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  Overshooting the critical threshold for the Greenland ice sheet

Bochow, N., Poltronieri, A., Robinson, A., Montoya, M., Rypdal, M., Boers, N. (2023): Overshooting the critical threshold for the Greenland ice sheet. - Nature, 622, 528-536.
https://doi.org/10.1038/s41586-023-06503-9

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Bochow, Nils1, Autor              
Poltronieri, Anna2, Autor
Robinson, Alexander1, Autor              
Montoya, Marisa2, Autor
Rypdal, Martin2, Autor
Boers, Niklas1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Melting of the Greenland ice sheet (GrIS) in response to anthropogenic global warming poses a severe threat in terms of global sea-level rise (SLR)1. Modelling and palaeoclimate evidence suggest that rapidly increasing temperatures in the Arctic can trigger positive feedback mechanisms for the GrIS, leading to self-sustained melting2,3,4, and the GrIS has been shown to permit several stable states5. Critical transitions are expected when the global mean temperature (GMT) crosses specific thresholds, with substantial hysteresis between the stable states6. Here we use two independent ice-sheet models to investigate the impact of different overshoot scenarios with varying peak and convergence temperatures for a broad range of warming and subsequent cooling rates. Our results show that the maximum GMT and the time span of overshooting given GMT targets are critical in determining GrIS stability. We find a threshold GMT between 1.7 °C and 2.3 °C above preindustrial levels for an abrupt ice-sheet loss. GrIS loss can be substantially mitigated, even for maximum GMTs of 6 °C or more above preindustrial levels, if the GMT is subsequently reduced to less than 1.5 °C above preindustrial levels within a few centuries. However, our results also show that even temporarily overshooting the temperature threshold, without a transition to a new ice-sheet state, still leads to a peak in SLR of up to several metres.

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Sprache(n): eng - Englisch
 Datum: 2023-10-182023-10-19
 Publikationsstatus: Final veröffentlicht
 Seiten: 22
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1038/s41586-023-06503-9
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: FutureLab - Artificial Intelligence in the Anthropocene
Model / method: Nonlinear Data Analysis
Research topic keyword: Tipping Elements
OATYPE: Hybrid Open Access
 Art des Abschluß: -

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Titel: Nature
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 622 Artikelnummer: - Start- / Endseite: 528 - 536 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals353
Publisher: Nature