CMG: Assessing Ice Type Distributions and Characteristic Scales Using Wavelets

University Of Washington, Seattle WA

Investigators

Abstract

Funds are provided to develop the statistical theory required to assess changes in ice thickness distributions and to apply this theory to the wavelet analysis of ice draft measurements from submarine cruises spanning the years 1976 to 1997. This effort will advance the knowledge and understanding of Arctic sea ice and how its distribution varies both spatially and temporally. Because ice thickness data are significantly autocorrelated and have distributions that differ markedly from the Gaussian (normal) distribution, standard statistical tests for assessing changes in distributions cannot be used. The proposed effort simplifies the nature of the non-Gaussianity by partitioning the ice measurements into different types according to thickness (new, first year, medium multiyear and ridged). This partitioning leads to series that are binary-valued, thus yielding a simple non-Gaussian distribution with which to deal. Tests of differences in ice type distributions then serve as surrogates for tests of differences in the more complicated ice thickness distributions. In addition, the largest observed component of the wavelet analysis can be used to define a characteristic scale for an ice type. Spatial and temporal variations in this characteristic scale provide another characterization of how Arctic sea ice varies, which is complementary to variations captured by ice type distributions. The proposed effort will also establish a rigorous statistical theory for evaluating changes in characteristic scales. Variations in sea ice distribution is often viewed as and indicator of climate variation. Better characterization of this spatial and temporal variability will improve an important signal of climate variability.