Clean seas: a North Sea test site |
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| Authors: | Helen M. Snaith Corresponding author Martin Gade Gordon W. Jolly Antoine Mangin Vittorio Barale Ove Rud |
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| Affiliation: | 1. James Rennell Division for Ocean Circulation and Climate, Southampton Oceanography Centre , European Way , Southampton SO14 3ZH, UK;2. Institut für Meereskunde , Universit?t Hamburg, Troplowitzstraβe 7/111, D-22527 Hamburg , Germany;3. Satellite Observing Systems, 15 Church Street , Godalming, Surrey GU7 1EL, UK;4. ACRI , Mecanique Appliquée et Sciences de l'environnement, 260, route du Pin Montand, BP234 , 06904 Sophia Antipolis Cedex, France;5. Marine Environment Unit, Space Applications Institute , Joint Research Centre of the European Commission I-21020 , Ispra (VA), Italy;6. Remote Sensing Laboratory, Department of Physical Geography , Stockholm University , 10691, Stockholm, Sweden |
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| Abstract: | The Clean Seas project focused on the role that existing Earth observing satellites might play in monitoring marine pollution. Results are presented here from August 1997, for the North Sea test site, using sea surface temperature (SST), colour and synthetic aperture radar (SAR) images in conjunction with a hydrodynamic model. There was good correlation between data sources, e.g. between SST and ERS-2 SAR images. Both datasets showed the development of fine plume structures close to the Rhine outflow, apparently associated with the outflow, and possibly caused by tidal pulsing of the Rhine Plume. The model reproduced general temperature and sediment distributions well, but fine structures were not reproduced. Model sediment distribution patterns were verified using ‘chlorophyll concentration’ data from colour sensors, representative of sediment concentration in turbid water. In conjunction with the visible channels of the Advanced Very High Resolution Radiometer and Along-Track Scanning Radiometer, they give an uncalibrated measure of the sediment load. The model gives a more complete picture of the temporal dispersion of the Rhine Plume over time than is evident from the remotely sensed data alone. |
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