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dc.contributor.authorKwiatkowski, L
dc.contributor.authorYool, A
dc.contributor.authorAllen, JI
dc.contributor.authorAnderson, TR
dc.contributor.authorBarciela, R.
dc.contributor.authorBuitenhuis, ET
dc.contributor.authorButenschön, M
dc.contributor.authorEnright, C
dc.contributor.authorHalloran, PR
dc.contributor.authorLe Quéré, C
dc.contributor.authorde Mora, L
dc.contributor.authorRacault, M-F
dc.contributor.authorSinha, B
dc.contributor.authorTotterdell, IJ
dc.contributor.authorCox, Peter M.
dc.date.accessioned2015-06-24T09:59:40Z
dc.date.issued2014-12-19
dc.description.abstractOcean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.en_GB
dc.description.sponsorshipNERCen_GB
dc.description.sponsorshipUK Met Officeen_GB
dc.description.sponsorshipEC FP7 GreenSeas projecten_GB
dc.identifier.citationVol. 11, pp. 7291 - 7304en_GB
dc.identifier.doi10.5194/bg-11-7291-2014
dc.identifier.grantnumberNE/K001345/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/17656
dc.language.isoenen_GB
dc.publisherEuropean Geosciences Union (EGU) / Copernicus GmbHen_GB
dc.relation.urlhttp://www.biogeosciences.net/11/7291/2014/bg-11-7291-2014.htmlen_GB
dc.rightsThis work is distributed under the Creative Commons Attribution 3.0 License.en_GB
dc.titleIMarNet: An ocean biogeochemistry model intercomparison project within a common physical ocean modelling frameworken_GB
dc.typeArticleen_GB
dc.date.available2015-06-24T09:59:40Z
dc.identifier.issn1726-4170
dc.descriptionJournal Articleen_GB
dc.descriptionCopyright © Author(s) 2014.en_GB
dc.identifier.journalBiogeosciencesen_GB


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