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

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.

ExtAnt 将首次对南极洲目前和未来的高影响极端天气事件及相关风险进行全面评估。主要风险包括极端天气对脆弱冰架的影响（冰架的破裂会加速接地冰的流动并影响全球海平面）以及对高度专业化的南极生物多样性的影响。这个雄心勃勃的计划汇集了英国和国际领先的科学家，利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表面融化的影响。这些进步将彻底改变当前对极端情况的认识。 ExtAnt 的遗产将包括一个数据集，用于推进研究更广泛的影响，例如对生态系统的影响。ExtAnt 研究计划是围绕三个核心研究目标 (RA) 和实现这些目标的具体目标制定的，概述如下。 RA1。量化南极极端事件关键驱动因素的相对贡献，并确定人为强迫在特定观测案例中的作用。将使用已经和正在创建的大量新的高分辨率区域气候模型（RCM）再分析驱动的后报，结合观测，建立迄今为止最全面的南极极端天气记录。这将为通过量化特定大规模和天气现象（包括气旋和大气河流）的作用来评估极端事件的驱动因素提供基础。新的诊断模型功能将提供有关低纬度湿气来源的前所未有的定量信息。将使用多种方法以快速（使用现有模拟）或延迟（生成新的整体模拟）模式对极端事件归因进行评估。 RA2。解决当前极端事件的趋势和变化及其影响：特别是评估臭氧空洞、温室气体浓度和内部气候变化模式的作用。南极洲表现出地球上最大的内部气候变化，因此为了回答与为了了解极端事件发生/严重程度的趋势和变化，我们将使用气候模型模拟的大型集合（LE）。 LE 是通过使用相同的外部强迫（例如温室气体 (GHG) 或臭氧）多次（通常是数十次）运行气候模型来创建的。这将使我们能够解决最有利于极端事件发生的内部气候变化阶段以及南极洲的哪些地区，以及对温室气体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，以及与其对脆弱冰架影响相关的相关风险，并提供与评估对生态系统影响相关的信息。将对 21 世纪极端事件行为进行预测，以探索一系列可能的情况与内部变化和外部强迫相关的未来。将开发并使用统计 RCM 模拟器来帮助将 LE 气候模型模拟的输出转换为当地影响相关的规模。这将为新集成的融化湖模型提供输入/强迫，从而允许评估内部变异性的不同实现和不同强迫情景对冰架稳定性的影响。将使用包括机器学习 (ML)/人工智能 (AI) 在内的先进统计方法来选择 LE 预测的代表性样本以进行降尺度。此外，还将提供与生态系统相关的极端情况信息，以供正在进行和未来的生态/更广泛影响研究。