Evaluation of Winter Weather Prediction During Extreme Snowfall Events for the NE US.

M.S. Walters¹, J. Yang¹, M. Koukoula¹, G. Thompson², M. Astitha^1*

¹Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT

²Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO

Snowstorms capable of disrupting society are becoming more common across the eastern United States. For example, from January 5^th to March 22^nd of 2018, five of the top 100 most significant snowstorms, in terms of the total area and total population affected, enveloped the Northeastern United States according to the Northeast Snowfall Impact Scale (NESIS). Roughly 286 million people were directly impacted as a result of all five snowstorms which spanned a total area of 775 million square-miles. During the March 5^th to March 8^th snowstorm alone, a powerful Nor'easter caused whiteout conditions accompanied by wind gusts in excess of 50 miles-per-hour for multiple stations across the Northeastern United States. The combination of winter weather conditions led to hundreds-of-thousands of power outages, numerous road restrictions, the declaration of three states of emergencies, and several fatalities.

Accurate prediction of such extreme snowstorms is essential to protect the safety and well-being of the public and mitigate infrastructural and socioeconomic damages. Numerical Weather Prediction (NWP) of snowstorms faces challenges related to microphysical and boundary layer processes that hinder the accuracy of forecasts. We present an evaluation of winter storm prediction with respect to NWP models for the Northeast United States using WRF 3.7, WRF 3.8, and RAMS/ICLAMS forecasts. Snow storm prediction is evaluated for significant northeast snowstorms from 1997 to 2017 using 109 Meteorological Terminal Aviation Routine Weather Reports (METAR) and available radiosonde stations. Snow events have been identified using the Regional Snowfall Index (RSI) for the Northeast Region and the variables considered for this evaluation include variables associated with winter storm severity, precipitation type, snowfall ratios, snow density, and liquid to ice ratios for both the surface and vertical profiles. The results from the evaluation, including suggestions for improvement of the snow storm forecasts, will be discussed during the presentation of this study.