Time series analysis

Forecasting Atmospheric Carbon Dioxide

  1. Abstract As a greenhouse gas, carbon dioxide ((\text{CO}_2)) is one of the driving forces behind global warming. Since the beginning of the industrial revolution, atmospheric (\text{CO}_2) levels have risen more than (40\%) and give no idication of slowing down. This project utilizes seasonal autoregressive integrated moving average (SARIMA) models to accurately forecast atmospheric carbon dioxide concentrations 10 months into the future. It is our hope that these forecasts may be useful for anticipating other meteorological phenomena, such as catastrophic weather events and global temperature rises.