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Snow water equivalent retrieval in a Canadian boreal environment from microwave measurements using the HUT snow emission model

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5 Author(s)
V. Roy ; Centre d'Applic. et de Recherches en Teledetection, Univ. de Sherbrooke, Que., Canada ; K. Goita ; A. Royer ; A. E. Walker
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Snow water equivalent (SWE) is a critical parameter for climatological and hydrological studies over northern high-latitude areas. In this paper, we study the usability of the Helsinki University of Technology (HUT) snow emission model for the estimation of SWE in a Canadian boreal forest environment. The experimental data (airborne passive microwave and ground-based data) were acquired during the Boreal Ecosystem-Atmosphere Study winter field campaign held in February 1994 in Central Canada. Using the experimental dataset, surface brightness temperatures at 18 and 37 GHz (vertical polarization) were simulated with the HUT snow emission model and compared to those acquired by the airborne sensors. The results showed an important underestimation at 37 GHz (-27 K) and an overestimation at 18 GHz (10 K). In this paper, we demonstrate that the errors in the model simulations are due mainly to the extinction coefficient modeling, which is a function of snow grain size. Therefore, we propose a new semiempirical function for the extinction coefficient, based on an empirical correction to the Rayleigh scattering expression. Results presented in this paper show that the proposed function improves the HUT model accuracy to predict brightness temperature in the experimental context considered, with a mean error of ±5 K and ±9 K, respectively, at 18 and 37 GHz, and a negligible bias (less than 4 K) in both cases. These errors are comparable in magnitude to the accuracy of the radiometers used during the airborne flights. SWE was retrieved using the modified HUT snow emission model based on an iterative inversion technique. SWE was estimated with a mean error of ±10 mm and a negligible bias. Only a rough knowledge of mean snow grain size φ~ was required in the inversion procedure. The effects of possible errors on mean snow grain size φ~ are presented and discussed.

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IEEE Transactions on Geoscience and Remote Sensing  (Volume:42 ,  Issue: 9 )