A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment
The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality of the snowpack simulations, with dynamics that strongly affect the local hydrological regime, especially during the melting period. With the aim of reducing the modelling uncertainty, data assimilation...
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ftdoajarticles:oai:doaj.org/article:c8a7d722b93b4159ac433510824cfea6 2023-05-15T18:32:25+02:00 A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment G. Piazzi G. Thirel L. Campo S. Gabellani 2018-07-01T00:00:00Z https://doi.org/10.5194/tc-12-2287-2018 https://doaj.org/article/c8a7d722b93b4159ac433510824cfea6 EN eng Copernicus Publications https://www.the-cryosphere.net/12/2287/2018/tc-12-2287-2018.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-12-2287-2018 1994-0416 1994-0424 https://doaj.org/article/c8a7d722b93b4159ac433510824cfea6 The Cryosphere, Vol 12, Pp 2287-2306 (2018) Environmental sciences GE1-350 Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.5194/tc-12-2287-2018 2022-12-30T21:17:32Z The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality of the snowpack simulations, with dynamics that strongly affect 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 to investigate 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 parameter perturbation on the filter updating of the snowpack state; the system sensitivity to (3) the frequency of the assimilated observations, and (4) the ensemble size. The perturbation of the meteorological forcing data generally turns out to be insufficient for preventing the sample impoverishment of the particle sample, which is highly limited when jointly perturbating key model parameters. However, the parameter perturbation sharpens the system sensitivity to the frequency of the assimilated observations, which can be successfully relaxed by introducing indirectly estimated information on snow-mass-related variables. The ensemble size is found not to greatly impact the filter performance in this point-scale application. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 12 7 2287 2306 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 G. Piazzi G. Thirel L. Campo S. Gabellani A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality of the snowpack simulations, with dynamics that strongly affect 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 to investigate 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 parameter perturbation on the filter updating of the snowpack state; the system sensitivity to (3) the frequency of the assimilated observations, and (4) the ensemble size. The perturbation of the meteorological forcing data generally turns out to be insufficient for preventing the sample impoverishment of the particle sample, which is highly limited when jointly perturbating key model parameters. However, the parameter perturbation sharpens the system sensitivity to the frequency of the assimilated observations, which can be successfully relaxed by introducing indirectly estimated information on snow-mass-related variables. The ensemble size is found not to greatly impact the filter performance in this point-scale application. |
format |
Article in Journal/Newspaper |
author |
G. Piazzi G. Thirel L. Campo S. Gabellani |
author_facet |
G. Piazzi G. Thirel L. Campo S. Gabellani |
author_sort |
G. Piazzi |
title |
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
title_short |
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
title_full |
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
title_fullStr |
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
title_full_unstemmed |
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment |
title_sort |
particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an alpine environment |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-12-2287-2018 https://doaj.org/article/c8a7d722b93b4159ac433510824cfea6 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 12, Pp 2287-2306 (2018) |
op_relation |
https://www.the-cryosphere.net/12/2287/2018/tc-12-2287-2018.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-12-2287-2018 1994-0416 1994-0424 https://doaj.org/article/c8a7d722b93b4159ac433510824cfea6 |
op_doi |
https://doi.org/10.5194/tc-12-2287-2018 |
container_title |
The Cryosphere |
container_volume |
12 |
container_issue |
7 |
container_start_page |
2287 |
op_container_end_page |
2306 |
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1766216530600656896 |