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 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.

Data for Figure 3.41 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.41 is a summary figure showing simulated and observed changes in key large-scale indicators of climate change across the climate system, for continental, ocean basin and larger scales.  --------------------------------------------------- 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 data of each panel is provided in a single file. --------------------------------------------------- List of data provided --------------------------------------------------- This datasets contains global and regional anomaly time-series for: - near-surface air temperature (1850-2020) - precipitation (1950-2014) - sea ice extent (1979-2014) - ocean heat content (1850-2014) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- near-surface air temperature (tas) -fig_3_41_tas_global.nc, fig_3_41_tas_land.nc, fig_3_41_tas_north_america.nc, fig_3_41_tas_central_south_america.nc, fig_3_41_tas_europe_north_africa.nc, fig_3_41_tas_africa.nc, fig_3_41_tas_asia.nc, fig_3_41_tas_australasia.nc, fig_3_41_tas_antarctic.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 4, stat = 0 (mean) ocean heat content (ohc) -fig_3_41_ohc_global.nc: brown line: ncl5 = 0, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile) green line: ncl5 = 1, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile) black line: ncl5 = 2, ncl6 = 0 (mean) precipitation (pr) -fig_3_41_pr_60N_90N.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 2, stat = 0 (mean) sea ice extent (siconc) -fig_3_41_siconc_nh.nc, fig_3_41_siconc_sh.nc: brown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) green line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile) black line: exp = 2, stat = 0 (mean) The ensemble spread (shaded regions) of CMIP6 data shown in figure 3.41 are the mean, 5th and 95th percentiles. The in-file metadata labels the same ensemble spread with mean, min and max. --------------------------------------------------- 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 3.25 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.25 shows CMIP6 potential temperature and salinity biases for the global ocean, Atlantic, Pacific and Indian Oceans. --------------------------------------------------- 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 --------------------------------------------------- There are panels (a), (b), (c), (d), (e), (f), (g), (h). The data is in respective subdirectories. --------------------------------------------------- List of data provided --------------------------------------------------- The dataset contains modelled and observational ocean data (1981-2010) for different ocean basins (global, Atlantic, Pacific, Indian):  - Potential temperature from WOA18 observations - Salinity from WOA18 observations - Potential temperature bias (CMIP6 - WOA18) - Salinity bias (CMIP6 - WOA18) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a - panel_a/potential_temperature_bias_global_panel_a.nc: data for colored filled contours showing temperature bias from 1981 to 2010 - panel_a/WOA_potential_temperature_global_panel_a.nc: data for black contours showing WOA18 temperature from 1981 to 2010 Panel b - panel_b/salinity_bias_global_panel_b.nc:  data for colored filled contours showing salinity bias from 1981 to 2010 - panel_b/WOA_salinity_global_panel_b.nc: data for black contours showing WOA18 salinity from 1981 to 2010 Panel c - panel_c/potential_temperature_bias_atlantic_panel_c.nc: data for colored filled contours showing temperature bias from 1981 to 2010 - panel_c/WOA_potential_temperature_atlantic_panel_c.nc: data for black contours showing WOA18 temperature from 1981 to 2010 Panel d - panel_d/salinity_bias_atlantic_panel_d.nc: data for colored filled contours showing salinity bias from 1981 to 2010 - panel_d/WOA_salinity_atlantic_panel_d.nc: data for black contours showing WOA18 salinity from 1981 to 2010 Panel e - panel_e/potential_temperature_bias_pacific_panel_e.nc: data for colored filled contours showing temperature bias from 1981 to 2010 - panel_e/WOA_potential_temperature_pacific_panel_e.nc:  data for black contours showing WOA18 temperature from 1981 to 2010 Panel f - panel_f/salinity_bias_pacific_panel_f.nc: data for colored filled contours showing salinity bias from 1981 to 2010 - panel_f/WOA_salinity_pacific_panel_f.nc:  data for black contours showing WOA18 salinity from 1981 to 2010 Panel g - panel_g/potential_temperature_bias_indian_panel_g.nc: data for colored filled contours showing temperature bias from 1981 to 2010 - panel_g/WOA_potential_temperature_indian_panel_g.nc:  data for black contours showing WOA18 temperature from 1981 to 2010 Panel h - panel_h/salinity_bias_indian_panel_h.nc: data for colored filled contours showing salinity bias from 1981 to 2010 - panel_h/WOA_salinity_indian_panel_h.nc:  data for black contours showing WOA18 salinity from 1981 to 2010 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.

