The stratospheric impact on extreme weather events

平流层对极端天气事件的影响

• 批准号: NE/N014057/1
• 负责人: Daniel Mitchell
• 金额: $ 55.72万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FN014057%2F1
• 关键词: stratospheric; impact; extreme; weather; events

The winter of 2013/2014 has seen some of the coldest temperatures in the USA, and some of the heaviest rainfall in the Southern UK ever reported. Both are examples of extreme weather events, the impact of which is enormous on national infrastructure and economy. Current research suggests that the frequency of extreme events is increasing, with strong indications this may be due to humans pumping greenhouse gases into the atmosphere. While the weather on Earth occurs within the troposphere (the layer of the atmosphere between ~0-10km), the stratosphere (~10-50km) is known to play an important role in driving such weather events, especially during winter. The purpose of this project is to understand exactly how the stratosphere influences extreme weather events, and how this follows through to impacts on society, such as infrastructure damage, which can run into billions of pounds, and human deaths, which can be in the tens of thousands.As climate scientists, one tool available to us in understanding atmospheric dynamics and extremes, are computer models of our current and future climate. These models are similar to those that produce the weather forecasts seen on TV, but are adapted to be relevant for longer timescales. In this project the 'weather@home' framework will be utilised, which allows for the model simulations to be run on thousands of volunteered home computers, spreading the load and allowing for many more simulations to be run than otherwise possible. As the climate system is inherently chaotic, it is unlikely that the models will reproduce exactly the observed climate. Therefore typically on supercomputers, models are run ~5-10 times over the same time period, with slightly different starting conditions each time, to build up an ensemble of 'possible' climate scenarios. The advantage of the weather@home set up is that the models can be run many more times than this (of the order of 10,000). This is essential when considering extreme weather events, because they are by definition rare, and the events will only be captured in ~5% of the model simulations. Currently, the weather@home set up does not include a stratosphere-resolving model. This is a big issue because without the stratosphere providing a source of variability for extreme events at the surface, attribution statements, predictability, and ultimately estimated societal impacts will be biased. In this project the model will be further developed to include higher vertical resolution, allowing for a well-resolved stratosphere. Initial assessment will be to analyse the stratospheric dynamics that lead to these rare events at the surface. While it has been known that the stratosphere can influence the troposphere for over a decade, the driving conditions behind this are largely unknown. How the stratosphere impacts surface extreme climate is largely unknown, with most previous research focussing on the mean-state. With the shear number of model simulations available to capture internal climate variability, this project is ideally aimed at addressing questions relating to extremes.An advantage of using climate models (in conjunction with observations) is that they allow for experiments that cannot be tested in the real world. Such as what the climate would be like if humans never existed. In this project such experiments will also be performed to assess how the climate can be forced from different sources of variability. Experiments will be set up to look at how stratosphere-troposphere coupling, and subsequently the extreme events are influences by human induced climate change. Given the recent increase in extreme event attribution globally (for instance, the recent National Academy of Sciences review panel on this issue), an increased understanding of the processes driving extreme events will be invaluable for the scientific community.

2013/2014年的冬天是美国最冷的冬天，也是英国南部有史以来降雨量最大的冬天。两者都是极端天气事件的例子，其对国家基础设施和经济的影响巨大。目前的研究表明，极端事件的频率正在增加，强烈的迹象表明，这可能是由于人类向大气中排放温室气体。虽然地球上的天气发生在对流层（大气层在~0- 10公里之间），但平流层（~10- 50公里）已知在驱动此类天气事件方面发挥重要作用，特别是在冬季。这个项目的目的是了解平流层是如何影响极端天气事件的，以及这种影响是如何对社会产生影响的，比如基础设施的破坏，这可能会造成数十亿英镑的损失，以及数万人的死亡。作为气候科学家，我们了解大气动力学和极端天气的一个工具是我们现在和未来气候的计算机模型。这些模型类似于电视上看到的天气预报，但经过调整，适用于更长的时间尺度。在这个项目中，将使用“在家天气”框架，这使得模型模拟可以在数千台自愿的家用计算机上运行，分散负载，并允许运行比其他方式更多的模拟。由于气候系统本质上是混乱的，因此模型不太可能精确地再现观测到的气候。因此，通常在超级计算机上，模型在同一时间段内运行约5-10次，每次的启动条件略有不同，以建立一个“可能的”气候情景的集合。weather@home设置的优点是，模型可以运行比这更多的次数（大约10，000次）。在考虑极端天气事件时，这是必不可少的，因为它们根据定义是罕见的，并且这些事件仅在约5%的模型模拟中被捕获。目前，天气@home设置不包括平流层解析模型。这是一个大问题，因为如果没有平流层为地表极端事件提供可变性来源，归因陈述，可预测性和最终估计的社会影响将是有偏见的。在该项目中，将进一步开发该模型，以包括更高的垂直分辨率，从而考虑到分辨率良好的平流层。初步评估将分析导致这些罕见的地面事件的平流层动态。虽然人们已经知道平流层可以影响对流层超过十年，但这背后的驱动条件在很大程度上是未知的。平流层如何影响地面极端气候在很大程度上是未知的，大多数以前的研究集中在平均状态。由于模型模拟的切变数可用于捕捉内部气候变率，该项目的理想目标是解决与极端有关的问题。使用气候模型（与观测结合）的一个优点是，它们允许在真实的世界中进行无法测试的实验。例如，如果人类不存在，气候会是什么样子。在本项目中，还将进行此类实验，以评估气候如何受到不同变异源的影响。将建立实验来研究平流层-对流层耦合以及随后的极端事件如何受到人类引起的气候变化的影响。鉴于最近全球范围内极端事件归因的增加（例如，最近国家科学院审查小组就这一问题进行了审查），增加对极端事件驱动过程的了解对科学界来说将是非常宝贵的。

项目成果

Editorial: Climate Science Advances to Address 21st Century Weather and Climate Extremes

社论：气候科学的进步可应对 21 世纪的天气和极端气候

• DOI: 10.3389/fclim.2021.680291
• 发表时间: 2021
• 期刊: Frontiers in Climate
• 作者: Funk C

Severe Frosts in Western Australia in September 2016

• DOI: 10.1175/bams-d-17-0088.1
• 发表时间: 2018
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: M. Grose;M. Black;J. Risbey;P. Uhe;P. Hope;K. Haustein;D. Mitchell

Sustained Water Storage in Horn of Africa Drylands Dominated by Seasonal Rainfall Extremes

• DOI: 10.1029/2022gl099299
• 发表时间: 2022-10
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Markus Adloff;M. Singer;David A. MacLeod;K. Michaelides;N. Mehrnegar;Eleanor Hansford;C. Funk;D. Mitchell

Increasing risks of multiple breadbasket failure under 1.5 and 2 °C global warming

• DOI: 10.1016/j.agsy.2019.05.010
• 发表时间: 2019-10-01
• 期刊: AGRICULTURAL SYSTEMS
• 影响因子: 6.6
• 作者: Gaupp, Franziska;Hall, Jim;Dadson, Simon
• 通讯作者: Dadson, Simon

Larger Spatial Footprint of Wintertime Total Precipitation Extremes in a Warmer Climate

• 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