P52     Predicting wet snow and freezing rain icing events over Vermont using a WRF ensemble.

Siuta, David, and Jason Shafer, Northern Vermont University – Lyndon

Icing from wet snow and freezing rain storms have large societal impacts, which include disrupted travel, increased insurance claims, and prolonged power outages. Improved predictions of wet snow and freezing rain icing amounts allow for optimized storm planning and response strategies by utilities and agencies of transportation. Forecasts of wet snow and freezing rain icing accumulations over Vermont are evaluated for case studies spanning the winters of 2017-2018 and 2018-2019. Forecasts from a 15-member high-resolution Weather Research and Forecasting (WRF) model ensemble are compared to an ensemble of global model forecasts from the North American Ensemble Forecast System (NAEFS), Global Forecast System (GFS), and Global Deterministic Prediction System (GDPS). The mesoscale WRF ensemble is better able to discriminate the snow-phase type (wet snow vs. dry snow) at short lead times, which is often a function of terrain elevation. The global ensemble, however, remains more skilled in overall QPF forecasting for the case studies tested. Both forecast systems struggled to predict the magnitude of icing accumulation from freezing rain events.