Hidden Response Pathways in Historical Constraints on Climate Sensitivity
编号:1623 访问权限:仅限参会人 更新:2026-09-02 16:53:27 浏览:0次 口头报告

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摘要
Equilibrium climate sensitivity is a long-time response property, whereas historical climate records provide only finite, forced projections of the Earth system. This mismatch is important in a complex climate system where slow adjustment, ocean heat uptake, cloud feedbacks, and pattern effects can separate short-term surface-temperature variability from long-term response. We revisit fluctuation-based constraints on climate sensitivity by treating historical temperature variability as a projected fluctuation-memory coordinate. In CMIP5 this coordinate captures a substantial part of the ECS spread, but in CMIP6 the relationship weakens. We show that the missing information is not simply lost: after conditioning on the fluctuation-memory coordinate, CMIP6 retains a strong residual alignment between ECS and a finite CO2-response coordinate estimated from historical forced dynamics. A minimal two-mode stochastic response model, representing surface temperature coupled to a slow hidden response mode, explains this behavior as a hidden response pathway that is weakly projected onto historical fluctuations but visible in finite forced response. These hidden response pathways may involve ocean-mediated adjustment and heat uptake. Linear ARX and Neural ODE response estimators give consistent finite-response coordinates, suggesting that the signal is not an artifact of one dynamical estimator. The results suggest that emergent constraints should be viewed as projected fluctuation-response closure tests in a forced, complex Earth system.
 
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报告人
Yongwen Zhang
Kunming University of Science and Technology

稿件作者
Yongwen Zhang Kunming University of Science and Technology
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重要日期
  • 会议日期

    01月12日

    2027

    01月15日

    2027

  • 07月21日 2026

    初稿截稿日期

  • 01月15日 2027

    注册截止日期

主办单位
State Key Laboratory of Marine Environmental Science, Xiamen University (MEL)
Department of Earth Sciences, National Natural Science Foundation of China (NSFC)
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