A study of the microphysical processes in a numerically simulated heavy snowfall event in North China: The sensitivity of different snow intercept parameters
Journal
Meteorology and Atmospheric Physics
Journal Volume
104
Journal Issue
1-2
Pages
1-11
Date Issued
2009
Author(s)
Abstract
We performed a modeling study of the cloud processes in a heavy snowfall event occurring in North China on 20-22 December 2004. The nonhydrostatic Mesoscale Model (MM5) was used to carry out experiments with the Reisner-2 explicit microphysical parameterizations in four nested domains to test the sensitivity of simulated heavy snowfall to different snow intercept parameters. Results show that while the different intercept parameters do not significantly affect the accumulated snowfall amounts at the surface in either total amount or location, some microphysical characteristics of the modeled heavy snowfall event are impacted. The budget of cloud microphysics is analyzed to determine the dominant cloud processes. In the control experiment (CTL) with the snow intercept (Nos) specified as a function of temperature, the primary simulated hydrometeor is snow, and its mixing ratio is an order of magnitude larger than that of the other cloud species. Relative to CTL, the experiment with a fixed intercept (CON3E6) produced lower snow mixing ratios, more cloud water and graupel mixing ratios. Among the two experiments, while snowfall is slightly smaller in CON3E6, other processes like the rate of graupel fall, condensation and evaporation of cloud water, deposition and sublimation of graupel are all larger in CON3E6 than in CTL. Among CTL, CON3E6, and two more experiments (CON2E7: with a smaller fixed intercept; and NOSQS: Nos a function of snow mass mixing ratio), the budget shows that CON3E6 produces the smallest deposition and sublimation of snow, the largest deposition of cloud ice, and the largest conversion from cloud ice to snow. © Springer-Verlag 2008.
SDGs
Type
journal article