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

TL;DR

This study investigates sea-ice variability trends leading to an ice-free Arctic, revealing predictable changes in relaxation times and autocorrelation that challenge early warning signals for abrupt ice loss.

Contribution

It demonstrates that characteristic variability trends are robust indicators of sea-ice loss, but are limited in providing early warnings for abrupt Arctic ice disappearance.

Findings

Relaxation time decreases before summer ice loss due to thinner ice.

Relaxation time increases as the system becomes dominated by ocean heat capacity.

Trends in variability are robust across different climate models and scenarios.

Abstract

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.