Noise-shaped hysteresis cycles of the AMOC under increasing CO2 forcing.

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED Chaos Pub Date : 2025-02-01 DOI:10.1063/5.0241503
Matteo Cini, Giuseppe Zappa, Francesco Ragone, Susanna Corti
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引用次数: 0

Abstract

The Atlantic Meridional Overturning Circulation (AMOC) stability landscape is commonly investigated with single-realization hysteresis diagrams driven by freshwater input in the North Atlantic Ocean. However, the effect of CO2 forcing on one side and the role of internal climate variability on the timing of tipping and the AMOC hysteresis on the other side remain less explored. Here, we address this gap by running three independent AMOC hysteresis simulations, consisting of a slow ramp-up plus ramp-down in the CO2 concentration (0.2 ppm/year) within the PlaSim-Large-Scale Geostrophic (LSG) intermediate complexity model. We show that the realizations of the CO2-driven hysteresis cycle, and particularly, the timing of the tipping and recovery, are remarkably affected by internal climate variability. In one of the three simulations, we even observe a reversed cycle, where the AMOC recovers at a higher CO2 level than at the collapse point. While statistical Early Warning Signals (EWSs) show some success in detecting the tipping points, we also find that the internal variability in the EWS considerably reduces the predictability of collapse and leads to false positives of an approaching AMOC tipping. We suggest that the AMOC collapse in the presence of internal climate variability may have characteristics that deviate substantially from the behavior seen in simple models and that caution is needed when interpreting results from a single-experiment realization. Our findings highlight the need for a probabilistic approach in defining a "safe operating space" for AMOC stability, since it might not be possible to define a single critical CO2 threshold to prevent AMOC collapse.

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Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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