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Kristopher J. Sanders and Brian L. Barjenbruch


Substantial 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.).

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Adam L. Houston, Noah A. Lock, Jamie Lahowetz, Brian L. Barjenbruch, George Limpert, and Cody Oppermann


The Thunderstorm Observation by Radar (ThOR) algorithm is an objective and tunable Lagrangian approach to cataloging thunderstorms. ThOR uses observations from multiple sensors (principally multisite surveillance radar data and cloud-to-ground lightning) along with established techniques for fusing multisite radar data and identifying spatially coherent regions of radar reflectivity (clusters) that are subsequently tracked using a new tracking scheme. The main innovation of the tracking algorithm is that, by operating offline, the full data record is available, not just previous cluster positions, so all possible combinations of object sequences can be developed using all observed object positions. In contrast to Eulerian methods reliant on thunder reports, ThOR is capable of cataloging nearly every thunderstorm that occurs over regional-scale and continental United States (CONUS)-scale domains, thereby enabling analysis of internal properties and trends of thunderstorms.

ThOR is verified against 166 manually analyzed cluster tracks and is also verified using descriptive statistics applied to a large (~35 000 tracks) sample. Verification also relied on a benchmark tracking algorithm that provides context for the verification statistics. ThOR tracks are shown to match the manual tracks slightly better than the benchmark tracks. Moreover, the descriptive statistics of the ThOR tracks are nearly identical to those of the manual tracks, suggesting good agreement. When the descriptive statistics were applied to the ~35 000-track dataset, ThOR tracking produces longer (statistically significant), straighter, and more coherent tracks than those of the benchmark algorithm. Qualitative assessment of ThOR performance is enabled through application to a multiday thunderstorm event and comparison to the behavior of the Storm Cell Identification and Tracking (SCIT) algorithm.

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John L. Campbell, Lindsey E. Rustad, Sarah Garlick, Noah Newman, John S. Stanovick, Ian Halm, Charles T. Driscoll, Brian L. Barjenbruch, Elizabeth Burakowski, Steven D. Hilberg, Kristopher J. Sanders, Jason C. Shafer, and Nolan J. Doesken


Ice storms are important winter weather events that can have substantial environmental, economic, and social impacts. Mapping and assessment of damage after these events could be improved by making ice accretion measurements at a greater number of sites than is currently available. There is a need for low-cost collectors that can be distributed broadly in volunteer observation networks; however, use of low-cost collectors necessitates understanding of how collector characteristics and configurations influence measurements of ice accretion. A study was conducted at the Hubbard Brook Experimental Forest in New Hampshire that involved spraying water over passive ice collectors during freezing conditions to simulate ice storms of different intensity. The collectors consisted of plates composed of four different materials and installed horizontally; two different types of wires strung horizontally; and rods of three different materials, with three different diameters, and installed at three different inclinations. Results showed that planar ice thickness on plates was 2.5–3 times as great as the radial ice thickness on rods or wires, which is consistent with expectations based on theory and empirical evidence from previous studies. Rods mounted on an angle rather than horizontally reduced the formation of icicles and enabled more consistent measurements. Results such as these provide much needed information for comparing ice accretion data. Understanding of relationships among collector configurations could be refined further by collecting data from natural ice storms under a broader range of weather conditions.

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