Simulation Of Blowing Snow In The Canadian Arctic Using A Double-Moment Model

We describe in this paper the development of a double-moment modelof blowing snow and its application to the Canadian Arctic. Wefirst outline the formulation of the numerical model, whichsolves a prognostic equation for both the blowing snow mixingratio and total particle numbers, both moments of particles thatare gamma-distributed. Under idealized simulations, the modelyields realistic evolutions of the blowing snow particledistributions, transport and sublimation rates as well as the thermodynamic fields at low computational costs. A parametrizationof the blowing snow sublimation rate is subsequently derived. The model and parametrization are then applied to a Canadian Arctictundra site prone to frequent blowing snow events. Over a period of210 days during the winter of 1996/1997, the near-surfacerelative humidity consistently approaches saturationwith respect to ice. These conditions limit snowpack erosion byblowing snow sublimation to 3 mm snow water equivalent (swe)with surface sublimation removing an additional 7 mm swe.We find that our results are highly sensitiveto the proper assimilation of the humidity measurements and the evolving thermodynamic fields in the atmospheric boundary layer during blowingsnow. These factors may explain the lower values of blowing snow sublimationreported in this paper than previously published for the region.     

WRF模式云参数化方案对一次深对流系统模拟的验证和改进

使用中尺度数值模式WRF中的双参数云微物理方案WDM6针对2008年台风“凤凰”登陆过程中造成的强降水进行数值模拟,通过卫星模拟器利用MTSAT-1R和TRMM卫星观测的红外云顶黑体亮温TBB、PR雷达反射率资料使用统计方法验证模拟结果。通过修改云水向雨水自动转化过程、冰晶核化过程、雪和霰的下落末速度、雪和霰的截距进行敏感性试验,减小模拟结果和卫星观测结果的差异。研究结果表明:WDM6方案模拟的台风“凤凰”登陆后的降水,强对流云系及对流柱状雷达回波基本符合实况,但模拟结果局部偏强。WDM6方案模拟产生了较多的浅对流云,低估了对流云系的出现频率。不同云类型模拟的雷达回波均偏强,对流云系雷达回波垂直分布接近观测。敏感性试验结果说明修改WDM6方案中云水向雨水自动转化率有效地改善了模拟效果。同时发现云滴初始数浓度影响云水向雨水自动转化率并最终影响云系结构和雷达反射率的模拟结果,过高的云滴初始数浓度会使模拟结果变差。