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

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.

Nonlinear response of precipitation to climate indices using a non‐stationary Poisson‐generalized Pareto model: case study of southeastern Canada

“…Some applications with the cubic splines and B‐spline functions for a POT framework were provided, respectively, in Chavez‐Demoulin and Davison () and Thiombiano et al . (). The use of B‐spline functions with the GEV distribution was also proposed in Padoan and Wand () and Nasri et al .…”

“…Thiombiano et al . () identified the AO and PNA indices as the two dominant climatic patterns that influence the intensity of extreme daily precipitation amounts over southeastern Canada using a rank‐based correlation analysis. They also found an east–west correlation sign shift between the AO index and the studied extreme precipitation events.…”

“…Various B‐spline functions were evaluated with the GPD model in the work of Thiombiano et al . () and allowed modelling linear as well as nonlinear interactions.…”

Changes in Extreme Precipitation: A Case Study in the Middle and Lower Reaches of the Yangtze River in China

“…The EASMI was averaged from June to August to reflect the effects of the monsoon season in the MLR-YR. The Peaks-Over-Threshold (POT) approach, which is described by the generalized Pareto distribution (GPD), is widely used to estimate extreme values, including extreme precipitation, extreme temperature and wind velocity [30][31][32]. The POT approach utilizes threshold excesses above a given threshold to determine whether an extreme precipitation event occurs [33,34].…”

Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large‐scale climate anomalies

“…Even though some stations of APC2 have the latest data collected, daily precipitation data of many stations ended before 2010. However, APC2 is the most homogeneous long‐term measured data currently available for Canadian daily precipitation and has been widely used for Canadian climate analysis [e.g., DeBeer et al ., ; Tan and Gan , ; Thiombiano et al ., ; Vincent et al ., ]. More detailed information on APC2 daily precipitation data sets is given in Mekis and Vincent [].…”