The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 10, Number 4 (2016), 2075-2101.
Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia
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. Southeastern 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 Niño-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.
Ann. Appl. Stat., Volume 10, Number 4 (2016), 2075-2101.
Received: September 2015
Revised: June 2016
First available in Project Euclid: 5 January 2017
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Winter, Hugo C.; Tawn, Jonathan A.; Brown, Simon J. Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia. Ann. Appl. Stat. 10 (2016), no. 4, 2075--2101. doi:10.1214/16-AOAS965. https://projecteuclid.org/euclid.aoas/1483606852