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Validation of the energy budget of an alpine snowpack simulated by several snow models (Snow MIP project)

  • Pierre Etchevers (a1), Eric Martin (a1), Ross Brown (a2), Charles Fierz (a3), Yves Lejeune (a1), Eric Bazile (a4), Aaron Boone (a4), Yong-Jiu Dai (a5), Richard Essery (a6), Alberto Fernandez (a7), Yeugeniy Gusev (a8), Rachel Jordan (a9), Victor Koren (a10), Eva Kowalczyk (a11), N. Olga Nasonova (a8), R. David Pyles (a12), Adam Schlosser (a13), Andrey B. Shmakin (a14), Tatiana G. Smirnova (a15), Ulrich Strasser (a16), Diana Verseghy (a2), Takeshi Yamazaki (a17) and Zong-Liang Yang (a18)...

Abstract

Many snow models have been developed for various applications such as hydrology, global atmospheric circulation models and avalanche forecasting. The degree of complexity of these models is highly variable, ranging from simple index methods to multi-layer models that simulate snow-cover stratigraphy and texture. In the framework of the Snow Model Intercomparison Project (SnowMIP), 23 models were compared using observed meteorological parameters from two mountainous alpine sites. The analysis here focuses on validation of snow energy-budget simulations. Albedo and snow surface temperature observations allow identification of the more realistic simulations and quantification of errors for two components of the energy budget: the net short- and longwave radiation. In particular, the different albedo parameterizations are evaluated for different snowpack states (in winter and spring). Analysis of results during the melting period allows an investigation of the different ways of partitioning the energy fluxes and reveals the complex feedbacks which occur when simulating the snow energy budget. Particular attention is paid to the impact of model complexity on the energy-budget components. The model complexity has a major role for the net longwave radiation calculation, whereas the albedo parameterization is the most significant factor explaining the accuracy of the net shortwave radiation simulation.

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References

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