Abstract
This editorial essay concerns the use (or lack thereof) of the statistics of extremes in climate change research. So far, the statistical theory of extreme values has been primarily applied to climate under the assumption of stationarity. How this theory can be applied in the context of climate change, including implications for the analysis of the economic impacts of extremes, is described. Future research challenges include the statistical modeling of complex extreme events, such as heat waves, and taking into account spatial dependence in the statistical modeling of extremes for fields of climate observations or of numerical model output. Addressing these challenges will require increased collaboration between climate scientists and statisticians.
Similar content being viewed by others
References
Ballester J, Giorgi F, Rodó J (2010) Changes in European temperature extremes can be predicted from changes in PDF central statistics: a letter. Clim Change 98:277–284
Coles S (2001) An introduction to statistical modeling of extreme values. Springer, London
Cooley D (2009) Extreme value analysis and the study of climate change: a commentary on Wigley 1988. Clim Change 97:77–83
Davison AC, Smith RL (1990) Models for exceedances over high thresholds. J R Stat Soc, B 52:393–442
Dorland C, Tol RSJ, Palutikof JP (1999) Vulnerability of the Netherlands and Northwest Europe to storm damage under climate change. Clim Change 43:513–535
Embrechts P, Klüppelberg C, Mikosch T (1997) Modelling extremal events for insurance and finance. Springer, Berlin
Gumbel EJ (1941) The return period of flood flows. Ann Math Stat 12:163–190
Gumbel EJ (1958) Statistics of extremes. Columbia University Press, New York
Jagger TH, Elsner JB, Saunders MA (2008) Forecasting US insured hurricane losses. In: Diaz HF, Murnane RJ (eds) Climate extremes and society. Cambridge University Press, Cambridge, pp 189–208
Katz RW (2002) Stochastic modeling of hurricane damage. J Appl Meteorol 41:754–762
Katz RW, Brown BG (1992) Extreme events in a changing climate: variability is more important than averages. Clim Change 21:289–302
Katz RW, Parlange MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25:1287–1304
Mearns LO, Katz RW, Schneider SH (1984) Extreme high-temperature events: changes in their probabilities with changes in mean temperature. J Clim Appl Meteorol 23:1601–1613
Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305:994–997
Nadarajah S (2005) Extremes of daily rainfall in West Central Florida. Clim Change 69:325–342
Solow AR (1999) On testing for change in extreme events. Clim Change 42:341–349
Solow AR, Moore L (2000) Testing for trend in a partially incomplete hurricane record. J Clim 13:3696–3699
Stephenson A, Gilleland E (2006) Software for the analysis of extreme events: the current state and future directions. Extremes 8:87–109
Weitzman ML (2009) On modeling and interpreting the economics of catastrophic climate change. Rev Econ Stat 91:1–19
Wigley TML (1985) Impact of extreme events. Nature 316:106–107
Wigley TML (1988) The effect of changing climate on the frequency of absolute extreme events. Clim Monit 17:44–55 (reprinted in Climatic Change (2009) 97:67–76)
Zwiers FW, Kharin VV (1998) Changes in the extremes of the climate simulated by CCC GCM2 under CO2 doubling. J Clim 11:2200–2222
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Katz, R.W. Statistics of extremes in climate change. Climatic Change 100, 71–76 (2010). https://doi.org/10.1007/s10584-010-9834-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10584-010-9834-5