The study area has chosen along the N-S transect across the Himalaya, Gangetic plains and Chotanagpur plateau. We basically tried to observe the variation in the most important climatic variables i.e. Net Surface Radiation (Rn), Temperature, Rainfall, Evapotranspiration (ET) etc. during 2000-2016. Generally the meteorological parameters shows its variability over a large spatial domain and remains invariable for closer ground based observations. In contrast, the satellite data is capable to present a synoptic view in a single image. Therefore it is more reliable to use the satellite dataset for the study of such meteorological parameters. The TRMM monthly average precipitation (0.25° X 0.25°), MODIS-Terra 8 day average LST product (1km X 1km), MERRA-2 radiation (0.5° x 0.625°) and GLDAS reanalysis model data (0.25°X0.25°) has been used to study and analyse the spatial variability and distribution of rainfall, surface temperature, energy fluxes and evapotranspiration, respectively. The results have shown that the overall annual average rainfall has a gradual decreasing trend. It results after the correlation with temperature (>35°C) that the regions with low rainfall (<1000mm) have to witness warmer temperature conditions (>43°C). The difference in maximum and minimum temperature is increasing at the rate of 1°C per five years. The east-west central line of the Bihar, along the river Ganga is found to be the line of division i.e. almost 80% of the area which witness >35°C temperature lies below this line and few 10-20% lies above it. The results for Rn have shown an overall increasing trend over the period of time. The Nepal has a wider stretch of Rn due to its mountain topography followed by the Jharkhand (plateau) and Bihar (plain). The ET has also an increasing trend over the period of time and the results are noticeable for western Bihar-Jharkhand. There is an upward latitudinal shifting of the low rainfall bands in both the pre-monsoon and monsoon conditions. Due to the lack of availability of ground truth data, we have to restrict with the remotely sensed dataset. Since the dataset chosen are well accepted globally, the data inaccuracy is minimal. Hence, the study will help to understand the fluctuation in local weather phenomenon may useful for adapting sustainable strategies to mitigate the climate change effect on local scale.