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LANS Informal Seminar: Peter Watson
October 30, 2019 @ 10:30 CDT
Seminar Title: Building Impact Forecasting Systems Based-on Numerical Weather Prediction Models: Lessons Learned in Weather-Related Power Outage Prediction
Speaker: Peter Watson, PhD Student, University of Connecticut
Date/Time: 2019-10-30 10:30
Location: Bldg. 240, Rm. 1404-05
Description:
With the apparent increase in the frequency and intensity of hurricanes, blizzards, and thunderstorms, predicting the impacts of these natural hazards is becoming more important. For weather-related hazards, Numerical Weather Prediction (NWP) models are perhaps the best way to describe these events in both time and space. However, these physical models currently have distinct technical shortcomings, especially when applied to particular hazards. And impact models forced with NWP forecasts become inextricably linked, where the uncertainties and biases of the weather forecasts are propagated into the impact predictions. The strengths and weaknesses of NWP in terms of what it can accurately predict, and how these aspects can be exploited to create useful, empirical, natural hazard impact models will be discussed. Specifically, lessons learned from creating the Outage Predictions Model (OPM), an operational, machine learning based, power outage prediction systems forced with NWP forecasts, will be presented.
Peter Watson is a PhD Student in Environmental Engineering at the University of Connecticut, and graduate of the University of Chicago (AB ’06). His research interests are in the application of machine learning and other modern modeling techniques to predict the impacts of natural hazards to inform the response, adaptation, and mitigation of these hazards. His PhD thesis focuses on weather-related power outage prediction, and how such models can grow in scale. His research has led to significant improvements to the operational Outage Prediction Model at the University of Connecticut, and to the Hurricane Outage Model at Los Alamos National Laboratory, where he just concluded a summer internship.