Takeishi Azusa, Storelvmo Trude, Fierce Laura
Department of Geology and Geophysics Yale University New Haven CT USA.
Currently at Laboratoire d'Aérologie University of Toulouse/CNRS Toulouse France.
J Geophys Res Atmos. 2020 Jun 27;125(12):e2019JD031890. doi: 10.1029/2019JD031890. Epub 2020 Jun 16.
Aerosol emissions from forest fires may impact cloud droplet activation through an increase in particle number concentrations ("the number effect") and also through a decrease in the hygroscopicity of the entire aerosol population ("the hygroscopicity effect") when fully internal mixing is assumed in models. This study investigated these effects of fire particles on the properties of simulated deep convective clouds (DCCs), using cloud-resolving simulations with the Weather Research and Forecasting model coupled with Chemistry for a case study in a partly idealized setting. We found that the magnitude of the hygroscopicity effect was in some cases strong enough to entirely offset the number/size effect, in terms of its influence on modeled droplet and ice crystal concentrations. More specifically, in the case studied here, the droplet number concentration was reduced by about 37% or more due solely to the hygroscopicity effect. In the atmosphere, by contrast, fire particles likely have a much weaker impact on the hygroscopicity of the pre-existing background aerosol, as such a strong impact would occur only if the fire particles mixed immediately and uniformly with the background. We also show that the differences in the number of activated droplets eventually led to differences in the optical thickness of the clouds aloft, though this finding is limited to only a few hours of the initial development stage of the DCCs. These results suggest that accurately and rigorously representing aerosol mixing and in models is an important step toward accurately simulating aerosol-cloud interactions under the influence of fires.
在模型假设完全内部混合的情况下,森林火灾产生的气溶胶排放可能会通过增加粒子数浓度(“数量效应”)以及降低整个气溶胶群体的吸湿性(“吸湿性效应”)来影响云滴活化。本研究利用天气研究与预报模型与化学模型耦合的云分辨模拟,在部分理想化的环境中进行案例研究,调查了火灾粒子对模拟深对流云(DCCs)特性的这些影响。我们发现,就其对模拟的液滴和冰晶浓度的影响而言,吸湿性效应的强度在某些情况下足以完全抵消数量/尺寸效应。更具体地说,在本文研究的案例中,仅由于吸湿性效应,液滴数浓度就降低了约37%或更多。相比之下,在大气中,火灾粒子对预先存在的背景气溶胶吸湿性的影响可能要弱得多,因为只有当火灾粒子与背景立即且均匀混合时才会产生如此强烈的影响。我们还表明,最终活化液滴数量的差异导致了高空云层光学厚度的差异,不过这一发现仅限于深对流云初始发展阶段的几个小时。这些结果表明,在模型中准确而严格地表示气溶胶混合是朝着准确模拟火灾影响下的气溶胶 - 云相互作用迈出的重要一步。