Data for Figure 10.6 from Chapter 10 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 10.6 is an illustration of some model biases in simulations performed with dynamical 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: 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 two panels ((a) and (b)), which are further divided into 6 maps and 1 boxplot. Data is provided for all subpanels. --------------------------------------------------- List of data provided --------------------------------------------------- Boxplot data point is annual summer mean (JJA) surface air temperature (panel (a)) and precipitation (panel (b)) for western Mediterranean mean (lon: 10°W-10°E, lat: 33°N-45°N) between 1986 and 2005 for: - Observational datasets - Each model of CMIP5, CMIP6, HighResMIP, EURO-CORDEX 11 and EURO-CORDEX 44 Mapplot data is mean (1986-2005) annual summer mean (JJA) surface air temperature (panel (a)) and precipitation (panel (b)) for the western Mediterranean (lon: 15°W-15°E, lat: 28°N-50°N) regrided on a 1°x1° regular grid for: - Absolute values for reference observational dataset (BerkeleyEarth (a), CRU TS (b)) - Ensemble biases of CMIP5, CMIP6, HighResMIP, EURO-CORDEX 11 and EURO-CORDEX 44 --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel (a): - Data file: Observed (Berkeley Earth) mean (1986-2005) annual summer mean (JJA) surface air temperature over the western Mediterranean (top left): Fig_10_6_panel-a_mapplot_tas_obs_single_single_mean.nc - Data files: Ensemble mean (1986-2005) annual summer mean (JJA) surface air temperature bias over the western Mediterranean (top right): Fig_10_6_panel-a_mapplot_tas_bias_cmip5_tas_cmip5_map_MultiModelMean_bias.nc, Fig_10_6_panel-a_mapplot_tas_bias_cmip6_tas_cmip6_map_MultiModelMean_bias.nc, Fig_10_6_panel-a_mapplot_tas_bias_hrmip_tas_hrmip_map_MultiModelMean_bias.nc, Fig_10_6_panel-a_mapplot_tas_bias_cdx44_tas_cdx44_map_MultiModelMean_bias.nc, Fig_10_6_panel-a_mapplot_tas_bias_cdx11_tas_cdx11_map_MultiModelMean_bias.nc - Data file: Observed (black boxplots), reanalysis (black boxplots) and modelled (CMIP5: blue boxplots, CMIP6: red boxplots, HighResMIP: orange boxplots, CORDEX EUR-44: light blue boxplots, CORDEX EUR-11: green boxplots) annual summer mean (JJA) surface air temperature values (i.e. underlying data points of the boxplot) over the western Mediterranean (bottom part): Fig_10_6_panel-a_boxplot.csv Panel (b): - Data file: Observed (CRU TS) mean (1986-2005) annual summer mean (JJA) precipitation rate over the western Mediterranean (top left): Fig_10_6_panel-b_mapplot_pr_obs_single_masked_cru_single_mean.nc - Data files: Ensemble mean (1986-2005) annual summer mean (JJA) precipitation rate bias over the western Mediterranean (top right): Fig_10_6_panel-b_mapplot_pr_bias_cmip5_pr_cmip5_map_MultiModelMean_bias.nc, Fig_10_6_panel-b_mapplot_pr_bias_cmip6_pr_cmip6_map_MultiModelMean_bias.nc, Fig_10_6_panel-b_mapplot_pr_bias_hrmip_pr_hrmip_map_MultiModelMean_bias.nc,  Fig_10_6_panel-b_mapplot_pr_bias_cdx44_pr_cdx44_map_MultiModelMean_bias.nc, Fig_10_6_panel-b_mapplot_pr_bias_cdx11_pr_cdx11_map_MultiModelMean_bias.nc - Data file: observed (black boxplots), reanalysis (black boxplots) and modelled (CMIP5: blue boxplots, CMIP6: red boxplots, HighResMIP: orange boxplots, CORDEX EUR-44: light blue boxplots, CORDEX EUR-11: green boxplots) annual summer mean (JJA) precipitation rate values (i.e. underlying data points of the boxplot) over the western Mediterranean (bottom part): Fig_10_6_panel-b_boxplot.csv Acronyms: CMIP - Coupled Model Intercomparison Project, HighResMIP - High Resolution Model Intercomparison Project, 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.

