168284dabc3d46e4a7f1e83c57da2240",
                "short_code": "ob",
                "title": "FAAM C315 DCMEX flight: Airborne atmospheric measurements from instruments on board the BAE-146 aircraft.",
                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for the Deep Convective Microphysics Experiment (DCMEX) project. Flight C315 took place on 8th August 2022 over New Mexico, USA."
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            "observation": {
                "ob_id": 38212,
                "uuid": "5c6cab17105147ba84a294be46c83153",
                "short_code": "ob",
                "title": "FAAM C296 DCMEX Test flight: Airborne atmospheric measurements from instruments on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from instruments on board the FAAM BAE-146 aircraft collected for DCMEX FAAM Aircraft Project project. Flight C296 took place on 22nd June 2022 over the UK."
            },
            "onlineresource_set": []
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        {
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            "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information.",
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            "observation": {
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                "short_code": "ob",
                "title": "CRU CY4.06: Climatic Research Unit year-by-year variation of selected climate variables by country  version 4.06 (Jan. 1901 - Dec. 2021)",
                "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.06 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency: including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure, potential evapotranspiration and wet day frequency. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2022 by CRU at the University of East Anglia and extends the CRU CY4.06 data to include 2021. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.06 is derived directly from the CRU time series (TS) 4.06 dataset. CRU CY version 4.06 spans the period 1901-2021 for 292 countries.\r\n\r\nTo understand the CRU CY4.06 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.06. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.06 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users."
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                "title": "CRU JRA v2.3: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2021.",
                "abstract": "The CRU JRA V2.3 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different). The data are available at a 6 hourly time-step from January 1901 to December 2021.\r\n\r\nThe dataset is constructed by regridding data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA), adjusting where possible to align with the CRU TS 4.06 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS\r\nmonthly high-resolution gridded multivariate climate dataset.\r\nSci Data 7, 109 (2020). https://doi.org/10.1038/s41597-020-0453-3\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001"
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                "ob_id": 38227,
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                "short_code": "ob",
                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure TS.9 v20220922",
                "abstract": "Data for Figure TS.9 from the Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure TS.9 shows changes in well-mixed greenhouse gas (WMGHG) concentrations and effective radiative forcing (EFR).\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Arias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\nPlease also include citations of the related publications for Figure 2.4b provided at the end of this abstract.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with data provided for panels b and c. Links to the code which contains the data for other panels are provided in the Related Documents section of this catalogue record.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n - Panel TS.9a => Figure 2.3 c\r\n - Panel TS.9b => Figure 2.4 b\r\n - Panel TS.9c => Figure 2.5 a,b,c\r\n - Panel TS.9d => Figure 2.10\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n - Panel TS.9b => Figure 2.4 b\r\n - Panel TS.9c => Figure 2.5 a,b,c\r\n\r\n\r\n---------------------------------------------------\r\nTemporal Range of Paleoclimate Data\r\n---------------------------------------------------\r\nThis dataset covers a paleoclimate timespan from 450 Ma to 2020. \r\nMa refers to millions of years before present.\r\n\r\n\r\n---------------------------------------------------\r\nNotes on reproducing the figure from the provided data\r\n---------------------------------------------------\r\nData for figures 2.3 c and 2.10 are contained within the code to generate the figures which is linked in the Related Documents section of this catalogue record and data for Figure 2.5 and 2.4 panel b are provided. The corresponding catalogue records for Figure 2.5 and 2.4 are linked in the Related Records section below.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n - Link to the report component of the underlying chapter figures from which this figure was generated (Chapter 2)\r\n - Link to the Supplementary Material for Chapter 2, which contains details on the input data used in Table 2.SM.1\r\n- Links to catalogue records of relevant figures the data is taken from in the Related Records section of this catalogue record\r\n- Link to code which contains data for figure 2.3 and 2.10\r\n\r\n\r\n---------------------------------------------------\r\nRelated publications for figure 2.4 panel b datasets\r\n---------------------------------------------------\r\nPlease include the following citations of related publications from which the figure 2.4 panel b datasets originate. Relations to individual datasets are listed at the top of each dataset. Links are provided in the Related Documents section of the figure 2.4 catalogue record which is linked to this record.