Abstract

Long term trends in Arctic sea ice are of particular interest with regard to global temperature, climate change, and industry. This thesis uses microwave scatterometer data from QuikSCAT and radiometer data to analyze intra- and interannual trends in first-year and multi-year Arctic sea ice. It develops a sea ice type classification method. The backscatter of first-year and multi-year sea ice are clearly identifiable and are observed to vary seasonally. Using an average of the annual backscatter trends obtained from QuikSCAT, a classification of multi-year ice is obtained which is dependent on the day of the year (DOY). Validation of the classification method is done using regional ice charts from the Canadian Ice Service. Differences in ice classification are found to be less than 6% during the winters of 06-07, 07-08, and the end of 2008. Anomalies in the distribution of sea ice backscatter from year to year suggest a reduction in multi-year ice cover between 2003 and 2009 and an approximately equivalent increase in first-year ice cover.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2011-06-10

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd4477

Keywords

QuikSCAT, sea ice classification, Arctic, microwave remote sensing

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