Snowstorms in Upstate New York: synoptics, spatial modeling and temporal variability
This dissertation examines the characteristics of snowstorms that affect Central New York, a subsection of the eastern Great Lakes region, in a series of chapters organized as journal articles. The first article develops a classification scheme to categorize snowstorms in Central New York from the 1...
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SURFACE at Syracuse University
2019
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| Online Access: | https://surface.syr.edu/etd/1120 https://surface.syr.edu/cgi/viewcontent.cgi?article=2121&context=etd |
| Summary: | This dissertation examines the characteristics of snowstorms that affect Central New York, a subsection of the eastern Great Lakes region, in a series of chapters organized as journal articles. The first article develops a classification scheme to categorize snowstorms in Central New York from the 1985/86 season to the 2014/15 season. Twelve different snowstorm types were classified by their connection to the Great Lakes, the presence or absence of a synoptic low, or their area of cyclogenesis. The second article uses the 2055 classified snowstorms to examine their relative contribution to seasonal snowfall totals. Although lake-effect snowstorms are the dominant snowfall contributor for most of Central New York, their contributions vary considerably across the region. These storms contribute approximately 50% of the seasonal snowfall totals in the Tug Hill, and only about 25% in southeastern Central New York. Instead, Nor’easters are the dominant snowfall contributor in southeastern Central New York. Model results can accurately estimate seasonal snowfall contributions using a location’s latitude, longitude, elevation and distance from the lake, or its latitude, longitude, and 5 km elevation exposure. The third article examines the typical snowfall distributions and synoptic conditions associated with the different snowstorms. Localized snowfall patterns are most common when there is a surface high pressure over the United States and a low over northeastern Canada. This setup combined with cold air (< 20˚C), often initiates the formation of lake-effect or lake-enhanced snow, potentially leading to the localized snowfall patterns. Regional-wide snowfall was most common with cyclonic snowstorms (Nor’easters and Rocky lows). These storms are often associated with an omega-blocking pattern, and heavier snowfall is common when air trajectories pass directly over the long-axis of Lake Ontario. The fourth and fifth articles examine how snowfall totals for the different snowstorm types have changed over time, and potential causes for these changes. This is the first study to directly assess seasonal snowfall trends for individual snowstorm types. Lake-effect snowfall significantly (p ≤ 0.05) increased in areas furthest from the lake from 1985/86 – 2014/15, while snowfall from clippers decreased across the entire region. Snowfall from lake snowstorms also increased in Region 3, but trends were inconsistent. Snowfall significantly increased in the late-1980s and late 1990s, but significantly decreased in the mid-1990s. The variability in trends may be linked to environmental conditions, as air temperatures were incorporated in 21/35 of the significant models. The Great Lakes also influenced seasonal snowfall totals mostly in Regions 1 and 3, while precipitation and average temperatures are the most influential factors in Regions 4 and 5. Teleconnections affect seasonal snowfall the most for Nor’easters, as above normal snowfall often occurs with the positive phases of the AO and PDO and the negative phase of the NAO. Lake-effect snowfall is mostly influenced by the WP, while teleconnections in the Atlantic Ocean and Arctic largely affect snowfall totals from storms originating in western Canada. Together, these articles highlight the importance of examining individual snowstorm types in the Great Lakes region and showcase potential forcings behind seasonal variations. This study also highlights the importance of understanding the seasonal snowfall contribution of different snowstorm types and how it is changing, so that accurate predictions can be made for future climate scenarios. |
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