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  Remotely sensing potential climate change tipping points across scales

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

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 Creators:
Lenton, Timothy M.1, Author
Abrams, Jesse F.1, Author
Bartsch, Annett1, Author
Bathiany, Sebastian2, Author              
Boulton, Chris A.1, Author
Buxton, Joshua E.1, Author
Conversi, Alessandra1, Author
Cunliffe, Andrew M.1, Author
Hebden, Sophie1, Author
Lavergne, Thomas1, Author
Poulter, Benjamin1, Author
Shepherd, Andrew1, Author
Smith, Taylor1, Author
Swingedouw, Didier1, Author
Winkelmann, Ricarda2, Author              
Boers, Niklas2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 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.

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Language(s): eng - English
 Dates: 2023-12-182024-01-062024-01-06
 Publication Status: Finally published
 Pages: 15
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41467-023-44609-w
MDB-ID: pending
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: FutureLab - Artificial Intelligence in the Anthropocene
PIKDOMAIN: RD1 - Earth System Analysis
Organisational keyword: RD1 - Earth System Analysis
Research topic keyword: Tipping Elements
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
OATYPE: Gold Open Access
 Degree: -

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Title: Nature Communications
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 15 Sequence Number: 343 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals354
Publisher: Nature