Data for Figure 3.5 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.5 shows the standard deviation of annually averaged zonal-mean near-surface air temperature. --------------------------------------------------- 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 --------------------------------------------------- - Simulated (CMIP6) standard deviation of near-surface air temperature - Observed standard deviation of near-surface air temperature CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Datafile: fig_3_5.nc, black lines: - HadCRUT5: model = 62 - BerkleyEarth: model = 61 - NOAAGlobalTemp-Interim: model = 60 - Kadow: model = 59 - colored lines: model = 0, 1, ..., 58 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 - Link to the code for the figure, archived on Zenodo.

Gridded model estimates of nitrate-N stored in the vadose (unsaturated) zone. This dataset presents annual gridded estimates of nitrate stored in the vadose zone for 1900 - 2000 on a 0.5 degree grid (units: kg N/grid cell). Data are supplied as a single netCDF for all years. This data was derived by Ascott et al. (2017). Global models of depth to groundwater table, subsurface porosity and groundwater recharge were used to derive estimates of nitrate travel time in the vadose zone. The travel time was combined with annual estimates of nitrate leaching from the base of the soil zone for 1900 - 2000 to estimate total nitrate stored in the vadose zone. For full details of the dataset derivation, please refer to Ascott et al. (2017). Ascott, M.J., Gooddy, D.C., Wang, L., Stuart, M.E., Lewis, M.A., Ward, R.S. and Binley, A.M. (2017) Global patterns of nitrate storage in the vadose zone. Nature Communications 8(1), 1416.

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 Figure 3.3 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.3 shows the global annual-mean surface (2 m) air temperature (°C) and the model bias to ERA5. --------------------------------------------------- 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 surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 - Global bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 to reanalysis ERA5 - Global root mean square bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP6 for the period 1995–2014 to reanalysis ERA5 - Global bias of modelled annual-mean surface (2 m) air temperature (°C) of CMIP5 for the period 1985–2004 to reanalysis ERA5 CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. ERA5 is the fifth generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis of the global climate. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/tas_mean_cmip6.nc; global map - panel_b/tas_bias_cmip6.nc; global map - panel_c/tas_rms_bias_cmip6.nc; global map - panel_d/tas_bias_cmip5.nc; global map --------------------------------------------------- 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.

The European Monitoring and Evaluation Program Unified Model for the UK (EMEP4UK) simulates the year 2001 to 2014 UK daily average atmospheric composition at a horizontal resolution of 5 x 5 km2. The species included in this dataset are surface daily average concentrations of: nitric oxide (NO), nitrogen dioxide (NO2), particulate matter (PM10 and PM2.5), ammonia (NH3), nitric acid (HNO3), sulphur dioxide (SO2), ammonium (NH4+), nitrate (NO3-), sulphate (SO42-), PM2.5 organic matter, and ground level ozone (O3). The EMEP4UK model framework consists of an atmospheric chemistry transport model (ACTM) which simulates hourly to annual average atmospheric composition and deposition of various pollutants and the weather research and forecast model (WRF). Pollutants simulated include fine particulate matter (PM10, PM2.5), secondary organic aerosols (SOA), elemental carbon (EC), secondary inorganic aerosols (SIA), sulphur dioxide (SO2), ammonia (NH3), nitrogen oxides (NOx), and ground level ozone (O3). Dry and wet deposition of pollutants are also generated by the EMEP4UK. WRF is used to calculate the required meteorological input data for the ACTM. The version of EMEP4UK used to model the 2001-2014 dataset available here is based on the EMEP Meteorological Synthesizing Centre West (MSC-W) model version rv4.4. A more recent version of this dataset, calculated using the EMEP model version rv4.17 and the WRF model version 3.7.1 is available at https://doi.org/10.5285/b0545f67-e47c-4077-bf3c-c5ffcd6b72c8. Notes: Only the simulations for the years between 2002-2012 include data for from forest fire. The emissions used for simulating the years 2013 and 2014 are the same as the year 2012 (updated date will be made available as soon as 2013 and 2014 national emission inventory data have been processed). The calculated year 2001-2012 use a different version of the WRF model, moreover for the year 2013 and 2014 the WRF model setup was changed as the specific Humidity is no longer nudged with re-analysis in the WRF simulation. Acknowledgements required (third-party datasets used to drive the model): The WRF model calculated meteorology uses the dataset from NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. (http://www.wrf-model.org/). National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2000, updated daily. NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. (http://doi.org/10.5065/D6M043C6). Emissions data from the EMEP emissions center (www.emep.int), and NAEI web site (http://naei.defra.gov.uk).

