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Activity Number: 199 - SPEED: Data Expo
Type: Contributed
Date/Time: Monday, July 30, 2018 : 11:35 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #332685
Title: The Impact of Bias and Uncertainty of Weather Forecasts on Storm Events
Author(s): Mary Frances Dorn* and Kimberly Kaufeld
Companies: Los Alamos National Laboratory and Los Alamos National Laboratory
Keywords: weather; uncertainty; kriging; forecasting

Tropical and winter storms can cause widespread damage to electric distribution networks. These distribution networks are mostly above ground, and are exposed to direct damage from severe weather conditions associated with these storms. For example, during winter storms, the combined stress of the weight of ice, the increased wind resistance of the conductors, and broken tree limbs can damage lines, poles, and support structures. Since winter storms are difficult to identify, we analyze patterns in weather forecasts to identify these events and validate them against the historical records from the National Weather Service. We also compare forecasted wind data from tropical storms to imperfect historical data in order to develop a model that we can be used to supplement the wind data available to help predict winter storms. Finally, the bias and uncertainty of using different spatial scales have not been addressed in the electrical power world. We explore different methods to assess the impact of the varying spatial scales on the electrical distribution network.

Authors who are presenting talks have a * after their name.

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