Neven S. Fučkar
Catalan Institute of Climate Sciences (IC3), Barcelona, Spain

Clusters of interannual sea ice variability in the Northern Hemisphere

Time and place
Monday 14 September 2015, 14.00 NB! Unusal time
Room A601, Arrhenius Labo0ratory, 6th floor Please notice the room

We determine robust modes of the northern hemisphere (NH) sea ice
variability on interannual timescales disentangled from the long-term
climate change. This study focuses on sea ice thickness (SIT),
reconstructed with an ocean-sea-ice general circulation model, because
SIT has a potential to contain most of the interannual memory and
predictability of the NH sea ice system. We use the K-means cluster
analysis - one of clustering methods that partition data into groups
or clusters based on their distances in the physical space without the
typical constraints of other unsupervised learning statistical methods
such as the widely-used principal component analysis. To adequately
filter out climate change signal in the Arctic from 1958 to 2013 we
have to approximate it with a 2nd degree polynomial. Using 2nd degree
residuals of SIT leads to robust K-means cluster patterns, i.e.
invariant to further increase of the polynomial degree. A set of
clustering validity indices yields K=3 as the optimal number of SIT
clusters for all considered months and seasons with strong
similarities in their cluster patterns. The associated time series of
cluster occurrences exhibit predominant interannual persistence with
mean timescale of about 2 years. Compositing analysis of the NH
surface climate conditions associated with each cluster indicates that
wind forcing seem to be the key factor driving the formation of
interannual SIT cluster patterns during the winter. Climate memory in
SIT with such interannual persistence could lead to increased
predictability of the Artic sea ice cover beyond seasonal timescales.