Diagnosing Snowband Predictability Using a Multimodel Ensemble System

Abstract

he forecast uncertainty of mesoscale snowband formation and evolution is compared using predictions from a 16-member multimodel ensemble at 12-km grid spacing for the 25 December 2002, 12 February 2006, and 14 February 2007 northeast U.S. snowstorms. Using these predictions, the case-to-case variability in the predictability of band formation and evolution is demonstrated. Feature-based uncertainty information is also presented as an example of what may be operationally feasible from postprocessing information from future short-range ensemble forecast systems. Additionally, the initial condition sensitivity of band location in each case is explored by contrasting the forecast evolutions of initial condition members with large differences in snowband positions. Considerable uncertainty in the occurrence, and especially timing and location, of band formation and subsequent evolution was found, even at forecast projections <24 h. The ensemble provided quantitative mesoscale band uncertainty information, and differentiated between high-predictability (14 February 2007) and low-predictability (12 February 2006) cases. Among the three cases, large (small) initial differences in the upper-level PV distribution and surface mean sea level pressure of the incipient cyclone were associated with large (small) differences in forecast snowband locations, suggesting that case-to-case differences in predictability may be related to the quality of the initial conditions. The complexity of the initial flow may also be a discriminator. Error growth was evident in each case, consistent with previous mesoscale predictability research, but predictability differences were not correlated to the degree of convection. Discussion of these results and future extensions of the work are presented.