Analysis and prediction of heavy banded snow events in the Northeastern United States using independent variables

Wintertime precipitation has a large impact on the northeastern United States each year. Within any given storm, there is potential for mesoscale banding, some of which can produce heavy amounts of snowfall. Previous studies have shown that banded snow events require strong values of frontogenesis, weak moist symmetric stability, and moisture to form within any given storm. This study seeks to find answers to two questions. The first is whether it is possible to predict mesoscale snow banding events based on independent variables such as topographic height, frontogenesis, equivalent potential vorticity, and mixing ratio at multiple atmospheric levels. The second question is whether these variables can be combined into a forecasting tool to predict the occurrence of snow banding and, if so, what combination of these variables can be used to predict the possibility and location of the mesoscale snow band. For this study, storms were first identified using GOES satellite archive data, obtained from the NCDC GIBBS archive (http://www.ncdc.noaa.gov/gibbs). Storms seen on satellite imagery were gathered into a database. Using WSR-88D radar data, banding events were identified in the storm database with the storms containing changes in 24 hour snow depth of 8 inches or greater. Using classification systems developed by Novak et al (2004), the type of banding was identified within storms. A gridded area was defined over the northeastern United States with 20 km spacing between grid points. The grid was rotated 45 degrees to align with the axis of the Appalachian Mountains to align the vertical axis of the grid with the highest peaks of the region and the horizontal axis perpendicular to the mountain peaks. Topography for the region of study was classified based on elevation using the Integrated Data Viewer (IDV) data source of the National Geophysical Data Center (NGDC) ETOPO1 dataset. Heights were interpolated to the grid points developed in the 20 km resolution grid. Basic classification schemes involving elevation were employed to correlate the existence of a banding event with the topographical classification. Model data from the North American Regional Reanalysis (NARR-A) were obtained and used in GEMPAK, with data interpolated to the 20 km resolution grid. Results from analysis of multiple storm cases will be presented in this poster.