\r\n\r\nAhn, J., Brook, E. J., Mitchell, L., Rosen, J. McConnell, J. R., Taylor, K., Etheridge, D., and Rubino, M. (2012b). Atmospheric CO2 over the last 1000 years: A high-resolution record from the West Antarctic Ice Sheet (WAIS) Divide ice core, Global Biogeochemical Cycles, 26, GB2027 , doi:10.1029/2011GB004247.\r\n\r\nBauska, T. K., Joos, F., Mix, A. C., Roth, R., Ahn, J., & Brook, E. J. (2015). Links between atmospheric carbon dioxide, the land carbon reservoir and climate over the past millennium. Nature Geoscience. https://doi.org/10.1038/ngeo2422\r\n\r\nRubino, M., Etheridge, D. M., Thornton, D. P., Howden, R., Allison, C. E., Francey, R. J., Langenfelds, R. L., Steele, L. P., Trudinger, C. M., Spencer, D. A., Curran, M. A. J., van Ommen, T. D., & Smith, A. M. (2019). Revised records of atmospheric trace gases CO2, CH4, N2O, and d13C-CO2 over the last 2000 years from Law Dome, Antarctica. Earth System Science Data, 11(2), 473–492. https://doi.org/10.5194/essd-11-473-2019\r\n\r\nSIEGENTHALER, U. R. S., MONNIN, E., KAWAMURA, K., SPAHNI, R., SCHWANDER, J., STAUFFER, B., STOCKER, T. F., BARNOLA, J.-M., & FISCHER, H. (2005). Supporting evidence from the EPICA Dronning Maud Land ice core for atmospheric CO2 changes during the past millennium. Tellus B, 57(1), 51–57. https://doi.org/10.1111/j.1600-0889.2005.00131.x\r\n\r\nMitchell, L., Brook, E., Lee, J. E., Buizert, C., & Sowers, T. (2013). Constraints on the late Holocene anthropogenic contribution to the atmospheric methane budget. Science. https://doi.org/10.1126/science.1238920\r\n\r\nFlückiger, J., Dällenbach, A., Blunier, T., Stauffer, B., Stocker, T. F., Raynaud, D., & Barnola, J. M. (1999). Variations in atmospheric N2O concentration during abrupt climatic changes. Science. https://doi.org/10.1126/science.285.5425.227\r\n\r\nMachida, T., Nakazawa, T., Fujii, Y., Aoki, S., & Watanabe, O. (1995). Increase in the atmospheric nitrous oxide concentration during the last 250 years. Geophysical Research Letters, 22(21), 2921–2924. https://doi.org/10.1029/95GL02822\r\n\r\nRyu, Y., Ahn, J., Yang, J.-W., Jang, Y., Brook, E., Timmermann, A., Hong, S., Han, Y., Hur, S., & Kim, S. (2020). Atmospheric nitrous oxide during the past two millennia, Global Biogeochemical Cycles, 34, e2020GB006568. https://doi.org/10.1029/2020GB006568\r\n\r\nSowers, T. (2001). N2O record spanning the penultimate deglaciation from the Vostok ice core. Journal of Geophysical Research: Atmospheres, 106(D23), 31903–31914. https://doi.org/10.1029/2000JD900707"
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            "observation": {
                "ob_id": 38230,
                "uuid": "d75fd35a7444433c9b5b78ef110495ab",
                "short_code": "ob",
                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure TS.22 v20220923",
                "abstract": "Data for Figure TS.22 from the Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure TS.22 shows a synthesis of the geographical distribution of climatic impact-drivers changes and the number of AR6 WGI reference regions where they are projected to change.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Arias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels with data provided for all panels.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - geographical location of regions belonging to one of five groups characterized by a specific combination of changing climatic impact-drivers (CIDs).\r\n - number of AR6 WG1 regions where Climatic Impact Drivers are projected to change if a global warming level of 2°C is reached compared to a climatological reference period included within 1960-2014\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n -  'Figure-F-Panels_IDL.xlsx' - Datafile containing data for both figures in excel sheets\r\n\r\nIndividual panel data in csv format:\r\n\r\n - Panel a: 'Figure-F-Panel_a_IDL.csv' - Description of the clustering used to generate panel a\r\n \r\n - Panel b: 'consolidated_data_figure_SPM.9.csv' - Same data used for Figure SPM.9 (count of regions with increasing or decreasing changes in climatic impact-drivers). First row relates to darker purple bars, second row to lighter purple bars, third row refers to lighter brown bars and fourth row to darker brown bars.\r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Link to the related record SPM.9 identical to panel b is provided in the Related Records section under Datasets.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n - Link to the report component of the underlying figures from which this figure was generated (Figure SPM.9)\r\n - Link to the SPM.9 catalogue record at CEDA"
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                "short_code": "ob",
                "title": "Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure TS.19 v20220923",
                "abstract": "Data for Figure TS.19 from the Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure TS.19 shows carbon sink response in a scenario with net carbon dioxide (CO2) removal from the atmosphere. \r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Arias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallée, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. Sörensson, S. Szopa, I. Takayabu, A.-M. Tréguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. 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. 33−144, doi:10.1017/9781009157896.002.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains data for 50-year periods during 2000-2300 for:\r\n \r\n - Atmospheric CO2 concentration\r\n - Net CO2 emissions (accumulated over 50 yer periods)\r\n - Net land flux (accumulated over 50 yer periods)\r\n - Net ocean flux (accumulated over 50 yer periods)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data file: Data_Figure_5_33.csv:\r\n \r\n - row 1: x-axis values.\r\n - row 2: light blue bars.\r\n - row 3: orange bars.\r\n - row 4: green bars.\r\n - row 5: blue bars\r\n - row 6: relates with the values written in black over the corresponding arrows (row 2 values plus values written in black)\r\n - row 7: Standard deviation over orange bars.\r\n - row 8: Standard deviation over green bars.\r\n - row 9: Standard deviation over blue bars.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n This figure was created in Excel and the error bars (standard deviation) were added in Adobe Illustrator.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Technical Summary)\r\n - Link to the report component of the underlying chapter figures from which this figure was generated (Chapter 5)\r\n - Link to the Supplementary Material for Chapter 5, which contains details on the input data used in Table 5.SM.6"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38242,
