Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology
Studies of coastal seas in Europe have noted the high variability of the CO<sub>2</sub> system. This high variability, generated by the complex mechanisms driving the CO<sub>2</sub> fluxes, complicates the accurate estimation of these mechanisms. This is particularly prono...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-06-01
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| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/12/3369/2015/bg-12-3369-2015.pdf |
| _version_ | 1830477037264961536 |
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| author | G. Parard A. A. Charantonis A. A. Charantonis A. Rutgerson |
| author_facet | G. Parard A. A. Charantonis A. A. Charantonis A. Rutgerson |
| author_sort | G. Parard |
| collection | DOAJ |
| description | Studies of coastal seas in Europe have noted the high variability of the
CO<sub>2</sub> system. This high variability, generated by the complex mechanisms
driving the CO<sub>2</sub> fluxes, complicates the accurate estimation of these
mechanisms. This is particularly pronounced in the Baltic Sea, where the
mechanisms driving the fluxes have not been characterized in as much detail
as in the open oceans. In addition, the joint availability of in situ
measurements of CO<sub>2</sub> and of sea-surface satellite data is limited in the
area. In this paper, we used the SOMLO (self-organizing multiple linear output; Sasse et al., 2013) methodology,
which combines two existing methods (i.e. self-organizing maps and multiple
linear regression) to estimate the ocean surface partial pressure of CO<sub>2</sub>
(<i>p</i>CO<sub>2</sub>) in the Baltic Sea from the remotely sensed sea surface temperature,
chlorophyll, coloured dissolved organic matter, net primary production, and
mixed-layer depth. The outputs of this research have a horizontal resolution
of 4 km and cover the 1998–2011 period. These outputs give a monthly map of
the Baltic Sea at a very fine spatial resolution. The reconstructed <i>p</i>CO<sub>2</sub>
values over the validation data set have a correlation of 0.93 with the in
situ measurements and a root mean square error of 36 μatm. Removing any
of the satellite parameters degraded this reconstructed CO<sub>2</sub> flux, so we
chose to supply any missing data using statistical imputation. The <i>p</i>CO<sub>2</sub>
maps produced using this method also provide a confidence level of the
reconstruction at each grid point. The results obtained are encouraging given
the sparsity of available data, and we expect to be able to produce even more
accurate reconstructions in coming years, given the predicted acquisition of
new data. |
| first_indexed | 2024-12-21T16:05:46Z |
| format | Article |
| id | doaj.art-f7a797abced24218a36fc2276bf8974a |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-21T16:05:46Z |
| publishDate | 2015-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-f7a797abced24218a36fc2276bf8974a2022-12-21T18:57:54ZengCopernicus PublicationsBiogeosciences1726-41701726-41892015-06-01123369338410.5194/bg-12-3369-2015Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodologyG. Parard0A. A. Charantonis1A. A. Charantonis2A. Rutgerson3Department of Earth Sciences, Uppsala University, Uppsala, SwedenCentre d'études et de recherche en informatique, Conservatoire des Arts et Métiers, Paris, FranceLaboratoire d'océanographie et du climat: expérimentations et approches numériques, Université Pierre et Marie Curie, Paris, FranceDepartment of Earth Sciences, Uppsala University, Uppsala, SwedenStudies of coastal seas in Europe have noted the high variability of the CO<sub>2</sub> system. This high variability, generated by the complex mechanisms driving the CO<sub>2</sub> fluxes, complicates the accurate estimation of these mechanisms. This is particularly pronounced in the Baltic Sea, where the mechanisms driving the fluxes have not been characterized in as much detail as in the open oceans. In addition, the joint availability of in situ measurements of CO<sub>2</sub> and of sea-surface satellite data is limited in the area. In this paper, we used the SOMLO (self-organizing multiple linear output; Sasse et al., 2013) methodology, which combines two existing methods (i.e. self-organizing maps and multiple linear regression) to estimate the ocean surface partial pressure of CO<sub>2</sub> (<i>p</i>CO<sub>2</sub>) in the Baltic Sea from the remotely sensed sea surface temperature, chlorophyll, coloured dissolved organic matter, net primary production, and mixed-layer depth. The outputs of this research have a horizontal resolution of 4 km and cover the 1998–2011 period. These outputs give a monthly map of the Baltic Sea at a very fine spatial resolution. The reconstructed <i>p</i>CO<sub>2</sub> values over the validation data set have a correlation of 0.93 with the in situ measurements and a root mean square error of 36 μatm. Removing any of the satellite parameters degraded this reconstructed CO<sub>2</sub> flux, so we chose to supply any missing data using statistical imputation. The <i>p</i>CO<sub>2</sub> maps produced using this method also provide a confidence level of the reconstruction at each grid point. The results obtained are encouraging given the sparsity of available data, and we expect to be able to produce even more accurate reconstructions in coming years, given the predicted acquisition of new data.https://www.biogeosciences.net/12/3369/2015/bg-12-3369-2015.pdf |
| spellingShingle | G. Parard A. A. Charantonis A. A. Charantonis A. Rutgerson Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology Biogeosciences |
| title | Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology |
| title_full | Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology |
| title_fullStr | Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology |
| title_full_unstemmed | Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology |
| title_short | Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology |
| title_sort | remote sensing the sea surface co sub 2 sub of the baltic sea using the somlo methodology |
| url | https://www.biogeosciences.net/12/3369/2015/bg-12-3369-2015.pdf |
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