Description
The Arctic plays a vital role in regulating global temperatures. Through extensive research, it was found that the region’s oldest and thickest ice on this extent has significantly and continually decreased over the years. The thinning of ice due to warmer temperatures over the years is directly affecting the population of polar bears negatively. As the ice constitutes polar bear prey territory, the thinning of ice makes it more difficult for polar bears to prey on seals; ice is more easily moved by ocean currents and wind when it is thin. By the monitored ice coverage in the Arctic from as early as 1980, to 2016, and on a yearly scale, data has been collected from previous research to modify a mathematical model under climate change to accommodate the declining of ice coverage. It was determined that ice is at its thickest in March, and at its thinnest in September. By analyzing one month on the segment of the decline of ice coverage, a first-order differential equation was generated based on the rate of ice coverage change. Utilizing Excel, Matlab and concepts learned in the Differential Equations class, modeling ice coverage based on the available data makes it possible to generate an equation by solving a first-order differential equation to predict a trend of the ice coverage in future years. The results of the work allow the public to be more conscious about the warming of global temperatures. With knowledge of this subject, the public can look into aspects of their daily lives and find better ways to regulate global temperatures in a positive way. This opportunity creates a chance to save the lives of polar bears.
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