Modeling Waves of Extreme Temperature: The Changing Tails of Four Cities
AbstractHeat waves are a serious threat to society, the environment, and the economy. Estimates of the recurrence probabilities of heat waves may be obtained following the successful modeling of daily maximum temperature, but working with the latter is difficult as we have to recognize, and allow for, not only a time trend but also seasonality in the mean and in the variability, as well as serial correlation. Furthermore, as the extreme values of daily maximum temperature have a different form of nonstationarity from the body, additional modeling is required to completely capture the realities. We present a time series model for the daily maximum temperature and use an exceedance over high thresholds approach to model the upper tail of the distribution of its scaled residuals. We show how a change-point analysis can be used�to identify seasons of constant crossing rates and how a time-dependent shape parameter can then be introduced to capture a change in the distribution of the exceedances. Daily maximum temperature series for Des Moines, New York, Portland, and Tucson are analyzed. In-sample and out-of-sample goodness-of-fit measures show that the proposed model is an excellent fit to the data. The fitted model is then used to estimate the recurrence probabilities of runs over seasonally high temperatures, and we show that the probability of long and intense heat waves has increased considerably over 50 years. We also find that the increases vary by city and by time of year.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of the American Statistical Association.
Volume (Year): 107 (2012)
Issue (Month): 497 (March)
Contact details of provider:
Web page: http://www.tandfonline.com/UASA20
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.