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Ocean Science An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 4
Ocean Sci., 7, 445–454, 2011
https://doi.org/10.5194/os-7-445-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: ECOOP (European Coastal-shelf sea Operational Observing and...

Ocean Sci., 7, 445–454, 2011
https://doi.org/10.5194/os-7-445-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Jul 2011

Research article | 04 Jul 2011

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

A. L. Gemmell1, R. M. Barciela2, J. D. Blower1, K. Haines1, Q. Harpham3, K. Millard3, M. R. Price2, and A. Saulter2 A. L. Gemmell et al.
  • 1Environmental Systems Science Centre, Harry Pitt Building, 3 Earley Gate, Whiteknights, University of Reading, Reading, RG6 6AL, UK
  • 2The Met Office, Fitzroy Road, Exeter, Devon, EX1 3PB, UK
  • 3HR Wallingford, Howbery Park, Wallingford, Oxfordshire, OX10 8BA, UK

Abstract. As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards.

The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data.

Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

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