COMPASS: COnvection Morphology Parameter Space Study

了解和预报深层对流风暴的强度和结构特征作为风暴环境的函数是一个有趣的科学问题，也是业务预报员的极大兴趣。本研究旨在探索调节对流风暴形态和强度的大参数空间的几个新维度。该研究将使用全物理三维云模拟模型进行，初始化的环境设计允许对八个独立参数进行独立调查，这些参数被认为是风暴结构对风暴环境敏感性的主要原因。探索性研究已经证明，至少在全参数空间的一部分，风暴对大多数这些参数具有很大的敏感性。已经发现的敏感性包括整体对流有效势能（CAPE）和整体剪切，包裹浮力和剪切剖面的形状，以及混合层和湿层的深度。相对湿度廓线的形状和云底温度是其他可能重要的参数。虽然已经报告的初步结果是探索许多相关参数空间维度的第一步，但研究结果需要扩展以包含更大范围的参数值。为了满足这些需求，该项目将通过构建和分析更完整的理想化云模拟档案来扩展先前的研究。由于构建模拟环境和分析模型输出所需的工具已经大部分到位，因此预计进展会很快。在分析模式数据时，重点将放在量化风暴形态变化和记录各种相互竞争的物理机制的影响上。预计对这些模拟的研究将大大提高对大范围环境条件下对流风暴行为的认识，并将使改进风暴预报的目标取得进展。

Understanding and forecasting the intensity and structural characteristics of deep convective storms as a function of the storm environment is an interesting scientific problem and of great interest to operational forecasters. This research seeks to explore several new dimensions of the large parameter space that regulates the morphology and intensity of convective storms. The study will be undertaken using a full-physics three dimensional cloud simulation model, initialized with environments designed to permit independent investigation of eight separate parameters that are believed to be responsible for much of the sensitivity of storm structure to storm environment. Exploratory studies have already demonstrated the existence of large sensitivities of storms to most of these parameters, in at least portions of the full parameter space. Sensitivities already found include bulk convective available potential energy (CAPE) and bulk shear, the shapes of parcel buoyancy and shear profiles, and the depths of both the mixed layer and moist layer. The shape of the relative humidity profile and the temperature at cloud base are other parameters of potential importance. Although the preliminary results already reported constitute a first step in exploring many of the relevant parameter space dimensions, the findings need to be extended to embrace a larger range of values of parameters. In order to address these needs, this project will expand the previous research by building and analyzing a more complete archive of idealized cloud simulations. Progress is expected to be rapid because the tools needed to build the simulation environments and to analyze the model output are already mostly in place. In the analysis of the model data, emphasis will be placed on quantifying the storm morphology variations and on documenting the effects of the various competing physical mechanisms. It is expected that study of these simulations will significantly enhance understanding of convective storm behavior within a broad range of environmental conditions and will allow progress towards the goal of improving storm forecasts.