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Communication Dans Un Congrès Année : 2017

Snow multivariable data assimilation for hydrological predictions in Alpine sites

Résumé

This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state.

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Dates et versions

hal-02606219 , version 1 (16-05-2020)

Identifiants

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Gaia Piazzi, Guillaume Thirel, Lorenzo Campo, Simone Gabellani, H. Stevenin. Snow multivariable data assimilation for hydrological predictions in Alpine sites. EGU General Assembly 2017, Apr 2017, Vienna, Austria. pp.1. ⟨hal-02606219⟩

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