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A statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation.

A statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation.
A statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation.
The biological carbon pump (BCP) is one of the atmospheric CO2 pathways into the ocean and plays a major role in climate regulation. Primary production in the ocean uptakes CO2 to produce organic matter, which enters the food chain and undergoes transformations to become particulate organic carbon (POC). The POC sinks transporting carbon into the ocean, creating a POC flux. As it sinks, POC gets respired and releases CO2 back into the environment, attenuating the flux. The deeper this happens, the longer the released CO2 stays away from the atmosphere. Sediment traps and the Martin’s curve, a statistical fit of a power law, are commonly used to describe this flux attenuation with depth. The use of sediment traps assumes the flux captured by traps deployed simultaneously at different depths comes from the same region. The source of the flux plays a key role in understanding observations of the BCP. Unusual/unexpected flux profiles might be caused by variability in fields on the ocean’s surface. To know the source region of the flux, one must find its “statistical funnel”. A particle backtracking approach can be used to achieve this; however, the currently used approach does not account for uncertainties in ocean currents. Additionally, the existing method for the statistical funnel backtracks particles until they reach the ocean’s surface. This is not necessarily accurate as the surface layer of the ocean is well mixed. Particles in the mixed surface layer does not make sense as particles could come from any point within the mixed layer.
Here I suggest a method to calculate a statistical funnel considering uncertainties in ocean currents. From this funnel study I also suggest a method to estimate the contributions of spatial variability in the traps’ catchment areas to the uncertainty in Martin’s “b-value” (which represents the flux attenuation). The method also suggests a spatially adjusted b-value, which considers each trap’s catchment area. Finally, I present a case study that found that spatial variability can contribute up to 25% in the uncertainty in a b-value obtained from POC flux observation.
University of Southampton
Espinola, Benoit Henri Guillaume
b6c5a42f-9068-4ed6-a1a6-8e83628787fb
Espinola, Benoit Henri Guillaume
b6c5a42f-9068-4ed6-a1a6-8e83628787fb
Hickman, Anna
a99786c6-65e6-48c8-8b58-0d3b5608be92
Henson, Stephanie
d6532e17-a65b-4d7b-9ee3-755ecb565c19
Briggs, Nathan
a53aa80d-785a-4ace-99d3-72fa05e94471
Carvalho, Filipa
36e42d6d-2fe2-444d-9c23-0d49194bbe4e

Espinola, Benoit Henri Guillaume (2022) A statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation. University of Southampton, Doctoral Thesis, 57pp.

Record type: Thesis (Doctoral)

Abstract

The biological carbon pump (BCP) is one of the atmospheric CO2 pathways into the ocean and plays a major role in climate regulation. Primary production in the ocean uptakes CO2 to produce organic matter, which enters the food chain and undergoes transformations to become particulate organic carbon (POC). The POC sinks transporting carbon into the ocean, creating a POC flux. As it sinks, POC gets respired and releases CO2 back into the environment, attenuating the flux. The deeper this happens, the longer the released CO2 stays away from the atmosphere. Sediment traps and the Martin’s curve, a statistical fit of a power law, are commonly used to describe this flux attenuation with depth. The use of sediment traps assumes the flux captured by traps deployed simultaneously at different depths comes from the same region. The source of the flux plays a key role in understanding observations of the BCP. Unusual/unexpected flux profiles might be caused by variability in fields on the ocean’s surface. To know the source region of the flux, one must find its “statistical funnel”. A particle backtracking approach can be used to achieve this; however, the currently used approach does not account for uncertainties in ocean currents. Additionally, the existing method for the statistical funnel backtracks particles until they reach the ocean’s surface. This is not necessarily accurate as the surface layer of the ocean is well mixed. Particles in the mixed surface layer does not make sense as particles could come from any point within the mixed layer.
Here I suggest a method to calculate a statistical funnel considering uncertainties in ocean currents. From this funnel study I also suggest a method to estimate the contributions of spatial variability in the traps’ catchment areas to the uncertainty in Martin’s “b-value” (which represents the flux attenuation). The method also suggests a spatially adjusted b-value, which considers each trap’s catchment area. Finally, I present a case study that found that spatial variability can contribute up to 25% in the uncertainty in a b-value obtained from POC flux observation.

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Published date: 17 October 2022

Identifiers

Local EPrints ID: 469678
URI: http://eprints.soton.ac.uk/id/eprint/469678
PURE UUID: 0e29caec-0f05-4496-aafc-38ec5f12c83b
ORCID for Benoit Henri Guillaume Espinola: ORCID iD orcid.org/0000-0003-2412-9645
ORCID for Anna Hickman: ORCID iD orcid.org/0000-0002-2774-3934

Catalogue record

Date deposited: 22 Sep 2022 16:33
Last modified: 03 Dec 2022 02:56

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Contributors

Thesis advisor: Anna Hickman ORCID iD
Thesis advisor: Stephanie Henson
Thesis advisor: Nathan Briggs
Thesis advisor: Filipa Carvalho

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