Monthly Variation in Near Surface Air Temperature Lapse Rate Across Ganga Basin, India

Abstract

In hydrological and terrestrial models, the temperature at any ungauged location is commonly determined by interpolating surface air temperature observations obtained from a sparse network of temperature sensors using the standard environmental lapse rate (−0.65 °C/100 m). Though simplistic, this interpolation technique can often lead to incorrect results, as the standard environmental lapse rate may not account for temporal and regional variations. In this study, linear regression relationships are developed to estimate average minimum, average, and average maximum near-surface air temperature lapse rates (at monthly time scales) for the Ganga basin, India. Normal daily air temperature data from 178 stations and the latitude, longitude, and elevation of the stations were used for developing the regression equations. The computed temperature gradients exhibit seasonal variation. The lapse rates obtained for summer months are steeper when compared to lapse rates observed in winter months. The highest lapse rate is observed for the average maximum temperature in April month (−0.76 °C/100 m), whereas the lowest lapse rate is observed for the average minimum temperature in December month (−0.21 °C/100 m). The standard environmental lapse rate (−0.65 °C/100 m) is only observed for the monthly average maximum and average temperature for March and May, respectively. A very good agreement between the interpolated and the observed temperature is obtained for the monthly average temperature. The developed regression equations can be reliably used to predict the temperature in the Ganga basin.KeywordsLapse rateSurface temperatureGanga basinMonthly variation