SGER: Exploring Arctic Ice Thickness Distribution with Wavelets

University Of Washington, Seattle WA

Investigators

Abstract

This research explores the feasibility of using wavelet analysis to assess spatial variability in the distribution of arctic pack ice. Wavelets have been used in recent years to analyze a variety of geophysical processes, but they have not yet been used to study pack ice. They provide an exact decomposition of the sample variance, for a spatial series, in terms of coefficients that are indexed according to both location and scale. This information can be used in turn to statistically assess spatial variability in the variance. Because they provide this information, they are a potentially useful tool for use in characterizing and studying multi-scale, nonstationary features such as pack ice. This work seeks to demonstrate, through application of wavelet analysis to a large existing database derived from submarine-based observations, that wavelets can be a powerful tool for determining which spatial scales make the greatest contributions to overall variance in arctic pack ice thickness. Knowledge of these statistical properties is essential for assessing whether observed variations reflect climate change or are due merely to sampling uncertainty. The anticipated successful completion of this demonstration will provide the impetus for a broader research effort that will address pack ice response to climate variability. This work will also help to publicize the potential uses of wavelets in studying other geophysical processes and will, in so doing, facilitate their integration into university courses on data analysis.