ESRL/PSD Seminar Series

Abstract

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By definition, extreme temperatures are rare, and yet the theory of extreme value statistics has seldom been applied to model temperature extremes. We applied extreme value analysis to quantify the influence of atmospheric blocking, the North Atlantic Oscillation (NAO), and El Niño-Southern Oscillation (ENSO) on heat waves in Europe. Firstly, a novel combination of extreme value and geometric distributions were fitted to observed daily temperature maxima from 74 stations across Europe, covering 1951−2010, to establish a stationary model of the expected magnitude, frequency and duration of hot spells that did not explicitly account for atmospheric drivers. Monthly time series of NAO, ENSO and 4 coherent atmospheric blocking regions were then incorporated as non-stationary covariates in the distribution parameter estimates to assess the dependence of heat waves on the atmospheric covariates. We concluded that ENSO does not have a significant influence on heat wave magnitude or frequency; the NAO is a significant driver of heat wave magnitude, frequency and duration in northern Europe and Atlantic bordering stations; and that atmospheric blocking is a significant driver of all aspects of heat waves in all parts of Europe.

Health impacts of heat waves are often worse when high daily maximum temperatures are accompanied by high minima or when events occur very early or late within the expected hot season. We therefore developed our approach further by exploring the use of bivariate extreme value theory to examine joint crossing of high maximum and minimum temperature thresholds in Florida using a high resolution gridded dataset. We investigated changes in the aforementioned heat wave characteristics through time and also included an examination of event timing within the year. Findings indicate that there is considerable spatial variability in heat wave characteristics although heat waves have become increasingly frequent and intense throughout much of the state.

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