14.3 Enhancing Ice Storm Detection and Characterization from the New York State Mesonet

Thursday, 16 January 2020: 2:00 PM
203 (Boston Convention and Exhibition Center)
Junhong (June) Wang, SUNY, Albany, NY; SUNY Albany, Albany, NY; and J. P. Shultis, J. A. Brotzge, C. D. Thorncroft, and N. P. Bassill

Intense ice storms lead to extremely hazardous conditions which can last up to days or weeks, causing large amounts of damage to property and infrastructure over their duration. The Northeast experiences the highest frequency of ice storms within the entirety of the United States. During last 22 years (1997-2018) there were a total of 45 ice storms recorded in New York State (NYS). They affected a total of 257 counties during this time in NYS and caused total $102 billion damages. This work attempts to enhance ice storm detection and characterization utilizing the data collected from the New York State Mesonet (NYSM). NYSM consists of 126 stations across the state collecting measurements of multiple meteorological variables, as well as images every five minutes. In addition, in a first for a state mesonet, NYSM has three sub-networks (“Profiler”, “Flux”, and “Snow”) comprised of 17, 17, and 20 sites to provide atmospheric vertical profiles, the surface energy budget, and snow water equivalent, respectively. NYSM is the first network operationally making 10-m wind measurements from two independent sensors: propeller wind monitor and sonic anemometer. During ice storm events, large wind speed differences would be reported between propeller and sonic anemometers because the propeller had developed a coating of ice, thus either completely stopping its spinning, or slowing it drastically. An algorithm is developed to detect and record freezing rain (i.e. ice storm) events based on NYSM wind speed differences, a temperature threshold, precipitation measurements and camera images. Looking at a case from April 14-16 2018, it was seen that using this method to detect freezing rain vastly improved the spatial and temporal extent of freezing rain event than what was reported. This information is incredibly important for the public, and may be used to make better decisions in the future. NYSM data are also useful to understand the ice storm formation processes, especially the thermodynamic and wind profiles from the NYSM profiler network.
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