COMPASS: COnvection Morphology Parameter Space Study

了解和预报作为风暴环境函数的深对流风暴的强度和结构特征是一个有趣的科学问题，对业务预报员来说也是非常有意义的。 这项研究旨在探索几个新的尺寸的大参数空间，调节对流风暴的形态和强度。 这项研究将使用一个全物理三维云模拟模型进行，初始化的环境设计，允许独立调查的八个独立的参数，被认为是负责风暴结构的风暴环境的敏感性。 探索性研究已经表明，风暴对这些参数中的大多数参数存在很大的敏感性，至少在整个参数空间的一部分。 已经发现的敏感性包括散装对流可用位能（CAPE）和散装剪切，包裹浮力和剪切剖面的形状，以及混合层和潮湿层的深度。 相对湿度廓线的形状和云底温度是其他具有潜在重要性的参数。虽然初步结果已经报告构成了探索许多相关的参数空间维度的第一步，调查结果需要扩展到包括更大范围的参数值。 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以前的研究。 预计进展将很快，因为建立模拟环境和分析模型输出所需的工具已经基本到位。 在分析模型数据时，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加强对各种环境条件下对流风暴行为的了解，并将有助于朝着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.