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- Bauwens, Maite, et al.
(författare)
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A Nonlinear Multi-Proxy Model Based on Manifold Learning to Reconstruct Water Temperature from High Resolution Trace Element Profiles in Biogenic Carbonates
- 2010
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Ingår i: Geoscientific Model Development. - : Copernicus Publications. - 1991-959X .- 1991-9603. ; 3:3, s. 653-667
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Tidskriftsartikel (refereegranskat)abstract
- A long standing problem in paleoceanography concerns the reconstruction of water temperature from δ18O carbonate, which for freshwater influenced environments is hindered because the isotopic composition of the ambient water (related to salinity) affects the reconstructed temperature. In this paper we argue for the use of a nonlinear multi-proxy method called Weight Determination by Manifold Regularization to develop a temperature reconstruction model that is less sensitive to salinity variations. The motivation for using this type of model is twofold: Firstly, observed nonlinear relations between specific proxies and water temperature motivate the use of nonlinear models. Secondly, the use of multi-proxy models enables salinity related variations of a given temperature proxy to be explained by salinity-related information carried by a separate proxy. Our findings confirm that Mg/Ca is a powerful paleothermometer and highlight that reconstruction performance based on this proxy is improved significantly by combining its information with the information of other trace elements in multi-proxy models. Using Mg/Ca, Sr/Ca, Ba/Ca and Pb/Ca the WDMR model enabled a temperature reconstruction with a root mean squared error of ±2.19 °C for a salinity range between 15 and 32.
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| 2. |
- Bauwens, Maite, et al.
(författare)
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On Climate Reconstruction using Bivalve Shells : Three Methods to interpret the Chemical Signature of a Shell
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The chemical composition of a bivalve shell is strongly coupled to the seasonal variations in the environment. The nonlinear nature of this relation however makes it hard to predict, e.g. the temperature, from the chemical composition of a shell. In this paper we compare the ability of three nonlinear system identification methods to reconstruct the temperature from the chemical composition of a shell. The comparison shows that nonlinear multi-proxy approaches are potential tools for climate reconstructions with a preference for manifold based methods that results in smoother and a more precise temperature reconstruction.
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| 3. |
- Bauwens, Maite, et al.
(författare)
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On Climate Reconstruction Using Bivalve Shells : Three Methods To Interpret the Chemical Signature of a Shell
- 2011
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier. - 0169-2607 .- 1872-7565. ; 104:2, s. 104-111
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Tidskriftsartikel (refereegranskat)abstract
- To improve our understanding of the climate process and to assess the human impact on current global warming, past climate reconstruction is essential. The chemical composition of a bivalve shell is strongly coupled to environmental variations and therefore ancient shells are potential climate archives. The nonlinear nature of the relation between environmental condition (e.g. the seawater temperature) and proxy composition makes it hard to predict the former from the latter, however. In this paper we compare the ability of three nonlinear system identification methods to reconstruct the ambient temperature from the chemical composition of a shell. The comparison shows that nonlinear multi-proxy approaches are potentially useful tools for climate reconstructions and that manifold based methods result in smoother and more precise temperature reconstruction.
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| 4. |
- Bauwens, Maite, et al.
(författare)
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On Climate Reconstruction using Bivalve Shells: Three Methods to interpret the Chemical Signature of a Shell
- 2009
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Ingår i: Proceedings of the 7th IFAC Symposium on Modelling and Control in Biomedical Systems (including Biological Systems). - 9783902661494 ; , s. 407-412
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Konferensbidrag (refereegranskat)abstract
- The chemical composition of a bivalve shell is strongly coupled to the seasonal variations in the environment. The nonlinear nature of this relation however makes it hard to predict, e.g. the temperature, from the chemical composition of a shell. In this paper we compare the ability of three nonlinear system identification methods to reconstruct the temperature from the chemical composition of a shell. The comparison shows that nonlinear multi-proxy approaches are potential tools for climate reconstructions with a preference for manifold based methods that results in smoother and a more precise temperature reconstruction.
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