Analyzing and Presenting Modern Temperature Trends

Abstract

In this paper, we examine temperature trends in data from the last century, taken from the National Oceanic and Atmospheric Administration (NOAA) Global Surface Summary of the Day. Expanding upon the model presented in "Local Warming" by Vanderbei, we run least absolute deviation and least squares regressions after applying techniques from major modern surface temperature analyses by NOAA and Berkeley Earth. To explore the effect of gaps in the datasets, we implement the scalpel technique from Berkeley Earth and find that, with our model, piecewise regression is skewed by shorter datasets that are heavily affected by the modeling of the solar cycle. We also extend our model to consider semiannual seasonality that has dominant effects on temperature fluctuations at lower latitudes, with the aim of increasing the accuracy of our model in the tropics. Finally, we create a framework for displaying our results via a website that allows people to access information about temperature trends in their area, with the goal of changing people's perceptions of global warming on a local basis by providing simple data that is very personally relevant.