Snow multivariable data assimilation for hydrological predictions in Alpine sites

Piazzi, G. ; Thirel, G. ; Campo, L. ; Gabellani, S. ; Stevenin, H.

Type de document
Communication scientifique sans actes
Langue
Anglais
Affiliation de l'auteur
CIMA RESEARCH FOUNDATION SAVONA ITA ; IRSTEA ANTONY UR HBAN FRA ; CIMA RESEARCH FOUNDATION SAVONA ITA ; CIMA RESEARCH FOUNDATION SAVONA ITA ; DIPARTIMENTO TERRITORIO AMBIENTE E RISORSE IDRICHE REGIONE AUTONOMA VALLE D'AOSTA ITA
Année
2017
Résumé / Abstract
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.
Source
Geophysical Research Abstracts, vol. 19, 1 p.
Congrès
EGU General Assembly 2017, 23/04/2017 - 28/04/2017, Vienna, AUT

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