Climate Change and Storm-Induced Coastal Energy System Vulnerabilities


Researchers from Johns Hopkins University and Texas A&M have applied advanced statistical methods for analysis of hurricane-induced power outages. The team compared the predictive accuracy of five distinct statistical models for estimating power outage durations caused by Hurricane Ivan in 2004 and then validated their models against two other hurricanes. Their results reveal that: 1) the location and duration of hurricane power outages can be accurately predicted, 2) seasonal hurricane count forecasts can be substantially improved by using more complete climate data and flexible statistical methods, and 3) climate change induced changes in hurricane hazards will likely lead to increased numbers and durations of outages. Accurate prediction of power outages is a critical capability for utility companies to plan their restoration efforts more efficiently; design, site, and harden critical energy- and electricity-dependent infrastructure; and reduce outage frequencies and durations. The next step is to couple the appropriate methods with downscaled climate models to deliver final project methodological insights on the impacts of climate change on coastal energy system vulnerabilities.


Nateghi, R., S. D. Guikema, and S. M. Quiring. 2011. “Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes,” Risk Analysis, 31(12), 1897–1906. DOI: 10.1111/j.1539-6924.2011.01618.x.