Abstract
This paper presents a new triple-moment blowing snow model PIEKTUK-T by including predictive equations for three moments of the gamma size distribution. Specifically, predictive equations for the total number concentration, total mass mixing ratio, and total radar reflectivity for blowing snow are included. Tests in the context of idealized experiments and observed case studies demonstrate that the triple-moment model performs better than the double-moment model PIEKTUK-D in predicting the evolution of the number concentration, mixing ratio, shape parameter, and visibility in blowing snow, provided that the fall velocities for the total number concentration, mass mixing ratio, and radar reflectivity are weighted by the same order of the respective moments in both models. The power law relationship between the radar reflectivity factor and particle extinction coefficient found in PIEKTUK-T is consistent with one observed in snow storms. Coupling of the triple-moment blowing snow model to an atmospheric model would allow realistic studies of the effect of blowing snow on weather and climate.
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