Uncertainties in the Projection of Sterodynamic Sea Level in CMIP6 Models

Abstract Sterodynamic sea level (SdynSL) is an essential component of sea level that climate models can simulate directly. Here, we disentangle the impacts of intermodel uncertainty, internal variability, and scenario uncertainty on SdynSL projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Regarding the global mean, intermodel (scenario) uncertainty dominates before (after) ∼2070, while internal variability is negligible. At the regional scale, intermodel uncertainty is the largest contributor, whereas internal variability plays a secondary role mainly in the tropical Indo‐Pacific Ocean. Scenario uncertainty becomes significant in certain regions toward the end of this century. The anthropogenic signal of global mean SdynSL emerges at the beginning of this century relative to 1971–2000. In contrast, the anthropogenic signals of regional SdynSL are likely to emerge over 70% of the global ocean by the 2090s, which could be advanced to the 2040s if model differences can be totally eliminated.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-04-25
DOI
https://doi.org/10.1029/2024gl113691
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

Uncertainties in the Projection of Sterodynamic Sea Level in CMIP6 Models

Kewei Lyu, Yiwen Li, Hailong Liu, Chenyang Jin et al.
Geophysical Research Letters
Climate variability and models
article

Uncertainties in the Projection of Sterodynamic Sea Level in CMIP6 Models

Kewei Lyu, Yiwen Li, Hailong Liu, Chenyang Jin, Pengfei Lin
article en

Abstract

Abstract Sterodynamic sea level (SdynSL) is an essential component of sea level that climate models can simulate directly. Here, we disentangle the impacts of intermodel uncertainty, internal variability, and scenario uncertainty on SdynSL projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Regarding the global mean, intermodel (scenario) uncertainty dominates before (after) ∼2070, while internal variability is negligible. At the regional scale, intermodel uncertainty is the largest contributor, whereas internal variability plays a secondary role mainly in the tropical Indo‐Pacific Ocean. Scenario uncertainty becomes significant in certain regions toward the end of this century. The anthropogenic signal of global mean SdynSL emerges at the beginning of this century relative to 1971–2000. In contrast, the anthropogenic signals of regional SdynSL are likely to emerge over 70% of the global ocean by the 2090s, which could be advanced to the 2040s if model differences can be totally eliminated.

Geophysical Research LettersVol. 52(8)
Xiamen University (CN), Chinese Academy of Sciences (CN), China University of Geosciences (Beijing) (CN), Shanghai Meteorological Bureau (CN), Institute of Atmospheric Physics (CN), University of Chinese Academy of Sciences (CN), Laoshan Laboratory, Shanghai Ecological Forecasting and Remote Sensing Center
Openalex Percentile: Top 91%
Climate variability and models
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Uncertainties in the Projection of Sterodynamic Sea Level in CMIP6 Models — Kewei Lyu, Yiwen Li, et al. · Geophysical Research Letters (2025) | TGRS Research Map | TGRS