670 WRF Simulation, PBL Sensitivity, and Analysis of the December 2013 New England Ice Storm

Tuesday, 14 January 2020
Hall B (Boston Convention and Exhibition Center)
Julia M. Simonson, Univ. of Maine, Orono, ME; and S. D. Birkel, K. A. Maasch, P. A. Mayewski, B. Lyon, and A. M. Carleton

Handout (1.9 MB)

Ice storms pose significant damage risk to electric utility infrastructure. In 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. 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, conditions are not sufficiently reproduced at the station scale to the precision required for accurate classification of precipitation type. No single PBL scheme produces the most robust solution for all variables or station locations, although one scheme generally yields the least realistic model output. Model output is also highly sensitive to the choice of reanalysis [we tested the ECMWF ERA-Interim (ERAI), ERA5, and the NCEP North American Regional Reanalysis (NARR)], the use of grid nudging, and the number of model levels. In all, we find that careful model sensitivity testing and extensive validation are necessary components for robust simulation of ice storms.
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