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Data are netCDF formatted

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  • 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.

  • The Global Ozone Monitoring Experiment (GOME) was an instrument aboard ERS-2. The main scientific objective of the GOME mission is to measure the global distribution of ozone and several trace gases which play an important role in the ozone chemistry of the Earth's stratosphere and troposphere, for example, NO2, BrO, OClO, and SO2. This dataset contains version 1.2 ozone profiles derived by the Remote Sensing Group (RSG) at the STFC Rutherford Appleton Laboratory, Oxfordshire, UK, as part of the National Centre for Earth Observation (NCEO). These were derived from radiances measured by the GOME on-board ERS-2. The collection also includes total column ozone, column BrO, and column NO2 as well as cloud heights derived from the Along Track Scanning Radiometer (ATSR), which are included to aid interpretation of the ozone profiles.

  • Measurements from a LI-COR LI-7500 open path gas analyser operating at infra-red wavelengths deployed at the Chilbolton Facility for Atmospheric and Radio Research site in Chilbolton, Hampshire. The instrument measures the absorption due to carbon dioxide at specific wavelengths along its 0.125m measurement path. Internally-stored calibration data are used to convert these absorption values to a mole concentration for each gas. Carbon dioxde and water vapour mole concentrations from this instrument are also provided with sonic anemomenter data at a 20Hz data acquisition rate for eddy covariance calculations in another CFARR dataset. Measurements are taken at 10s intervals and are archived at this temporal resolution. Data are in netCDF.

  • This dataset contains coupled physical-biogeochemical ocean second generation Canadian Earth System Model (CanESM2) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes. Job IDs included in this dataset: CanESM2 surface fluxes (started on 18th for first, 21st for second, and on the 19th for other 2): RCP85: u-ao419 RCP26: u-ao519 Constant atm CO2: RCP85: u-ao529 RCP26: u-ao531 (reduce walltime for nemo to test) This data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.

  • Cloud base and backscatter data from the Met Office's Jenoptik CHM15k Nimbus ceilometer located at Eskdalemuir, Dumfriesshire, Scotland. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

  • The ACTIVE (Aerosol and chemical transport in tropical convection) Natural Environment Research Council (NERC) funded consortium project, combined field measurements and a range of modelling tools at different scales to address questions related to the composition of the tropical tropopause layer (TTL). ACTIVE utilised the Australian Egrett aircraft operated by Airborne Research Australia (ARA) and the NERC Dornier 228 operated by the British Airborne Research and Survey Facility (ARSF) to measure chemical species and aerosol in the inflow and outflow of tropical storms. Cloud-scale and large-scale modelling studies assisted in the interpretation of the measurements to distinguish the different contributions to the TTL composition. The dataset contains the Egrett aircraft core instruments measurements from ARA Grob G520T Egrett aircraft.

  • Cloud base and backscatter data from the Met Office's Vaisala CL31 ceilometer located at Wittering, Sussex. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed. The Vaisala CL31 instrument replaced a Vaisala CT25k instrument previously operated at the site until November 2016.

  • Cloud base and backscatter data from the Met Éireann's Vaisala Ct25k ceilometer located at Shannon, South West, Ireland. The Met Éireann's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

  • This dataset contains coupled physical-biogeochemical ocean second generation Geophysical Fluid Dynamics Laboratory (GFDL-ESM2M) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes. Job IDs included in this dataset are: GFDL-ESM2M surface fluxes (started on 19th July ~14h): RCP85: u-ao541 (copy from u-ao419, change model names, restart + reduce walltime for nemo to test ) RCP26: u-ao551 (copy from u-ao541 and change rcp26 surface fluxes) Constant atm CO2: RCP85: u-ao552 (copy from u-ao541 with cst atm changes) RCP26: u-ao554 (copy from u-ao551 with cst atm changes) This data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.