**Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya**

**Shaktiman Singh 1,\* , Anshuman Bhardwaj <sup>1</sup> , Atar Singh <sup>2</sup> , Lydia Sam <sup>1</sup> , Mayank Shekhar <sup>3</sup> , F. Javier Martín-Torres 1,4 and María-Paz Zorzano 1,5**


Received: 21 October 2019; Accepted: 2 December 2019; Published: 4 December 2019

**Abstract:** The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (*Ta*) 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<sup>a</sup>* recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (*Ts*) 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<sup>a</sup>* vs. *T<sup>s</sup>* relationship: (i) *T<sup>s</sup>* are strongly correlated with *T<sup>a</sup>* (R<sup>2</sup> = 0.77, root mean square difference (RMSD) = 5.9 ◦C, *n* = 11,101 at daily scale and R<sup>2</sup> = 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<sup>a</sup>* vs. *T<sup>s</sup>* 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 *Ts* products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting *Ta* by *Ts* as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived *Ts* in place of discrete in situ *T<sup>a</sup>* extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.

**Keywords:** Himalaya; land surface temperature; air temperature; topography; MODIS
