Scaling of coastal phytoplankton features by optical remote sensors: comparison with a regional ecosystem model

Abstract

Different scales of hydrological and biological patterns of the Bay of Biscay are assessed using space‐borne and airborne optical remote sensing data, field measurements and a 3‐dimensional biophysical model. If field measurements provide accurate values on the vertical dimension, ocean colour data offer frequent observations of surface biological patterns at various scales of major importance for the validation of ecosystem modelling. Although the hydro‐biological model of the continental margin reproduces the main seasonal variability of surface biomass, the optical remote sensing data have helped to identify low grid resolution, input inaccuracies and neglect of swell‐induced erosion mechanism as model limitations in shallow waters. Airborne remote sensing is used to show that satellite data and field measurements are unsuitable for comparison in the extreme case of phytoplankton blooms in patches of a few hundred metres. Vertically, the satellite observation is consistent with near surface in situ measurements as the sub‐surface chlorophyll maximum usually encountered in summer is not detected by optical remote sensing. A mean error (δC/C) of 50.5% of the chlorophyll‐a estimate in turbid waters using the SeaWiFS‐OC5 algorithm allows the quantitative use of ocean colour data by the coastal oceanographic community.

Acknowledgments

The authors would like to thank the SeaWiFS Project (Code 970.2) and the Distributed Active Archive Center (Code 902) at the Goddard Space Flight Center, Greenbelt, MD 20771, for the production and distribution of these data, respectively. These activities are sponsored by NASA's Mission to Planet Earth Program. The authors are indebted to NASA and GSFC for SeaWiFS data and SeaDAS software. We are extremely grateful to all who provided the field measurements allowing the calibration of the ocean colour algorithm: J.F. Chiffoleau (BloomSeine, Marina 8, CadHiver), the Ifremer's group of Port‐en‐Bessin (SeineSat), V. Duquesne (SRN), J.M. Froidefond (Biomet), S. L'Helguen and N. Savoye (Bloom/QuickSeine), A. Herbland and C. Labry (Plagia), L. Lampert and T. Labasque (Modycot.99), P. Cann (Ecoloire). This work was supported by Ifremer. The authors thank Olivier Archer for providing useful tools to visualize SeaWiFS scenes and field data.