  Ice storms pose significant damage risk to electric utility infrastructure.
In an attempt to improve storm response and minimize costs, energy companies
have supported the development of ice accretion forecasting techniques
utilizing meteorological output from numerical weather prediction (NWP) models.
The majority of scientific literature in this area focuses on the application
of NWP models, such as the Weather Research and Forecasting (WRF) model, to ice
storm case studies, but such analyses tend to provide little verification of
output fidelity prior to use. This study evaluates the performance of WRF in
depicting the 21-23 December 2013 New England ice storm at the surface and in
vertical profile. A series of sensitivity tests are run using eight planetary
boundary layer (PBL) physics parameterizations, three reanalysis datasets, two
vertical level configurations, and with and without grid nudging. Simulated
values of precipitation, temperature, wind speed, and wind direction are
validated against surface and radiosonde observations at several station
locations across northeastern U.S. and southeastern Canada. The results show
that, while the spatially and temporally averaged statistics for near-surface
variables are consistent with those of select ice-storm case studies,
near-surface variables are highly sensitive to model when examined at the
station level. No single model configuration produces the most robust solution
for all variables or station locations, although one scheme generally yields
model output with the least realism. In all, we find that careful model
sensitivity testing and extensive validation are necessary components for
minimizing model-based biases in simulations of ice storms.
