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The Future of Extreme European Winter Weather

The Future of Extreme European Winter Weather
欧洲极端冬季天气的未来
批准号:
NE/S014713/1
负责人:
Peter Watson
金额:
$66.6万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
Every time there is an extreme weather event, there is much speculation about the role played by climate change. Questions that are particularly relevant for Europeans include how is climate change affecting the occurrence of flooding brought about by severe storminess, like that seen in the 2013/14 winter, or storms Emma and Friederike in 2017/18? How is it affecting cold air outbreaks like the "Beast from the East" in 2018? Until now, our capacity for studying the impact of climate change on weather extremes has been limited. This is because we could not run atmospheric models that can successfully simulate weather events like these for long enough to be able to study climate change's effect - this requires thousands of years of simulation time. But I have recently led development of a system that can achieve this, using distributed computing and an atmospheric model with a fine enough grid spacing to be able to simulate extreme storms and anticyclones realistically. I will exploit this system to show how climate change is affecting extreme weather systems, with a particular focus on winter storms in Europe. This will done by seeing how the model simulations respond to specified changes in greenhouse gas levels and other atmospheric constituents and changes in the oceans and sea ice associated with climate change. This allows an exquisite level of control over the climate change scenario being simulated, and makes it possible to simulate a wide range of futures.However, it is not sufficient to run a single climate model and just report its best estimate of climate change's effect. It also needs to be shown what is the range of possible outcomes. This is necessary to ensure that decision-makers can prepare for the worst possible outcomes whilst not wasting resources on adapting to scenarios that are very unlikely. It is also very important to understand the physical mechanisms behind climate change's impact, so that we can make better judgements about how much to trust the model simulations.I will investigate the main sources of uncertainty in how climate change will affect weather extremes in a given future scenario: 1. Uncertainty about how to best model the atmosphere.2. Uncertainty about how atmospheric dynamics will change, for example the shift in the mean latitude of the jet stream, or changes in the frequency of blocking events (when stable, high-pressure systems form and divert storms to the north and south).3. Uncertainty in the future factors that will influence the atmosphere, namely ocean temperatures, ice cover and the atmospheric chemical composition (including man-made greenhouse gases and aerosols).To understand the mechanisms behind how climate change is affecting Europe's weather, I will first separate the changes in man-made greenhouse gas and aerosol levels in the atmosphere from the oceanic changes, then further divide the latter into changes in different regions (such as the North Atlantic, the Arctic, the tropics etc.). Experiments will be done to see the effect of each change separately. This will help to answer questions such as how are North Atlantic storms affected by warming of the ocean waters there, which may invigorate storms by evaporating more water, providing more fuel for their growth? Are changes more due to remote influences of the tropics and Arctic? There has been much speculation in the media about the melting of sea ice in the Arctic being a driver of European extreme weather, for instance, but is still very scientifically controversial, and its impact on extreme weather events has not been studied in this way before.Overall, this research will give us much greater confidence and understanding about how climate change will be felt through extreme European winter weather, informing governments and industries about the difference that reducing greenhouse gas emissions will make, and helping decision-makers to plan for the future.
期刊论文(10)
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会议论文
Generating samples of extreme winters to support climate adaptation
生成极端冬季样本以支持气候适应
DOI: 10.1002/essoar.10508424.1
发表时间: 2021
期刊:
影响因子: --
作者: [Leach N]
通讯作者: Leach N
Using Deep Learning for an Analysis of Atmospheric Rivers in a High-Resolution Large Ensemble Climate Data Set
使用深度学习分析高分辨率大型集合气候数据集中的大气河流
DOI: 10.1029/2022ms003495
发表时间: 2023
期刊: Journal of Advances in Modeling Earth Systems
影响因子: 6.8
作者: [Higgins T]
通讯作者: Higgins T
DOI: 10.1029/2022jd038163
发表时间: 2023-05-27
期刊: JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
影响因子: 4.4
作者: [Vosper,Emily, Watson,Peter, Mitchell,Dann]
通讯作者: Mitchell,Dann
DOI: 10.1029/2020gl091990
发表时间: 2021-04-28
期刊: GEOPHYSICAL RESEARCH LETTERS
影响因子: 5.2
作者: [Bevacqua, Emanuele, Shepherd, Theodore G., Mitchell, Dann]
通讯作者: Mitchell, Dann
7
    Computational biomechanical modelling to predict musculoskeletal dynamics: application for 3Rs and changing muscle-bone dynamics
    • 批准号:
      BB/Y00180X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $59.83万
    • 财政年份:
      2024
    • 负责人:
      Peter Watson
    • 依托单位:
    Future Rainfall and Flood Extremes (FURFLEX)
    • 批准号:
      NE/Z000076/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $108.29万
    • 财政年份:
      2024
    • 负责人:
      Peter Watson
    • 依托单位:
    海外基金