Climate Dynamics

, Volume 51, Issue 9–10, pp 3927–3942 | Cite as

Limited predictability of extreme decadal changes in the Arctic Ocean freshwater content

  • Torben SchmithEmail author
  • Steffen M. Olsen
  • Ida M. Ringgaard
  • Wilhelm May


Predictability of extreme changes in the Arctic Ocean freshwater content and the associated release into the subpolar North Atlantic up to one decade ahead is investigated using a CMIP5-type global climate model. The perfect-model setup consists of a 500 year control run, from which selected 10 year long segments are predicted by initialized, perturbed ensemble predictions. Initial conditions for these are selected from the control run to represent large positive or negative decadal changes in the total freshwater content in the Arctic Ocean. Two different classes of ensemble predictions are performed, one initialized with the ‘observed’ ocean globally, and one initialized with the model climatology in the Arctic Ocean and with the observed ocean elsewhere. Analysis reveals that the former yields superior predictions 1 year ahead as regards both liquid freshwater content and sea ice volume in the Arctic Ocean. For prediction years two and above there is no overall gain in predictability from knowing the initial state in the Arctic Ocean and damped persistence predictions perform just as well as the ensemble predictions. Areas can be identified, mainly in the proper Canadian and Eurasian basins, where knowledge of the initial conditions gives a gain in predictability of liquid freshwater content beyond year two. Total freshwater export events from the Arctic Ocean into the subpolar North Atlantic have no predictability even 1 year ahead. This is a result of the sea ice component not being predictable and LFW being on the edge of being predictable for prediction time 1 year.


Arctic ocean Predictability Sea ice Freshwater 



Support from the European Community 7th Framework Programme (FP7/2007–2013) under Grant Number 308299 (NACLIM), from the European Research Council under the European Community 7th Framework Programme (FP7/2007–2013)/ERC under Grant Number 610055 (ICE2ICE) and from the European Union Horizon 2020 research and innovation programme under Grant Number 727852 (Blue-Action) is gratefully acknowledged. Valuable suggestions from the anonymous reviewers are appreciated.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Danish Meteorological InstituteCopenhagenDenmark
  2. 2.Niels Bohr InstituteUniversity of CopenhagenCopenhagenDenmark
  3. 3.Centre for Environmental and Climate ResearchLund UniversityLundSweden

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