Understanding and Representing Atmospheric Convection across Scales - ParaCon Phase 2

理解和表示跨尺度的大气对流 - ParaCon 第 2 阶段

• 批准号: NE/T003898/1
• 负责人: Andrew Ross
• 金额: $ 43.23万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FT003898%2F1
• 关键词: Understanding; Representing; Atmospheric; Convection; across

Cumulus clouds are produced by the vigorous ascent of buoyant air, a process known as convection. The weather and climate of the tropics are dominated by cumulus clouds, and severe weather at all latitudes involves convection. Convection communicates heat and moisture from the Earth's surface throughout the atmosphere. It is the main process controlling the change of temperature and moisture content with height in the tropical atmosphere. On the global scale, cumulus clouds are responsible for the majority of the rainfall, and convection is a crucial component in the overall pattern of the Earth's atmospheric flows.Computer modelling of the atmosphere is essential for both numerical weather prediction (NWP) and climate projections. Society benefits enormously from their outputs to inform decision making on all scales from the individual member of the public to weather-sensitive business activities, the energy sector, the emergency services, and government policy on climate risks. Computer models for NWP and for climate projection divide the atmosphere into boxes with typical horizontal sizes of 10km and 100km respectively. Convective elements such as thunderstorms, on the other hand, are typically only around 1km in size so they cannot be explicitly represented in the models. Instead we must somehow estimate what cumulus clouds will be present in each of the boxes and what their collective effects will be on the larger-scale atmosphere. This is known as a cumulus parameterization.Cumulus parameterization is a stubborn and difficult problem and is the largest single uncertainty that we face. It is a severe and unforgiving test of just how well we understand the fundamental science of convection and its role in the atmosphere. Defects in the existing parameterizations are known to translate into serious deficiencies in weather and climate models. These include errors in the distribution, timing, and intensity of convective rainfall, as well as the behaviour of larger-scale weather systems that are coupled to convection.ParaCon Phase 2 is a wide-ranging plan to redesign the convection parameterization for the Met Office Model, to demonstrate clear improvements in model fidelity and performance, and to lay the groundwork for the next generation of parameterization research.In Phase 1 we have developed a new convection scheme infrastructure called CoMorph, which enables many of the assumptions that are made in such parameterizations to be relaxed, removed or generalized and we have begun the process of developing a formulation based on alternative and more general assumptions. Also in Phase 1 we have performed promising investigations into radically different formulations based on modelling convection as a manifestation of turbulence, and on a multi-fluid approach that relaxes the usual assumptions even further than CoMorph does.In Phase 2 we will continue the development of CoMorph with a view to its adoption for operational forecasting. Building on the work in Phase 1, improved formulations for the components of the scheme will be developed and implemented. The performance of CoMorph will be evaluated in a wide range of test cases. These will include comparison with a suite of high-resolution simulations of idealized convective archetypes conducted in Phase 1, as well as a range of operational-style configurations.In Phase 2 we will also continue to develop the turbulence-based and multi-fluid-based approaches and to evaluate their potential for representing convection in atmospheric models. A key goal will be to clarify the relationship between the three approaches and to understand the extent to which some unification or combination of the approaches might be possible and beneficial.

积云云是由浮力空气的剧烈上升产生的，这是一种称为对流的过程。热带地区的天气和气候主要由云层云主导，所有纬度的恶劣天气都涉及对流。对流在整个大气中传达了地球表面的热量和水分。这是控制温度和水分含量随热带气氛中高度的变化的主要过程。在全球范围内，积云云负责大部分降雨，对流是地球大气流的整体模式的关键组成部分。社会从其产出中巨大的收益，以从个人成员到对天气敏感的商业活动，能源部门，紧急服务和政府政府对气候风险的所有规模上的决策。 NWP和气候投影的计算机模型将大气分为典型的水平尺寸分别为10公里和100公里。另一方面，对流元素（例如雷暴）的大小通常仅约1公里，因此在模型中不能明确表示它们。取而代之的是，我们必须以某种方式估计每个盒子中都会出现哪些积云云以及它们对大规模氛围的集体影响会产生什么。这被称为积云参数化。库姆群岛参数化是一个固执且困难的问题，是我们面临的最大的单一不确定性。这是我们对我们理解对流的基本科学及其在大气中的作用的严重测试。已知现有参数化的缺陷将转化为天气和气候模型中的严重缺陷。这些包括在分布，时机和对流降雨的强度以及与对流耦合的大型天气系统的行为。Paracon第2阶段是一项广泛的计划，是重新设计MET办公室模型的对流参数化的广泛计划，以证明模型和绩效的明确改进，并为下一阶段的研究提供了新的一代研究。 Comorph，可以使许多参数化中做出的假设放松，去除或广义，我们已经开始基于替代性和更一般假设来开发公式的过程。同样，在第1阶段，我们对基于建模对流作为湍流的表现进行了对根本不同的配方进行了有前途的研究，并采用了一种多流体方法，该方法比Comorph更宽松了通常的假设。在第2阶段，我们将继续开发Comorph，以对其进行操作预测。在第1阶段的工作的基础上，将开发和实施改进该计划组件的配方。 Comorph的性能将在广泛的测试用例中进行评估。这些将包括与第1阶段进行的理想对流原型以及一系列操作式配置的一系列高分辨率模拟的比较。在第2阶段，我们还将继续开发基于湍流和基于多流体的方法，并评估它们在大气模型中代表对流的潜力。一个关键目标是阐明这三种方法之间的关系，并了解方法可能有可能且有益的某种统一或组合的程度。

项目成果

Understanding mechanisms for trends in Sahelian squall lines: Roles of thermodynamics and shear

了解萨赫勒飑线趋势的机制：热力学和切变的作用

• DOI: 10.1002/qj.3955
• 发表时间: 2021
• 期刊: Quarterly Journal of the Royal Meteorological Society
• 影响因子: 8.9
• 作者: Bickle M

Kilometer-scale simulations of trade-wind cumulus capture processes of mesoscale organization

中尺度组织信风积云捕获过程的公里级模拟

• DOI: 10.1002/essoar.10511907.1
• 发表时间: 2022
• 作者: Saffin L

The Influence of the Diurnal Cycle in Wind Shear and Thermodynamics on Squall Lines in the West African Monsoon

风切变的昼夜循环和热力学对西非季风飑线的影响

• DOI: 10.1175/jas-d-21-0025.1
• 发表时间: 2022
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Bickle M