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Other research product . 2018

Assessment of a physical-biogeochemical coupled model system for operational service in the Baltic Sea

Wan, Z.; She, J.; Maar, M.; Jonasson, L.; Baasch-Larsen, J.;
Open Access
Published: 15 Jan 2018

Thanks to the abundant observation data, we are able to deploy the traditional point-to-point comparison and statistical measures in combination with a comprehensive model validation scheme to assess the skills of the biogeochemical model ERGOM in providing an operational service for the Baltic Sea. The model assessment concludes that the operational products can resolve the main observed seasonal features for phytoplankton biomass, dissolved inorganic nitrogen, dissolved inorganic phosphorus and dissolved oxygen in euphotic layers as well as their vertical profiles. This assessment reflects that the model errors of the operational system at the current stage are mainly caused by insufficient light penetration, excessive organic particle export downward, insufficient regional adaptation and some from improper initialization. This study highlights the importance of applying multiple schemes in order to assess model skills rigidly and identify main causes for major model errors.

34 references, page 1 of 4

Allen, J. I., Holt, T. J., Blackford, J., and Proctor, R.: Error quantification of a high-resolution coupled hydrodynamic-ecosystem coastal-ocean model: Part 2. Chlorophyll-a, nutrients and SPM, J. Marine Syst., 68, 381-404, 2007.

Almroth, E. and Skogen, M. D.: A North Sea and Baltic Sea model ensemble eutrophication assessment, Ambio, 39, 59-69, 2010. [OpenAIRE]

Berg, P. and Poulsen, J. W.: Implementation details for HBM, DMI Technical Report No. 12-11, ISSN: 1399-1388, Copenhagen, 2012.

Bergstro¨m, S.: Development and application of a conceptual runoff model for Scandinavian catchments, Ph. D. thesis, SMHI Reports RHO, No. 7, Norrko¨ping, 1976.

Bergstro¨m, S.: The HBV model - its structure and applications, SMHI Reports RH, No. 4, Norrko¨ping, 1992.

Conkright, M. E., Locarnini, R., Garcia, H., O'Brien, T., Boyer, T. P., Stephens, C., and Antonov, J.: World ocean atlas 2001, objective analyses, data statistics and figures, CDROM documentation, National Oceanographic Data Center, Silver Spring, MD, 2002.

Edelvang, K., Kaas, H., Erichsen, A. C., Alvarez-Berastegui1, D., Bundgaard, K., and Jørgensen, P. V.: Numerical modeling of phytoplankton biomass in coastal waters, J. Marine Sys., 57, 13-29, 2005.

Eilola, K., Meier, H. E. M., and Almroth, E.: On the dynamics of oxygen, phosphorus and cyanobacteria in the Baltic Sea: a model study, J. Marine Syst., 75, 163-184, 2009.

Fennel, W.: Model of the yearly cycle of nutrients and plankton in the Baltic Sea, J. Marine Syst., 6, 313-329, 1995.

Fennel, W. and Neumann, T.: The mesoscale variability of nutrients and plankton as seen in a coupled model, Ger. J. Hydrogr., 48, 49-71, 1996.

Funded by
Development and pre-operational validation of upgraded GMES Marine Core Services and capabilities
  • Funder: European Commission (EC)
  • Project Code: 218812
  • Funding stream: FP7 | SP1 | SPA
Related to Research communities
European Marine Science Marine Environmental Science : Development and pre-operational validation of the Ocean Monitoring and Forecasting component of the future GMES Marine Core Service
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