Providing climatic data like temperature in good spatial resolution is a key requirement for many geographical, ecological and bioclimatic researches. With this in mind, various related studies use thermal remote sensing images as auxiliary data to enhance the air temperature interpolation outcomes. Normally summer season images are used as auxiliary data and less attention has been paid to winter season acquired images which covered by snowy areas. For this purpose, the data used was temperature data and four Landsat thermal images for ۱۹۸۶ and ۱۹۹۹ December. We investigated the Snow Covered Area (SCA) extent impact on air temperature interpolation. To calculate the area of snow cover, band combination and NDSI index were calculated to understand which extent of snow cover could be important in interpolation of air temperature. Results show that, Thermal Co-Kriging (TCK) for December of ۱۹۸۶ provide better results with more snow affected thermal image. While, in ۱۹۹۹ although different results were obtained but the best selected output did not show impacts of different snow cover area. These results revealed that probably the SCA extent threshold could be different and could be find with more research. At the end, we know that number of our observation stations are too low and considering the Kriging requirements like normal distribution and stationarity is toilsome but we should consider that this problem exist in the regions with low density of gauges and should find a way to enhance the air temperature interpolation in these cases

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