CR 47:187-199 (2011)  -  DOI:

Stochastic modeling of hot weather spells and their characteristics

M. N. Khaliq1,*, T. B. M. J. Ouarda2, P. Gachon1, L. Sushama3

1Adaptation and Impacts Research Section, Atmospheric Science and Technology Directorate, Environment Canada, Place Bonaventure, Northeast Tower, 800 Gauchetiere Street West, Office 7810, Montreal, Quebec H5A 1L9, Canada
2INRS-ETE, University of Quebec, 490 de la Couronne, Quebec City, Quebec G1K 9A9, Canada
3Centre ESCER, University of Quebec at Montreal, Quebec H3C 3P8, Canada

ABSTRACT: Stochastic characterization of hot weather events (HWEs) is useful for developing probabilistic climate change information. We assumed that simultaneous exceedances of daily minimum and maximum temperatures (i.e. Tmin and Tmax, respectively), above the selected thresholds for these temperatures, form alternating sequences of `hot weather´ and `non-hot weather´ spells. This behavior is stochastically characterized by a generalization of the compound Poisson process. The generalization is achieved by randomizing the mean rate of occurrence of the original Poisson process with the gamma distribution. The resulting compound Poisson process gamma (CPPG) model consists of 2 basic components: one relates to the occurrence of HWEs and the other to their durations. Detailed validation of the CPPG model is presented for HWEs derived from homogenized Tmin and Tmax observations from McTavish station (located in the centre of Montreal, southern Quebec, Canada) for the June-August hot summer season over the period 1941-2000. Results of the study suggest that the CPPG model can adequately describe occurrences of HWEs and the distributions of their durations (including distributions of extreme durations), as well as the distributions of the number of hot days, when assessed on the basis of the Kolmogorov-Smirnov and chi-squared goodness-of-fit tests. A non-stationary framework is introduced and applied to 2 contrasting sets of non-stationary observations of HWEs from Les Cedres and La Tuque (southern Quebec) for the 1941-2000 period. The results of the non-stationary modeling approach demonstrate that the developed methodology is generally applicable and could be useful in developing probabilistic information about various ­characteristics of hot weather climate for a particular location or a larger spatial domain.

KEY WORDS: Climate change · Compound Poisson process · Hot weather spells · Logarithmic ­distribution · Negative binomial distribution · Poisson-gamma model

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Cite this article as: Khaliq MN, Ouarda TBMJ, Gachon P, Sushama L (2011) Stochastic modeling of hot weather spells and their characteristics. Clim Res 47:187-199.

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