The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (T_a) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of T_a recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (T_s) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the T_a vs. T_s relationship: (i) T_s are strongly correlated with T_a (R² = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R² = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported T_a vs. T_s relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed T_s products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting T_a by T_s as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived T_s in place of discrete in situ T_a extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.