Term of Award

Spring 2021

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Mathematical Sciences

Committee Chair

Danial Jones

Committee Member 1

Yan Wu

Committee Member 2

Yongki Lee

Abstract

The vertical distribution of ozone in the atmosphere has significant consequences for climate and life's existence on the Earth's surface. Methods of defining the vertical ozone structure rely on the combination of physical, chemical, and dynamic properties. As a step toward an alternative approach for describing vertical structure in ozone concentration, here we apply an unsupervised classification technique (i.e., Gaussian mixture modeling or GMM) to observed and modeled ozone profiles. As GMM is automated, standardized, and robust in nature, it automatically identifies spatially coherent classes without using any latitude or longitude information. Possibly it can be a useful complement to existing classification to deal with an enormous, ever-increasing volume of observational and computer model data.

Research Data and Supplementary Material

No

Available for download on Sunday, January 30, 2022

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