This study investigates the synoptic and mesoscale features associated with specific snowband motion characteristics. A classification scheme for snowband motion will be described, wherein bands are categorized into four modes: laterally translating, laterally quasi-stationary, hybrid, and pivoting. Laterally translating bands exhibit predominantly cross-axis motion, thereby favoring uniform snowfall accumulation along their paths. In contrast, laterally quasi-stationary bands exhibit near-zero cross-axis motion, favoring heavy snowfall accumulation along a narrow corridor. Hybrid bands are dominated by along-axis motion, but with a concurrent cross-axis component of motion, favoring snowfall accumulations on an intermediate spatial scale. Finally, pivoting bands exhibit pronounced rotation over a limited region, yielding a quasi-stationary band in that region, where heavy snowfall accumulation is particularly favored. Using archived WSR-88D data, 71 heavy snow cases in the Northeast U.S. (spanning the years 2005–2010) have been classified according to this scheme. Gridded data from the 0.5° resolution NCEP Climate Forecast System Reanalysis are used to identify synoptic and mesoscale features associated with these cases.
Preliminary results suggest that low- to mid-tropospheric temperature advection, flow confluence/diffluence, curvature, and horizontal shear in the near-band environment are useful in distinguishing between environments favoring laterally translating, laterally quasi-stationary, hybrid, or pivoting snowband modes. These environmental attributes may be described by partitioning the Q-vector into along- and cross-isentrope components. Composite fields that typify the synoptic and mesoscale environments attending each snowband mode will be presented, along with selected case studies.