A novel turbulence closure for high-fidelity numerical weather prediction
用于高保真数值天气预报的新型湍流闭合
基本信息
- 批准号:NE/X018164/1
- 负责人:
- 金额:$ 116.2万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The representation of turbulent processes in numerical weather prediction (NWP) models is key for capturing extreme weather events such as convective storms, heavy rainfall and accompanying damaging winds. Convective scale phenomena are manifested locally but are born through the interactions between large and small-scale motions and therefore are challenging to predict. Conventional turbulence modelling requires a clear scale separation between turbulent and synoptic flow implying that all turbulence is parametrised. However, increasing the resolution of NWP models to the sub-kilometric scales makes the boundary layer and the cloud-scale flows partially resolved. Hence, the fundamental assumptions behind turbulence closures do not hold in this resolution regime which is termed the 'grey zone' of turbulence. This results in substantial implications for high-resolution NWP with limitations for the value of sub-kilometric models. The novel method proposed here has the potential to overcome these limitations, thereby realising the full value of sub-kilometre simulations and leading to higher fidelity operational weather forecasts.The project aims to break the deadlock of grey-zone turbulence modelling by developing a dynamic length scale closure. The method will be implemented within the Met Office Unified Model (UM) and is expected to lead to significant improvements in the prediction of high-impact weather events. The novel closure will provide better parametrisation of subgrid turbulence which will result in a more faithful representation of resolved turbulence structures in very high resolution models. This will lead in turn to more accurate simulation of the evolution of the atmospheric boundary layer and its transitions, whilst also improving the representation of moist convective turbulence seamlessly across the scales, thereby better predicting the timing and development of convective clouds. As a starting point, the new method will provide a relaxation of the assumptions made within the current operational UM turbulence blending scheme, a necessary step in order to facilitate adaptation to the sub-km resolution regime. Going a step further and combining the dynamic approach with a higher order closure will result in a truly novel model able to reproduce the transitions of turbulent transport across the scales, from the fully resolved all the way to the fully parametrised turbulence regime.The new method will be developed in steps of varying complexity starting from the dynamic blending of the current operational UM scheme and moving gradually to a higher-order dynamic, 3-dimensional turbulence scheme with self-adapting closure parameters. The new dynamic approaches will be evaluated against the conventional static schemes and validated with data from the WesCon field campaign as well as other readily-available observational datasets. WesCon has an emphasis on the understanding of updrafts and turbulence and their interaction with other processes, making this a unique testbed for the validation of the proposed approach. At the same time our work will focus on thoroughly understanding the length scales of unresolved turbulence, especially in deep storm clouds where current knowledge is limited. We will carefully assess the impact of gradually increasing the complexity of the new method examining the benefits for the increased fidelity of weather forecasts.
