Drivers and Impacts of Extreme Weather Events in Antarctica (ExtAnt)

南极洲极端天气事件的驱动因素和影响 (ExtAnt)

• 批准号: NE/Y503307/1
• 负责人: Thomas Bracegirdle
• 金额: $ 171.55万
• 依托单位: British Antarctic Survey
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FY503307%2F1
• 关键词: Drivers; Impacts; Extreme; Weather; Events; Drivers; Impacts; Extreme; Weather; Events

ExtAnt will provide the first comprehensive assessment of present day and future high impact extreme weather events in Antarctica, and associated risks. Key risks include impacts of extreme weather on vulnerable ice shelves, the breakup of which can speed up flow of grounded ice and affect global sea level, and on the highly specialised Antarctic biodiversity. This ambitious programme brings together leading UK and international scientists to use new modelling resources and methods to elucidate drivers of extreme events. New modelling capability will be developed to quantify impacts of extreme events on surface melt of ice shelves. These advances will bring a step change over current knowledge of extremes. ExtAnt's legacy will include a dataset for advancing research into broader impacts, for example on ecosystems.The ExtAnt programme of research has been developed around three core research aims (RAs) and specific objectives to achieve these, outlined as follows. RA1. Quantify the relative contributions of key drivers of Antarctic extreme events and determine the role of anthropogenic forcing in specific observed cases.A wealth of new high resolution regional climate model (RCM) reanalysis-driven hindcasts that have been and are being created will be used, along with observations, to establish the most comprehensive record to date of Antarctic weather extremes. This will provide a foundation for assessing drivers of extreme events by quantifying the roles of specific large-scale and synoptic phenomena, including cyclones and atmospheric rivers. New diagnostic model capabilities will provide unprecedented quantitative information on lower-latitude sources of moisture. Anthropogenic drivers will be assessed using a multi-method approach to extreme event attribution in rapid (use existing simulations) or delayed (generating new ensemble simulations) mode. RA2. Resolve present day trends and variability of extreme events and their impacts: in particular, assess the roles of the ozone hole, GHG concentrations and modes of internal climate variability.Antarctica exhibits the largest internal climate variability on earth, therefore in order answer questions relating to trends and variability of the occurrence / severity of extreme events, we will use large ensembles (LEs) of climate model simulations. LEs are created by running a climate model many times (often 10s of times) with the same external forcing (e.g. greenhouse gases (GHGs) or ozone). This will allow us to resolve the phases of internal climate variability most conducive to the occurrence of extremes and over which parts of Antarctica, alongside responses to anthropogenic forcing from GHGs and stratospheric ozone. RA3. Quantify the severity and frequency of future Antarctic extreme events, and associated risks related to their impacts on vulnerable ice shelves, and provide information relevant for assessing impacts on ecosystems.Projections of 21st century behaviour of extreme events will be developed to explore a range of possible futures associated with both internal variability and external forcing. A statistical RCM-emulator will be developed and used to help translate output from LE climate model simulations to local impact-relevant scales. This will provide input/forcing for a newly integrated melt lake model allowing impacts of different realisations of internal variability and different forcing scenarios on ice shelf stability to be assessed. Advanced statistical methods, including machine learning (ML) / artificial intelligence (AI), will be used to select a representative sample of LE projections for downscaling. Additionally, information on extremes relevant to ecosystems will be provided for ongoing and future research into ecological/broader impacts.

现存将对南极洲的当今和未来高影响极端天气事件以及相关风险进行首次全面评估。关键风险包括极端天气对脆弱的冰架的影响，其破裂可以加快接地冰的流动并影响全球海平面，以及高度专业的南极生物多样性。这个雄心勃勃的计划将英国和国际科学家汇集在一起​​使用新的建模资源和方法来阐明极端事件的驱动因素。将开发新的建模能力来量化极端事件对冰架的表面熔体的影响。这些进步将对当前对极端知识的了解带来一步变化。现有的遗产将包括一个数据集，用于推进更广泛影响的研究，例如在生态系统上。现有的研究计划是在三个核心研究目标（RAS）（RAS）和实现这些目标的特定目标围绕以下概述的。 RA1。量化南极极端事件的关键驱动因素的相对贡献，并确定人为强迫在特定观察的情况下的作用。新的高分辨率区域气候模型（RCM）重新分析驱动的后播已经和正在创建的，将与观察结果一起使用，以建立最全面的记录，以建立最全面的天气。这将为您通过量化特定的大规模和概要现象的作用，包括旋风和大气河的角色来评估极端事件的驱动因素。新的诊断模型功能将提供有关较低水分来源的前所未有的定量信息。人为驱动因素将使用多方法方法来评估快速（使用现有模拟）或延迟（生成新的集合模拟）模式的极端事件归因的方法。 RA2。 Resolve present day trends and variability of extreme events and their impacts: in particular, assess the roles of the ozone hole, GHG concentrations and modes of internal climate variability.Antarctica exhibits the largest internal climate variability on earth, therefore in order answer questions relating to trends and variability of the occurrence / severity of extreme events, we will use large ensembles (LEs) of climate model simulations. LE是通过多次（通常为10次）运行气候模型（例如温室气体（GHG）或臭氧）来创建的。这将使我们能够解决内部气候变异性的阶段最有利于极端发生的发生，而南极洲部分地区的发生，以及对GHG和平流层臭氧的人为强迫的反应。 RA3。量化未来南极极端事件的严重性和频率，以及与它们对弱势冰架的影响相关的相关风险，并提供有关评估对生态系统的影响的信息。将开发并使用统计RCM启示剂，以帮助将LE气候模型模拟的输出转化为局部影响相关的尺度。这将为新整合的熔体湖模型提供输入/强制，从而可以评估内部变异性的不同实现和不同的强迫方案的影响。包括机器学习（ML） /人工智能（AI）在内的先进统计方法将用于选择LE投影的代表性样本以进行缩小。此外，将提供有关与生态系统相关的极端信息的信息，以进行生态/更广泛影响的持续研究和未来的研究。