Annual update of Climate Reconstruction AI (CRAI) infilled HadCRUT5 of near-surface temperature change 1850 to 2024

An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set infilled by Artificial Intelligence Software to train/evaluate models to reconstruct missing values in climate data (e.g., HadCRUT4, HadCRUT5) based on a U-Net with partial convolutions. The full dataset is in the process to be published at the World Data Center for Climate (WDCC) with the full 1,000 members: https://www.wdc-climate.de Core Data from UK Metoffice: C. P. Morice, J. J. Kennedy, N. A. Rayner, J. P. Winn, E. Hogan, R. E. Killick, R. J. H. Dunn, T. J. Osborn, P. D. Jones and I. R. Simpson (2021), An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set, Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361 Research Papers of AI Technology and Scientific Application: Kadow, C., Hall, D.M. & Ulbrich, U. Artificial intelligence reconstructs missing climate information. Nat. Geosci. 13, 408–413 (2020). https://doi.org/10.1038/s41561-020-0582-5 Plésiat, É., Dunn, R.J.H., Donat, M.G. et al. Artificial intelligence reveals past climate extremes by reconstructing historical records. Nat Commun 15, 9191 (2024). https://doi.org/10.1038/s41467-024-53464-2 Software: Johannes Meuer, Étienne Plésiat, Naoto Inoue, Maximilian Witte, Stephan Seitz, & Christopher Kadow. (2024). FREVA-CLINT/climatereconstructionAI: Guacamole (v1.0.4). Zenodo. https://doi.org/10.5281/zenodo.13767317