Abstract
Thunderstorms are one of the most damaging weather phenomena in the United States, but they are also one of the least predictable. This unpredictable nature can make it especially challenging for emergency responders, infrastructure managers, and power utilities to be able to prepare and react to these types of events when they occur. Predictive analytical methods could be used to help power utilities adapt to these types of storms, but there are uncertainties inherent in the predictability of convective storms that pose a challenge to the accurate prediction of storm-related outages. Describing the strength and localized effects of thunderstorms remains a major technical challenge for meteorologists and weather modelers, and any predictive system for storm impacts will be limited by the quality of the data used to create it. We investigate how the quality of thunderstorm simulations affects power outage models by conducting a comparative analysis, using two different numerical weather prediction systems with different levels of data assimilation. We find that limitations in the weather simulations propagate into the outage model in specific and quantifiable ways, which has implications on how convective storms should be represented to these types of data-driven impact models in the future.
Highlights
IntroductionWeather-related power outages, and the severe weather events that cause them, pose a persistent threat to the functioning of the infrastructure and economy of the United States
Weather-related power outages, and the severe weather events that cause them, pose a persistent threat to the functioning of the infrastructure and economy of the United States.These types of power outages affect millions of people and cost the U.S economy tens of billions of dollars every year; the rate at which they occur appears to be increasing [1]
While the two thunderstorm-related outage models shown here are acceptably skilled at predicting the total number of damages for each storm event, they have difficulty predicting the location of storm impacts
Summary
Weather-related power outages, and the severe weather events that cause them, pose a persistent threat to the functioning of the infrastructure and economy of the United States. These types of power outages affect millions of people and cost the U.S economy tens of billions of dollars every year; the rate at which they occur appears to be increasing [1]. Anticipating the damages that storms can cause is a critical step in electrical utility managers’ storm outage management process. Changes in the climatic patterns of thunderstorms can already be seen in a time series analysis [5], and long-term climate projections suggest that, because of climate change, thunderstorms are likely to become stronger, more frequent, and more damaging [6,7]
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