Evidence and Prediction Regarding the Continuous Global Warming: A Severe Domino Effect

Abstract

Global warming has been a major threat to Earth for decades; still, this issue has not been taken seriously by many. Although it is proven that one of its main causes is human activity, humanity’s effort towards a safer, healthier planet has been minimal. After years of neglect, global warming has worsened, and its adverse effects have become more severe. This paper aims to underscore the necessity of human efforts and universal contribution to subside the devastating ramifications of global warming. To investigate the past, present, and possible future consequences of global warming, this paper analyzes data mostly obtained from the United States Environmental Protection Agency (EPA). The paper also presents graphs that clearly illustrate the increases in global sea levels, permafrost temperatures, sea surface temperatures, and concentrations of greenhouse gases. Furthermore, the paper utilizes a linear regression machine learning algorithm, a method widely used by researchers to create predictive models, to depict future trends of the data of the aforementioned subjects. This analysis and visualization of data conclude that a so-called “domino effect” was certainly present as some environmental changes of global warming. To solve the problem of global warming, the paper finally uses the K-neighbor regression method in Python to predict the amount of power generated in the solar power systems of Berkeley, California in an accurate, flexible way.