In the Himalayan region, aerosols received much attention because they affect the regional as well as local climate. Aerosol Optical Depth (AOD) observation from satellite are limited in the Himalayan region mainly due to high surface reflectance. To overcome this limitation, we have conducted a multivariate regression analysis to predict the AOD over the cryospheric portion of Nepalese Himalaya. Prediction using three meteorological variables from ERA-Interim: relative humidity, wind velocity components (U10 and V10) were taken into account for model development as independent variables, while the longest time series AOD observation at Pokhara station is used as dependent variable. Model coefficients were found significant at 95 percent level with 0.53 coefficients of determination for daily values. Correlation coefficients between model output and AERONET observations were found to be 0.68, 0.73, 0.75, 0.83, and 0.82 at Lumbini, Kathmandu Bode (KTM-BO), Kathmandu University (KTM-UN), Jomson, and Pyramid laboratory/observatory (EVK2CNR) AERONET stations, respectively. Model overestimate AOD at Jomsom, and EVK2CNR AERONET stations while slightly underestimates AOD in Lumbini, KTM-UN, and KTM-BO AERONET station, respectively. Both model output and MODIS observation showed that the highest AOD over Nepal is observed during winter and pre-monsoon season. While lowest AOD is observed during monsoon, and post-monsoon season. The result of this research supports that the use of linear regression model yields good estimation for daily average AOD in Nepal. The model that we have presented could possibly be used in other mountain regions for climate research.
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