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|Title:||On the temporal consistency of chlorophyll products derived from three ocean-colour sensors|
|Authors:||BREWIN Robert; MELIN Frederic; SATHYENDRANATH Shubha; STEINMETZ Francois; CHUPRIN Andrei; GRANT M.|
|Citation:||ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING vol. 97 p. 171-184|
|Publisher:||ELSEVIER SCIENCE BV|
|Type:||Articles in periodicals and books|
|Abstract:||Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, between July 2002 and December 2010, the SeaWiFS, MODIS-Aqua and MERIS ocean colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002-2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean.These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflected previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.|
|JRC Directorate:||Sustainable Resources|
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