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On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model

机译:用云系统解析模型模拟理想化超级单体风暴中气溶胶效应的鲁棒性

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A cloud system-resolving model (the Weather Research and Forecasting model) with 1 km horizontal grid spacing is used to investigate the response of an idealized supercell storm to increased cloud droplet concentrations associated with polluted conditions. The primary focus is on exploring robustness of simulated aerosol effects in the face of complex process interactions and feedbacks between the cloud microphysics and dynamics. Simulations are run using sixteen different model configurations with various microphysical or thermodynamic processes modified or turned off. Robustness of the storm response to polluted conditions is also explored for each configuration by performing additional simulations with small perturbations to the initial conditions. Differences in the domain-mean accumulated surface precipitation and convective mass flux between polluted and pristine conditions are small for almost all model configurations, with relative differences in each quantity generally less than 15%. Configurations that produce a decrease (increase) in cold pool strength in polluted conditions also tend to simulate a decrease (increase) in surface precipitation and convective mass flux. Combined with an analysis of the dynamical and thermodynamic fields, these results indicate the importance of interactions between microphysics, cold pool evolution, and dynamics along outflow boundaries in explaining the system response. Several model configurations, including the baseline, produce an overall similar storm response (weakening) in polluted conditions despite having different microphysical or thermodynamic processes turned off. With hail initiation turned off or the hail fallspeed-size relation set to that of snow, the model produces an invigoration instead of weakening of the storm in polluted conditions. These results highlight the difficulty of foreseeing impacts of changes to model parameterizations and isolating process interactions that drive the system response to aerosols. Overall, these findings are robust, in a qualitative sense, to small perturbations in the initial conditions. However, there is sensitivity in the magnitude, and in some cases sign, of the storm response to polluted conditions with small perturbations in the temperature of the thermal used to initiate convection (less than ±0.5 K) or the vertical shear of the environmental wind (±5%). It is concluded that reducing uncertainty in simulations of aerosol effects on individual deep convective storms will likely require ensemble methods in addition to continued improvement of model parameterizations.
机译:使用水平网格间距为1 km的云系统解析模型(天气研究和预报模型)来研究理想化的超级单体风暴对与污染条件相关的云滴浓度增加的响应。面对云微观物理与动力学之间复杂的过程交互作用和反馈,主要重点是探索模拟气溶胶效应的鲁棒性。使用十六种不同的模型配置进行仿真,并修改或关闭各种微物理或热力学过程。通过对初始条件进行较小扰动的附加模拟,还探索了每种配置对风暴对受污染条件的响应的鲁棒性。对于几乎所有模型配置,在污染和原始条件之间的区域平均累积表面降水和对流质量通量的差异都很小,每种数量的相对差异通常小于15%。在受污染的条件下会导致冷池强度降低(增加)的构造还倾向于模拟表面降水和对流质量通量的降低(增加)。结合对动力学和热力学领域的分析,这些结果表明微观物理学,冷池演化和沿流出边界的动力学之间相互作用的重要性对于解释系统响应非常重要。尽管关闭了不同的微物理或热力学过程,包括基线在内的几种模型配置在受污染的条件下仍会产生总体上相似的风暴响应(减弱)。在关闭冰雹引发或将冰雹坠落速度-大小关系设置为雪的情况下,该模型会产生振奋作用,而不是在污染情况下减弱风暴。这些结果凸显了预见模型参数化更改的影响以及隔离驱动系统对气溶胶响应的过程相互作用的困难。总体而言,从质的角度来看,这些发现对初始条件下的小扰动具有鲁棒性。但是,风暴对受污染条件的响应在一定程度上具有敏感性,在某些情况下甚至有迹象表明,用于引发对流的热温度(小于±0.5 K)或环境风的垂直切变的扰动很小。 (±5%)。结论是,除了继续改进模型参数化之外,减少对单个深对流风暴的气溶胶效应模拟中的不确定性可能还需要整体方法。

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