65th IHC Booklet/Program (pdf - 4.9MB) - Office of the Federal ...

A Methodology for Incorporating Hurricane Forecast Errors into Decision-Support
Systems for Energy and Utility Companies
A. B. Schumacher 1 , S. M. Quiring 2
(schumacher@cira.colostate.edu)
1 Cooperative Institute for Research in the Atmosphere;
2 Department of Geography, Texas A&M University
A variety of decision-support systems, such as those employed by energy and utility
companies, utilize the National Hurricane Center (NHC) forecasts of track and intensity to
inform operational decision-making as a hurricane approaches. Changes in hurricane intensity
and track, especially just prior to landfall, can negatively impact the accuracy of these decisionsupport
systems. This study demonstrates how the Monte Carlo wind speed probability
(MCWSP) can be applied to develop probabilistic estimates of the impact of the approaching
storm. Our methodology utilizes the 1000 individual forecast realizations generated by the
MCWSP algorithm, instead of the wind speed probabilities, coupled with a power outage model
to generate a distribution of power outage predictions for three past storms. Based on power
outage data from a Gulf Coast utility company we found that the ensemble average was a better
predictor of damage to the power system than predictions made using the official National
Hurricane Center forecast. We believe that this methodology can be used to incorporate
information about tropical cyclone forecast errors into decision support systems that utilize NHC
track and intensity data.
Poster Session – Page 34