Trend detection in surface air temperature in Ontario and Quebec, Canada during 1967–2006 using the discrete wavelet transform

Abstract

The main purpose of this study is to detect trends in the mean surface air temperature over the southern parts of Ontario and Quebec, Canada, for the period of 1967–2006. This is accomplished by determining the most dominant periodic components that affect trends in different temperature data categories (monthly, seasonally-based, seasonal, and annual), which were obtained from a total of five stations. The discrete wavelet transform (DWT) technique, the Mann–Kendall (MK) trend test, and sequential Mann–Kendall analysis were used in this study — co-utilizing these techniques in temperature trend studies has not been explored extensively. The mother wavelet, number of decomposition levels, and boundary condition were determined using a newly proposed criterion based on the relative error of the MK Z-values between the original data and the approximation component of the last decomposition level. This study found that all stations experienced positive trends: significant trends were observed in all of the monthly, seasonally-based, and annual data. For the different seasons, although the trend values were all positive, not all stations experienced significant trends. It was found that high-frequency components ranging from 2 to 12months were more prominent for trends in the higher resolution data (i.e. monthly and seasonally based). The positive trends observed for the annual data are thought to be mostly attributable to warming during winter and summer seasons, which are manifested in the form of multiyear to decadal events (mostly between 8 and 16years).