This dataset contains standardised data for figures and results used in the Indicators of Global Climate Change paper (https://doi.org/10.5194/essd-2023-166). 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 https://github.com/ClimateIndicator/anthropogenic-warming-assessment Earth's energy imbalance 1971-2022 Matthew Palmer, Karina von Schuckmann https://github.com/ClimateIndicator/ocean-heat-content Effective radiative forcing 1750-2022 Chris Smith, Piers Forster https://github.com/ClimateIndicator/forcing-timeseries Global mean surface temperature anomalies 1850-2022 Blair Trewin https://github.com/ClimateIndicator/GMST Global temperature extreme anomalies 1950-2022 Mathias Hauser, Dominik Schumacher, Sonia Seneviratne https://github.com/ClimateIndicator/cip_extremes Greenhouse gas concentrations 1750-2022 Chris Smith https://github.com/ClimateIndicator/forcing-timeseries Greenhouse gas emissions 1750-2022 William Lamb https://github.com/ClimateIndicator/GHG-Emissions-Assessment Remaining carbon budgets in 0.1°C increments Robin Lamboll https://github.com/Rlamboll/CarbonBudget 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.).