Numerical prediction of fog: A novel parameterization for droplet formation

A novel aerosol activation scheme was developed and implemented into the WRF Thompson–Eidhammer Aerosol‐Aware microphysical module. While in most of the numerical weather prediction (NWP) models the activation is based on updraft velocity, even in the fog, the new parameterization considers the local rate of cooling and water vapor flux in the evaluation of the aerosol activation rate. In addition, diagnostic variables are added to evaluate the visibility reduction due to formation of haze droplets. The impact of changing the activation scheme is demonstrated by a case study of a well‐observed fog event. Data observed during the fog event campaign at Budapest and observed at standard meteorological stations are compared with the output of the numerical model. The results are summarized as follows: (i) the inhomogeneous spatial and temporal distribution of the number concentration of droplets is an inherent characteristic of the new parameterization scheme. (ii) Compared to the prior parameterization based on updraft velocity, the new parameterization scheme increases the number concentration of the droplets significantly, especially at the top of the fog. As a consequence, it reduces the downward short‐wave radiation flux prolonging the lifetime of the fog by about 30–60 min. (iii) Analyses reveal that earlier dissipation of the fog comparing to the observed data cannot be explained only by overestimation of the downward short‐wave radiation flux. (iv) The new method is able to evaluate the reduction of visibility due to haze.

一种新的气溶胶活化方案被开发出来，并应用于WRF汤普森 - 艾德哈默尔气溶胶感知微物理模块中。在大多数数值天气预报（NWP）模型中，活化是基于上升气流速度的，即使在雾中也是如此，而新的参数化方案在评估气溶胶活化率时考虑了局部冷却速率和水汽通量。此外，还添加了诊断变量来评估由于霾滴形成而导致的能见度降低。通过对一次观测良好的雾事件的案例研究，展示了改变活化方案的影响。将布达佩斯雾事件活动期间观测到的数据以及在标准气象站观测到的数据与数值模型的输出进行了比较。结果总结如下：（i）液滴数浓度不均匀的时空分布是新参数化方案的固有特征。（ii）与先前基于上升气流速度的参数化方案相比，新的参数化方案显著增加了液滴的数浓度，尤其是在雾顶处。因此，它减少了向下的短波辐射通量，使雾的持续时间延长了约30 - 60分钟。（iii）分析表明，与观测数据相比雾消散更早不能仅仅用向下短波辐射通量的高估来解释。（iv）新方法能够评估由于霾导致的能见度降低。