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Towards a multi-platform assimilative system for North Sea biogeochemistry
  • +8
  • Jozef Skakala,
  • David Andrew Ford,
  • Jorn Bruggeman,
  • Tom Hull,
  • Jan Kaiser,
  • Robert R King,
  • Benjamin Roger Loveday,
  • Matthew R. Palmer,
  • Timothy James Smyth,
  • Charlotte Anne June Williams,
  • Stefano Ciavatta
Jozef Skakala
Plymouth Marine Laboratory, Plymouth Marine Laboratory

Corresponding Author:[email protected]

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David Andrew Ford
Met Office, Met Office
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Jorn Bruggeman
PML, PML
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Tom Hull
Centre for Environment, Fisheries and Aquaculture Science, Centre for Environment, Fisheries and Aquaculture Science
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Jan Kaiser
University of East Anglia, University of East Anglia
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Robert R King
Met Office, Met Office
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Benjamin Roger Loveday
Plymouth Marine Laboratory, Plymouth Marine Laboratory
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Matthew R. Palmer
National Oceanography Centre, National Oceanography Centre
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Timothy James Smyth
Plymouth Marine Laboratory, Plymouth Marine Laboratory
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Charlotte Anne June Williams
National Oceanography Centre, National Oceanography Centre
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Stefano Ciavatta
Plymouth Marine Laboratory/National Centre for Earth Observation, Plymouth Marine Laboratory/National Centre for Earth Observation
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Abstract

Oceanography has entered an era of new observing platforms, such as biogeochemical Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centres will use multi-platform assimilation to integrate those valuable data into ecosystem reanalyses and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation and introduce multi-platform data assimilation in a (pre)operational model of the NWE Shelf-sea ecosystem. We test the impact of the different multi-platform system components (glider vs satellite, physical vs biogeochemical) on the simulated biogeochemical variables. To characterize the model performance we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical data assimilation, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.