Abstract
Klaus Hasselmann’s revolutionary intuition in climate science was to use the stochasticity associated with fast weather processes to probe the slow dynamics of the climate system. Doing so led to fundamentally new ways to study the response of climate models to perturbations, and to perform detection and attribution for climate change signals. Hasselmann’s programme has been extremely influential in climate science and beyond. In this Perspective, we first summarize the main aspects of such a programme using modern concepts and tools of statistical physics and applied mathematics. We then provide an overview of some promising scientific perspectives that might clarify the science behind the climate crisis and that stem from Hasselmann’s ideas. We show how to perform rigorous and data-driven model reduction by constructing parameterizations in systems that do not necessarily feature a timescale separation between unresolved and resolved processes. We outline a general theoretical framework for explaining the relationship between climate variability and climate change, and for performing climate change projections. This framework enables us seamlessly to explain some key general aspects of climatic tipping points. Finally, we show that response theory provides a solid framework supporting optimal fingerprinting methods for detection and attribution.
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Acknowledgements
V.L. acknowledges support received from the European Union (EU) Horizon 2020 research and innovation programme through the projects TiPES (grant agreement no. 820970) and CriticalEarth (grant agreement no. 956170) and by the EPSRC through grant EP/T018178/1. M.D.C. acknowledges the European Research Council under the EU Horizon 2020 research and innovation programme (grant no. 810370) and the Ben May Center grant for theoretical and/or computational research. This work has been also partially supported by the Office of Naval Research (ONR) Multidisciplinary University Research Initiative (MURI) grant N00014-20-1-2023. Finally, the authors thank many close collaborators over the years without whom this review would have not been possible: O. Altaratz, P. Ashwin, P. Berloff, R. Blender, T. Bódai, N. Boers, H. Dijkstra, T. Dror, B. Dubrulle, D. Faranda, K. Fraedrich, V. M. Gálfi, G. Gallavotti, N. Glatt-Holtz, G. Gottwald, A. Gritsun, A. von der Heydt, D. Kondrashov, I. Koren, S. Kravtsov, T. Kuna, J. Kurths, H. Liu, F. Lunkeit, D. Neelin, G. Pavliotis, C. Penland, F. Ragone, L. Roques, J. Roux, M. Santos Gutiérrez, S. Schubert, E. Simonnet, A. Speranza, K. Srinivisan, A. Tantet, T. Tél, S. Vannitsem, S. Wang, J. Wouters, N. Zagli, and I. Zaliapin, with special gratitude to A. Chorin, M. Ghil, J. C. McWilliams, D. Ruelle and R. Temam for their guidance and inspirational works.
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Lucarini, V., Chekroun, M.D. Theoretical tools for understanding the climate crisis from Hasselmann’s programme and beyond. Nat Rev Phys 5, 744–765 (2023). https://doi.org/10.1038/s42254-023-00650-8
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