Trends in sea-ice variability on the way to an ice-free Arctic
European Geosciences Union (EGU)
Open access. © Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License.
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.
This work was carried out under the programme of the Netherlands Earth System Science Centre (NESSC), financially supported by the Ministry of Education, Culture and Science (OCW). We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. We thank Vasilis Dakos for helping to apply his early warnings R package and Chao Li for making available the MPI-ESM model output. S. B. gratefully acknowledges Arie Staal for his fruitful and revealing approaches to savour scientific achievements. We are also indebted to Till Wagner and Ian Eisenman for their valuable comments and their very amiable and cooperative spirit.
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record. The final author version was published under the title: Statistical indicators of Arctic sea-ice stability-prospects and limitations and is available in ORE via https://ore.exeter.ac.uk/repository/handle/10871/23493