Hope Umd 0117E 21241.Pdf (10.43Mb)
ABSTRACT Title of Document: Quantification of the Past and Future Anthropogenic Effect on Climate Change Using the Empirical Model of Global Climate, an Energy Balance Multiple Linear Regression Model Austin Patrick Hope, Doctor of Philosophy, 2020 Directed by: Professor Ross J. Salawitch, Department of Atmospheric and Oceanic Science, Department of Chemistry and Biochemistry, Earth System Science Interdisciplinary Center and Assistant Professor Timothy P. Canty, Department of Atmospheric and Oceanic Science, Marine Estuarine Environmental Sciences program The current episode of global warming is one of, if not the, biggest challenge to modern society as the world moves into the 21st century. Rising global temperatures due to anthropogenic emissions of greenhouse gases are causing sea level rise, extreme heat waves, droughts and floods, and other major social and economic disruptions. To prepare for and potentially reverse this warming trend, the causes of climate change must not only be understood, but thoroughly quantified so that we can attempt to make reasonable predictions of the future rise in global temperature and its associated consequences. The project described in this dissertation seeks to use a simple model of global climate, utilizing an energy balance and multiple linear regression approach, to provide a quantification of historical temperature trends and use that knowledge to provide probabilistic projections of future temperature. By considering many different greenhouse gas and aerosol emissions scenarios along with multiple possibilities for the role of the ocean in the climate system and the extent of climate feedbacks, I have determined that there is a 50% probability of keeping global warming beneath 2 °C if society can keep future emissions on the pathway suggested by the RCP 4.5 scenario, which includes moderately ambitious emissions reductions policies, and a 67% probability of keeping global warming beneath 1.5 °C if society can keep emissions in line with the very ambitious RCP 2.6 scenario.
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