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  • This dataset collection contains air quality data from the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme 'Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)'.

  • Data for Figure 3.7 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.7 shows regression coefficients and corresponding attributable warming estimates for individual CMIP6 models. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains information on global temperature attributable warming (2010-2019 relative to 1850-1900) from CMIP6 models:  - Regression coefficients for two way regression (2010-2019 relative to 1850-1900) - Regression coefficients for three way regression (2010-2019 relative to 1850-1900) - Attributable warming for two way regression (2010-2019 relative to 1850-1900) - Attributable warming for three way regression (2010-2019 relative to 1850-1900) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/regression_coeff_two_way_regression.csv has data for brown and green crosses - panel_b/regression_coeff_three_way_regression.csv has data for grey, green and blue crosses - panel_c/attributable_warming_two_way_regression.csv has data for brown and green crosses - panel_d/attributable_warming_three_way_regression.csv has data for grey, green and blue crosses Details about the data provided in relation to the figure in the header of every file. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.

  • Data used in Climate Change 2001, the Third Assessment Report (TAR) of the United Nations Intergovernmental Panel on Climate Change (IPCC). Simulations of global climate models were run by various climate modelling groups coordinated by the World Climate Research Programme (WCRP) on behalf of the United Nations Intergovernmental Panel on Climate Change (IPCC). Climatology data calculated from global climate model simulations of experiments representative of Special Report on Emission Scenarios (SRES) scenarios: A1F, A1T, A1a, A2a, A2b, A2c, B1a, B2b. The climatologies are 30-year averages. Climate anomalies are expressed relative to the period 1961-1990. The monthly climatology data covers the period from 1961-2100. The climatologies are of global scope and are provided on latitude-longitude grids.

  • Input data for Figure 2.16 from Chapter 2 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 2.16 provides global precipitation minus evaporation trend maps and time series from a variety of data sources --------------------------------------------------- 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: Gulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels, with input data provided for all panels in the main directory --------------------------------------------------- List of data provided --------------------------------------------------- The datasets contains: - Global precipitation and evaporation data from ERA5 reanalysis - Time series of global, land-only and ocean-only average annual P–E (mm day–1) from the following reanalysis products: 20CRv3, ERA5, ERA20CM, MERRA, CFSR, ERA20C, JRA55 and MERRA2. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - Data files: IntermediateData_era5_evap_2.nc and era5_tp_2.nc Panel b: - Data file: GPME2.csv and GPME2.mat Panel c: - Data file: LPME2.csv and LPME2.mat Panel d: - Data file: OPME2.csv and OPME2.mat For panels b to d: I.     Column 2: orange solid line II.    Column 3: cyan solid line III.   Column 4: black solid line IV.   Column 5: grey solid line V.    Column 6: blue solid line VI.   Column 7: dark green solid line VII.  Column 8: brown solid line VIII. Column 9: green solid line 20CRv3 is the NOAA-CIRES-DOE Twentieth Century Reanalysis Version 3. ERA5 is a reanalysis of the global climate from 1950 to present, developed by ECMWF. ERA20CM is a twentieth century atmospheric model ensemble developed by ECMWF. MERRA stands for Modern-Era Retrospective analysis for Research and Applications. CFSR stands for Climate Forecast System Reanalysis. ERA20C is the first atmospheric reanalysis of the 20th century, from 1900-2010, developed by ECMWF. JRA55 stands for Japanese 55-year Reanalysis. MERRA2 stands for Modern-Era Retrospective analysis for Research and Applications, version 2. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Additional information to correctly reproduce the figure in the corresponding readme files for code archived on Zenodo (see the link to code provided in the Related Documents section of this catalogue record). --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Chapter 2) - Link to the Supplementary Material for Chapter 2, which contains details on the input data used in Table 2.SM.1 - Link to the code for the figure, archived on Zenodo.

