Synoptic climatology of snowfall in the northeastern United States: an analysis of snowfall amounts from diverse synoptic weather types

In this study, a quantitative estimate of the amount of snowfall resulting from several different snowstorm types or tracks is presented. A modified version of Kalkstein and Corrigan's (1986) Temporal Synoptic Index (TSI) is employed to classify synoptic weather patterns across the northeastern US from 1971-2000. First, six-hourly winter weather data from Syracuse, NY is subjected to principal components analysis. A cluster analysis is subsequently performed on the loading scores, generating a calendar of 19 synoptic weather types. These types are grouped into three primary synoptic weather patterns: Coastal Storms, Lake-Effect Patterns, and Overrunning Storms. The calendar of synoptic types is compared to a gridded snowfall dataset for the northeastern United States to determine the amount and spatial distribution of snowfall from each of the primary synoptic weather patterns.; Overrunning storms are found to cause most of the snowfall in most areas; however, lake-effect snowfall predominates in areas closer to the Great Lakes and the higher elevations of the Appalachians, where as much as 50% of all snowfall is attributable to lake-effect snowfall. While coastal storms are significant snowfall producers along the eastern seaboard, they do not provide the majority of the snowfall in any portion of the study area. Two and three-day sequences of synoptic weather type are analyzed and classified according to snowstorm type. These sequences correspond to storm tracks and weather patterns described in the literature, including persistent lake-effect events, Colorado Low Pressure systems, Alberta Clippers, and events that transition from coastal storms to lake-effect patterns.