Since the Industrial Revolution of the nineteenth century, anthropogenic climate change has manifested itself in the increased frequency of temperatures and precipitation that are significantly different from normal values, known as climate extremes (IPCC 2014; Reidmiller et al. 2018). Studying climate extremes is increasingly urgent because the rising number of extreme events has adversely impacted economic and health outcomes. For example, a multiday heatwave throughout much of the eastern United States in July 2019 presented an increased risk of heat stroke to many residents unaccustomed to temperatures above 32.2°C (90°F) (Peltz 2019). There is also now an increased risk of economic disruption as millions of Americans living in coastal areas continue to sell their homes and move to avoid rising sea levels (Gopal 2019). The impact of climate extremes also extends to the insurance industry. Increasing climate variability and occurrence of extremes can cause deviations from the estimation of future health insurance costs, and this will have “considerable financial consequences” (Owen 2019).
To educate the public and policy-makers about climate extremes, several indices measuring them have been created. One of the first, the Climate Extremes Index (CEI) from the National Centers for Environmental Information (NCEI), formerly the National Climatic Data Center (NCDC), was created in the 1990s to quantify the extremes that the country as a whole was experiencing (Karl et al. 1996). However, the CEI has remained complex enough that it is very difficult for the public to interpret, and it has only been minimally updated since its inception (Gleason et al. 2008). In this paper, the CEI is recalculated using the Z-score statistic (Larson and Farber 2006) to calculate the CEI on a numerical scale and increase usability at smaller spatial scales. After recalculating the CEI, we combine it with values from the Centers for Disease Control and Prevention’s (CDC) Social Vulnerability Index (SVI; Flanagan et al. 2011) to create a climate Extremes Vulnerability Index (EVI) that can be used by policy-makers, planners, and the public to identify areas of the United States that may be more at risk of experiencing climate extremes.
We thank Deke Arndt and Karin Gleason from NCEI for their instrumental advice and guidance throughout the completion of this project. Karin Gleason of NCEI provided the unpublished data to the first author in 2018. We would also like to thank Alison Smith from the College of Environment + Design at UGA for her invaluable assistance with creating the maps, and the anonymous reviewers for their comments.
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