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Version: 0.0.1 | Published: 13 Jun 2023 | Updated: 716 days ago

Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.19 (v20220622)

Dataset

Summary

Citation:
Jury, M.; Turner, A., 2023, Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.19 (v20220622), NERC EDS Centre for Environmental Data Analysis, https://dx.doi.org/10.5285/e79aab21bf644e61bf5dacd02199daa3

Documentation

Description:
Data for Figure 10.19 from Chapter 10 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 10.19 shows¬†changes in the Indian summer monsoon in the historical and future periods. --------------------------------------------------- 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: Doblas-Reyes, F.J., A.A. S??rensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate 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. P?©an, 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. Yelek?ßi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1363‚Äì1512, doi:10.1017/9781009157896.012. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has 6 subpanels. Data for all subpanels is provided. --------------------------------------------------- List of data provided --------------------------------------------------- The dataset contains: APHRODITE station density for June-September (JJAS) 1956 Precipitation June-September (JJAS): - Model mean bias 1985-2010 - Observed and modelled trends: CRU TS 1950-2000, CMIP6 hist-GHG & hist-aer 1950-2000, and CMIP6 SSP5-8.5 2015-2100 trends - Observed and model relative anomalies over 1950-2100 with respect to 1995-2014 averages over central India (lon: 76¬?E-87¬?E, lat: 20¬?N-28¬?N) - Modelled change until 2081‚Äí2100 with¬†respect to 1995-2014 averages over central India (lon: 76¬?E-87¬?E, lat: 20¬?N-28¬?N) - Trends in relative precipitation anomalies (baseline 1995-2014) over past (1950-2000) and future (2015-2100) period over central India (lon: 76¬?E-87¬?E, lat: 20¬?N-28¬?N). - Trend difference between the 3 MPI-ESM runs with the lowest and the 3 MPI-ESM runs with the highest trend --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel (a): APHRODITE station density for JJAS 1956: - Data file: Fig_10_19_panel-a_mapplot_APHRODITE_stationdensity_single_mean.nc Panel (b): CMIP6 mean precipitation bias June-September mean 1985-2010 mean with respect to CRU TS: - Data file: Fig_10_19_panel-b_mapplot_pr_cmip6_bias_pr_cmip6_maps_past_bias_MultiModelMean_bias.nc Panel (c): OLS linear precipitation for June-September mean trend of CRU TS 1950-2000 (top left), CMIP6 hist-GHG (bottom left) & hist-aer (bottom right) 1950-2000, and CMIP6 SSP5-8.5 2015-2100 (top right): - Data files: Fig_10_19_panel-c_mapplot_pr_cmip6_mean_trend_future_pr_cmip6_maps_trend_future_MultiModelMean_trend.nc, Fig_10_19_panel-c_mapplot_pr_histaer_mean_trend_past_pr_aer_maps_trend_past_MultiModelMean_trend.nc, Fig_10_19_panel-c_mapplot_pr_histghg_mean_trend_past_pr_ghg_maps_trend_past_MultiModelMean_trend.nc, Fig_10_19_panel-c_mapplot_pr_obs_mean_trend_past_CRU_single_trend.nc; Panel (d): Observed and model relative precipitation¬†June-September mean anomalies over 1950-2100 in respect to 1995-2014 averages over central India (lon: 76¬?E-87¬?E, lat: 20¬?N-28¬?N) (CRU TS (brown), GPCC (dark blue), REGEN (green), APHRO-MA (light brown), IITM all-India rainfall (light blue), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink), CMIP6 hist-aer (grey), hist-GHG (light blue) CMIP6 historical/SSP5-8.5 (dark red) and CMIP5 historical/RCP8.5 (dark blue) and Modelled change until 2081‚Äí2100 in respect to 1995-2014 averages over central India (CMIP6 SSP5-8.5 (dark red) and CMIP5 historical/RCP8.5 (dark blue)): - Data files: Fig_10_19_panel-d_timeseries.csv, Fig_10_19_panel-d_boxplot.csv Panel (e): OLS linear trends in relative precipitation June-September mean anomalies (baseline 1995-2014) over past (1950-2000) and future (2015-2100) period over central India (lon: 76¬?E-87¬?E, lat: 20¬?N-28¬?N) of observations (GPCC, CRU TS, REGEN and APRHO-MA: black crosses) and models (individual members of CMIP5 historical-RCP8.5 (blue), CMIP6 historical-SSP5-8.5 (dark red), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink circles), CMIP6 hist-GHG (blue triangles), CMIP6 hist-aer (grey triangles)), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading): - Data file: Fig_10_19_panel-e_trends.csv Panel (f): June-September mean 2016-2045 OLS linear trend difference in precipitation between the 3 MPI-ESM runs with the lowest and the 3 MPI-ESM runs with the highest trend: - Data file: Fig_10_19_panel-f_mapplot_pr_mpige_mean_trend_future_spread_single_trend-difference-min3-max3.nc Acronyms: CMIP - Coupled Model Intercomparison Project, APHRODITE - ASIAN PRECIPITATION - HIGHLY-RESOLVED OBSERVATIONAL DATA INTEGRATION TOWARDS EVALUATION OF WATER RESOURCES, CRU TS- Climatic Research Unit Time Series, GHG - Greenhouse gas, IITM - Indian Institute of Technology Madras, RCP - Representative Concentration Pathway, DAIMP - Detection and Attribution Model Intercomparison Project, SSP - Shared Socioeconomic Pathways, GPCC - GLOBAL PRECIPITATION CLIMATOLOGY CENTRE, REGEN - Rainfall Estimates on a Gridded Network, S MILEs -single model initial-condition large ensembles, d4PDF - Database for Policy Decision-Making for Future Climate Change, MIROC - Model for Interdisciplinary Research on Climate, MPI - Max-Planck-Institut f?ºr Meteorologie, ESM - Earth System Model, Cordex ‚Äì Coordinated Regional Climate Downscaling Experiment, OLS - ordinary least squares regression. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- The code for ESMValTool is provided. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Chapter 10) - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11 - Link to the code for the figure, archived on Zenodo.
Is Part Of:
IPCC (AR6) Chapter 10: Linking global to regional climate change

Coverage

Spatial Coverage:
India
Start Date:
01 January 1950
End Date:
31 December 2100

Geographic Bounding Box

Lower Left Latitude:
-5
Lower Left Longitude:
60
Upper Right Latitude:
35
Upper Right Longitude:
100

Provenance

Source:
Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI). Data files converted to BADC-CSV format by CEDA staff. Data curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).

Accessibility

Access

Access Service:
This data is publicly avaliable for download. When using these data you must cite them correctly using the citation given on the Data Catalogue record.
Format:
  • txt
  • netCDF
  • csv
Language:
en