Abstract
Nine in ten major outages in the US have been caused by hurricanes. Long-term outage risk is a function of climate change-triggered shifts in hurricane frequency and intensity; yet projections of both remain highly uncertain. However, outage risk models do not account for the epistemic uncertainties in physics-based hurricane projections under climate change, largely due to the extreme computational complexity. Instead they use simple probabilistic assumptions to model such uncertainties. Here, we propose a transparent and efficient framework to, for the first time, bridge the physics-based hurricane projections and intricate outage risk models. We find that uncertainty in projections of the frequency of weaker storms explains over 95% of the uncertainty in outage projections; thus, reducing this uncertainty will greatly improve outage risk management. We also show that the expected annual fraction of affected customers exhibits large variances, warranting the adoption of robust resilience investment strategies and climate-informed regulatory frameworks.
Highlights
Nine in ten major outages in the US have been caused by hurricanes
There exists a significant body of literature on the relationship between climate change and hurricane activity, with most studies reporting a decrease in storm frequency due to climate c hange[20,48,49,53]
Simple probabilistic assumptions are made to perturb hurricane activity. We address these fundamental gaps by proposing a transparent and efficient approach to, for the first time, link the knowledge provided by physics-based projections of hurricane activity under climate change with electric power distribution infrastructure risk models, providing a pathway for better integration of climate physics within intricate engineering risk models
Summary
Nine in ten major outages in the US have been caused by hurricanes. Long-term outage risk is a function of climate change-triggered shifts in hurricane frequency and intensity; yet projections of both remain highly uncertain. Outage risk models do not account for the epistemic uncertainties in physics-based hurricane projections under climate change, largely due to the extreme computational complexity. In an effort to minimize the impact of hurricane-induced power outages, several research studies have developed forecast models to provide estimates of the extent of power outages prior to a storm landfall[7,29,31,33,34,37]. Such short-term forecasts allow utilities to improve their preparation, response and recovery efforts. Potential economic damages are known to increase with storm frequency and intensity[19,39], including at the extremes[4]
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