Abstract. Obtaining high resolution records of surface temperature from satellite sensors is important in the Arctic because meteorological stations are scarce and widely scattered in those vast and remote regions. Surface temperature is the primary climatic factor that governs the existence, spatial distribution and thermal regime of permafrost which is a major component of the terrestrial cryosphere. Land Surface (skin) Temperatures (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to ground-based nearsurface air (T air ) and ground surface temperature (GST) measurements obtained from 2000 to 2008 at herbaceous and shrub tundra sites located in the continuous permafrost zone of Northern Québec, Nunavik, Canada, and of the North Slope of Alaska, USA. LSTs (temperatures at the surface materials-atmosphere interface) are found to be better correlated with T air (1-3 m above the ground) than with available GST (3-5 cm below the ground surface). As T air is most often used by the permafrost community, this study focused on this parameter. LSTs are in stronger agreement with T air during the snow cover season than in the snow free season. Combining Aqua and Terra LST-Day and LST-Nigh acquisitions into a mean daily value provides a large number of LST observations and a better overall agreement with T air . Comparison between mean daily LSTs and mean daily T air , for all sites and all seasons pooled together yields a very high correlation (R = 0.97; mean difference (MD) = 1.8 • C; and standard deviation of MD (SD) = 4.0 • C). The large SD can be explained by the influence of surface heterogeneity within the MODIS 1 km 2 grid cells, the presence of undetected clouds and the inherent difference between LST and T air . Retrieved over several years, MODIS LSTs offer a great potential for monitoring surface temperature changes in high-latitude tundra regions and are a promising source of input data for integration into spatially-distributed permafrost models.

The Land Surface Temperature (LST) products of the Moderate Resolution Imaging Spectroradiometers (MODIS) aboard NASA's Terra and Aqua satellites were used to develop maps of annual near‐surface temperatures for comparison with the spatial distribution of permafrost and boundaries of the permafrost zones. The methodological approach involved fitting a sinusoidal model over the daily LST readings to reproduce seasonal thermal variations near the ground for each 1‐km2 pixel. Calculations of mean annual surface temperatures and of thawing and freezing indices led to the development of regional maps, in this case for northern Québec and Labrador. The maps show the expected geographic distribution of near‐surface temperatures and acceptably represent known permafrost boundaries. Ongoing efforts to incorporate snow and vegetation cover from complementary remotely sensed data should improve the ground surface temperature mapping capability based on this approach. Copyright © 2009 John Wiley & Sons, Ltd.

Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1-25 km) for the past decade (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). In this paper, we provide: (1) a review of previous validation of MODIS/AATSR L2; (2) a description of the processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max: −1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions.

Paleoclimate reconstructions are generally validated on recent periods. To obtain a set of instrumental records at the regional scale, a time series of monthly mean temperatures in Northeastern Canada were interpolated for the 1961-2000 period. Records were provided by 202 meteorological stations. Temperatures derived from a Canadian regional climate model (Climate Model CRCM 4.2.3 from the AMNO domain produced at ∼50 km resolution) were added as secondary information to take into account local heterogeneity and temporal dependencies. Geostatistical interpolation of the measured temperature was calculated using CRCM modelled data as a covariable and then compared to an ordinary kriging performed on a time series of mean temperature anomalies. Spherical distances between locations were calculated taking into account the curvature of the Earth with monthly semivariances being modelled using Cauchy variograms. Mean absolute error values (1.5 ± 1.2°C) were calculated for the whole period using cross-validation procedures. Errors were found to have the same order of magnitude in the central part of the study area where few recorded temperatures were available. Monthly mean temperature grids are publicly available through the Institut National de la Recherche Scientifique

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 (<i>R</i>>0.93 and mean difference of &minus;1.86 °C). Mean differences ranged between &minus;0.51 °C and &minus;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