Exploring the Effects of Different Snowstorm Types on School Closings in Central New York State

Authors: Justin Hartnett*,
Topics: Climatology and Meteorology, Hazards, Risks, and Disasters, Hazards and Vulnerability
Keywords: Snowstorms, lake-effect, snowfall, school closings, snow day
Session Type: Poster
Day: 4/4/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download

Central New York is infamous for seasonal snowfall totals regularly exceeding 254 cm. Snowfall in this region helps generate revenue through winter recreation, it provides a substantial snow cover to insulate plants, it replenishes water resources in soils; and it helps regulate air temperatures. Snowstorms are especially influential on society, as school officials are confronted with difficult decisions as to whether they should close the district. These decisions can result in ‘wasted’ snow days if the severe weather does not come to fruition, or life-altering consequences if correct decisions are not made.

The decision to close a school district is confounded by uncertainties in meteorological models, which are especially difficult in Central New York because snowfall occurs from a variety of snowstorm types, including lake-effect snowstorms. This research examines whether school closings in Central New York are influenced by the type of snowstorm to affect the region. Days in which the 99 school districts in Central New York issued a ‘snow day’ were examined from 1985/86 – 2014/15. Similarities in the days in which ‘snow days’ occurred are examined, including information about the districts (e.g. number of students, size of district, average distance traveled by students) and about the snowstorm (e.g. snowfall, type, temperature). In due course, the goal is to provide a standardized regression model capable of determining whether a school district should close. This will allow a more standardized methodology f school closings in Central New York, and will reduce the likelihood of false positives and false negatives.

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