Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia
Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia
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模拟厄尔尼诺南方涛动对澳大利亚极端空间温度事件的影响
DOI：
10.1214/16-aoas965
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
S. Brown
中科院分区：
文献类型：
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作者：
Hugo C. Winter;J. Tawn;S. Brown
在评估高温造成的风险时，不仅需要考虑不同地点的温度，还需要考虑预计有多少地点同时处于高温状态。覆盖大面积的热点事件有可能给卫生服务带来巨大压力，并对农业造成破坏，导致高死亡人数和巨大经济损失。2009年初，澳大利亚东南部经历了一场严重的热浪;维多利亚州有374人死亡，墨尔本录得自1859年有记录以来的最高气温（Nairn和福塞特，2013年）。气候科学特别感兴趣的一个领域是大规模气候现象，如厄尔尼诺-南方涛动（ENSO）对极端温度的影响。在这里，我们开发了一个框架，基于极值理论来估计ENSO对澳大利亚各地极端温度的影响。这种方法使我们能够估计在重要地点（如墨尔本）的ENSO温度变化，以及在ENSO的特定阶段，我们是否更有可能在更大的空间范围内观察到高温。为此，我们设计了一套措施，可用于有效地总结极端温度事件的许多重要的空间方面。这些措施估计使用我们的极端值框架，我们验证我们是否可以准确地复制2009年澳大利亚热浪，然后使用该模型来估计有一个更严重的事件比已经观察到的概率。
When assessing the risk posed by high temperatures, it is necessary to consider not only the temperature at separate sites but also how many sites are expected to be hot at the same time. Hot events that cover a large area have the potential to put a great strain on health services and cause devastation to agriculture, leading to high death tolls and much economic damage. South-eastern Australia experienced a severe heatwave in early 2009; 374 people died in the state of Victoria and Melbourne recorded its highest temperature since records began in 1859 (Nairn and Fawcett, 2013). One area of particular interest in climate science is the effect of large scale climatic phenomena, such as the El Nino-Southern Oscillation (ENSO), on extreme temperatures. Here, we develop a framework based upon extreme value theory to estimate the effect of ENSO on extreme temperatures across Australia. This approach permits us to estimate the change in temperatures with ENSO at important sites, such as Melbourne, and also whether we are more likely to observe hot temperatures over a larger spatial extent during a particular phase of ENSO. To this end, we design a set of measures that can be used to effectively summarise many important spatial aspects of an extreme temperature event. These measures are estimated using our extreme value framework and we validate whether we can accurately replicate the 2009 Australian heatwave, before using the model to estimate the probability of having a more severe event than has been observed.