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Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling

Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling
Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling
To describe the underlying processes involved in oceanic plankton dynamics is crucial for the determination of energy and mass flux through an ecosystem and for the estimation of biogeochemical element cycling. Many planktonic ecosystem models were developed to resolve major processes so that flux estimates can be derived from numerical simulations. These results depend on the type and number of parameterizations incorporated as model equations. Furthermore, the values assigned to respective parameters specify a model's solution. Representative model results are those that can explain data; therefore, data assimilation methods are utilized to yield optimal estimates of parameter values while fitting model results to match data. Central difficulties are (1) planktonic ecosystem models are imperfect and (2) data are often too sparse to constrain all model parameters. In this review we explore how problems in parameter identification are approached in marine planktonic ecosystem modelling.
1726-4170
1647-1701
Schartau, Markus
ae10d82f-2a65-453c-abe9-dc8e12bc2443
Wallhead, Philip
dc13616e-b3ba-4a01-aa1a-468f44adef03
Hemmings, John
37ca72f5-01fe-4a4f-a439-eb6ae46f4dcb
Löptien, Ulrike
d8bacc36-12db-410a-be83-4a4d37391bd3
Kriest, Iris
74cf835f-c26c-4082-8073-8991bc19d21b
Krishna, Shubham
7d8e2c6a-06e0-4133-a308-49c7213faa82
Ward, Ben A.
9063af30-e344-4626-9470-8db7c1543d05
Slawig, Thomas
82b92653-9546-477c-b830-ef37a7925610
Oschlies, Andreas
75e18f55-3134-44a2-82ba-71334397727f
Schartau, Markus
ae10d82f-2a65-453c-abe9-dc8e12bc2443
Wallhead, Philip
dc13616e-b3ba-4a01-aa1a-468f44adef03
Hemmings, John
37ca72f5-01fe-4a4f-a439-eb6ae46f4dcb
Löptien, Ulrike
d8bacc36-12db-410a-be83-4a4d37391bd3
Kriest, Iris
74cf835f-c26c-4082-8073-8991bc19d21b
Krishna, Shubham
7d8e2c6a-06e0-4133-a308-49c7213faa82
Ward, Ben A.
9063af30-e344-4626-9470-8db7c1543d05
Slawig, Thomas
82b92653-9546-477c-b830-ef37a7925610
Oschlies, Andreas
75e18f55-3134-44a2-82ba-71334397727f

Schartau, Markus, Wallhead, Philip, Hemmings, John, Löptien, Ulrike, Kriest, Iris, Krishna, Shubham, Ward, Ben A., Slawig, Thomas and Oschlies, Andreas (2017) Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling. Biogeosciences, 14 (6), 1647-1701. (doi:10.5194/bg-14-1647-2017).

Record type: Article

Abstract

To describe the underlying processes involved in oceanic plankton dynamics is crucial for the determination of energy and mass flux through an ecosystem and for the estimation of biogeochemical element cycling. Many planktonic ecosystem models were developed to resolve major processes so that flux estimates can be derived from numerical simulations. These results depend on the type and number of parameterizations incorporated as model equations. Furthermore, the values assigned to respective parameters specify a model's solution. Representative model results are those that can explain data; therefore, data assimilation methods are utilized to yield optimal estimates of parameter values while fitting model results to match data. Central difficulties are (1) planktonic ecosystem models are imperfect and (2) data are often too sparse to constrain all model parameters. In this review we explore how problems in parameter identification are approached in marine planktonic ecosystem modelling.

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bg-14-1647-2017
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Accepted/In Press date: 21 February 2017
e-pub ahead of print date: 29 March 2017
Published date: 29 March 2017

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Local EPrints ID: 416692
URI: https://eprints.soton.ac.uk/id/eprint/416692
ISSN: 1726-4170
PURE UUID: fd76c504-f255-48ac-b239-e37023351df0

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Date deposited: 05 Jan 2018 17:30
Last modified: 09 Dec 2019 18:27

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