Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/tc-2017-286
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
11 Jan 2018
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal The Cryosphere (TC).
A Particle Filter scheme for multivariate data assimilation into a point-scale snowpack model in Alpine environment
Gaia Piazzi1, Guillaume Thirel2, Lorenzo Campo1, and Simone Gabellani1 1CIMA Research Foundation, Savona, 17100, Italy
2Hydrosystems and Bioprocesses Research Unit (HBAN), Irstea, Antony, 92160, France
Abstract. The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality of the snowpack simulations, whose dynamics strongly affects the local hydrological regime, especially during the melting period. With the aim of reducing the modelling uncertainty, data assimilation techniques are increasingly being implemented for operational purposes. This study aims at investigating the performance of a multivariate Sequential Importance Resampling – Particle Filter scheme designed to jointly assimilate several ground-based snow observations. The system, which relies on a multilayer energy-balance snow model, has been tested at three Alpine sites: Col de Porte (France), Torgnon (Italy), and Weissfluhjoch (Switzerland). The implementation of a multivariate data assimilation scheme faces several challenging issues, which are here addressed and extensively discussed: (1) the effectiveness of the perturbation of the meteorological forcing data in preventing the sample impoverishment; (2) the impact of the parameters resampling on the filter updating of the snowpack state; (3) the system sensitivity to the frequency of the assimilated observations.
Citation: Piazzi, G., Thirel, G., Campo, L., and Gabellani, S.: A Particle Filter scheme for multivariate data assimilation into a point-scale snowpack model in Alpine environment, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-286, in review, 2018.
Gaia Piazzi et al.
Gaia Piazzi et al.
Gaia Piazzi et al.

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Short summary
The study focuses on the development of a multivariate Particle filtering data assimilation scheme into a point-scale snow model. One of the main challenging issues concerns the impoverishment of the particles sample, which is addressed by perturbing the meteorological data and resampling the model parameters. An additional snow density model is introduced to reduce the sensitivity to the frequency of the assimilated observations. In this configuration,the system reveals satisfying performances.
The study focuses on the development of a multivariate Particle filtering data assimilation...
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