Analysis of Daily Air Temperatures across a Topographically Complex Alpine Region of Southwestern Yukon, Canada
Keywords: Yukon climate, HOBO data logger, meteorological station network, daily and hourly temperature dataset, time series analysis, seasonal-trend decomposition (STL)
AbstractThis study provides an analysis of six years of daily air temperature data collected using 16 HOBO® UA-002-64 Pendant data loggers placed along a 280 km transect in southwestern Yukon and northern British Columbia. Correlation and time series analyses, including Seasonal Decomposition of Time Series by Loess (STL) methods, revealed very high correlations among all data series at daily to annual timescales. The two meteorological stations in the region are found to be generally representative of the greater area, and local temperature variability appears to be predominantly determined by synoptic-scale weather patterns. The annual temperature cycle in this region is complex and has annually repeating components at all study sites across the region. The analysis of daily data using the STL method can provide new insight into climate time series and enhance our ability to observe patterns and extremes in temperatures across varying spatial and temporal scales. Data loggers provide a cost-effective way of obtaining similar (and sometimes higher-quality) information compared to meteorological stations or gridded global datasets.