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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
翻译
每次发生极端天气事件时,人们都会对气候变化所扮演的角色进行很多猜测。与欧洲人特别相关的问题包括,气候变化如何影响2013/14年冬季严重风暴或2017/18年艾玛和弗里德里克风暴造成的洪水?像2018年的“东方来的野兽”,它是如何影响冷空气爆发的?到目前为止,我们研究气候变化对极端天气影响的能力有限。这是因为我们无法运行能够成功模拟此类天气事件的大气模型,以便能够研究气候变化的影响-这需要数千年的模拟时间。但我最近领导开发了一个可以实现这一目标的系统,使用分布式计算和一个具有足够精细网格间距的大气模型,能够逼真地模拟极端风暴和反气旋。我将利用这个系统来展示气候变化如何影响极端天气系统,特别关注欧洲的冬季风暴。这将通过观察模型模拟如何对温室气体水平和其他大气成分的特定变化以及与气候变化相关的海洋和海冰变化做出反应来实现。这使得对所模拟的气候变化情景进行精确的控制成为可能,并使模拟广泛的未来成为可能。然而,仅仅运行一个单一的气候模型并报告其对气候变化影响的最佳估计是不够的。还需要说明可能的结果范围。这是必要的,以确保决策者能够为最坏的可能结果做好准备,同时不会浪费资源来适应非常不可能的情景。了解气候变化影响背后的物理机制也是非常重要的,这样我们就可以更好地判断模式模拟的可信度。我将调查在给定的未来情景下,气候变化如何影响极端天气的主要不确定性来源:1.不确定如何最好地模拟大气。2.大气动力学将如何变化的不确定性,例如急流平均纬度的变化,或阻塞事件频率的变化(当稳定的高压系统形成并将风暴转向南北时)。3.未来影响大气的因素,即海洋温度、冰盖和大气化学成分的不确定性(包括人为温室气体和气溶胶)。为了了解气候变化如何影响欧洲天气的机制,我将首先将大气中人为温室气体和气溶胶水平的变化与海洋变化分开,然后将后者进一步划分为不同区域的变化(如北大西洋、北极、热带等)。将分别进行实验以观察每种变化的效果。这将有助于回答诸如北大西洋风暴如何受到那里海洋沃茨变暖的影响等问题,这可能会通过蒸发更多的水来激发风暴,为它们的生长提供更多的燃料?变化更多是由于热带和北极的遥远影响吗?例如,媒体上有很多关于北极海冰融化是欧洲极端天气的驱动因素的猜测,但在科学上仍然存在很大的争议,而且以前从未以这种方式研究过它对极端天气事件的影响。总的来说,这项研究将使我们对欧洲冬季极端天气如何感受气候变化有更大的信心和理解,向政府和行业通报减少温室气体排放将带来的变化,并帮助决策者规划未来。
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)
专著(0)
科研奖励(0)
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
共 7 条
    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