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arXiv 1601.06286physics.ao-phphysics.data-an
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走向无冰北极途中海冰变化的趋势

Trends in sea-ice variability on the way to an ice-free Arctic

Sebastian Bathiany, Bregje van der Bolt, Mark S. Williamson, Timothy M. Lenton, Marten Scheffer, Egbert van Nes, Dirk Notz

摘要:

北极海冰的减少是否会达到一个临界点,超过这个临界点,一个大的海冰区域就会突然消失,这一点一直受到广泛的争论。动力系统理论预测,当系统向临界点不稳定时,速度会减慢。在简单的随机系统中,这可能导致方差和自相关性增加,可能会产生突变的早期预警。在这里,我们的目标是建立北极海冰的损失是否会遵循这些概念性的预测,以及海冰变化的趋势,可以预期从工业化前的条件下,对北极是无冰在全年。为此,我们应用了一个模型层次结构,包括两个盒子模式和一个全面的地球系统模型。我们发现,在夏季冰消失之前,冰量的年度弛豫时间持续而稳健地减少,因为较薄的冰可以更快地适应扰动。此后,弛豫时间增加,这主要是因为当无冰季节变长时,系统变得由海水的大热容量所支配。这两种趋势都延续到海冰厚度在时间序列中的自相关性。这些变化对模式中气候变率的性质和起源是稳健的,几乎不依赖于反馈的平衡。因此,可以预期未来的特征趋势。由于这些趋势并不是冰量突然减少所特有的,因此早期预警的前景似乎非常有限。这一结果也有影响的统计指标,在其他系统的有效质量随时间变化,影响其弛豫时间的趋势。然而,状态和变化之间的鲁棒关系将允许仅从短观测来估计海冰变化。这可以帮助人们估计未来极端事件的可能性和持续性。

英文摘要:

It has been widely debated whether Arctic sea-ice loss can reach a tipping point beyond which a large sea-ice area disappears abruptly. The theory of dynamical systems predicts a slowing down when a system destabilises towards a tipping point. In simple stochastic systems this can result in increasing variance and autocorrelation, potentially yielding an early warning of an abrupt change. Here we aim to establish whether the loss of Arctic sea ice would follow these conceptual predictions, and which trends in sea ice variability can be expected from pre-industrial conditions toward an Arctic that is ice-free during the whole year. To this end, we apply a model hierarchy consisting of two box models and one comprehensive Earth system model. We find a consistent and robust decrease of the ice volume's annual relaxation time before summer ice is lost because thinner ice can adjust more quickly to perturbations. Thereafter, the relaxation time increases, mainly because the system becomes dominated by the ocean water's large heat capacity when the ice-free season becomes longer. Both trends carry over to the autocorrelation of sea ice thickness in time series. These changes are robust to the nature and origin of climate variability in the models and hardly depend on the balance of feedbacks. Therefore, characteristic trends can be expected in the future. As these trends are not specific to the existence of abrupt ice loss, the prospects for early warnings seem very limited. This result also has implications for statistical indicators in other systems whose effective mass changes over time, affecting the trend of their relaxation time. However, the robust relation between state and variability would allow an estimate of sea-ice variability from only short observations. This could help one to estimate the likelihood and persistence of extreme events in the future.

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