Abstract
Spatially continuous satellite infrared temperature measurements are essential for understanding the consequences and drivers of change, at local and regional scales, especially in northern and alpine environments dominated by a complex cryosphere where in situ observations are scarce. We describe two methods for producing daily temperature fields using MODIS “clear-sky” day-time Land Surface Temperatures (LST). The Interpolated Curve Mean Daily Surface Temperature (ICM) method, interpolates single daytime Terra LST values to daily means using the coincident diurnal air temperature curves. The second method calculates daily mean LST from daily maximum and minimum LST (MMM) values from MODIS Aqua and Terra. These ICM and MMM models were compared to daily mean air temperatures recorded between April and October at seven locations in southwest Yukon, Canada, covering characteristic alpine land cover types (tundra, barren, glacier) at elevations between 1,408 m and 2,319 m. Both methods for producing mean daily surface temperatures have advantages and disadvantages. ICM signals are strongly correlated with air temperature (R2 = 0.72 to 0.86), but have relatively large variability (RMSE = 4.09 to 4.90 K), while MMM values had a stronger correlation to air temperature (R2 = 0.90) and smaller variability (RMSE = 2.67 K). Finally, when comparing 8-day LST averages, aggregated from the MMM method, to air temperature, we found a high correlation (R2 = 0.84) with less variability (RMSE = 1.54 K). Where the trend was less steep and the y-intercept increased by 1.6 °C compared to the daily correlations. This effect is likely a consequence of LST temperature averages being differentially affected by cloud cover over warm and cold surfaces. We conclude that satellite infrared skin temperature (e.g., MODIS LST), which is often aggregated into multi-day composites to mitigate data reductions caused by cloud cover, changes in its relationship to air temperature depending on the period of aggregation.
Highlights
High latitudes in the Northern Hemisphere have experienced significant recent warming, with Yukon and parts of Alaska experiencing the greatest warming of sub-arctic environments over the last 50 years [1,2]
Land Surface Temperatures (LST) values (MMM method) provided better agreement with daily air temperature averages, the very small number of daily averages indicated that direct calculation of average LST was not always feasible for the study area
The average LST calculated from the minimum LST (MMM) algorithm had an even stronger correlation with air temperature (R2 = 0.90) and smaller variability (RMSE = 2.67 K)
Summary
High latitudes in the Northern Hemisphere have experienced significant recent warming, with Yukon and parts of Alaska experiencing the greatest warming of sub-arctic environments over the last 50 years [1,2]. This warming trend is expected to continue throughout the Arctic [3]. Mean surface temperature provides a fundamental measure for understanding change occurring in Arctic, sub-Arctic and alpine land surface processes. The absence of fine scale, continuous temperature monitoring over large geographical areas makes identifying climate induced changes difficult. In Yukon, Canada, which has an area of 483,450 km, there are only eleven meteorological stations maintained by Environment Canada (http://www.climate.weatheroffice.gc.ca)
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