对流冷锋的阵风锋跟踪
Tracking the Gust Fronts of Convective Cold Pools
摘要：
人们越来越认识到冷池可以影响新对流单体的形成。然而，通过冷池相互作用对流组织的全部复杂性知之甚少。这种认识的缺乏可能部分是由于复杂的动力模式所形成的降水细胞和他们的冷池。此外，冷池如何确切地相互作用还不清楚。为了更好地了解这种动态，我们开发了一个冷池阵风锋的跟踪算法。而不是跟踪热力学异常，这通常不符合阵风锋边界，我们的方法跟踪动态冷池流出。我们的算法首先确定的降水事件的轨迹。第二，相对于该原点和对于每个方位角箱，采用近表面水平径向速度$v_r$中的最陡梯度来确定冷池阵风前缘的相应轨迹。最陡的$v_r$ -梯度意味着最大的上升气流速度，因此最强的动态触发。结果进行了比较，以前的算法的基础上最陡的温度梯度-突出的好处，这里描述的方法在确定动态活跃的阵风锋区。将该方法应用于一系列数值实验，该算法成功地跟踪了冷池的合奏。一个给定的事件的峰值雨强和最大$v_r$为它的相关冷池阵风锋之间出现线性关系-一个关系被发现是几乎独立的特定的敏感性实验。
英文摘要：
It is increasingly acknowledged that cold pools can influence the initiation of new convective cells. Yet, the full complexity of convective organization through cold pool interaction is poorly understood. This lack of understanding may partially be due to the intricacy of the dynamical pattern formed by precipitation cells and their cold pools. Additionally, how exactly cold pools interact is insufficiently known. To better understand this dynamics, we develop a tracking algorithm for cold pool gust fronts. Rather than tracking thermodynamic anomalies, which do not generally coincide with the gust front boundaries, our approach tracks the dynamical cold pool outflow. Our algorithm first determines the locus of the precipitation event. Second, relative to this origin and for each azimuthal bin, the steepest gradient in the near-surface horizontal radial velocity $v_r$ is employed to determine the respective locus of the cold pool gust front edge. Steepest $v_r$-gradients imply largest updraft velocities, hence strongest dynamical triggering. Results are compared to a previous algorithm based on the steepest gradient in temperature --- highlighting the benefit of the method described here in determining dynamically active gust front regions. Applying the method to a range of numerical experiments, the algorithm successfully tracks an ensemble of cold pools. A linear relation emerges between the peak rain intensity of a given event and maximal $v_r$ for its associated cold pool gust front --- a relation found to be nearly independent of the specific sensitivity experiment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