  • Data for Figure 3.24 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.24 shows biases in zonal mean and equatorial sea surface temperature (SST) in CMIP5 and CMIP6 models. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has three panels (a), (b), (c), with data provided for all panels in subdirectories named panel_a, panel_b and panel_c. --------------------------------------------------- List of data provided --------------------------------------------------- The dataset contains sea surface temperature (SST) data (1979-1999):  - Modelled zonal mean SST biases from CMIP5 - Modelled zonal mean SST biases from CMIP6 - Modelled zonal mean SST biases from HighResMIP - Modelled equatorial SST biases from CMIP5 - Modelled equatorial SST biases from CMIP6 - Modelled equatorial SST biases from HighResMIP - Modelled mean equatorial SST from CMIP5 - Modelled mean equatorial SST from CMIP6 - Modelled mean equatorial SST from HighResMIP - Observed mean equatorial SST from HadISST v1 --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/zonal_sst_bias.csv has zonal mean sea surface temperature bias over the period 1979-1999, there are data for blue (CMIP5), red (CMIP6) and green (HighResMIP) shadings representing 5th and 95th percentile over ensemble - panel_b/equatorial_sst_bias.csv  has equatorial mean sea surface temperature bias over the period 1979-1999, there are data for blue (CMIP5), red (CMIP6) and green (HighResMIP) shadings representing 5th and 95th percentile over ensemble - panel_c/equatorial_sst_means.csv  has equatorial mean sea surface temperature over the period 1979-1999, there are data for black (HadISSTv1),  blue (CMIP5), red (CMIP6) and green (HighResMIP) shadings representing 5th and 95th percentile over ensemble Details about the data provided in relation to the figure in the header of every file. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- For equatorial SSTs and equatorial SST biases, the data has longitude coordinate which goes 20 to 380 degrees. It was done with python package iris not to break the lines through Atlantic. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the code for the figure, archived on Zenodo.

  • Data for Figure 3.28 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.28 shows long-term trends in halosteric and thermosteric sea level in CMIP6 models and observations. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has panels (a), (b), (c), (d), (e), (f), with data provided for all panels in subdirectories named panel_a, panel_b, panel_c, panel_d, panel_e and panel_f. --------------------------------------------------- List of data provided --------------------------------------------------- The datasets contains:  - Atlantic and Pacific halosteric sea level trend from CMIP6 models (1950-2014) - Atlantic and Pacific halosteric sea level trend from Durack&Wijffels observations (1950-2019) - Atlantic and Pacific halosteric sea level trend from EN4 observations (1950-2019) - Atlantic and Pacific halosteric sea level trend from Ishii observations (1955-2019) - Atlantic and Pacific thermosteric sea level trend from CMIP6 models (1950-2014) - Atlantic and Pacific thermosteric sea level trend from Durack&Wijffels observations (1950-2019) - Atlantic and Pacific thermosteric sea level trend from EN4 observations (1950-2019) - Atlantic and Pacific thermosteric sea level trend from Ishii observations (1955-2019) - Global halosteric sea level trends from Durack&Wijffels observations (1950-2019) - Global halosteric sea level trends from EN4 observations (1950-2019) - Global halosteric sea level trends from Ishii observations (1955-2019) - Global halosteric sea level trends from CMIP6 multi-model mean (1950-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/halosteric_trends_hist-nat.csv has data for green and black markers. - panel_a/halosteric_trends_historical.csv has data for orange and black markers. - panel_b/thermosteric_trends_hist-nat.csv has data for green and black markers. - panel_b/thermosteric_trends_historical.csv has data for orange and black markers. - panel_c/halosteric_trends_map_DW.nc has data for filled colored contours. - panel_d/halosteric_trends_map_EN4.nc has data for filled colored contours. - panel_e/halosteric_trends_map_Ishii.nc has data for filled colored contours. - panel_f/halosteric_trends_map_cmip6.nc has data for filled colored contours. For panels a and b details about the data provided in relation to the figure in the header of every file. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- The observational data from here (top right panel) is taken from the file: DurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc. The field of interest are salinity_mean (shown as black contours) and salinity_change (shown in colourscale). The file was archived as input data for Figure 2.27. The link to this dataset is provided in the Related Documents section of this catalogue record. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the input dataset for figure 3.28 - Link to the code for the figure, archived on Zenodo - Link to the figure on the IPCC AR6 website

  • Data for Figure 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. Sörensson, 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. 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. 1363–1512, 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 2081‒2100 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 2081‒2100 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 für Meteorologie, ESM - Earth System Model, Cordex – 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.

