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Marine ecosystem models for earth systems applications: the MarQUEST experience

Allen, J. I., Aiken, J., Anderson, R., Buitenhuis, E., Cornell, S., Geider, R., Haines, K. ORCID: https://orcid.org/0000-0003-2768-2374, Hirata, T., Holt, J., Le Quere, C., Hardman-Mountford, N., Ross, O., Sinha, B. and While, J. (2010) Marine ecosystem models for earth systems applications: the MarQUEST experience. Journal of Marine Systems, 81 (1-2). pp. 19-33. ISSN 0924-7963

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To link to this item DOI: 10.1016/j.jmarsys.2009.12.017

Abstract/Summary

The MarQUEST (Marine Biogeochemistry and Ecosystem Modelling Initiative in QUEST) project was established to develop improved descriptions of marine biogeochemistry, suited for the next generation of Earth system models. We review progress in these areas providing insight on the advances that have been made as well as identifying remaining key outstanding gaps for the development of the marine component of next generation Earth system models. The following issues are discussed and where appropriate results are presented; the choice of model structure, scaling processes from physiology to functional types, the ecosystem model sensitivity to changes in the physical environment, the role of the coastal ocean and new methods for the evaluation and comparison of ecosystem and biogeochemistry models. We make recommendations as to where future investment in marine ecosystem modelling should be focused, highlighting a generic software framework for model development, improved hydrodynamic models, and better parameterisation of new and existing models, reanalysis tools and ensemble simulations. The final challenge is to ensure that experimental/observational scientists are stakeholders in the models and vice versa.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
ID Code:7263
Uncontrolled Keywords:Ecosystem models; Plankton functional types; Data assimilation; Hydrodynamic models; Coastal zone processes; Model validation
Publisher:Elsevier

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