Published October 11, 2023 | Version v2023.10.11
Software Open

Indicators of Global Climate Change 2022

  • 1. UK Met Office
  • 2. University of Oxford
  • 3.
  • 4. University of Leeds
  • 5. Environment Canada
  • 6. ETH Zürich
  • 7. Mercator Research Institute
  • 8. Imperial College
  • 9. Météo France
  • 10. Australian Bureau of Meteorology
  • 11. Mercator Ocean


This dataset contains standardised data for figures and results used in the Indicators of Global Climate Change paper:

Forster, P. M., Smith, C. J., Walsh, T., Lamb, W. F., Lamboll, R., Hauser, M., Ribes, A., Rosen, D., Gillett, N., Palmer, M. D., Rogelj, J., von Schuckmann, K., Seneviratne, S. I., Trewin, B., Zhang, X., Allen, M., Andrew, R., Birt, A., Borger, A., Boyer, T., Broersma, J. A., Cheng, L., Dentener, F., Friedlingstein, P., Gutiérrez, J. M., Gütschow, J., Hall, B., Ishii, M., Jenkins, S., Lan, X., Lee, J.-Y., Morice, C., Kadow, C., Kennedy, J., Killick, R., Minx, J. C., Naik, V., Peters, G. P., Pirani, A., Pongratz, J., Schleussner, C.-F., Szopa, S., Thorne, P., Rohde, R., Rojas Corradi, M., Schumacher, D., Vose, R., Zickfeld, K., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 15, 2295–2327,, 2023

The below table details the author(s) of each dataset contained within the repository, and their homepages.

Dataset Author(s) Original code repository
Attribution of historical warming 1850-2022 Tristram Walsh,
Aurélien Ribes,
Nathan Gillett,
Chris Smith

Earth's energy imbalance 1971-2022 Matthew Palmer,
Karina von Schuckmann
Effective radiative forcing 1750-2022 Chris Smith,
Piers Forster
Global mean surface temperature anomalies 1850-2022 Blair Trewin
Global temperature extreme anomalies 1950-2022 Mathias Hauser,
Dominik Schumacher,
Sonia Seneviratne
Greenhouse gas concentrations 1750-2022 Chris Smith
Greenhouse gas emissions 1750-2022 William Lamb
Remaining carbon budgets in 0.1°C increments Robin Lamboll

Each data file has associated metadata in YML format with details on the contact author and original repository of the source code (note no code is retained on this data repository). The metadata files include additional information about each dataset, including short descriptions, file sizes and MD5 hashes.

.md and YML format files can be opened by any text editor (Notepad etc.).


This release contains the indicators of global climate change updated to the end of 2022. Datasets included are:

  • Attribution of historical warming 1850-2022
  • Earth's energy imbalance 1971-2022
  • Effective radiative forcing 1750-2022
  • Global mean surface temperature anomalies 1850-2022
  • Global temperature extreme anomalies 1950-2022
  • Greenhouse gas concentrations 1750-2022
  • Greenhouse gas emissions 1750-2022
  • Remaining carbon budgets in 0.1°C increments


  • Correction to metadata in Walsh attributed warming data set


  • Update to attributed warming summary table following update to Gillett et al. in v2023.05.25
  • Simplified metadata YML files for each data file


  • Update of Gillett et al. attributed warming to include percentiles and fix bug


  • Scope of F-gas emissions changed to original AR6 categories (i.e. excluding Montreal gas emissions).
  • Land use emissions reduced to remove double-counting of emissions reported in both PRIMAP-hist and GFED databases.
  • Greenhouse gas emissions are reported both on native emissions units and CO2e for CH4 and N2O, and all source datasets provided.
  • Metadata updated to include additional code repository source for historical climate change attribution.


  • Original 2022 Climate Indicators data



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