Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1)
Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1)
Biogeochemical ocean circulation models used to investigate the role of plankton ecosystems in global change rely on adjustable parameters to compensate for missing biological complexity. In principle, optimal parameter values can be estimated by fitting models to observational data, including satellite ocean colour products such as chlorophyll that achieve good spatial and temporal coverage of the surface ocean. However, comprehensive parametric analyses require large ensemble experiments that are computationally infeasible with global 3-D simulations. Site-based simulations provide an efficient alternative but can only be used to make reliable inferences about global model performance if robust quantitative descriptions of their relationships with the corresponding 3-D simulations can be established.
697-731
Hemmings, J.C.P.
ebf33f54-d2b2-4ab3-9ac8-fd9dc9ae6a7f
Challenor, P.G.
a7e71e56-8391-442c-b140-6e4b90c33547
Yool, A.
882aeb0d-dda0-405e-844c-65b68cce5017
23 March 2015
Hemmings, J.C.P.
ebf33f54-d2b2-4ab3-9ac8-fd9dc9ae6a7f
Challenor, P.G.
a7e71e56-8391-442c-b140-6e4b90c33547
Yool, A.
882aeb0d-dda0-405e-844c-65b68cce5017
Hemmings, J.C.P., Challenor, P.G. and Yool, A.
(2015)
Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1).
Geoscientific Model Development, 8, .
(doi:10.5194/gmd-8-697-2015).
Abstract
Biogeochemical ocean circulation models used to investigate the role of plankton ecosystems in global change rely on adjustable parameters to compensate for missing biological complexity. In principle, optimal parameter values can be estimated by fitting models to observational data, including satellite ocean colour products such as chlorophyll that achieve good spatial and temporal coverage of the surface ocean. However, comprehensive parametric analyses require large ensemble experiments that are computationally infeasible with global 3-D simulations. Site-based simulations provide an efficient alternative but can only be used to make reliable inferences about global model performance if robust quantitative descriptions of their relationships with the corresponding 3-D simulations can be established.
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Published date: 23 March 2015
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Marine Systems Modelling
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Local EPrints ID: 369876
URI: http://eprints.soton.ac.uk/id/eprint/369876
ISSN: 1991-9603
PURE UUID: 92b78f5c-80df-4a4e-97f7-3e3f5231f98c
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Date deposited: 08 Oct 2014 09:15
Last modified: 14 Mar 2024 18:09
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Author:
J.C.P. Hemmings
Author:
P.G. Challenor
Author:
A. Yool
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