Sensitivity of extreme events to climate change: The case of autocorrelated time series

Abstract

SUMMARYThe relative sensitivity of an extreme event is defined as the partial derivative of its probability with respect to the location or scale parameter of the distribution of the variable involved. Of particular interest in climate applications are extreme events of the form, the maximum of a sequence of observations of the variable exceeding a threshold. In this case, the relative sensitivities are directly related to the hazard rate for the distribution of the maximum. By means of simulations, this hazard rate is determined for the maximum of a finite sequence of autocorrelated random variables. For large values, the hazard rate rises more steeply than the asymptotic theory based on the type I extreme value distribution would predict. Unless the degree of autocorrelation is quite high, the hazard rate does not differ much for large values from that for independent time series. The hazard rate for the so-called 'penultimate approximation', based on the type Ill extreme value distribution, is also compared to the exact hazard rate under dependence. These results imply that the relative sensitivity of extreme events to overall climate change is even greater than the asymptotic theory would predict. Time series of daily maximum temperature, data that possess substantial autocorrelation, are utilized for illustrative purposes. KEY WORDS Autoregressive processHazard rate Maximum Type I extreme value distribution

Extreme events in a changing climate: Variability is more important than averages

“…At least qualitatively, our theoretical results turn out to be quite robust. Moreover, any discrepancies that exist appear to be in the direction of even greater actual relative sensitivity than the theory predicts (Katz and Brown, 1992).…”

Going to the Extremes

“…Extreme events such as heatwaves, heavy rain or snow events and droughts are responsible for a disproportionately large part of climate-related damages (Kunkel et al, 1999;Easterling et al, 2000;Meehl et al, 2000) and hence are of great concern to the impact community and stakeholders (Katz et al, 2005;Negri et al, 2005). Katz and Brown (1994) first suggested that the sensitivity of extremes to changes in mean climate may be greater than one would assume from simply shifting the location of the climatological distributions. Since then, observations of historical changes as well as future projections confirm that changes in the distributional tails of climate variables may not occur in proportion to changes in the mean, particularly for precipitation, and may not be symmetric in nature, as demonstrated by differential changes in maximum vs. minimum temperatures (e.g., Kharin and Zwiers, 2005;Robeson, 2004;Tank and Konnen, 2003;Easterling et al, 2000).…”

Mitigation of climate change impacts on raptors by behavioural adaptation: ecological buffering mechanisms

“…In particular, we simulated (1) decreasing average precipitation in southern Africa (IPCC, 2001a, and references therein;IPCC, 2001b;Walther et al, 2002), (2) increasing variation in annual precipitation amounts (Katz and Brown, 1992;Matyasvszky et al, 1993;Karl and Knight, 1998), and (3) changing temporal auto-correlation in precipitation (Katz and Brown, 1994;Wigley et al, 1998).…”