Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM
The study of past climates and of mechanisms that have influenced their evolution is the key to anticipate the future climate changes. This doctoral thesis focusses on the Holocene climate, the ongoing interglacial, that starts about 11,700 years ago. The current paleoclimate knowledge is based on t...
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ftunistlouisbrus:oai:dial.uclouvain.be:boreal:154845 2024-05-12T08:00:23+00:00 Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM Mairesse, Aurélien UCL - SST/ELI/ELIC - Earth & Climate UCL - Faculté des Sciences Goosse, Hugues Renssen, Hans Van Oost, Kristof Fichefet, Thierry Dekeersmaecker, Marie-Laurence Seidenkrantz, Marit-Solveig 2014 http://hdl.handle.net/2078.1/154845 eng eng boreal:154845 http://hdl.handle.net/2078.1/154845 info:eu-repo/semantics/openAccess Climate Data assimilation Paleoclimate Holocene LOVECLIM model Proxy record info:eu-repo/semantics/doctoralThesis 2014 ftunistlouisbrus 2024-04-18T17:52:25Z The study of past climates and of mechanisms that have influenced their evolution is the key to anticipate the future climate changes. This doctoral thesis focusses on the Holocene climate, the ongoing interglacial, that starts about 11,700 years ago. The current paleoclimate knowledge is based on the one hand, on the climate models results and, on the other hand, on the reconstruction of physical variables derived from climate archives as the ice cores, the marine cores or the pollens for instance. These two types of information are complementary. Here we have combined them to obtain reconstructions of past climates using data assimilation. This technique is standard in many disciplines but not yet in paleoclimatology. The data assimilation method applied here is a particle filter. It is based on the selection of the members of an ensemble of simulations performed with the climate model LOVECLIM that have the best agreement with the reconstructions. Additional simulations are designed to investigate the contribution of various forcing to the observed changes over the Holocene. Our results demonstrate that the data assimilation can be used to objectively identify the incompatibilities that could exist between temperature reconstructions that are based on different archives. Also, the data assimilation methodology allows selecting mechanisms that, according to LOVECLIM, have influenced the climate as reconstructed using indirect indicators. For instance, about 2700 years ago, the colder Arctic climate suggested by the proxy data, may be the result of a decrease in westerlies. Including the climatic response to volcanic eruptions in our experiments does not significantly improve the agreement between simulated results and reconstructions over the Holocene. (SC - Sciences) -- UCL, 2014 Doctoral or Postdoctoral Thesis Arctic DIAL@USL-B (Université Saint-Louis, Bruxelles) Arctic |
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Open Polar |
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DIAL@USL-B (Université Saint-Louis, Bruxelles) |
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ftunistlouisbrus |
language |
English |
topic |
Climate Data assimilation Paleoclimate Holocene LOVECLIM model Proxy record |
spellingShingle |
Climate Data assimilation Paleoclimate Holocene LOVECLIM model Proxy record Mairesse, Aurélien Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
topic_facet |
Climate Data assimilation Paleoclimate Holocene LOVECLIM model Proxy record |
description |
The study of past climates and of mechanisms that have influenced their evolution is the key to anticipate the future climate changes. This doctoral thesis focusses on the Holocene climate, the ongoing interglacial, that starts about 11,700 years ago. The current paleoclimate knowledge is based on the one hand, on the climate models results and, on the other hand, on the reconstruction of physical variables derived from climate archives as the ice cores, the marine cores or the pollens for instance. These two types of information are complementary. Here we have combined them to obtain reconstructions of past climates using data assimilation. This technique is standard in many disciplines but not yet in paleoclimatology. The data assimilation method applied here is a particle filter. It is based on the selection of the members of an ensemble of simulations performed with the climate model LOVECLIM that have the best agreement with the reconstructions. Additional simulations are designed to investigate the contribution of various forcing to the observed changes over the Holocene. Our results demonstrate that the data assimilation can be used to objectively identify the incompatibilities that could exist between temperature reconstructions that are based on different archives. Also, the data assimilation methodology allows selecting mechanisms that, according to LOVECLIM, have influenced the climate as reconstructed using indirect indicators. For instance, about 2700 years ago, the colder Arctic climate suggested by the proxy data, may be the result of a decrease in westerlies. Including the climatic response to volcanic eruptions in our experiments does not significantly improve the agreement between simulated results and reconstructions over the Holocene. (SC - Sciences) -- UCL, 2014 |
author2 |
UCL - SST/ELI/ELIC - Earth & Climate UCL - Faculté des Sciences Goosse, Hugues Renssen, Hans Van Oost, Kristof Fichefet, Thierry Dekeersmaecker, Marie-Laurence Seidenkrantz, Marit-Solveig |
format |
Doctoral or Postdoctoral Thesis |
author |
Mairesse, Aurélien |
author_facet |
Mairesse, Aurélien |
author_sort |
Mairesse, Aurélien |
title |
Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
title_short |
Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
title_full |
Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
title_fullStr |
Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
title_full_unstemmed |
Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM |
title_sort |
analysis of the holocene climate variability using a data assimilation method in the model loveclim |
publishDate |
2014 |
url |
http://hdl.handle.net/2078.1/154845 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
boreal:154845 http://hdl.handle.net/2078.1/154845 |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1798842270065098752 |