  • The Netatmo V1 dataset contains observations from all Public Weather Stations (PWS) contributing to the Netatmo database within Europe. Netatmo is a company that designs and manufactures a range of smart weather station instruments for the home. The dataset is for a single year (2020), made available for use within the EUMETNET Sandbox project. EUMETNET (a grouping of 31 European National Meteorological Services) instigated the EUMETNET Sandbox project to bring novel observations and observations from technology trials and field campaigns to the research community to enable R&D activities. The data are not quality controlled and are presented in the format provided by Netatmo. The data are provided in a single file per month per country*. The data were extracted from the Netatmo database country by country. The meteorological values are unchanged from those extracted from the Netatmo archive. For example, there is no Quality Control of the data, no calibration of the instruments and no unit conversions have been applied. The data were extracted from the Netatmo database by Netatmo operators of the Netatmo system. The data have not been manipulated to meet any international data format standards. For each station there is always a metadata file 'n'.metadata.json. There are up to 4 data files associated with each station represented by a metadata file. In some cases, all 4 data files are present for the station. In other cases, only one data file is present. The 'n' in the file name allows the metadata file to be associated with the meteorological data files 1. n.pressure.historic.csv - surface pressure for station n 2. n.outdoor.historic.csv - Contains air temperature and humidity for station n 3. n.wind.historic.csv - Contains wind and gust data for station n 4. n.rain.historic.csv - rainfall data for station n The data files are semi-colon separated and use UNIX epoch time *Countries present in the Netatmo dataset Austria, Spain, Iceland, Norway, Belgium, Finland, Italy, Poland, Switzerland, France, Luxembourg, Portugal, Cyprus, United Kingdom, Latvia, Serbia, Czech Republic, Greece, Montenegro, Sweden, Germany, Croatia, North Macedonia, Slovenia, Denmark, Hungary, Malta, Slovakia, Estonia, Ireland and the Netherlands

  • Data for Figure 3.13 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.13 shows annual-mean precipitation rate (mm day-1) for the period 1995-2014. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has six panels, with data provided for four panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Global modelled annual-mean precipitation (mm/day) of CMIP6 for the period 1995–2014 - Global bias of modelled annual-mean precipitation (mm/day) of CMIP6 for the period 1995–2014 to GPCP - Global root mean square bias of modelled precipitation (mm/day) of CMIP6 for the period 1995–2014 to GPCP - Global bias of modelled annual-mean precipitation (mm/day) of CMIP5 for the period 1985–2004 to GPCP GPCP is the Global Precipitation Climatology Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/fig_3_13_a.nc - panel_b/fig_3_13_b.nc - panel_c/fig_3_13_c.nc - panel_d/fig_3_13_d.nc --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.

  • Data for Figure 3.17 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.17 shows observed and simulated global monsoon domain, intensity, and circulation.  --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels, with data provided for all panels in a single file.   --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains - Observed and simulated global monsoon domain and summer minus winter precipitation and 850hPa wind velocity - Global land monsoon precipitation index and Northern Hemisphere summer monsoon circulation index. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- All data are given in global_monsoon.nc file. Panel a: - uRef & vRef: vector - prRef: shading - domainRef: domain (1 = monsoon, 0 = not monsoon) Panel b: - uMME & vMME: vector - prMME: shading - domainMME: monsoon domain (1 = monsoon, 0 = not monsoon) Panel c: - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip6: red curve and shading - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip5: blue curve and shading - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_amip: yellow curve and shading - GMprecip_CMAP: black dotted curve - GMprecip_CRU-TS: black solid curve - GMprecip_GPCC: black dashed-dotted curve - GMprecip_GPCP-SG: black dashed curve Panel d: - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip6: red curve and shading - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip5: blue curve and shading - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_amip: yellow curve and shading - Max-min range of NHMcirc_20CRv3: grey hatching - NHMcirc_ERA-20C: black dash-dotted curve - NHMcirc_ERA5: black solid curve - NHMcirc_JRA-55: dashed curve - NHMcirc_MERRA2: dotted curve --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means and percentiles are calculated after weighting individual members with the inverse of the ensemble size of the same model, which is given as the weight attribute of each variable. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains supporting information on the figure in Section and details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.