Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia

Abstract

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 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.

A spatio-temporal model for Red Sea surface temperature anomalies

“…. , A T being short-tailed with finite lower and upper end points; this agrees with previous studies on extreme low and high temperatures (Thibaud et al 2016;Winter et al 2016). We also calculate the site-wise 80% and 90% quantiles of the estimated GPD distributions.…”

“…In some instances, interest lies in the largest values of a spatial process, such as determining the likely spatial extent of a flood event or a heatwave; example methods and applications can be found in Davison et al (2012), Winter et al (2016) and Tawn et al (2018). Approaches include max-stable processes (Smith 1990;Schlather 2002) and Pareto processes (Ferreira and De Haan 2014); these are applicable when locations experience concomitant extremes, which may not always be the case.…”

Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios

“…The conditional extremes model has the ability to be more flexible with asymptotic dependence classes; it can account for asymptotic independence and asymptotic dependence (Heffernan and Tawn, 2004;Keef et al, 2013). It can also be used to analyse more than two i.i.d variables more easily than copula-based methods 190 (Winter and Tawn, 2016); we restrict the theory provided here to the bivariate case. The conditional model has been used for different purposes: spatial or temporal dependence between extremes (Winter and Tawn, 2016;Winter et al, 2016), dependence between extreme hazards (Zheng et al, 2014) and even financial purposes (Hilal et al, 2011).…”

“…It can also be used to analyse more than two i.i.d variables more easily than copula-based methods 190 (Winter and Tawn, 2016); we restrict the theory provided here to the bivariate case. The conditional model has been used for different purposes: spatial or temporal dependence between extremes (Winter and Tawn, 2016;Winter et al, 2016), dependence between extreme hazards (Zheng et al, 2014) and even financial purposes (Hilal et al, 2011). The conditional extremes model assesses the dependence structure between several variables conditioning on one being extreme and aims to model the conditional distribution.…”

Modelling The Spatial Extent and Severity of Extreme European Windstorms

“…when c = 0. Models that capture asymptotic independence are less well established; see Ledford and Tawn (1996), Heffernan and Tawn (2004), Wadsworth and Tawn (2012) and Winter et al (2016) for some examples. We have shown that our model captures the property of asymptotic independence over space, while accounting for the complex non-stationarity of the extratropical cyclone system.…”