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MITRE: Mesoscale convective systems over India, Tracking, Research, and Experimentation

MITRE：印度上空的中尺度对流系统、跟踪、研究和实验

基本信息

批准号：
NE/W007924/1
负责人：
Kieran Mark Rainwater Hunt
金额：
$ 73.17万
依托单位：
University of Reading
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FW007924%2F1
关键词：
MITRE Mesoscale convective systems over

项目摘要

India receives 80% of its yearly rainfall during the summer monsoon, which is active from June through September. The primary cause of this rainfall is convection, where solar heating of the surface (and surface warming of the lower atmosphere) causes updrafts which lift moist air into the cooler upper atmosphere where it condenses and rains out. Convection exists on a range of scales, from individual cells tens of metres across, to tropical storms and cyclones thousands of kilometres across. In the monsoon, however, it is most commonly organised into systems from several to several hundred kilometres in scale, known as mesoscale convective systems (MCSs). MCSs have a complex structure, typically consisting of regions of both convective updrafts and stratiform outflow, they are responsible for a majority of the total monsoon rainfall as well as a majority of the extreme rainfall events occurring year-round. Despite their importance, they have not been studied in great detail over India, owing to the difficulty in tracking and collecting information about them.This project aims to vastly expand our understanding of the variability of MCSs over India and the surrounding region, to explore their role in sustaining and modifying the monsoon, to quantify how well they are forecast and uncover potential sources of forecast error, and to project their response to climate change. Work will be carried out in collaboration with partners at the Met Office, the National Centre for Medium-Range Weather Forecasting (Delhi), the Indian Institute of Tropical Meteorology (Pune) and the Indian Institute of Technology Delhi.The first task will be to track MCSs in satellite data, where they show up as large areas of very cold cloud, to create a multi-decade database of MCS tracks. Using this database, we will seek to understand what causes MCSs to occur preferentially in particular locations (e.g. soil moisture, vertical wind shear) and at particular times (e.g. monsoon variability), as well as how their structure and intensity change due to environmental (e.g. the Himalayas) and meteorological (e.g. local atmospheric stability) stimuli. The project will then move to a monsoon-orientated point of view, where we will seek to understand how MCSs assist the monsoon in advancing northward through India during its onset in June, and how they interact with the tropical depressions that pass through monsoonal India several times per season.The second half the project focus on investigating MCS behaviour in models, ranging from those used for weather forecasting to those used to project climate change. Using archived forecast data from our partner institutes, we will quantify how well MCSs are captured in these models, at short range (< 7 days), medium range (7-15 days) and seasonal range (15-60 days). We will explore sources of forecast error, such as the timing of convection, and test whether statistical techniques could be used to improve future forecasts. Finally, we will quantify how MCS frequency, intensity, and behaviour will respond to projected climate change scenarios. We will apply tracking techniques to established climate model (e.g. CMIP6) output, but will also run our own high-resolution simulations focused over India, capable of more accurate MCS simulation. We expect that the methodology and results of this project will be valuable to other researchers working on monsoons and convective systems across the globe; to forecasters of Indian weather; and for policymakers exploring long term disaster mitigation and water security strategies over South Asia.

印度每年80%的降雨量来自夏季季风，夏季季风从6月持续到9月。这种降雨的主要原因是对流，太阳对地表的加热（以及低层大气的表面变暖）导致上升气流，将潮湿的空气提升到较冷的高层大气中，在那里它凝结并下雨。对流存在于各种尺度上，从直径几十米的单个细胞，到直径数千公里的热带风暴和气旋。然而，在季风中，它最常被组织成几到几百公里尺度的系统，称为中尺度对流系统（mcs）。MCSs具有复杂的结构，通常由对流上升气流和层状外流气流区域组成，它们负责大部分季风总降雨量以及大部分全年发生的极端降雨事件。尽管它们很重要，但由于难以追踪和收集有关它们的资料，在印度没有对它们进行非常详细的研究。该项目旨在极大地扩展我们对印度及周边地区mcs变异性的理解，探索它们在维持和改变季风方面的作用，量化它们的预测效果，揭示预测误差的潜在来源，并预测它们对气候变化的反应。这项工作将与气象局、国家中期天气预报中心（德里）、印度热带气象研究所（浦那）和印度理工学院德里的合作伙伴合作进行。第一个任务将是在卫星数据中追踪MCS，在那里它们显示为大面积的非常冷的云，以创建一个几十年的MCS轨迹数据库。利用这个数据库，我们将试图了解是什么原因导致mcs优先发生在特定地点（例如土壤湿度，垂直风切变）和特定时间（例如季风变率），以及它们的结构和强度如何因环境（例如喜马拉雅山）和气象（例如当地大气稳定性）刺激而变化。然后，该项目将转向以季风为导向的观点，在那里，我们将试图了解mcs如何帮助季风在6月份开始时向北推进，穿越印度，以及它们如何与热带低气压相互作用，热带低气压每个季节几次穿过季风印度。项目的后半部分侧重于调查模型中的MCS行为，从用于天气预报的模型到用于预测气候变化的模型。利用来自合作机构的存档预测数据，我们将量化这些模型在短期（< 7天）、中期（7-15天）和季节性范围（15-60天）下对mcs的捕获情况。我们将探讨预测误差的来源，如对流的时间，并测试是否可以使用统计技术来改进未来的预测。最后，我们将量化MCS的频率、强度和行为将如何响应预测的气候变化情景。我们将把跟踪技术应用于已建立的气候模式（例如CMIP6）输出，但也将运行我们自己的高分辨率模拟，重点是印度，能够更准确地模拟MCS。我们期望这个项目的方法和结果将对全球其他研究季风和对流系统的研究人员有价值；印度天气预报员；也为决策者探索南亚的长期减灾和水安全战略提供了帮助。