Preprints
https://doi.org/10.5194/egusphere-2024-1258
https://doi.org/10.5194/egusphere-2024-1258
21 May 2024
 | 21 May 2024
Status: this preprint is open for discussion.

Quantifying radiative effects of light–absorbing particles deposition on snow at the SnowMIP sites

Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova

Abstract. The deposition of light-absorbing particles (LAPs) leads to a decrease of surface albedo over snow covered surfaces. This effect, by increasing the energy absorbed by the snowpack, enhances snow melt and accelerates snow aging, process which in turn is responsible for further decreasing the snow albedo. Capturing this combined process is important in land surface modelling, as the change in surface reflectivity connected with the deposition of LAPs can modulate time and magnitude of snowmelt and runoff. These processes impact regional water resources, and can also lead to relevant feedbacks to the global climate system. We have recently developed a new numerical snowpack model for the GFDL land model (A Global Land Snow Scheme, or GLASS). GLASS provides a detailed description of snow mass and energy balance, as well as the evolution of snow microphysical properties (grain shape and size). We now extend this model to account for the presence of light-absorbing impurities, modelling their dry and wet deposition in the snowpack, the evolution of their vertical distribution in the snow due to precipitation and snow melt, and the effect of their concentration on snow optical properties. To test the effects of the resulting snow scheme, we force the GFDL land model with deposition of black carbon, mineral dust and organic carbon obtained from a general circulation model (GFDL AM4.0). We evaluate the new model configuration at a set of instrumented sites, including an alpine site (Col de Porte, France) where in-situ observations of snow (including spectral measurements of snow reflectivity and concentration of LAPs) allow for a comprehensive model evaluation. For the Col de Porte site, we show that GLASS reproduces the observed magnitudes of impurities concentration in the snowpack throughout a winter season. The seasonal evolution of the snow optical diameter is also qualitatively reproduced by the model, although the increase in snow grain diameter during the melt season appears to be underestimated. For a set of instrumented sites spanning a range of climates and LAP deposition rates (the `SnowMIP' sites) we then evaluate the number of snow-days lost due to the deposition of dust and carbonaceous aerosols. We find that this loss ranges between 5 and 24 days depending on the site. The resulting snow model with LAP-aware snow reflectivity show a good agreement with measurements of broadband albedo and seasonal SWE over the study sites.

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Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova

Status: open (until 14 Jul 2024)

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  • RC1: 'Comment on egusphere-2024-1258', Anonymous Referee #1, 20 Jun 2024 reply
Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova

Model code and software

GLASS snow model including LAPs deposition, model input and output data Enrico Zorzetto, Elena Shevliakova, Sergey Malyshev, and Paul Ginoux https://zenodo.org/records/10901373

Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova

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Short summary
Light-absorbing particles (LAPs) deposition on snow leads to a darkening of the snow surface and can thus accelerate snow melt. Understanding to what extent different types of LAPs contribute to snow melt is important both to predict changes in water availability and for improving global climate model predictions. Here we extend a recently developed snow model to account for the deposition of LAPs in the snowpack and evaluate the effect of snow darkening on accelerating snow melt.