Composite analysis of heavy snow events within the Springfield and St. Louis, Missouri National Weather Service County Warning Areas

A climatology and composite analysis of 28 cold season (October 1980 - March 2008) heavy snow events within the Springfield (SGF) and St. Louis, Missouri (LSX) National Weather Service (NWS) County Warning Areas (CWAs) are presented utilizing snowfall data from the National Climatic Data Center (NCDC) Cooperative Summary of the Day (COOP) collection. COOP snow events with amounts greater than 6 in. (15.24 cm) in at least one CWA were identified as heavy snow cases. Sixty-four heavy snow cases were identified for the period of study and were then classified based on the orientation of the axis of greatest snowfall. This procedure yielded 36 southwest-northeast (SW/NE) oriented cases, 21 west-east (W/E) cases, 5 northwest-southeast (NW/SE) cases, and two "other" cases where there was no well-defined axis of greatest snowfall orientation. Since the most common orientation was SW/NE, these cases were investigated further. System-relative composites were generated using the General Meteorological Package (GEMPAK) and the North American Regional Reanalysis (NARR) dataset, where the initial analysis time (i.e., t = 0 h) for each SW/NE case was defined as the date and time when the NARR 850-hPa low was closest to the 92nd meridian. Composites were also calculated at 6-h intervals beginning 12 h before (t = -12 h) to 12 h after (t = +12 h) the initial analysis time to depict the evolution of features associated with heavy snow-producing systems in the region. The composites indicated the presence of large-scale ascent through jet-streak interaction and differential positive vorticity advection. As the composite system entered the region, an increase in mesoscale forcing collocated within an area of large-scale ascent developed over the study area in association with strengthening low-level frontogenesis and reduced symmetric stability. In addition, a case study was presented to illustrate how the composite fields are characteristic of an individual event. Finally, case-by-case variability was investigated by comparing the individual cases with the composited fields through a statistical analysis to assist in determining the degree of representativeness of the composite fields.