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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
该博士项目是nerc资助的财团GloSAT产生的两个博士项目之一。GloSAT将把观测到的地表温度记录扩展到18世纪,并利用历史船舶数据、航海日志和其他来源扩大历史气候变化数据的覆盖范围。该学生将利用多种数据来源,包括气候模式数据和古气候数据,识别过去在陆地和海洋上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对海平面压力的早期观测,分析早期极端事件的物理机制和空间范围,其中许多观测资料现在已经可以获得。气候模式的输出将用于确定这些事件的机制和可能的原因。学生将根据用于解释最近极端天气事件的技术,确定个别事件的概率是否受到外部驱动因素(如火山爆发和太阳变化)的影响。它们还将根据GloSAT项目的结果,确定这些事件受北大西洋涛动(NAO)、大西洋多年代际变率(AMV)或厄尔尼诺等大规模气候变率影响的程度。例如,如果在欧洲的太阳活动极小期出现创纪录的寒冷冬季,将会探索这一假设(Lockwood等人,Env.)。Res. Let. 2010),以及火山爆发后异常温暖潮湿的冬季的程度。对海洋极端温度的分析将研究是什么导致了海洋热浪和寒潮。这对于理解极端的海洋热浪在多大程度上可能叠加在未来的变暖趋势上,对珊瑚等海洋生物造成潜在的破坏性后果是必要的。这将有助于将可能的未来事件置于罕见的过去事件的背景下,例如,通过解决“如果这件事发生在今天会是什么样子”的问题。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、气象局和爱丁堡大学、雷丁大学、东安格利亚大学、南安普顿大学和约克大学的研究人员组成。他或她将由Hegerl指导,由Ed Hawkins(雷丁)和Andrew Schurer(爱丁堡)提供支持。我们将至少每季度向霍金斯咨询一次,要么是在项目会议期间,要么是通过访问。该学生将被连接到新成立的充满活力的爱丁堡地球,生态和环境DTP(18名学生/年),并将加入Hegerl的研究小组。学生将接受NERC DTP(可转换技能、写作、计算和演讲技能)的培训,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、气候变率和极端事件的机制、极值统计、气候建模、气候模式分析,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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