Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model

• Published in: The Cryosphere
• Main Authors: Carmagnola, C. M., Morin, S., Lafaysse, M., Domine, F., Lesaffre, B., Lejeune, Y., Picard, G., Arnaud, L.
• Format: Text
• Language: English
• Published: 2018
• Subjects: Greenland; Summit Camp
• Online Access: https://doi.org/10.5194/tc-8-417-2014; https://tc.copernicus.org/articles/8/417/2014/

In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure has up to now been characterised by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter ( d opt ). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). d opt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of d opt , including a re-formulation of the original Crocus scheme and the parameterisations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m 2 kg −1 . Incorporating the optical diameter as a fully fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.