This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 2015 to 2070. WACCM-X is a global atmosphere model covering altitudes from the surface up to ~500 km, i.e., including the troposphere, stratosphere, mesosphere and thermosphere. WACCM-X version 2.0 (Liu et al., 2018) was used, part of the Community Earth System Model (CESM) release 2.1.0 (http://www.cesm.ucar.edu/models/cesm2) made available by the National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9 degrees latitude and 2.5 degrees longitude (giving 96 latitude points and 144 longitude points) and 126 vertical levels. Further description of the model and simulation setup is provided by Cnossen (2022) and references therein. A large number of variables is included on standard monthly mean output files on the model grid, while selected variables are also offered interpolated to a constant height grid or vertically integrated in height (details below). Zonal mean and global mean output files are included as well. The data are provided in NetCDF format and file names have the following structure: f.e210.FXHIST.f19_f19.h1a.cam.h0.[YYYY]-[MM][DFT].nc where [YYYY] gives the year with 4 digits, [MM] gives the month (2 digits) and [DFT] specifies the data file type. The following data file types are included: 1) Monthly mean output on the full grid for the full set of variables; [DFT] = 2) Zonal mean monthly mean output for the full set of variables; [DFT] = _zm 3) Global mean monthly mean output for the full set of variables; [DFT] = _gm 4) Height-interpolated/-integrated output on the full grid for selected variables; [DFT] = _ht A cos(latitude) weighting was used when calculating the global means. Data were interpolated to a set of constant heights (61 levels in total) using the Z3GM variable (for variables output on midpoints, with 'lev' as the vertical coordinate) or the Z3GMI variable (for variables output on interfaces, with ilev as the vertical coordinate) stored on the original output files (type 1 above). Interpolation was done separately for each longitude, latitude and time. Mass density (DEN [g/cm3]) was calculated from the M_dens, N2_vmr, O2, and O variables on the original data files before interpolation to constant height levels. The Joule heating power QJ [W/m3] was calculated using Q_J = (sigma_P*B^2)*((u_i - U_n)^2 + (v_i-v_n)^2 + (w_i-w_n)^2) with sigma_P = Pedersen conductivity[S], B = geomagnetic field strength [T], ui, vi, and wi = zonal, meridional, and vertical ion velocities [m/s] and un, vn, and wn = neutral wind velocities [m/s]. QJ was integrated vertically in height (using a 2.5 km height grid spacing rather than the 61 levels on output file type 4) to give the JHH variable on the type 4 data files. The QJOULE variable also given is the Joule heating rate [K/s] at each of the 61 height levels. All data are provided as monthly mean files with one time record per file, giving 672 files for each data file type for the period 2015-2070 (56 years). References: Cnossen, I. (2022), A realistic projection of climate change in the upper atmosphere into the 21st century, in preparation. Liu, H.-L., C.G. Bardeen, B.T. Foster, et al. (2018), Development and validation of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X 2.0), Journal of Advances in Modeling Earth Systems, 10(2), 381-402, doi:10.1002/2017ms001232.

Data for Figure 3.18 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.18 shows instantaneous Northern-Hemisphere blocking frequency (% of days) in the extended northern winter season (DJFM) for the years 1979-2000.   --------------------------------------------------- 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. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains blocking freuency  (1979-2000) of - ERA5 reanalysis - CMIP5 and CMIP6 multi-model mean ERA5 is the fifth generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis of the global climate. 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 --------------------------------------------------- AR6_WG1_Chap3_Figure3_18_blocking.csv (lines and shading) Corresponding line and shading colours are described in the metadata associated with the datafile --------------------------------------------------- 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.

Airborne remote sensing measurements collected on 20 June 2019 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter Aircraft for the NET-Sense - joint NASA ESA Temperature Sensing Experiment (HyTES19) project (flight reference: 2019_171a). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager. Data were collected over the Grosseto, Italy area.

Wind profiles from a Galion G4000 Doppler lidar for the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project, derived from conical scans at 30 degree and 50 degree beam elevation angles. The University of Leeds participation in the project- MOSAiC Boundary Layer -was funded by the Natural Environment Research Council (NERC, grant: NE/S002472/1) and involved instrumentation from the Atmospheric Measurement and Observations Facility of the UK's National Centre for Atmospheric Science (NCAS AMOF). This was a year-long project on the German icebreaker Polarstern to study Arctic climate focused on measurements of atmospheric boundary layer dynamics and turbulent structure. The Galion wind profiler provides high resolution (~15m vertical and 5 minute temporal) measurements of wind profiles. Data are only available where sufficient particles are available to backscatter the laser light - in the clean arctic environment, this requires cloud or precipitation.