Detrended fluctuation analysis of daily atmospheric surface temperature records in Atlantic Canada

The presence and properties of long‐range correlations in temperature data reflect interactions among climate components; therefore, the quantitative characterization of scaling aspects of temperature patterns is important to climate research and can serve as an effective constituent of tests for climate models. The article presents the results of a study using multiscale characterization of daily atmospheric surface temperature patterns in Atlantic Canada. Important influences in this region are exerted from the west (the Pacific Ocean), the south (the Gulf of Mexico) and the north (the Arctic), while a significant easterly impact is due to the Atlantic Ocean; the corresponding processes involve a wide range of spatial and temporal scales. The objective of the present study of long‐term temperature recordings was to evaluate the scaling properties produced in this geographical context. The data consist of homogenized daily atmospheric temperature time series recorded in stations from Atlantic Canada over a time interval of more than 100 years. Detrended fluctuation analysis (DFA) was applied both to maximum and minimum temperature records. The atmospheric temperature pattern produced by the interplay of factors of different strengths and dominating various time‐space scales was found to be characterized by consistent scaling properties, expressed over time intervals ranging from months to decades. Higher values of DFA scaling exponents were obtained for minimum temperature compared to maximum temperature records. Site‐specific properties include stronger pattern persistence—higher DFA exponents—for oceanic than for coastal locations; persistence tends to decrease with increasing distance from the coast for distances up to 10 kilometres. Scaling exponents tend to increase with decreasing difference between average minimum and maximum temperature, which may be relevant for the assessment of future changes in pattern variability if climate change involves modified contrasts between minimum and maximum temperature values.