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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 7
The Cryosphere, 12, 2287–2306, 2018
https://doi.org/10.5194/tc-12-2287-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
The Cryosphere, 12, 2287–2306, 2018
https://doi.org/10.5194/tc-12-2287-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Jul 2018

Research article | 12 Jul 2018

A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment

Gaia Piazzi et al.
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Gaia Piazzi on behalf of the Authors (19 Apr 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Apr 2018) by Marie Dumont
RR by Anonymous Referee #2 (25 May 2018)
RR by Matthieu Lafaysse (05 Jun 2018)
ED: Publish subject to minor revisions (review by editor) (07 Jun 2018) by Marie Dumont
AR by Gaia Piazzi on behalf of the Authors (11 Jun 2018)  Author's response    Manuscript
ED: Publish subject to technical corrections (26 Jun 2018) by Marie Dumont
Publications Copernicus
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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 particle sample, which is addressed by jointly perturbing meteorological data and model parameters. An additional snow density model is introduced to reduce sensitivity to the availability of snow mass-related observations. In this configuration, the system reveals a satisfying performance.
The study focuses on the development of a multivariate particle filtering data assimilation...
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