Acknowledgements

DWP and PS acknowledge funding from NERC projects NE/P013406/1 (A-CURE) and NE/S005390/1 (ACRUISE). DWP, GCV, PS, SB, MD, EF, PH, KJ, JL, PM, MN, LR, CR and JV acknowledge funding from the European Union’s Horizon 2020 research and innovation programme iMIRACLI under Marie Skłodowska-Curie grant agreement No 860100. PS additionally acknowledges support from the ERC project RECAP and the FORCeS project under the European Union’s Horizon 2020 research programme with grant agreements 724602 and 821205. GCV was partly supported by the European Research Council (ERC) Synergy Grant “Understanding and Modelling the Earth System with Machine Learning (USMILE)” under the Horizon 2020 research and innovation programme (Grant agreement No. 855187).
The authors also gratefully acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. In particular, DO and ØS acknowledge support from the Research Council of Norway funded project INES (270061). High-performance computing and storage resources for NorESM2 were provided by the Norwegian infrastructure for computational science (through projects NN2345K, NN9560K, NS2345K, NS9560K, and NS9034K).