Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates?
The average depth in the ocean at which the majority of sinking organic matter particles remineralise is a fundamental parameter in the ocean's role in regulating atmospheric CO<sub>2</sub>. Observed spatial patterns in sinking fluxes and relationships between the fluxes of differen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-09-01
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| Series: | Biogeosciences |
| Online Access: | http://www.biogeosciences.net/12/5547/2015/bg-12-5547-2015.pdf |
| _version_ | 1818115394799403008 |
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| author | J. D. Wilson A. Ridgwell S. Barker |
| author_facet | J. D. Wilson A. Ridgwell S. Barker |
| author_sort | J. D. Wilson |
| collection | DOAJ |
| description | The average depth in the ocean at which the majority of sinking organic
matter particles remineralise is a fundamental parameter in the ocean's role
in regulating atmospheric CO<sub>2</sub>. Observed spatial patterns in sinking fluxes
and relationships between the fluxes of different particles in the modern
ocean have widely been used to invoke controlling mechanisms with important
implications for CO<sub>2</sub> regulation. However, such analyses are limited by the
sparse spatial sampling of the available sediment trap data. Here we explore
whether model ocean circulation rates, in the form of a transport matrix, can
be used to derive remineralisation rates and infer sinking particle flux
curves from the much more highly resolved observations of dissolved nutrient
concentrations. Initially we show an example of the method using a transport
matrix from the MITgcm model and demonstrate that there are a number of
potential uncertainties associated with the method. We then use the Earth
system model GENIE to generate a synthetic tracer data set to explore the
method and its sensitivity to key sources of uncertainty arising from errors
in the tracer observations and in the model circulation. We use a 54-member
ensemble of different, but plausible, estimates of the modern circulation to
explore errors associated with model transport rates. We find that
reconstructed re-mineralisation rates are very sensitive to both errors in
observations and model circulation rates, such that a simple inversion cannot
provide a robust estimate of particulate flux profiles. Estimated
remineralisation rates are particularly sensitive to differences between the
"observed" and modelled circulation because remineralisation rates are 3–4
magnitudes smaller than transport rates. We highlight a potential method of
constraining the uncertainty associated with using modelled circulation
rates, although its success is limited by the observations currently
available. Finally, we show that there are additional uncertainties when
inferring particle flux curves from reliable estimates of remineralisation
rates due to processes that are not restricted to the vertical water column
transport, such as the cycling of dissolved organic matter. |
| first_indexed | 2024-12-11T04:05:56Z |
| format | Article |
| id | doaj.art-0e1ddd3b1b004c1dab9c11ab6670451c |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-11T04:05:56Z |
| publishDate | 2015-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-0e1ddd3b1b004c1dab9c11ab6670451c2022-12-22T01:21:31ZengCopernicus PublicationsBiogeosciences1726-41701726-41892015-09-0112185547556210.5194/bg-12-5547-2015Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates?J. D. Wilson0A. Ridgwell1S. Barker2School of Earth and Ocean Sciences, Cardiff University, Cardiff, UKSchool of Geographical Sciences, University of Bristol, Bristol, UKSchool of Earth and Ocean Sciences, Cardiff University, Cardiff, UKThe average depth in the ocean at which the majority of sinking organic matter particles remineralise is a fundamental parameter in the ocean's role in regulating atmospheric CO<sub>2</sub>. Observed spatial patterns in sinking fluxes and relationships between the fluxes of different particles in the modern ocean have widely been used to invoke controlling mechanisms with important implications for CO<sub>2</sub> regulation. However, such analyses are limited by the sparse spatial sampling of the available sediment trap data. Here we explore whether model ocean circulation rates, in the form of a transport matrix, can be used to derive remineralisation rates and infer sinking particle flux curves from the much more highly resolved observations of dissolved nutrient concentrations. Initially we show an example of the method using a transport matrix from the MITgcm model and demonstrate that there are a number of potential uncertainties associated with the method. We then use the Earth system model GENIE to generate a synthetic tracer data set to explore the method and its sensitivity to key sources of uncertainty arising from errors in the tracer observations and in the model circulation. We use a 54-member ensemble of different, but plausible, estimates of the modern circulation to explore errors associated with model transport rates. We find that reconstructed re-mineralisation rates are very sensitive to both errors in observations and model circulation rates, such that a simple inversion cannot provide a robust estimate of particulate flux profiles. Estimated remineralisation rates are particularly sensitive to differences between the "observed" and modelled circulation because remineralisation rates are 3–4 magnitudes smaller than transport rates. We highlight a potential method of constraining the uncertainty associated with using modelled circulation rates, although its success is limited by the observations currently available. Finally, we show that there are additional uncertainties when inferring particle flux curves from reliable estimates of remineralisation rates due to processes that are not restricted to the vertical water column transport, such as the cycling of dissolved organic matter.http://www.biogeosciences.net/12/5547/2015/bg-12-5547-2015.pdf |
| spellingShingle | J. D. Wilson A. Ridgwell S. Barker Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? Biogeosciences |
| title | Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? |
| title_full | Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? |
| title_fullStr | Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? |
| title_full_unstemmed | Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? |
| title_short | Can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates? |
| title_sort | can organic matter flux profiles be diagnosed using remineralisation rates derived from observed tracers and modelled ocean transport rates |
| url | http://www.biogeosciences.net/12/5547/2015/bg-12-5547-2015.pdf |
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