[THIS DATASET HAS BEEN WITHDRAWN]. 5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [1]. SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. NOTE: the difference between this dataset with the previously published dataset 'Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015 [2]), apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Keller et al., 2015 [3], Tanguy et al., 2014 [4]) was used, whereas in this version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. [2] Tanguy, M.; Hannaford, J.; Barker, L.; Svensson, C.; Kral, F.; Fry, M. (2015). Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]. NERC Environmental Information Data Centre. https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0 [3] Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J. A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., and Dixon, H. (2015). CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use, Earth Syst. Sci. Data Discuss., 8, 83-112, doi:10.5194/essdd-8-83-2015. [4] Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D. G.; Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC Environmental Information Data Centre. https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e Full details about this dataset can be found at https://doi.org/10.5285/ed7444fc-8c2a-473e-98cd-e68d3cffa2b0

The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. SWdown or surface incident shortwave radiation is the surface incident shortwave radiation measured in W/m2 at 3 hourly resolution, based on the average over the next 3 hours at the surface and at 0.5 x 0.5 degrees spatial resolution.

The WATCH forcing data (WFD) is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or dat formats. The data covers land points only and excludes the Antarctica. Rainf or rainfall rate is the rainfall rate based on the Global Precipitation Climatology Centre (GPCC) bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Rainf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this rainfall dataset is available from the EIDC. These rainfall datasets contain rainfall data only and need to be combined with the respective WFD snowfall datasets to obtain precipitation data.

[THIS DATASET HAS BEEN WITHDRAWN]. 1km resolution gridded potential evapotranspiration over Great Britain for the years 1961-2012. This dataset contains time series of two potential evapotranspiration variables. The first is potential evapotranspiration (PET) (mm/day) calculated using the Penman-Monteith equation [1] for FAO-defined well-watered grass [2]. The second is potential evapotranspiration with interception correction (PETI) (mm/day), which adds a correction for interception by a well-watered grass on days in which there is rainfall. Both PET and PETI are calculated using the Climate Hydrology and Ecology research Support System meteorology dataset (CHESS-met) meteorological variables [3]. [1] Monteith, J. L.: Evaporation and environment, in: 19th Symposia of the Society for Experimental Biology, University Press, Cambridge, 1965 [2] Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration - Guidelines for computing crop water requirements, Food and Agriculture Organization of the United Nations, Rome, Italy, FAO Irrigation and Drainage Paper, 1998. [3] Robinson, E. L., Blyth, E., Clark, D. B., Finch, J., Rudd, A. C. (2015). Climate hydrology and ecology research support system meteorological dataset (1961-2012) [CHESS-met] . NERC-Environmental Information Data Centre https://doi.org/10.5285/80887755-1426-4dab-a4a6-250919d5020c Full details about this dataset can be found at https://doi.org/10.5285/d329f4d6-95ba-4134-b77a-a377e0755653

An ensemble of simulations made using the Unified Model version 6.6 (HadGEM2) in AMIP (atmosphere only) configuration for the SAPRISE (South Asian PRecIpitation: A SEamless assessment) project. The simulations are used to investigate the impacts of aerosols on the South Asian Monsoon. The four-member ensemble of simulations are forced with anthropogenic-only aerosols i.e. sulphur dioxide, black carbon and biomass burning aerosols. The simulations cover the period from 1850-2000. Since aerosol-only simulation is not compulsory in CMIP5, these four runs are complements to other CMIP5 simulations conducted by Met Office using the HadGEM2-ES (vn 6.6).