Identifying the Fingerprint of Climate Change in U.S. Billion Dollar Weather Disasters

The number of billion dollar weather disasters identified by NOAA has risen steadily. In the 1980s, it was remarkable to get more than one in a year, while in recent years, the nation averages more than one per month. The rise in billion dollar disasters has been frequently cited as evidence for the impact of climate change on the U. S.. We present a quantitative analysis of the link between climate change and the frequency and weather disasters in the U. S.. We use the annual average of the change in information due to perspective (ChIP) applied to air temperature as our metric of the strength of climate change. ChIP, a novel metric based on information theory, quantifies the attributability of daily temperatures to climate change as the log of the ratio of the likelihood of an observed temperature to the likelihood of a no-warming counterfactual. Although the relationship with annual temperature anomalies is significant, we find that the population-weighted average of ChIP is the best predictor of the total number of disasters in the U.S.. This holds true for most specific disaster types including wildfire, severe-storms, and hurricanes. ChIP is also a reliable predictor of the number of disasters across the majority of states and disaster types. Over its nearly 250 year history, the distribution of people, infrastructure, and economic activities like agriculture in the U.S. developed in response to the historical climate of the country. ChIP quantifies the difference between these expected conditions and conditions in today’s anthropogenically-forced climate. We hypothesize that the strong relationship between disasters and ChIP means that ChIP is a reliable metric of the stress of climate change on society.