How Should Snow Squall Warnings Be Verified?

On 30 January 2019, a mesoscale convective system tracked from Ohio to New England, producing snow squalls with observed surface wind gusts up to 56 knots (29 ms^-1). The snow squalls and associated whiteout conditions produced traffic and flight delays throughout the afternoon and evening hours. Around 1730 UTC, low visibility and icy roads from the melting and refreezing of snow on road surfaces caused a 27 vehicle pileup on Route 222 in Berks County, Pennsylvania, resulting in 1 fatality and 23 injuries. All major New York City airports were at a ground stop during the late afternoon hours while the snow squalls moved through.

The 30 January 2019 snow squall event represented the first widespread use of the modern National Weather Service Snow Squall Warning (SQW), which became operational during the winter of 2018-19. A total of 49 SQWs were issued by ten Weather Forecast Offices.

An ongoing operational question is how best to devise a verification methodology for SQWs, given that snow squall impacts - mainly in the form of highway accidents and pileups - are modulated by a number of non-meteorological and human factors. Some of these factors include road design, traffic volume and speed, driver skill, driver situational awareness, and the presence/absence of road chemicals. Conversely, a verification methodology based strictly on directly-sensed meteorological observations (e.g., ≤¼ statute mile visibility in heavy snow lasting < 1 hour along with wind gusts exceeding a specified threshold) may not sample the most intense portion(s) of a snow squall.

It is argued that a “total observation concept” could be applied to the verification of SQWs. In addition to surface observations, this would include utilization of radar reflectivity, webcams, spotter reports, and remotely sensed winds near radar sites coincident with snow squalls. This presentation will cover the mesoscale and synoptic setting of the 30 January 2019 snow squall event and a discussion of potential verification methods for SQWs.