Comparison of MODIS-derived land surface temperatures with near-surface soil and air temperature measurements in continuous permafrost terrain

In Arctic and sub-Arctic regions, meteorological stations are scattered and poorly distributed geographically; they are mostly located along coastal areas and are often unreachable by road. Given that high-latitude regions are the ones most significantly affected by recent climate warming, there is a need to supplement existing meteorological station networks with spatially continuous measurements such as those obtained by spaceborne platforms. In particular, land surface (skin) temperature (LST) retrieved from satellite sensors offer the opportunity to utilize remote sensing technology to obtain a consistent coverage of a key parameter for climate, permafrost, and hydrological research. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms offers the potential to provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS were compared to ground-based near-surface air and soil temperature measurements obtained at herbaceous and shrub tundra sites located in the continuous permafrost zone of northern Québec, Canada, and the North Slope of Alaska, USA. LST values were found to be better correlated with near-surface air temperature (1–2 m above the ground) than with soil temperature (3–5 cm below the ground) measurements. A comparison between mean daily air temperature from ground-based station measurements and mean daily MODIS LST, calculated from daytime and nighttime temperature values of both Terra and Aqua acquisitions, for all sites and all seasons pooled together reveals a high correlation between the two sets of measurements (R>0.93 and mean difference of 1.86 °C). Mean differences ranged between 0.51 °C and 5.13 °C due to the influence of surface heterogeneity within the MODIS 1 km2 grid cells at some sites. Overall, it is concluded that MODIS offers a great potential for monitoring surface temperature changes in high-latitude tundra regions and provides a promising source of input data for integration into spatially-distributed permafrost models.