Improved snow ageing parameter for large-scale albedo modelling with Crocus

• Main Authors: Gaillard, Manon, Vionnet, Vincent, Lafaysse, Matthieu, Dumont, Marie, Ginoux, Paul
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2024
• Subjects: albedo
• Online Access: https://doi.org/10.5281/zenodo.11554926

Description Light-absorbing particles (LAPs) deposited at the snow surface significantly reduce its albedo and strongly affect the snow melt dynamics. The explicit simulation of these effects with advanced snow radiative transfer models can be associated with a large computational cost. Consequently, many albedo schemes used in snowpack models still rely on empirical parameterizations that do not account for the spatial variability of LAP deposition. In Gaillard et al. (2024), a new strategy of intermediate complexity that includes the effects of spatially variable LAP deposition on snow albedo was tested with the snowpack model Crocus. Itrelies on an optimization of the parameter that controls the evolution of snow albedo in the visible range. A global dataset ofLAP-informed and spatially variable values of this parameter was constructed. These revised parameter values improved snowalbedo simulations at the ten sites considered in the study by 10%, with the largest improvements found in the Arctic (morethan 25%). The data are distributed in a NetCDF file (gamma _tot_publish.nc ). More details about the dataset and the file format are given in the file readme_gamma.pdf .