Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

• Published in: The Cryosphere
• Main Authors: Roy, A., Royer, A., Montpetit, B., Bartlett, P. A., Langlois, A.
• Format: Text
• Language: English
• Published: 2018
• Subjects: Arctic; albedo; Subarctic
• Online Access: https://doi.org/10.5194/tc-7-961-2013; https://tc.copernicus.org/articles/7/961/2013/

Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, while it considers the liquid water content of the snowpack for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, arctic and subarctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.0 m 2 kg –1 , and a root mean square error (RMSE) of 5.1 m 2 kg –1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.