DOI: 10.5285/e046adc115b04395937e793c9f3dbcb1
title: Technical Summary of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure TS.12 (v20230301)

description: Input data for Figure TS.12 from the Technical Summary of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure TS.12 shows land-related changes relative to the 1850-1900 as a function of global warming levels. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: 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. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has six panels, with input data provided for all panels in subdirectories named Extremes, ModelSnow/sncbin and WaterCyclePanels. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Relative frequency and intensity changes of 1-in-10- and 1-in-50-year extreme daily heat (TXx) in CMIP6 models (ScenarioMIP) with respect to 1850-1900. Medians and 5, 17, 83, 95 percentiles. - Relative frequency and intensity changes of 1-in-10- and 1-in-50-year extreme daily precipitation rates (Rx1day) in CMIP6 models (ScenarioMIP) with respect to 1850-1900. Medians and 5, 17, 83, 95 percentiles. - Relative frequency and intensity changes of 1-in-10-year drought events in CMIP6 models (ScenarioMIP) with respect to 1850-1900. Medians and 5, 17, 83, 95 percentiles. - Monthly NH snow cover extent changes (in %), dependent on the GWL (with respect to 1850-1900), for CMIP6 models (historical + ScenarioMIP), with respect to snow cover extent at 0°C GWL (1850-1900) - Average precipitable water (annual mean), precipitation rate (annual mean + interannual variability), and runoff (annual mean + interannual variability) over tropical land (|latitude|&lt;30°), in the CMIP6 models that reach +5°C GWL in SSP5-8.5. - Average precipitable water (annual mean), precipitation rate (annual mean + interannual variability), and runoff (annual mean + interannual variability) over tropical land (|latitude|&gt;30°), in the CMIP6 models that reach +5°C GWL in SSP5-8.5. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - Data file: Extremes/TXx_freq_change_10_year_event.csv; relates to the orange clock symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/TXx_intens_change_10_year_event.csv; relates to the orange thermometer symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/TXx_freq_change_50_year_event.csv; relates to the brown clock symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/TXx_intens_change_50_year_event.csv; relates to the brown thermometer symbols and small orange 3-pronged symbols above and below. Panel b: - Data file: Extremes/Rx1day _freq_change_10_year_event.csv; relates to the orange clock symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/Rx1day _intens_change_10_year_event.csv; relates to the orange rain cloud symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/Rx1day _freq_change_50_year_event.csv; relates to the brown clock symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/Rx1day _intens_change_50_year_event.csv; relates to the brown rain cloud symbols and small orange 3-pronged symbols above and below. Panel c: - Data file: Extremes/drought _freq_change_10_year_event.csv; relates to the orange clock symbols and small orange 3-pronged symbols above and below. - Data file: Extremes/drought _intens_change_10_year_event.csv; relates to the orange drop symbols and small orange 3-pronged symbols above and below. Panel d: Data files: ModelSnow/sncbin/sncbin_{model}_historical_ssp{xyy}.nc. For each model and scenario, these files contain a table that gives the snow cover extent changes for each month of the year and for 0.2°C-wide temperature bins. The colours represent the 5 scenarios (see legend, standard IPCC scenario colour code). Each dot represents one GWL (0.2°C bins) for one model and one scenario. The linear multi-model regression lines are coloured dependent on the scenario they represent. The filenames have been changed from the GitHub for archival with '_ssp' in the filename replacing the original '+ssp'.For example, file 'sncbin_BCC-CSM2-MR_historical_ssp126.nc' is named 'sncbin_BCC-CSM2-MR_historical+ssp126.nc' on GitHub. This needs to be changed back when plotting with the code or amended in the code. Panel e: - Data files: WaterCyclePanels/Hydro_vars_change_20210201_derived_tropic.json. Multi-model mean precipitable water, precipitation, and runoff (annual mean and interannual variability (standard deviation)). Left part of the panel: * Black full line: Precipitable water, annual mean, multi-model mean * Brown full line: Runoff, annual mean, multi-model mean * Brown dashed line: Runoff, interannual variability, multi-model mean * Blue full line: Precipitation, annual mean, multi-model mean * Blue dashed line: Precipitation, interannual variability, multi-model mean Right part of the panel: 17-83% inter-model ranges for the +5°C GWL. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- This figure is plotted using python scripts which are archived on Zenodo at the link provided in the 'Related Documents' section of this catalogue record. A link to the GitHub repository for this figure is also provided. Please note that the filenames of the net-cdf files in ModelSnow/ have been changed from '+ssp' to '_ssp' which also needs to be amended in the code when running with these input files. Panel a: The Python script Extremes/TS2-Land-Extremes-202110.py reads the csv data sheets and plots the panel. Panel b: The Python script Extremes/TS2-Land-Extremes-202110.py reads the csv data sheets and plots the panel. Panel c: The Python script Extremes/TS2-Land-Extremes-202110.py reads the csv data sheets and plots the panel. Panel d: The Python script ModelSnow/AR6TS2-Snow.py reads the net-cdf data and plots the panel. Panel e: The Python script WaterCyclePanels/TS12-WaterCycle.py reads the json data sheets and plots the panel. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Technical Summary) - Link to the code for the figure, archived on Zenodo - Link to the TS_Fig12 GitHub repository