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Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

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Abstract

In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.

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Acknowledgments

The Authors are grateful to the International Development Research Center (IDRC) and to the Natural Sciences and Engineering Research Council of Canada (NSERC) for the financial support through the FACE project subvention (Faire Face Aux Changements Ensemble: mieux s’adapter aux changements climatiques au Canada et en Afrique de l’Ouest dans le domaine des ressources en eau). We also thank the Environment Canada Data Access Integration (DAI) portal for providing data from observed daily precipitation amounts.

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Authors and Affiliations

  1. Centre Eau Terre-Environnement, Institut National de la Recherche Scientifique, 490, de la Couronne Street, Québec City, G1K 9A9, Canada

    Alida N Thiombiano & André St-Hilaire

  2. Université de Moncton, 18 Antonine-Maillet Avenue, Moncton, NB, E1A 3EA, Canada

    Salaheddine El Adlouni & Nassir El-Jabi

  3. Institute Center for Water Advanced Technology and Environment Research (iWATER), Masdar Institute of Science and Technology, PO Box 54224, Abu Dhabi, United Arab Emirates

    Taha B.M.J Ouarda

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  1. Alida N Thiombiano
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  2. Salaheddine El Adlouni
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  3. André St-Hilaire
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  4. Taha B.M.J Ouarda
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  5. Nassir El-Jabi
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Correspondence to Alida N Thiombiano.

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Thiombiano, A.N., El Adlouni, S., St-Hilaire, A. et al. Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach. Theor Appl Climatol 129, 413–426 (2017). https://doi.org/10.1007/s00704-016-1789-7

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