Analysis of Ice-to-Liquid Ratios during Freezing Rain and the Development of an Ice Accumulation Model

Abstract

ubstantial freezing rain or drizzle occurs in about 24% of winter weather events in the continental United States. Proper preparation for these freezing rain events requires accurate forecasts of ice accumulation on various surfaces. The Automated Surface Observing System (ASOS) has become the primary surface weather observation system in the United States, and more than 650 ASOS sites have implemented an icing sensor as of March 2015. ASOS observations that included ice accumulation were examined from January 2013 through February 2015. The data chosen for this study consist of 60-min periods of continuous freezing rain with precipitation rates ≥ 0.5 mm h?1 (0.02 in. h?1) and greater than a trace of ice accumulation, yielding a dataset of 1255 h of observations. Ice:liquid ratios (ILRs) were calculated for each 60-min period and analyzed with 60-min mean values of temperature, wet-bulb temperature, wind speed, and precipitation rate. The median ILR for elevated horizontal (radial) ice accumulation was 0.72:1 (0.28:1), with a 25th percentile of 0.50:1 (0.20:1) and a 75th percentile of 1.0:1 (0.40:1). Strong relationships were identified between ILR and precipitation rate, wind speed, and wet-bulb temperature. The results were used to develop a multivariable Freezing Rain Accumulation Model (FRAM) for use in predicting ice accumulation incorporating these commonly forecast variables as input. FRAM performed significantly better than other commonly used forecast methods when tested on 20 randomly chosen icing events, with a mean absolute error (MAE) of 1.17 mm (0.046 in.), and a bias of ?0.03 mm (?0.001 in.).