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).