Enhancing Ice Storm Detection from the New York State Mesonet

Lecture Center Concourse

Intense freezing rain/drizzle events 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. This work attempts to gather a more high-resolution picture of ice storm spatial coverage, as well as duration of freezing effects, 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. 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. With visits from field technicians, it was revealed that the propeller had developed a coating of ice, thus either completely stopping its spinning, or slowing it drastically. Looking at the winter of 2017-8, data was analyzed across all stations that reported similar wind speed differences to create an algorithm to detect freezing events with more rigor. It was found that along with wind speed differences, a temperature threshold can also be drawn to more accurately label an event as freezing rain. Looking at a case from April 14-15 2018, it was seen that using this method to detect freezing rain vastly improved the spatial extent of freezing rain than what was reported. This information is incredibly important for the public, and may be used to make better decisions in the future.