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)'.

The NIWA-UKCA2 model contribution to the CCMI-2022 set of experiments defined by the SPARC- and IGAC-supported Chemistry-Climate Model Initiative. The CCMI-2022 set of model experiments focus on the stratosphere, with the goals of providing updated projections of the future evolution of ozone and improving our understanding of chemistry-climate interactions and how they are represented in models. The NIWA-UKCA2 chemistry-climate model is run by the modelling team at NIWA (National Institute of Water and Atmospheric Research) in New Zealand and configured to follow forcings as laid out in the CCMI2022 founding document (Plummer et al., 2021) SPARC and IGAC projects coordinate international research in atmospheric chemistry. SPARC (Stratosphere-troposphere Processes And their Role in Climate) is a core project of the World Climate Research Programme (WCRP). IGAC is the International Global Atmospheric Chemistry which currently operates under the umbrella of Future Earth.

Data for the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). When using the datasets from this collection please use the citation indicated on each individual specific dataset, rather than the citation for the entire collection. Figure datasets related to this collection: - data for Figure SPM.1 - data for Figure SPM.2 - data for Figure SPM.3 - data for Figure SPM.4 - data for Figure SPM.5 - data for Figure SPM.6 - data for Figure SPM.7 - data for Figure SPM.8 - data for Figure SPM.9 - data for Figure SPM.10

The aim of the EUMETNET Sandbox is to bring novel observations and observations from technology trials and field campaigns to the research community to enable R&D activities. The first datasets to be made available on the Sandbox are two datasets from Personal Weather Stations (PWS) provided by Netatmo and WOW. These datasets are historical archives for a single year (2020) to support development of quality control tools and other activities carried out by EUMETNET Members and ECMWF. The Netatmo and WOW Datasets contain land surface observations, usually from weather stations located in the gardens of the public. The data are not quality controlled prior to being made available in the CEDA Archive. The datasets are stored in the format and resolution provided by the Met Office (for WOW data) and Netatmo. The WOW data are stored in a csv format with a single file per month. The files contain the data from all WOW stations within Europe. The Netatmo data are stored in tar/zip files, one file per country per month.

This collection contains data from the ForestScan project which investigated novel technologies such as Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle-based Laser Scanning (UAV-LS) to complement manual plot based measurements of AGB by collecting and analysing such data for three tropical sites in French Guiana (Paracou), Gabon (Lopé) and Malayisa (Sepilok). In addition at each of these sites airborne laser scanning data is available. The specific objectives of the study are (i) the development of a protocol for acquiring such measurements in tropical forests; (ii) analysing scaling properties of forest structure in tropical forests and (iii) high precision limited area measurement (plot census, TLS and UAV-LS) with wide area airborne laser scanning. Ultimately this effort will support the systematic collection and understanding of reference data for biomass product validation as required for the CEOS Good Practices Guideline

This dataset collection contains datasets relating to the figures found in the IPCC Sixth Assessment Report (AR6) Chapter 3: Human influence on the climate system. When using datasets from this collection please use the citation indicated in each specific dataset rather than the citation for the entire collection. Figure datasets related to this collection: - data for Figure 3.2 - data for Figure 3.3 - data for Figure 3.4 - data for Figure 3.5 - data for Figure 3.6 - data for Figure 3.7 - data for Figure 3.8 - data for Figure 3.9 - data for Figure 3.10 - data for Figure 3.11 - data for Figure 3.12 - data for Figure 3.13 - data for Figure 3.14 - data for Figure 3.15 - data for Figure 3.16 - data for Figure 3.17 - data for Figure 3.18 - data for Figure 3.19 - data for Figure 3.20 - data for Figure 3.21 - data for Figure 3.22 - data for Figure 3.23 - data for Figure 3.24 - data for Figure 3.25 - data for Figure 3.26 - data for Figure 3.27 - input data for Figure 3.27 - data for Figure 3.28 - input data for Figure 3.28 - data for Figure 3.29 - data for Figure 3.30 - data for Figure 3.31 - data for Figure 3.32 - data for Figure 3.33 - data for Figure 3.34 - data for Figure 3.35 - data for Figure 3.36 - data for Figure 3.37 - data for Figure 3.38 - data for Figure 3.39 - data for Figure 3.40 - data for Figure 3.41 - data for Figure 3.42 - data for Figure 3.43 - data for Figure 3.44 - data for Cross-Chapter Box 3.1.1 - data for Cross-Chapter Box 3.2.1 - data for FAQ 3.1, Figure 1 - data for FAQ 3.2., Figure 1 - data for FAQ 3.3, Figure 1

