Poster Session P2.51 Prediction of snow particle habit types within a single-moment bulk microphysical scheme

Wednesday, 12 July 2006
Grand Terrace (Monona Terrace Community and Convention Center)
Mark T. Stoelinga, University of Washington, Seattle, WA; and C. P. Woods and J. D. Locatelli

Handout (221.2 kB)

Bulk microphysical schemes typically represent snow particles in a broad-brush, simplistic way. One common assumption is that snow particles are spheres of constant density, and that their fall speeds follow a single velocity-diameter power law relationship. These assumptions affect virtually every production process for snow that is represented in the scheme, often in quantitatively significant ways. We have attempted to improve the representation of snow by allowing it to form in a number of different habit types, each with its own mass-diameter and velocity-diameter relationship (as determined empirically from snow particle observations). Each habit type gains mass by deposition when temperature and humidity conditions exist that are conducive to growth of that habit type. The mass fractions of the different habit types are tracked with separate prognostic equations, but for simplicity, all processes other than depositional growth are applied to the snow field as a whole, with mass-weighted mean values of habit-dependent parameters (such as the constants in the velocity and mass power laws) used in the calculations.

The enhanced scheme is verified for two case studies: a mid-latitude frontal precipitation band over the northeastern Pacific Ocean and a frontal/orographic precipitation event over the Cascade Mountains in Oregon. The scheme performs well at producing particle types that were observed (and not producing those that were not observed). In addition to improving quantitative precipitation forecasts, the scheme can also provide valuable particle type forecasts for snowfall at the ground, which in turn may be valuable for snow density/depth and avalanche forecasting.

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