Hydrometeor Lofting and Mesoscale Snowbands

Environments that accompany mesoscale snowbands in extratropical cyclones feature strong midlevel frontogenesis and weak symmetric stability, conditions conducive to vigorous ascent. Prior observational and numerical studies document the occurrence of upward vertical velocities in excess of 1 m s−1 near the comma head of winter cyclones. These values roughly correspond to the terminal fall velocity of snow; snow lofting has been measured directly with vertically pointing radars. Here, we investigate the occurrence of lower-tropospheric snow lofting near mesoscale bands and its contribution to snowfall heterogeneity. We test the hypothesis that hydrometeor lofting substantially influences snowfall distributions by analyzing the vertical snow flux in case-study simulations, by computing snow trajectories, and by testing sensitivity of simulated snowbands to parameterized snow terminal fall velocity and advection. These experiments confirm the presence of upward snow flux in the lower troposphere upstream of simulated mesoscale snowbands for two events (27 January 2015 and 2 February 2016). The band of lower-tropospheric lofting played a more important role in the January 2015 case relative to the February 2016 event. Lofting enhances the horizontal advection of snow by increasing hydrometeor residence time aloft, influencing the surface snowfall distribution. Experimental simulations illustrate that while lofting and advection influence the snow distribution, these processes reduce snowfall heterogeneity, contrary to our initial hypothesis. Our findings indicate that considerable horizontal displacement can occur between the locations of strongest ascent and heaviest surface snowfall. Numerical forecasts of snowbands are sensitive to formulations of terminal fall velocity of snow in microphysical parameterizations due to this lofting and transport process.

Viscous symmetric stability of circular flows

The linear stability properties of viscous circular flows in a rotating environment are studied with respect to symmetric perturbations. Through the use of an effective energy or Lyapunov functional, we derive sufficient conditions for Lyapunov stability with respect to such perturbations. For circular flows with swirl velocity V(r) we find that Lyapunov stability is determined by the properties of the function ℱ(r) = (2V/r + f)/Q (with f the Coriolis parameter, r the radius and Q the absolute vorticity) instead of the customary Rayleigh discriminant Φ(r) = (2V/r + f)Q. The conditions for stability are valid for flows with non-zero Q everywhere. Further, the flows are presumed stationary, incompressible and velocity perturbations are required to vanish at rigid boundaries. For Lyapunov stable flows an upper bound for the increase of the total perturbation energy due to transient non-modal growth is derived which is valid for any Reynolds number. The theory is applied to Couette flow and the Lamb–Oseen vortex.

Correlations between Analyses and Forecasts of Banded Heavy Snow Ingredients and Observed Snowfall

North American Mesoscale (NAM) model forecasts of the occurrence, magnitude, depth, and persistence of ingredients previously shown to be useful in the diagnosis of banded and/or heavy snowfall potential are examined for a broad range of 25 snow events, with event total snowfall ranging from 10 cm (4 in.) to over 75 cm (30 in.). The ingredients examined are frontogenetical forcing, weak moist symmetric stability, saturation, and microphysical characteristics favorable for the production of dendritic snow crystals. It is shown that these ingredients, previously identified as being critical indicators for heavy and/or banded snowfall in major storms, are often found in smaller snowfall events. It is also shown that the magnitude, depth, and persistence of these ingredients, or combinations of these ingredients, appear to be good predictors of event total snowfall potential. In addition, a relationship is demonstrated between temporal trends associated with one of the ingredients (saturated, geostrophic equivalent potential vorticity) and event total snowfall. Correlations between forecast values of these ingredients and observed snowfall are shown to decrease substantially as forecast lead time increases beyond 12 h. It is hypothesized that model forecast positioning and timing errors are primarily responsible for the lower correlations associated with longer-lead forecasts. This finding implies that the best forecasts beyond 12 h may be produced by examining the diagnostics of heavy snow ingredients from a single, high-resolution model to determine snowfall potential, then using ensemble forecasting approaches to determine the most probable location and timing of any heavy snow.

A Forecast Strategy for Anticipating Cold Season Mesoscale Band Formation within Eastern U.S. Cyclones

An ingredients-based, time- and scale-dependent forecast strategy for anticipating cold season mesoscale band formation within eastern U.S. cyclones is presented. This strategy draws on emerging conceptual models of mesoscale band development, advances in numerical weather prediction, and modern observational tools. As previous research has shown, mesoscale band development is associated with frontogenesis in the presence of weak moist symmetric stability and sufficient moisture. These three parameters—frontogenesis, weak moist symmetric stability, and moisture—are used as the ingredients for identifying mesoscale band development in this strategy. At forecast projections beyond 2 days, the strategy assesses whether cyclogenesis is expected. Within 2 days of the event, the strategy places the band ingredients in the context of the broader synoptic flow, with attention to where deformation zones are present, to assess whether banding is possible. Within 1 day of the event, the strategy focuses on assessment of the ingredients to outline when and where band formation is favored. Plan-view and cross-sectional analyses of gridded model fields in conjunction with high-resolution model guidance are used to assess the likelihood of banding and to outline the threat area. Within 12 h, short-range forecasts of the band ingredients are evaluated in concert with observations to make specific band predictions. Particular emphasis is placed on the evolution of the frontogenetic forcing and moist symmetric stability. During the event, trends in observations and short-range model forecasts are used to anticipate the movement, intensity, and dissipation of the band. The benefits and practical challenges associated with the proposed strategy are illustrated through its operational application to the 25 December 2002 northeast U.S. snowstorm, during which intense mesoscale snowband formation occurred. Forecast products from this event demonstrate how the forecast strategy can lead to heightened situational awareness, in this case resulting in accurate band forecasts. This application shows that accurate operational forecasts of mesoscale bands can be made based on our current conceptual understanding, observational tools, and modeling capabilities.