An assessment of particle filtering methods and nudging for climate state reconstructions
Using the climate model of intermediate complexity LOVECLIM in an idealised framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle filter and the te...
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ftdoajarticles:oai:doaj.org/article:f2e2f6acb1a743b8ad112bb61b30fd15 2023-05-15T18:18:30+02:00 An assessment of particle filtering methods and nudging for climate state reconstructions S. Dubinkina H. Goosse 2013-05-01T00:00:00Z https://doi.org/10.5194/cp-9-1141-2013 https://doaj.org/article/f2e2f6acb1a743b8ad112bb61b30fd15 EN eng Copernicus Publications http://www.clim-past.net/9/1141/2013/cp-9-1141-2013.pdf https://doaj.org/toc/1814-9324 https://doaj.org/toc/1814-9332 doi:10.5194/cp-9-1141-2013 1814-9324 1814-9332 https://doaj.org/article/f2e2f6acb1a743b8ad112bb61b30fd15 Climate of the Past, Vol 9, Iss 3, Pp 1141-1152 (2013) Environmental pollution TD172-193.5 Environmental protection TD169-171.8 Environmental sciences GE1-350 article 2013 ftdoajarticles https://doi.org/10.5194/cp-9-1141-2013 2022-12-31T14:55:22Z Using the climate model of intermediate complexity LOVECLIM in an idealised framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle filter and the test case corresponds to the climate of the high latitudes of the Southern Hemisphere during the past 150 yr. The data-assimilation methods constrain the model by pseudo-observations of surface air temperature anomalies obtained from the same model, but different initial conditions. All three data-assimilation methods provide with good estimations of surface air temperature and of sea ice concentration, with the nudging proposal particle filter obtaining the highest correlations with the pseudo-observations. When reconstructing variables that are not directly linked to the pseudo-observations such as atmospheric circulation and sea surface salinity, the particle filters have equivalent performance and their correlations are smaller than for surface air temperature reconstructions but still satisfactory for many applications. The nudging, on the contrary, obtains sea surface salinity patterns that are opposite to the pseudo-observations, which is due to a spurious impact of the nudging on vertical exchanges in the ocean. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Climate of the Past 9 3 1141 1152 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental pollution TD172-193.5 Environmental protection TD169-171.8 Environmental sciences GE1-350 |
spellingShingle |
Environmental pollution TD172-193.5 Environmental protection TD169-171.8 Environmental sciences GE1-350 S. Dubinkina H. Goosse An assessment of particle filtering methods and nudging for climate state reconstructions |
topic_facet |
Environmental pollution TD172-193.5 Environmental protection TD169-171.8 Environmental sciences GE1-350 |
description |
Using the climate model of intermediate complexity LOVECLIM in an idealised framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle filter and the test case corresponds to the climate of the high latitudes of the Southern Hemisphere during the past 150 yr. The data-assimilation methods constrain the model by pseudo-observations of surface air temperature anomalies obtained from the same model, but different initial conditions. All three data-assimilation methods provide with good estimations of surface air temperature and of sea ice concentration, with the nudging proposal particle filter obtaining the highest correlations with the pseudo-observations. When reconstructing variables that are not directly linked to the pseudo-observations such as atmospheric circulation and sea surface salinity, the particle filters have equivalent performance and their correlations are smaller than for surface air temperature reconstructions but still satisfactory for many applications. The nudging, on the contrary, obtains sea surface salinity patterns that are opposite to the pseudo-observations, which is due to a spurious impact of the nudging on vertical exchanges in the ocean. |
format |
Article in Journal/Newspaper |
author |
S. Dubinkina H. Goosse |
author_facet |
S. Dubinkina H. Goosse |
author_sort |
S. Dubinkina |
title |
An assessment of particle filtering methods and nudging for climate state reconstructions |
title_short |
An assessment of particle filtering methods and nudging for climate state reconstructions |
title_full |
An assessment of particle filtering methods and nudging for climate state reconstructions |
title_fullStr |
An assessment of particle filtering methods and nudging for climate state reconstructions |
title_full_unstemmed |
An assessment of particle filtering methods and nudging for climate state reconstructions |
title_sort |
assessment of particle filtering methods and nudging for climate state reconstructions |
publisher |
Copernicus Publications |
publishDate |
2013 |
url |
https://doi.org/10.5194/cp-9-1141-2013 https://doaj.org/article/f2e2f6acb1a743b8ad112bb61b30fd15 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Climate of the Past, Vol 9, Iss 3, Pp 1141-1152 (2013) |
op_relation |
http://www.clim-past.net/9/1141/2013/cp-9-1141-2013.pdf https://doaj.org/toc/1814-9324 https://doaj.org/toc/1814-9332 doi:10.5194/cp-9-1141-2013 1814-9324 1814-9332 https://doaj.org/article/f2e2f6acb1a743b8ad112bb61b30fd15 |
op_doi |
https://doi.org/10.5194/cp-9-1141-2013 |
container_title |
Climate of the Past |
container_volume |
9 |
container_issue |
3 |
container_start_page |
1141 |
op_container_end_page |
1152 |
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1766195088620257280 |