Atmosphere-cryosphere feedbacks based upon wavelet decomposition of NCEP upper air data and passive microwave sea ice concentrations

We examine twenty years of sea ice concentration in the Eastern Canadian Arctic from SMMR and SSM/I passive microwave imagery as well as upper air patterns from NCEP gridded analysis. The objective is to identify co-dependencies in the temporal patterns that may lead to insight into process feedbacks between the atmosphere and sea ice. Typically, temporal loadings for principal components of geopotential height and ice concentration have been examined for correlations, which have proven to be very poor.

In this study we decompose the principal component loadings into Daubechies wavelets and examine temporal covariance for the spring transitional season of March, April and May when synoptic linkages with changes in ice concentration may be expected to be significant. Indeed, there are notable and significant correlations in the wavelet approximation which may be interpreted as the temporal trend as well as higher order detail patterns representing oscillations at a variety of temporal scales. These associations represent specific linkage modes and are related to a similar analysis of the Arctic Oscillation.