Assessing Dynamic and Thermodynamic Variability in Initial and Boundary Conditions for Snowstorm Prediction in the Northeast United States

Abstract

Winter storms present significant hazards across the Northeast United States, often disrupting daily life. Numerical modeling of these storms is an important component for understanding the physical processes that cause significant impacts and for predicting their effects ahead of time. Initial and boundary conditions are an essential component to limited-area modeling; variability in these conditions can significantly alter the simulations. While previous modeling studies have investigated sensitivities in model physics, there has been limited exploration of the impact of different initial condition sources; differences within these sources can include horizontal and vertical resolution, data assimilation schemes, and domain. This study aims at identifying the sources of variability from the initialized atmospheric fields within four different sets of initial conditions and their impact on the prediction of winter precipitation processes. The key finding was that relative humidity across different initial and boundary conditions produced the most uncertainty on the model simulation, while variability in temperature or synoptic conditions had a minor role. To explain the precipitation differences seen during the simulations, vertical profiles of relative humidity and temperature were connected to microphysical hydrometeor species tracked within the model. The findings suggested that relative humidity differences are heavily linked to precipitation accumulation discrepancies and were the main source of variability from the initial conditions. These results call for the development of more accurate relative humidity profiles for model initial and boundary conditions.