Fundamental influences of large-scale wave dynamics on tropical weather systems

大尺度波浪动力学对热带天气系统的基本影响

• 批准号: NE/I012419/1
• 负责人: John Methven
• 金额: $ 43.87万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI012419%2F1
• 关键词: Fundamental; influences; large; scale; wave

Scarcity of water has been identified as the most serious environmental threat facing the health and security of people living in the tropics. Pressures on water supply undermine stability through stresses on food availability and spread of disease e.g., malaria and meningitis. Yet predictions of precipitation show very high uncertainty in the Tropics and especially the arid climatic zones such as sub-Saharan Africa where the vulnerability of the population is amongst the highest in the world. The outlook for Sahel precipitation in coupled simulations of the twenty-first century remains very uncertain with no consensus as to whether there will be more or less rain in the future, or how the frequency and intensity of high impact weather will change. Skillful forecasts of rainfall would be of enormous benefit across all timescales ranging from hours to decades. In particular, short-range forecasts (up to 2 days) for the public and aviation industry, and medium-range forecasts (10-30 days) for agriculture, hydrology and health information. This is challenging since rainfall is organised through a complex interplay of large-scale wave patterns, weather systems and isolated deep convective updrafts. The locations of individual convective updrafts are not predictable and even the occurrence and evolution of mesoscale weather systems are poorly represented in Numerical Weather Prediction (NWP) models. However, there is some hope for greater predictability since the pattern of active and inactive regions of convection is often determined by large-scale wave structure. Examples of such phenomena include African Easterly Waves (AEWs) and equatorial waves. Owing to the waves, there is potential predictability for high impact weather events occurring simultaneously in several locations at once. For example, if several storms are spawned within a large-scale wave, each one of them could present a significant natural hazard, with safety and financial implications (such correlated events are not accounted for in the risk models used by the insurance industry). Unfortunately, there are severe deficiencies in the simulation of tropical large-scale waves which typically decay far too quickly in forecasts and propagate too slowly. However, it is difficult to amend models to improve the simulation of large-scale tropical waves because underpinning theory for tropical waves is currently too weak to unpick the problem. It is necessary to formulate better how different processes influence wave evolution so that modifications can be aimed at improving wave representation. The aim of the proposed project is to develop the theory behind large-scale waves in the tropics to the level where it can be applied in the quantitative diagnosis of observed weather systems. In doing so we aim to identify the processes that are most important in wave initiation, maintenance and propagation, and ways in which they are misrepresented in models, with a view to improving weather forecasts. The research will study the interplay between large-scale waves and convective rainfall through three stages of complexity: A) the dynamics of waves assuming small amplitude, B) large-amplitude aspects including vacillations between jet strength and wave amplitude, and C) explaining deficiencies in state-of-the-art forecasts of tropical waves using the new theory developed. The anticipated benefit of the research is improvement in weather forecasts of rainfall throughout the tropics at lead times of a day to a season. Stage C will be advanced through collaboration with project partners from two world-leading operational forecast centres: the Met Office and European Centre for Medium-Range Weather Forecasts.

缺水已被确定为热带地区人民健康和安全所面临的最严重的环境威胁。对供水的压力通过对粮食供应和疾病传播的压力破坏稳定，疟疾和脑膜炎。然而，在热带地区，特别是撒哈拉以南非洲等干旱气候区，降水预测的不确定性很高，那里的人口脆弱性是世界上最高的。在21世纪的耦合模拟中，萨赫勒降水的前景仍然非常不确定，对于未来降雨量是增加还是减少，或者高影响天气的频率和强度将如何变化，没有达成共识。熟练的降雨预报将在从几小时到几十年的所有时间尺度上带来巨大的好处。特别是为公共和航空业提供短期预报（最多2天），为农业、水文和卫生信息提供中期预报（10-30天）。这是具有挑战性的，因为降雨是通过大规模波浪模式、天气系统和孤立的深对流上升气流的复杂相互作用组织起来的。在数值天气预报模式中，单个对流上升气流的位置是不可预测的，甚至连中尺度天气系统的发生和演变也不能很好地反映出来。然而，由于对流活跃区和非活跃区的模式往往由大尺度波浪结构决定，因此有希望提高可预测性。这种现象的例子包括非洲东风波和赤道波。由于波浪的存在，对同时在几个地点发生的高影响天气事件有潜在的可预测性。例如，如果在一个大规模的波浪中产生几个风暴，每一个都可能构成重大的自然灾害，并带来安全和财务影响（保险业使用的风险模型中没有考虑到这种相关事件）。不幸的是，热带大尺度波的模拟存在严重的缺陷，这些波在预报中衰减得太快，传播得太慢。然而，由于目前对热带波的支撑理论太弱，很难解决这个问题，因此很难修改模式来改善对大尺度热带波的模拟。有必要更好地阐明不同过程如何影响波的演变，以便修改可以旨在改善波的表示。拟议项目的目的是发展热带地区大尺度波浪背后的理论，使其能够应用于对观测到的天气系统进行定量诊断。在这样做的过程中，我们的目标是确定的过程中最重要的波的启动，维护和传播，以及它们在模型中被歪曲的方式，以改善天气预报。该研究将通过三个复杂阶段研究大尺度波浪和对流降雨之间的相互作用：A）假设小振幅的波浪动力学，B）大振幅方面，包括急流强度和波浪振幅之间的波动，以及C）使用开发的新理论解释最先进的热带波浪预报中的缺陷。这项研究的预期好处是改善了整个热带地区降雨的天气预报，提前一天到一个季节。C阶段将通过与来自两个世界领先的业务预报中心的项目合作伙伴的合作来推进：气象局和欧洲中期天气预报中心。

项目成果

ENSO Impact on Kelvin Waves and Associated Tropical Convection

• DOI: 10.1175/jas-d-13-081.1
• 发表时间: 2013-10
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Gui‐Ying Yang;B. Hoskins

Linking African Easterly Wave Activity with Equatorial Waves and the Influence of Rossby Waves from the Southern Hemisphere

• DOI: 10.1175/jas-d-17-0184.1
• 发表时间: 2018-06-01
• 期刊: JOURNAL OF THE ATMOSPHERIC SCIENCES
• 影响因子: 3.1
• 作者: Yang, Gui-Ying;Methven, John;Hoskins, Brian
• 通讯作者: Hoskins, Brian

Overview of the West African Monsoon 20111

20111 西非季风概述

• DOI: 10.1002/wea.1896
• 发表时间: 2012
• 期刊: Weather
• 影响因子: 1.9
• 作者: Cornforth R

Isolating the Effects of Moisture Entrainment on Convectively Coupled Equatorial Waves in an Aquaplanet GCM

• DOI: 10.1175/jas-d-18-0098.1
• 发表时间: 2018-08
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Simon C. Peatman;J. Methven;S. Woolnough

The Equivalent Barotropic Structure of Waves in the Tropical Atmosphere in the Western Hemisphere

西半球热带大气波的等效正压结构

• DOI: 10.1175/jas-d-16-0267.1
• 发表时间: 2017
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Yang G