            "uuid": "05ca906615c4493a97f6eb0af416ce1c",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/ch6_fig20/v20220928",
            "numberOfFiles": 6,
            "volume": 188639,
            "fileFormat": "Data are csv formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38241,
                "uuid": "022d449b91eb453eb56228c17fdce725",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 6.20 (v20220928)",
                "abstract": "Data for Figure 6.20 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 6.20 shows projected changes in regional annual mean surface ozone (O3; ppb) from 2015 to 2100 in different shared socio-economic pathways (SSPs)\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Szopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figures 11 panels, with data provided for all panels in three files in the main directory.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains precomputed values of surface ozone concentrations across world regions for:\r\n - A 10-year mean period (2005 to 2014) from the historical simulation to represent present day regional mean values. Regional multi-model annual mean and standard deviation values are calculated across 5 different CMIP6 models\r\n - Annual multi-model mean values of surface ozone from 5 different CMIP6 models projected for 7 different future scenarios covering the period 2015 to 2100\r\n - Standard deviation values of surface ozone from 5 different CMIP6 models projected for 7 different future scenarios covering the period 2015 to 2100\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n All the data files provided are used to create the time series plots for each region. The numbers in each panel for each region are obtained from 'Surf_O3_data_05_14_mean_for_IPCC_figure_V1_5mods.csv', with the time series line for each scenario from 'Surf_O3_data_fut_mean_for_IPCC_figure_V1_5mods.csv' and the shading obtained by using the values in 'Surf_O3_SD_data_fut_mean_for_IPCC_figure_V1_5mods.csv'.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP stands for Shared Socioeconomic Pathway.\r\nppb stands for parts per billion.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The plotting code that is provided along with this dataset should just be able to read in each of the precomputed regional mean .csv files and then reproduce the time series figures. A link to the code archived on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n - Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 38245,
            "uuid": "40fe3b803d6a4066a3b6f8dc24de2f99",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_06/ch6_fig21/v20220928",
            "numberOfFiles": 6,
            "volume": 44000,
            "fileFormat": "Data are csv formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 38244,
                "uuid": "572c9744ddab47fc8a5b938c4a4f7387",
                "short_code": "ob",
                "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 6.21 (v20220928)",
                "abstract": "Data for Figure 6.21 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.21 shows future changes in regional five-year mean surface PM2.5 from 2015 to 2100 in different shared socio-economic pathways (SSPs).\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n 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:\r\n Szopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 11 panels with data provided for all panels in three files placed in the main directory.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains precomputed values of surface PM2.5 concentrations across world regions for:\r\n \r\n - A 10-year mean period (2005 to 2014) from the historical simulation to represent present day regional mean values. Regional multi-model annual mean and standard deviation values are calculated across 5 different CMIP6 models\r\n - Annual 5-year multi-model mean values of surface PM2.5 from 5 different CMIP6 models projected for 7 different future scenarios covering the period 2015 to 2100\r\n - Standard deviation values of surface PM2.5 from 5 different CMIP6 models projected for 7 different future scenarios covering 5-year mean periods from 2015 to 2100\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nPM2.5 refers to fine particulate matter air pollution with diameter of less than 2.5 microns.\r\nSSP stands for Shared Socioeconomic Pathway.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n All the data files provided are used to create the time series plots for each region. The numbers in each panel for each region are obtained from 'Surf_PM2pt5_data_05_14_mean_for_IPCC_figure_V1_5mods.csv', with the time series line for each scenario from 'Surf_PM2pt5_data_fut_mean_for_IPCC_figure_V1_5mods.csv' and the shading obtained by using the values in 'Surf_PM2pt5_SD_data_fut_mean_for_IPCC_figure_V1_5mods.csv'.\r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The plotting code that is provided along with this dataset should just be able to read in each of the precomputed regional mean .csv files and then reproduce the time series figures.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n - Link to the code for the figure, archived on Zenodo."
            },
            "onlineresource_set": []
        }
    ]
}