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Future sea level rise constrained by observations and long-term commitment

Open access
Mengel, Matthias, Levermann, Anders, Frieler, Katja, Robinson, Alexander, Marzeion, Ben, Winkelmann, Ricarda·2016·Proceedings of the National Academy of Sciences

Abstract

Significance: Anthropogenic sea level rise poses challenges to coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we present an approach that combines information about the equilibrium sea level response to global warming and last century's observed contribution from the individual components to constrain projections for this century. This “constrained extrapolation” overcomes limitations of earlier global semiempirical estimates because long-term changes in the partitioning of total sea level rise are accounted for. While applying semiempirical methodology, our method yields sea level projections that overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The method can thus lead to a better understanding of the gap between process-based and global semiempirical approaches.

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Metadata

Authors
Mengel, M., Levermann, A., Frieler, K., Robinson, A., Marzeion, B., & Winkelmann, R.
Venue
Proceedings of the National Academy of Sciences
Published
2016-02-22
Volume
113
Issue
10
Pages
2597-2602
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2282352865
Cited by
238
References
0
FWCI
23.63
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Future sea level rise constrained by observations and long-term commitment. https://app.cochat.ai/papers/10.1073/pnas.1500515113
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Mengel, M., Levermann, A., Frieler, K., Robinson, A., Marzeion, B., & Winkelmann, R. (2016). Future sea level rise constrained by observations and long-term commitment. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1500515113

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.