Data for Figure 3.31 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.31 shows evaluation of historical emission-driven CMIP6 simulations for 1850-2014. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Observed and simulated change in global mean atmospheric CO2 concentration (1850-2014) - Observed and simulated air surface temperature anomaly (1850-2014) - Observed and simulated change in land carbon uptake (1850-2014) - Observed and simulated change in ocean carbon uptake (1850-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- panel_a/fig_3_31_panel_a.nc: - dim0 = 0: 'ACCESS-ESM1-5 ', (turquoise solid line), Australian Community Climate and Earth System Simulator - Earth System Model - dim0 = 1: 'CNRM-ESM2-1', (light green solid line), National Centre for Meteorological Research - dim0 = 2: 'CanESM5-CanOE ', (orange solid line), Canadian Earth System Model - Canadian Ocean Ecosystem model - dim0 = 3: 'CanESM5', (dark green solid line). - dim0 = 4: 'MIROC-ES2L', (light purple solid line), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and Centre for Climate System Research / National Institute for Environmental Studies, Japan. - dim0 = 5: 'MPI-ESM1-2-LR ', (teal solid line), Max Planck Institute Earth System Model - dim0 = 6: 'MRI-ESM2-0', (lime solid line), Meteorological Research Institute of the Japan Meteorological Agency - dim0 = 7: 'NorESM2-LM', (pink solid line), The Norwegian Earth System Model - dim0 = 8: 'UKESM1-0-LL', (dark purple solid line), UK Earth System Model - dim0 = 9: 'MultiModelMean', (red solid line). - dim0 = 10: 'ESRL' (OBS), (black solid line). panel_b/fig_3_31_panel_b.nc - dim0_0 = 0: 'ACCESS-ESM1-5', - dim0_0 = 1: 'ACCESS-ESM1-5_historical'. - dim0_0 = 2: 'CNRM-ESM2-1'. - dim0_0 = 3: 'CNRM-ESM2-1_historical'. - dim0_0 = 4: 'CanESM5-CanOE '. - dim0_0 = 5: 'CanESM5-CanOE_historical'. - dim0_0 = 6: 'CanESM5'. - dim0_0 = 7: 'CanESM5_historical'. - dim0_0 = 8: 'MIROC-ES2L'. - dim0_0 = 9: 'MIROC-ES2L_historical'. - dim0_0 = 10: 'MPI-ESM1-2-LR '. - dim0_0 = 11: 'MPI-ESM1-2-LR_historical '. - dim0_0 = 12: 'MRI-ESM2-0'. - dim0_0 = 13: 'MRI-ESM2-0_historical'. - dim0_0 = 14: 'NorESM2-LM'. - dim0_0 = 15: 'NorESM2-LM_historical'. - dim0_0 = 16: 'UKESM1-0-LL'. - dim0_0 = 17: 'UKESM1-0-LL_historical'. - dim0_0 = 18: 'HadCRUT5' (OBS), Met Office Hadley Centre panel_c/fig_3_31_panel_c.nc - dim0 = 0: 'ACCESS-ESM1-5 '. - dim0 = 1: 'CNRM-ESM2-1'. - dim0 = 2: 'CanESM5-CanOE '. - dim0 = 3: 'CanESM5'. - dim0 = 4: 'MIROC-ES2L'. - dim0 = 5: 'MPI-ESM1-2-LR '. - dim0 = 6: 'MRI-ESM2-0'. - dim0 = 7: 'NorESM2-LM'. - dim0 = 8: 'UKESM1-0-LL'. - dim0 = 9: 'MultiModelMean'. - dim0 = 10: 'GCP' (OBS), Global Carbon Project (GCP) panel_d/fig_3_31_panel_d.nc - dim0 = 0: 'ACCESS-ESM1-5 '. - dim0 = 1: 'CNRM-ESM2-1'. - dim0 = 2: 'CanESM5-CanOE '. - dim0 = 3: 'CanESM5'. - dim0 = 4: 'MIROC-ES2L'. - dim0 = 5: 'MPI-ESM1-2-LR '. - dim0 = 6: 'MRI-ESM2-0'. - dim0 = 7: 'NorESM2-LM'. - dim0 = 8: 'UKESM1-0-LL'. - dim0 = 9: 'MultiModelMean'. - dim0 = 10: 'GCP' (OBS). Labels and colors for all figures are the same as for panel a. Historical values in panel b are plotted with the same colors as the corresponding simulation, but using dotted lines. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo - Link to the figure on the IPCC AR6 website

