Saide Pablo E, Thompson Gregory, Eidhammer Trude, da Silva Arlindo M, Pierce R Bradley, Carmichael Gregory R
Advanced Study Program and Atmospheric Chemistry Observations and Modeling Lab, National Center for Atmospheric Research, Boulder, Colorado, USA.
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA.
J Geophys Res Atmos. 2016 Sep 16;121(17):10294-10311. doi: 10.1002/2016JD025056. Epub 2016 Aug 23.
We use the WRF system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the US during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included and smoke emissions are constrained using an inverse modeling technique and satellite-based AOD observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRF-Chem for its use in applications such as NWP and cloud-resolving simulations.
我们使用WRF系统来研究中美洲生物质燃烧烟雾对美国春季发生的几次龙卷风爆发的影响。该模型配置了一种可感知气溶胶的微物理参数化方法,能够以经济高效的方式解析气溶胶-云-辐射相互作用,用于数值天气预报(NWP)应用。模型纳入了主要气溶胶排放,并使用反演建模技术和基于卫星的气溶胶光学厚度(AOD)观测数据来约束烟雾排放。开启和关闭火灾排放的模拟结果显示,在所研究的所有龙卷风爆发事件中都存在烟雾,并且烟雾导致气溶胶数浓度增加。然而,只有在低层云的云滴数浓度大幅增加,从而改变龙卷风形成的环境条件(云底变浅和低层风切变增强)的情况下,烟雾才会增加龙卷风发生和增强的可能性。烟雾的吸收和垂直范围也有影响,云层高度处的烟雾吸收往往会消耗云层,而云层上方的烟雾吸收会导致逆温层增强。将这些结果与配置了更复杂的气溶胶粒径和成分表示以及不同光学特性、微物理和激活方案的WRF-Chem模拟结果进行比较,我们发现在模拟的气溶胶光学厚度和气溶胶对风暴附近环境的影响方面存在相似性。这为可感知气溶胶的微物理方案提供了可靠性,作为一种计算成本较低的替代方案,可用于NWP和云解析模拟等应用中的WRF-Chem。