An approach for projecting the timing of abrupt winter Arctic sea ice loss

IF 1.7 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Camille Hankel, E. Tziperman
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引用次数: 0

Abstract

Abstract. Abrupt and irreversible winter Arctic sea ice loss may occur under anthropogenic warming due to the disappearance of a sea ice equilibrium at a threshold value of CO2, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in winter Arctic sea ice exists because fully coupled climate models are too computationally expensive to run to equilibrium for many CO2 values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO2 increase to demonstrate for the first time how a few time-dependent CO2 experiments can be used to predict the existence and timing of sea ice tipping points without running the model to steady state. This study highlights the inefficacy of using a single experiment with slow-changing CO2 to discover changes in the sea ice steady state and provides a novel alternate method that can be developed for the identification of tipping points in realistic climate models.
一种预测冬季北极海冰突然消失时间的方法
摘要在人为变暖的情况下,由于海冰平衡在CO2的反重力值(通常称为临界点)下消失,北极冬季海冰可能会突然和不可逆转地流失。先前的工作无法最终确定冬季北极海冰是否存在拐点,因为完全耦合的气候模型计算成本太高,无法达到许多CO2值的平衡。在这里,我们探索了在实际的二氧化碳增加率下,海冰与其平衡状态的偏差,首次演示了如何在不将模型运行到稳态的情况下,使用一些与时间相关的二氧化碳实验来预测海冰倾翻点的存在和时间。这项研究强调了使用缓慢变化的CO2的单一实验来发现海冰稳态变化的无效性,并提供了一种新的替代方法,可以开发用于识别现实气候模型中的倾翻点。
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来源期刊
Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics 地学-地球化学与地球物理
CiteScore
4.00
自引率
0.00%
发文量
21
审稿时长
6-12 weeks
期刊介绍: Nonlinear Processes in Geophysics (NPG) is an international, inter-/trans-disciplinary, non-profit journal devoted to breaking the deadlocks often faced by standard approaches in Earth and space sciences. It therefore solicits disruptive and innovative concepts and methodologies, as well as original applications of these to address the ubiquitous complexity in geoscience systems, and in interacting social and biological systems. Such systems are nonlinear, with responses strongly non-proportional to perturbations, and show an associated extreme variability across scales.
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