Introducing Thermal Inertia for Monitoring Snowmelt Processes With Remote Sensing

Abstract

Thermal inertia has been successfully used in remote sensing applications that span from geology, geomorphology to hydrology. In this paper, we propose the use of thermal inertia for describing snow dynamics. Two different formulations of thermal inertia were tested using experimental and simulated data related to snowpack dynamics. Experimental data were acquired between 2012 and 2017 from an automatic weather station located in the western Italian Alps at 2,160 m. Simulations were obtained using the one-dimensional multilayer Crocus model. Results provided evidences that snowmelt phases can be recognized, and average snowpack density can be estimated reasonably well from thermal inertia observations (R 2  = 0.71; RMSE = 65 kg/m 3 ). The empirical model was also validated with manual snow density measurements (R 2  = 0.80; RMSE = 54 kg/m 3 ). This study is the first attempt at the exploitation of thermal inertia for snow monitoring, combining optical and thermal remote sensing data.