LES4CCFM: Using LES to characterize and parameterize the convective cloud field

LES4CCFM：使用 LES 来表征和参数化对流云场

• 批准号: NE/N013727/1
• 负责人: Michael Herzog
• 金额: $ 43.24万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FN013727%2F1
• 关键词: LES4CCFM; Using; LES; characterize; parameterize

The aim of this project is to use Large Eddy Simulations (LES) to characterize and quantify key elements of convection. The work will be performed within the framework of a new parameterization, the Convective Cloud Field Model (CCFM) coupled to the UK Met Office Unified Model (UM). Outcomes from this work will not only lead to a better CCFM but more crucially, will inform any new or existing convection parameterization for the UM. The main focus during the first three years, the exploratory phase, is the improved physical understanding of convection and its representation in CCFM. CCFM is a multi-plume convection scheme and described in Wagner and Graf (2010). Using an entraining parcel model the scheme calculates possible clouds of different initial radii for a given environment and large scale forcing. The distinctive feature of CCFM is the cloud spectrum calculation which determines the actual number of possible clouds. The spectrum calculation is described by a multivariate Lotka-Volterra system in which clouds compete for CAPE (convective available potential energy) through their cloud work function. From the individual clouds and their number, mass fluxes and thus convective heating and moistening can be derived. Initial tests of CCFM have been performed within the ECHAM climate model. In single column mode and in terms of precipitation timing and intensity ECHAM-CCFM performs significantly better than the standard ECHAM. Although no tuning has been applied yet ECHAM-CCFM improves many of the known precipitation biases in global simulations of the atmosphere with prescribed sea surface temperatures. As part of the proposed project we will implement CCFM as an additional option for the parameterization of convection. UM-CCFM will used to translate findings from the LES studies in other work packages and to evaluate the impact of changes in the convection parameterization on large scale dynamics. Since observations are often sparse and incomplete, LES driven by observations offer the best tool for the evaluation of CCFM. High-resolution modelling so far has focused on describing the cumulus ensemble. Despite progress a real breakthrough has not been possible since the cumulus ensemble is an average over very different entities that strongly interact and that is difficult parameterize directly. The proposed project LES4CCFM will overcome limitations of previous high resolution studies by explicitly investigating individual clouds and the resulting cloud spectrum separately. We will use higher spatial resolution (order decametres) than many previous studies to ensure that important parts of the mixing between clouds and their environment through entrainment and detrainment are explicitly resolved. LES studies will be performed in three consecutive work packages. First, we improve the representation of individual clouds in convection parameterizations by comparing LES output with prediction from the entraining parcel model in CCFM. LES to study entrainment, detrainment will start from a known, thus prescribed cloud base. Atmospheric profiles will be based on field campaigns and intensive field observations. In a second work package will focus on the convective cloud trigger by performing LES with a fully interactive boundary layer including surface fluxes, cloud microphysics and radiation. This work will replace with currently rather simple and ad hoc convective cloud trigger in CCFM with one that is more sophisticated and physical based. As part of a third work package we will characterize the convective cloud spectrum as it evolves over time and after it reaches equilibrium. We will evaluate the predator-prey assumption in the CCFM spectrum calculation. The outcome will not only be a new convection scheme within the UM with much broader physical basis but in addition will deliver new quantitative insight into convective processes that is crucial for any convection parameterization development.

该项目的目的是利用大涡模拟（LES）来表征和量化对流的关键要素。这项工作将在一个新的参数化框架内进行，即对流云场模型（CCFM）与英国气象局统一模型（UM）耦合。这项工作的结果不仅将导致更好的CCFM，更重要的是，将为UM的任何新的或现有的对流参数化提供信息。前三年（探索阶段）的主要重点是提高对对流及其在CCFM中的表示的物理理解。CCFM是一种多羽流对流方案，Wagner和Graf（2010）对此进行了描述。该方案利用夹带包模式计算给定环境和大尺度强迫下不同初始半径的可能云。CCFM的显著特点是云谱计算，它决定了可能云的实际数量。频谱计算由多元Lotka-Volterra系统描述，其中云通过其云功函数竞争CAPE（对流有效势能）。从单个云及其数量，可以推导出质量通量，从而推导出对流加热和润湿。CCFM已在ECHAM气候模式中进行了初步试验。在单柱模式下，在降水时间和降水强度方面，ECHAM- ccfm明显优于标准ECHAM。ECHAM-CCFM虽然没有应用调优，但在具有规定海面温度的全球大气模拟中，它改善了许多已知的降水偏差。作为拟议项目的一部分，我们将实施CCFM作为对流参数化的附加选项。UM-CCFM将用于将LES研究的结果转化为其他工作包，并评估对流参数化变化对大尺度动力学的影响。由于观测往往是稀疏和不完整的，由观测驱动的LES为CCFM的评估提供了最好的工具。到目前为止，高分辨率模型主要集中在描述积云集合上。尽管取得了进展，但真正的突破还不可能，因为积云集合是在非常不同的实体上的平均值，这些实体相互作用强烈，很难直接参数化。拟议的LES4CCFM项目将克服以往高分辨率研究的局限性，明确地分别研究单个云和由此产生的云谱。我们将使用比许多以前的研究更高的空间分辨率（十米数量级），以确保通过夹带和夹带在云与其环境之间混合的重要部分得到明确的解决。LES研究将在三个连续的工作包中进行。首先，通过比较LES输出和CCFM中包裹模型的预测，我们改进了对流参数化中单个云的表示。LES研究夹带、夹带将从已知的、因而规定的云基开始。大气概况将以实地活动和密集的实地观测为基础。在第二个工作包中，将通过使用包括表面通量、云微物理和辐射在内的完全交互边界层执行LES，重点研究对流云触发器。这项工作将取代目前在CCFM中相当简单和特别的对流云触发器，使用一个更复杂和基于物理的触发器。作为第三个工作包的一部分，我们将描述对流云谱随时间演变和达到平衡后的特征。我们将评估CCFM频谱计算中的捕食者-猎物假设。结果将不仅是UM内具有更广泛物理基础的新对流方案，而且还将提供对对流过程的新的定量见解，这对于任何对流参数化的发展都是至关重要的。

项目成果

Two-Dimensional Evaluation of ATHAM-Fluidity, a Nonhydrostatic Atmospheric Model Using Mixed Continuous/Discontinuous Finite Elements and Anisotropic Grid Optimization

• DOI: 10.1175/mwr-d-15-0398.1
• 发表时间: 2016-10
• 期刊: Monthly Weather Review
• 影响因子: 3.2
• 作者: J. Savre;J. Percival;M. Herzog;C. Pain

A General Description of Entrainment in Buoyant Cloudy Plumes Including the Effects of Mixing-Induced Evaporation

浮力多云羽流夹带的一般描述，包括混合引起的蒸发的影响

• DOI: 10.1175/jas-d-17-0326.1
• 发表时间: 2019
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Herzog M