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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Main Author: Mairesse, Aurélien
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: Université catholique de Louvain 2014
Subjects:
Online Access:https://archimer.ifremer.fr/doc/00506/61719/65687.pdf
https://archimer.ifremer.fr/doc/00506/61719/
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spelling ftarchimer:oai:archimer.ifremer.fr:61719 2023-05-15T15:12:37+02:00 Analysis of the Holocene climate variability using a data assimilation method in the model LOVECLIM Mairesse, Aurélien 2014-12-17 application/pdf https://archimer.ifremer.fr/doc/00506/61719/65687.pdf https://archimer.ifremer.fr/doc/00506/61719/ eng eng Université catholique de Louvain https://archimer.ifremer.fr/doc/00506/61719/65687.pdf https://archimer.ifremer.fr/doc/00506/61719/ info:eu-repo/semantics/openAccess restricted use Climate Data assimilation Paleoclimate Holocene LOVECLIM model Proxy record text Thesis info:eu-repo/semantics/doctoralThesis 2014 ftarchimer 2021-09-23T20:33:09Z 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. Doctoral or Postdoctoral Thesis Arctic Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) Arctic
institution Open Polar
collection Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer)
op_collection_id ftarchimer
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.
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
publisher Université catholique de Louvain
publishDate 2014
url https://archimer.ifremer.fr/doc/00506/61719/65687.pdf
https://archimer.ifremer.fr/doc/00506/61719/
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation https://archimer.ifremer.fr/doc/00506/61719/65687.pdf
https://archimer.ifremer.fr/doc/00506/61719/
op_rights info:eu-repo/semantics/openAccess
restricted use
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