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Journal Article

Remotely sensing potential climate change tipping points across scales

Authors

Lenton,  Timothy M.
External Organizations;

Abrams,  Jesse F.
External Organizations;

Bartsch,  Annett
External Organizations;

/persons/resource/sebastian.bathiany

Bathiany,  Sebastian
Potsdam Institute for Climate Impact Research;

Boulton,  Chris A.
External Organizations;

Buxton,  Joshua E.
External Organizations;

Conversi,  Alessandra
External Organizations;

Cunliffe,  Andrew M.
External Organizations;

Hebden,  Sophie
External Organizations;

Lavergne,  Thomas
External Organizations;

Poulter,  Benjamin
External Organizations;

Shepherd,  Andrew
External Organizations;

Smith,  Taylor
External Organizations;

Swingedouw,  Didier
External Organizations;

/persons/resource/Ricarda.Winkelmann

Winkelmann,  Ricarda
Potsdam Institute for Climate Impact Research;

/persons/resource/Niklas.Boers

Boers,  Niklas
Potsdam Institute for Climate Impact Research;

External Ressource
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Fulltext (public)

lenton_2024_s41467-023-44609-w.pdf
(Publisher version), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Lenton, T. M., Abrams, J. F., Bartsch, A., Bathiany, S., Boulton, C. A., Buxton, J. E., Conversi, A., Cunliffe, A. M., Hebden, S., Lavergne, T., Poulter, B., Shepherd, A., Smith, T., Swingedouw, D., Winkelmann, R., Boers, N. (2024): Remotely sensing potential climate change tipping points across scales. - Nature Communications, 15, 343.
https://doi.org/10.1038/s41467-023-44609-w


Cite as: https://publications.pik-potsdam.de/pubman/item/item_29364
Abstract
Potential climate tipping points pose a growing risk for societies, and policy is calling for improved anticipation of them. Satellite remote sensing can play a unique role in identifying and anticipating tipping phenomena across scales. Where satellite records are too short for temporal early warning of tipping points, complementary spatial indicators can leverage the exceptional spatial-temporal coverage of remotely sensed data to detect changing resilience of vulnerable systems. Combining Earth observation with Earth system models can improve process-based understanding of tipping points, their interactions, and potential tipping cascades. Such fine-resolution sensing can support climate tipping point risk management across scales.