Monitoring of Arctic sea ice volume variability by an optimized observation system

Current observation systems of Arctic sea ice thickness and volume come with great uncertainty due to limited quality satellite and in situ observations. Using the Community Earth System Model Large Ensemble Project dataset, we investigate a statistical model based on local ice thickness measurements, able to reproduce the Arctic sea ice volume variability. A statistical model is proposed, computed by iterative correlation method. This observation system is able to reproduce the Arctic sea ice volume variability in pre and post-industrial conditions and also in future climate conditions. The Arctic sea ice thickness variability is both natural and anthropogenic. Until now, less attention has been given to the natural variability of the Arctic sea ice thickness. A principal component analysis over Arctic sea ice thickness time series shows the major modes of natural sea ice thickness variability. The fifth first modes account for more than 45% of the variability. The first mode is link to the Arctic Oscillation, which is a dipole spatial pattern of sea ice thickness variability with opposite signs of polarity between the East Siberian Sea and near the Fram Strait.