Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

对流组织与季风降水、大气、地表和海洋的相互作用 (INCOMPASS)

• 批准号: NE/L01386X/1
• 负责人: Andrew Turner
• 金额: $ 83.84万
• 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: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FL01386X%2F1
• 关键词: Interaction; Convective; Organization; Monsoon; Precipitation

The monsoon supplies the majority of water for agriculture and industry in South Asia, and is therefore critical to the well-being of a billion people. Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation. This project will use a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors. The observational analysis will feed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, will be set up in a range of different ways for the observational period. In particular, we will pioneer the test development of a new 100m-resolution atmospheric model, which we expect to greatly improve the representation of land-ocean-atmosphere interactions. Another priority will be to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it will be possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. Through model evaluation at a range of scales, the development of simple theoretical understanding of the rainfall processes, and working with groups responsible for operational model improvement, the project will lead directly to improvements in monsoon forecasts. By improving rainfall prediction, we expect the work to have an economic impact in India and internationally.

季风为南亚的农业和工业提供了大部分水，因此对于十亿人民的福祉至关重要。季风的积极和休息时期对农业的成功有重大影响，而降雨量的年度变化在国际规模上会产生经济后果。人口和发展中的经济不断增长意味着，理解和预测季风至关重要。尽管如此，我们有能力对季风进行建模，并在未来的几天到季节进行尺度的预测受到迅速发展的大错误的限制。在印度，天气预测模型的相对较差的表现是由于土地，海洋和大气之间存在非常牢固且复杂的关系，这些关系是由对流的过程以雨量繁殖的累积量为云的云而与之联系起来的。预测误差主要是因为对流云与大规模循环或表面条件没有准确链接，并且这些误差持续到长时间尺度。全球，天气和气候预测模型正在分辨出来，但季风降雨的错误并没有减少。缺乏对季风系统的土地，海洋和大气部分的详细观察，这是在一系列时间和空间尺度上，无法更透彻地了解季风对流云和陆地表面的过程，以及它们与大规模循环的相互作用。该项目将在印度和邻近的海洋上使用新的测量计划，以推进印度河社区的季风预测能力。 FAAM研究飞机到印度的首次分离，结合了一项密集的地面观测活动，将收集对陆地表面，土地和海洋上的边界层结构以及大气概况的新观察。我们将在陆地表面进行一系列新的长期测量能量和水交换。一个季风季节的研究测量将与印度运营网络的长期观察结合在一起。观察结果将集中在两个横断面上：在印度的北部平原上，涵盖了从灌溉到雨水喂养的一系列表面类型，以及潮湿的气候区域；以及整个西高止山脉（Western Ghat），从陆地到海洋和地形之间进行过渡。观测分析将代表季风过程的独特且前所未有的特征，该过程连接了控制降雨的土地，海洋和大气模式。长期测量将允许计算各种因素之间的统计关系。观察分析将直接在大都会办公室和NCMRWF的预测中直接提高。在这两个机构中，用于天气预报的MET办公室统一模型将在观察期间以各种不同的方式设置。特别是，我们将开拓新的100m分辨率大气模型的测试开发，我们希望该模型极大地改善了土地 - 大气相互作用的代表。另一个优先事项是改善季风预测中的土地表面建模。通过比较小域上非常高的分辨率模型的结果与代表全球天气模式的较低分辨率模型进行比较，可以描述控制季风降雨的关键过程，并指出如何在不同的应用中（例如天气预测或气候预测）中代表这些过程。通过在一系列量表的模型评估中，对降雨过程的简单理论理解的发展以及与负责运营模型改进的小组合作，该项目将直接导致季风预测的改进。通过改善降雨预测，我们预计这项工作将在印度和国际上产生经济影响。

项目成果

Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)

• DOI: 10.1007/s00382-018-4536-1
• 发表时间: 2018-11
• 期刊: Climate Dynamics
• 影响因子: 4.6
• 作者: A. Chevuturi;A. Turner;S. Woolnough;G. Martin;C. MacLachlan

A case-study of land-atmosphere coupling during monsoon onset in northern India

印度北部季风爆发期间陆地-大气耦合的案例研究

• DOI: 10.1002/qj.3538
• 发表时间: 2019
• 期刊: Quarterly Journal of the Royal Meteorological Society
• 影响因子: 8.9
• 作者: Barton E

Vertical and horizontal distribution of submicron aerosol chemical composition and physical characteristics across northern India during pre-monsoon and monsoon seasons

• DOI: 10.5194/acp-19-5615-2019
• 发表时间: 2019-04-30
• 期刊: ATMOSPHERIC CHEMISTRY AND PHYSICS
• 影响因子: 6.3
• 作者: Brooks, James;Allan, James D.;Coe, Hugh
• 通讯作者: Coe, Hugh

Black carbon physical and optical properties across northern India during pre-monsoon and monsoon seasons

• DOI: 10.5194/acp-19-13079-2019
• 发表时间: 2019-06
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: James Brooks;Dantong Liu;James D. Allan;P. I. Williams;J. Haywood;Ellie Highwood;S. K. Kompalli;S. S. Babu-S.;S. Satheesh;Andrew G. Turner;H. Coe

Biases in Model-Simulated Surface Energy Fluxes During the Indian Monsoon Onset Period

• DOI: 10.1007/s10546-018-0395-x
• 发表时间: 2019-02-01
• 期刊: BOUNDARY-LAYER METEOROLOGY
• 影响因子: 4.3
• 作者: Chakraborty, Tirthankar;Sarangi, Chandan;Evans, Jonathan
• 通讯作者: Evans, Jonathan