Identification of radiative and advective populations in Canadian temperature time series using the Linear Pattern Discrimination algorithm

Abstract

AbstractLong‐term high‐frequency air temperature time series, typically considered the most authoritative observed records for the detection of climate changes, appear physically heterogeneous by nature. We examine multiple Canadian air temperature records for the presence of physical heterogeneities, using the analysis of their diurnal temperature patterns as the main criterion for the separation of temperature series into ‘homogeneous’ populations. Based on the key differences observed in their diurnal air temperature patterns, two distinct populations of the air temperature sample are identified and assumed to be the result of different heat exchange mechanisms. The Linear Pattern Discrimination (LPD) algorithm, implemented in the R‐code, is introduced in this work and applied to 66‐year long hourly temperature records of 25 Canadian stations for the separation of the radiative temperature population from the advective temperature population and examination of incidences of specific, advective cases in air temperature data. The LPD analysis reveals a predominance of a remarkably warmer, radiatively driven air temperature regime. In contrast, the significantly colder and geographically controlled advective temperature regime plays a counterbalancing role on the overall magnitude of the midlatitude air temperature signal. Our findings suggest that a substantial temperature increase in annual averages of advective minima amplifies the effect of a positively shifted radiative temperature range, intensifying the overall heating observed in the Canadian North and northwestern regions.