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Climate and weather extremes in early instrumental records, mechanisms and consequences

Climate and weather extremes in early instrumental records, mechanisms and consequences
早期仪器记录中的气候和天气极端情况、机制和后果
批准号:
2406645
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

项目摘要

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中文摘要
翻译
这个博士项目是由NERC资助的GloSAT财团发起的两个博士项目之一。GloSAT将把观测到的地表温度记录追溯到18世纪,并使用历史船舶数据、航海日志和其他来源扩大历史气候变化数据的覆盖范围。学生将利用包括气候模型数据和古气候数据在内的多种数据来源,识别陆地和海洋上过去的极端季节性和月度事件。在可能的情况下,将利用历史天气分析数据和海平面压力的早期观测数据,分析早期极端天气的物理机制和空间范围,其中许多观测数据现已面世。气候模型的输出将被用来确定这些事件的机制和可能的原因。学生将在解释最近极端天气事件的技术的基础上,确定个别事件的概率是否受到外部驱动因素的影响,如火山喷发和太阳变化。他们还将根据GloSAT项目的结果,确定事件受大范围气候变异性的影响程度,例如北大西洋涛动(NAO)、大西洋十年变率(AMV)或厄尔尼诺。例如,如果欧洲创纪录的寒冷冬季往往发生在太阳活动极小期(Lockwood等人,环境),将探索这一假说。Res.让.对海洋极端温度的分析将调查是什么驱动了海洋热浪和寒流。这对于了解极端海洋热浪可能在多大程度上叠加未来变暖趋势,从而对珊瑚等海洋生物造成潜在破坏性后果来说是必要的。这将有助于把未来可能发生的事件放在过去罕见事件的背景下,例如,通过回答这样一个问题:如果今天发生,这一事件会是什么样子。该学生将成为英国跨学科项目团队的一员,该团队由来自国家海洋学中心、英国气象局以及爱丁堡大学、雷丁大学、东英吉利大学、南安普顿大学和约克大学的研究人员组成。他或她将由黑格尔监督,埃德·霍金斯(雷丁)和安德鲁·舒勒(爱丁堡)支持。霍金斯将至少每季度接受一次咨询,要么在项目会议旁边,要么通过访问。这名学生将被连接到新资助的充满活力的爱丁堡地球、生态和环境DTP(每年18名学生),并将加入Hegerl的研究小组。学生将接受NERC DTP(可转移技能、写作、计算和演示技能)培训,并申请在合适的暑期学校进行外部培训。在科学方面,学生将学习科学数据分析、气候变异性和极端事件的机制、极值统计、气候建模、气候模型分析,并了解定量和严格的分析方法。
英文摘要
This PhD project is one of two PhD projects arising from the NERC-funded consortium GloSAT. GloSAT will extend the observed surface temperature record back into the 18th century, and extend the coverage of historical climate change data using historical ship data, logbooks and other sources. The student will identify past extreme seasonal and monthly events over both land and ocean, making use of multiple data sources including climate model data and palaeoclimatic data. The physical mechanisms and spatial extent of early extremes will be analysed where possible, using historical weather analysis data and early observations of sea level pressure, many of which are now becoming available. Climate models output will be used to identify mechanisms and possible causes of these events.The student will determine if the probability of individual events has been affected by external drivers such as volcanic eruptions, and changes in the sun, building on techniques used to interpret recent extreme weather events. They will also determine the extent to which the events are influenced by large-scale climate variability, such as the North Atlantic Oscillation (NAO), Atlantic Multidecadal Variability (AMV) or El Nino, drawing on GloSAT project results. For example, the hypothesis will be explored if record cold winters tend to occur during solar minima in Europe (Lockwood et al., Env. Res. Let. 2010), and to what extent anomalously warm and wet winters follow volcanic eruptions.Analysis of temperature extremes over the ocean will investigate what drives marine heat waves and cold spells. This is necessary for understanding to what extent extreme marine heat waves might superimpose on the warming trend in the future, with potentially devastating consequences for marine life such as corals. This will help place possible future events into the context of rare past events, for example, by addressing the question 'what would this event be like if it occurred today'.The student will be part of the interdisciplinary UK-wide project team comprising researchers from the National Oceanography Centre, the Met Office and the Universities of Edinburgh, Reading, East Anglia, Southampton and York. He or She will be supervised by Hegerl, supported by Ed Hawkins (Reading) and Andrew Schurer (Edinburgh). Hawkins will be consulted at least quarterly, either adjacent to a project meeting, or through a visit. The student will be connected to the newly funded and vibrant Edinburgh Earth, Ecology and Environment DTP (18 students/year) and will join Hegerl's research group. The student will be trained by the NERC DTP (transferrable skills, writing, computing and presentation skills) and apply for external training in suitable summer schools. Scientifically, the student will learn scientific data analysis, mechanisms of climate variability and extreme events, extreme value statistics, climate modelling, climate model analysis and gain an understanding of quantitative and rigorous analysis approaches.
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