Data for Figure 3.4 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.4 shows observed and simulated time series of the anomalies in annual and global mean near-surface air temperature (GSAT).  --------------------------------------------------- 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 two panels, with data provided for all panels in subdirectories named panel_a and panel_b. --------------------------------------------------- List of data provided --------------------------------------------------- Observed and simulated global near-surface air temperature change (1850-2014) with uncertainty range for simulated time series. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- panel_a/fig_3_4_panel_a.nc - black line: model = 60 - red line: model = 59 - colored lines: model = 0, 1, ..., 58 panel_b/tsline_collect_tasa.nc: - red line: experiment = 0, stat = 0 - blue line: experiment = 1, stat = 0 - red shaded region: experiment = 0, stat = 1 and stat = 2 - blue shaded region: experiment = 1, stat = 1 and stat = 2 panel_b/tsline_collect_tasa_ref.nc - HadCRUT5: dataset = 0 - BerkleyEarth: dataset = 1 - NOAAGlobalTemp-Interim: dataset = 2 - Kadow: dataset =3 Where HadCRUT5, BerkleyEarth, NOAAGlobalTemp-Interim, and Kadow are gridded datasets of global historical surface temperature. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1

Data for Cross-Chapter Box 3.2, Figure 1 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Cross-Chapter Box 3.2, Figure 1 shows a comparison of observed and simulated changes in global mean temperature and precipitation extremes.  --------------------------------------------------- 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 --------------------------------------------------- Technically the figure has four panels, but since they are not marked all the data is in the parent directory. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Global annual maximum daily maximum daily maximum temperature (TXx) anomalies from 1953 to 2017 relative to 1961-1990 from HadEX3 observations and CMIP5 and CMIP6 models (human and natural forcings simulations) - Global annual maximum daily maximum daily maximum temperature (TXx) anomalies from 1953 to 2017 relative to 1961-1990 from HadEX3 observations and CMIP5 and CMIP6 models (natural forcings simulations) - Global annual maximum 1-day precipitation (rx1day) anomalies from 1953 to 2017  relative to 1961-1990 from HadEX3 observations and CMIP5 and CMIP6 models (natural forcing only simulations) - Global annual maximum 1-day precipitation (rx1day) anomalies from 1953 to 2017 relative to 1961-1990 from HadEX3 observations and CMIP5 and CMIP6 models (human and natural forcings simulations) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - txx_anomalies_timeseries_historical.csv has data for the blue (CMIP5), red (CMIP6) and black (HadEX3) lines as well as blue and red shadings showing TXx anomalies (top left panel) - txx_anomalies_timeseries_natural has data for the blue (CMIP5), red (CMIP6) and black (HadEX3) lines as well as blue and red shadings showing TXx anomalies  (bottom left panel) - rx1day_anomalies_timeseries_historical has data for the blue (CMIP5), red (CMIP6) and black (HadEX3) lines as well as blue and red shadings showing Rx1day anomalies   (top right panel) - rx1day_anomalies_timeseries_natural has data for the blue (CMIP5), red (CMIP6) and black (HadEX3) lines as well as blue and red shadings showing Rx1day anomalies  (bottom right panel) CMIP5 is the fifth phase of the Coupled Model Intercomparion Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid covering 1901-2018. --------------------------------------------------- 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 3.38 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.38 shows model evaluation of ENSO teleconnection for 2m-temperature and precipitation in boreal winter (December-January-February). --------------------------------------------------- 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 --------------------------------------------------- Data provided for all panels in one single directory --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains observed global patterns for: - temperature from the Berkeley Earth dataset over land - temperature from ERSSTv5 over ocean - precipitation from GPCC over land (shading, mm day–1) - precipitation from GPCP worldwide (contours, period: 1979-2014) and distributions of regression coefficients in IPCC regions for: - temperature - precipitation --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- maps: - reg_tas_NINO34_BEST_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over land) - reg_sst_NINO34_ERSSTv5_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over ocean) - reg_precip_NINO34_GPCP_ERSST5_1979_2018_DJF.nc (var = 'rc', lower map, contours) - reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc (var = 'rc', lower map, shading) histograms: - tas_enso_regression_pdf_v4_no_cosweight_DJF.nc . upper grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - tas_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dashed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for temperature: 'EAU/RFE/RAR/NWN/NCA/ENA/NSA/MED/NWS/ESAF' (see variable region_info with attributes making the association between the region index and the acronym/name). - pr_enso_regression_pdf_v4_no_cosweight_DJF.nc . lower grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - pr_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dahsed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for precipitation: 'EAS/SEA/EAU/WNA/NCA/SES/NSA/ESAF/SEAF/MED' (see variable info_region with attributes making the association between the region index and the acronym/name). ENSO is the El Niño Southern Oscillation. GPCC is the Global Precipitation Climatology Centre. GPCP is the Global Precipitation Climatology Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Data provided in reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc are in mm/month. Values should be divided by 30 for plotting in mm/day. --------------------------------------------------- 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 figure on the IPCC AR6 website