Intra-event variability of lake-effect snowstorms over the Tug Hill Plateau
Topics: Climatology and Meteorology
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Keywords: lake-effect, intra-event variability, Great Lakes, snowfall intensity
Session Type: Virtual Poster
Day: Friday
Session Start / End Time: 4/9/2021 11:10 AM (Pacific Time (US & Canada)) - 4/9/2021 12:25 PM (Pacific Time (US & Canada))
Room: Virtual 51
Authors:
Christopher Karmosky, SUNY - Oneonta
Justin J Hartnett, SUNY Oneonta
Arthur Samel, Bowling Green State University
Adam Burnett, Colgate University
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Abstract
Lake-effect snowstorms are notoriously difficult to forecast due to their localized nature and sensitivity to slight variations in wind directions. As atmospheric conditions change, the location and prevalence of intense (15 cm hr-1) snowband(s) can shift. This intra-event variability can drastically affect a location’s snowfall totals following a lake-effect storm. The purpose of this study is to examine the drivers behind the location and intensity of lake-effect snowbands over the Tug Hill Plateau of New York State. Snowfall events from the 1999/00 season to the 2018/19 season with at least 22.9 cm (9”) of snowfall at Redfield, NY were categorized as lake-effect snowstorms, lake-enhanced snowstorms, or synoptic storms. For lake-effect or lake-enhanced storms, NEXRAD data were used to estimate the snowfall intensity. It is evident that even the largest snowfall-producing events undergo considerable intra-event variability in the location and intensity of the snowband(s). To examine possible drivers of this intra-event variability, we examined the meteorological conditions during intense snowfall rates. Variables of interest included sea level pressure surface-850 mb temperature lapse rate, CAPE, vertical velocity, boundary layer height, 1000 mb specific humidity, and fetch across Lake Ontario. We hope to identify clear drivers behind intense snowfall-producing lake-effect snowbands over Redfield and potential causes for intra-event variability. Ultimately, results from this research can be used to reduce the uncertainty in snowfall forecasting for lake-effect events in the Great Lakes region. Furthermore, we seek to distinguish pure lake-effect events from those of mixed origins or lake-enhanced synoptic snowfall.
