Statistical indicators of Arctic sea-ice stability - prospects and limitations
Statistical indicators of Arctic sea-ice stability - prospects and limitations
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DOI：
10.5194/tc-10-1631-2016
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发表时间：
2016-01-01
期刊：
影响因子：
5.2
通讯作者：
Notz, Dirk
中科院分区：
文献类型：
--
作者：
Bathiany, Sebastian;van der Bolt, Bregje;Notz, Dirk
我们研究了北极海冰覆盖率和体积的平均值和变化之间的关系，在大范围的气候从全球冰覆盖到全球无冰条件。使用两列模型和几个全面的地球系统模型的层次结构，我们巩固了早期的研究结果，并表明，在简单的模型中发现的机制也占主导地位的北极海冰的年际变化在复杂的模型。在非常理想化的动力系统的基础上的预测相反，我们发现一个一致的和强大的减少夏季海冰体积的方差和自相关之前，海冰丢失。我们把这归因于这样一个事实，即较薄的冰可以更快地适应扰动。此后，自相关增加，主要是因为它成为主导的海水的大热容量时，无冰季节变得更长。我们表明，这些变化是强大的气候变率的性质和起源的模型，并不依赖于北极海冰的损失是否突然或不可逆转地发生。我们还表明，我们的气候变化太快，检测可靠的变化，年度时间序列的自相关性。根据这些结果，在海冰在“临界点”突然消失之前检测统计预警信号的前景似乎非常有限。然而，强大的状态和变化之间的关系可以是有用的，以建立简单的随机气候模型，并作出推论，过去和未来的海冰变化，只有短期的观测或重建。
We examine the relationship between the mean and the variability of Arctic sea-ice coverage and volume in a large range of climates from globally ice-covered to globally ice-free conditions. Using a hierarchy of two column models and several comprehensive Earth system models, we consolidate the results of earlier studies and show that mechanisms found in simple models also dominate the interannual variability of Arctic sea ice in complex models. In contrast to predictions based on very idealised dynamical systems, we find a consistent and robust decrease of variance and autocorrelation of sea-ice volume before summer sea ice is lost. We attribute this to the fact that thinner ice can adjust more quickly to perturbations. Thereafter, the autocorrelation increases, mainly because it becomes dominated by the ocean water's large heat capacity when the ice-free season becomes longer. We show that these changes are robust to the nature and origin of climate variability in the models and do not depend on whether Arctic sea-ice loss occurs abruptly or irreversibly. We also show that our climate is changing too rapidly to detect reliable changes in autocorrelation of annual time series. Based on these results, the prospects of detecting statistical early warning signals before an abrupt sea-ice loss at a "tipping point" seem very limited. However, the robust relation between state and variability can be useful to build simple stochastic climate models and to make inferences about past and future sea-ice variability from only short observations or reconstructions.