数值天气预报(NWP)模式中湍流过程的表示是捕捉对流风暴、暴雨和伴随的破坏性大风等极端天气事件的关键。对流尺度现象是局部表现的,但通过大小尺度运动之间的相互作用而产生,因此很难预测。传统的湍流模拟要求湍流和天气流之间有明显的尺度分离,这意味着所有的湍流都是参数化的。然而,将数值预报模式的分辨率提高到亚千米尺度会使边界层和云尺度的流动得到部分分辨。因此,湍流闭合背后的基本假设在这个被称为湍流灰色区域的分辨率机制中不成立。这对高分辨率数值预报产生了重大影响,并限制了亚公里模式的价值。本文提出的新方法有可能克服这些限制,从而实现亚公里模拟的全部价值,并带来更高保真度的业务天气预报。该项目旨在通过开发动态长度尺度闭合来打破灰色区域湍流模拟的僵局。该方法将在英国气象局统一模式(UM)内实施,预计将大大改进对高影响天气事件的预测。新的闭合将提供更好的亚格子湍流的参数化,这将导致在非常高的分辨率模式中更真实地表示已分辨的湍流结构。这将反过来导致更准确地模拟大气边界层的演变及其转变,同时也改善了湿对流湍流在整个尺度上的无缝表示,从而更好地预测对流云的时间和发展。作为起点,新方法将放宽目前运行的UM湍流混合方案中所做的假设,这是促进适应亚公里分辨率制度的必要步骤。更进一步,将动力学方法与高阶闭合相结合,将得到一个真正新颖的模式,能够再现从完全解析到全参数湍流模式的尺度上的湍流输送的转变。新方法将从当前运行的UM格式的动态混合开始,逐步发展到具有自适应闭合参数的高阶动态三维湍流模式。新的动态方法将对照传统的静态方案进行评估,并用WesCon现场活动的数据以及其他现成的观测数据集进行验证。WesCon的重点是了解上升气流和湍流及其与其他过程的相互作用,使其成为验证所建议方法的独特试验台。与此同时,我们的工作将集中于彻底了解未解决的湍流的长度尺度,特别是在目前知识有限的深风暴云中。我们将仔细评估逐步增加新方法复杂性的影响,研究提高天气预报保真度的好处。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Georgios Efstathiou其他文献
Female carrier of RPGR mutation presenting with high myopia
RPGR突变女性携带者出现高度近视
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:1.2
- 作者:
A. Seliniotaki;A. Ververi;Stavrenia C. Koukoula;Georgios Efstathiou;S. Gerou;N. Ziakas;A. Mataftsi - 通讯作者:
A. Mataftsi
Design and Application of a Data-Independent Precursor and Product Ion Repository
数据独立的前体和产物离子库的设计与应用
- DOI:
10.1007/s13361-012-0416-9 - 发表时间:
2012 - 期刊:
- 影响因子:3.2
- 作者:
K. Thalassinos;K. Thalassinos;J. Vissers;S. Tenzer;Y. Levin;Y. Levin;J. Thompson;David Daniel;Darrin K. Mann;Mark R. DeLong;M. Moseley;A. America;Andrew K. Ottens;G. Cavey;Georgios Efstathiou;J. Scrivens;J. Langridge;S. Geromanos - 通讯作者:
S. Geromanos
Quantitative Phosphoproteome Analysis Unveils LAT as a Modulator of CD3ζ and ZAP-70 Tyrosine Phosphorylation
定量磷酸化蛋白质组分析揭示 LAT 作为 CD3 z 和 ZAP-70 酪氨酸磷酸化的调节剂
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:3.7
- 作者:
M. Salek;S. McGowan;D. Trudgian;Omer Dushek;B. de Wet;Georgios Efstathiou;O. Acuto - 通讯作者:
O. Acuto
Expanded Prader-Willi Syndrome due to an Unbalanced de novo Translocation t(14;15): Report and Review of the Literature
由于不平衡的从头易位 t(14;15) 导致普瑞德-威利综合征扩大:报告和文献综述
- DOI:
10.1159/000504159 - 发表时间:
2019 - 期刊:
- 影响因子:1.7
- 作者:
A. Xefteris;Eleni Sekerli;A. Arampatzi;Sofia Charisiou;E. Oikonomidou;Georgios Efstathiou;N. Peroulis;A. Malamidou;Eleni Tsoulou;E. Agakidou;K. Sarafidis;Antonios Psarakis;Thomas Kataras;G. Daskalakis - 通讯作者:
G. Daskalakis
Incarcerated Amyand hernia with simultaneous rupture of an adenocarcinoma in an inguinal hernia sac: a case report
- DOI:
10.1186/s13256-015-0592-x - 发表时间:
2015-05-28 - 期刊:
- 影响因子:0.800
- 作者:
Ioannis Karanikas;Argyrios Ioannidis;Petros Siaperas;Georgios Efstathiou;Ioannis Drikos;Nicolaos Economou - 通讯作者:
Nicolaos Economou
Georgios Efstathiou的其他文献
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{{ truncateString('Georgios Efstathiou', 18)}}的其他基金
Adaptive turbulence modelling to improve high-impact weather forecasts in next generation atmospheric models
自适应湍流建模可改善下一代大气模型中的高影响天气预报
- 批准号:
NE/T011351/1 - 财政年份:2020
- 资助金额:
$ 116.2万 - 项目类别:
Fellowship
相似国自然基金
流体湍流运动的相关数学分析
- 批准号:10971174
- 批准年份:2009
- 资助金额:25.0 万元
- 项目类别:面上项目
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