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

基本信息

批准号：
NE/T003863/1
负责人：
John Thuburn
金额：
$ 63.97万
依托单位：
UNIVERSITY OF EXETER
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%2FT003863%2F1
关键词：
Understanding Representing Atmospheric Convection across

项目摘要

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.

积云是由浮力空气剧烈上升产生的，这一过程称为对流。热带地区的天气和气候以积云为主，所有纬度地区的恶劣天气都涉及对流。对流将地球表面的热量和水分传递到整个大气层。它是控制热带大气中温度和水分含量随高度变化的主要过程。在全球范围内，积云造成了大部分降雨，而对流是地球大气流动总体模式的重要组成部分。大气的计算机建模对于数值天气预报 (NWP) 和气候预测都至关重要。社会从他们的产出中获益匪浅，为从公众个人到对天气敏感的商业活动、能源部门、应急服务和政府气候风险政策等各个层面的决策提供信息。 NWP 和气候预测的计算机模型将大气划分为典型水平尺寸分别为 10 公里和 100 公里的方框。另一方面，雷暴等对流元素的大小通常只有 1 公里左右，因此无法在模型中明确表示。相反，我们必须以某种方式估计每个盒子中将出现哪些积云，以及它们对更大范围大气的集体影响。这被称为积云参数化。积云参数化是一个顽固而困难的问题，也是我们面临的最大的单一不确定性。这是对我们对对流基础科学及其在大气中的作用的理解程度的严峻且无情的考验。众所周知，现有参数化的缺陷会转化为天气和气候模型的严重缺陷。其中包括对流降雨的分布、时间和强度方面的误差，以及与对流耦合的大规模天气系统的行为。ParaCon 第 2 阶段是一项广泛的计划，旨在为英国气象局重新设计对流参数化模型，展示模型保真度和性能的明显改进，并为下一代参数化研究奠定基础。在第一阶段，我们开发了一种名为 CoMorph 的新对流方案基础设施，它使许多在这种参数化中做出的假设被放宽、删除或概括，我们已经开始开发基于替代和更一般假设的公式。同样在第一阶段，我们基于对流建模作为湍流的表现，以及比 CoMorph 更放松通常假设的多流体方法，对完全不同的公式进行了有前景的研究。在第二阶段，我们将继续开发CoMorph 旨在将其用于运营预测。在第一阶段工作的基础上，将制定并实施该计划各组成部分的改进方案。 CoMorph 的性能将在广泛的测试用例中进行评估。这些将包括与第一阶段进行的一套理想对流原型的高分辨率模拟以及一系列操作式配置的比较。在第二阶段，我们还将继续开发基于湍流和多流体的基于方法并评估它们在大气模型中表示对流的潜力。一个关键目标是澄清三种方法之间的关系，并了解这些方法的某种统一或组合可能和有益的程度。