On the temporal consistency of chlorophyll products derived from three ocean-colour sensors

Brewin, RJW, Mélin, F, Sathyendranath, S, Steinmetz, F, Chuprin, A and Grant, MG 2014 On the temporal consistency of chlorophyll products derived from three ocean-colour sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 97. 171-184. https://doi.org/10.1016/j.isprsjprs.2014.08.013

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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, 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 reflect 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.

Item Type: Publication - Article
Additional Keywords: Phytoplankton, Ocean colour, Merging, Remote sensing, Chlorophyll-a
Subjects: Earth Observation - Remote Sensing
Ecology and Environment
Marine Sciences
Divisions: Plymouth Marine Laboratory > Science Areas > Sea from Space (expired)
Depositing User: Robert Brewin
Date made live: 17 Oct 2014 09:40
Last Modified: 25 Apr 2020 09:56
URI: https://plymsea.ac.uk/id/eprint/6198

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