Regional ocean-colour chlorophyll algorithms for the Red Sea

• Published in: Remote sensing of environment 2015-08, Vol.165, p.64-85
• Main Authors: Brewin, Robert J.W., Raitsos, Dionysios E., Dall'Olmo, Giorgio, Zarokanellos, Nikolaos, Jackson, Thomas, Racault, Marie-Fanny, Boss, Emmanuel S., Sathyendranath, Shubha, Jones, Burt H., Hoteit, Ibrahim
• Format: Article
• Language: English
• Subjects: Algorithms; Chlorophyll; Chlorophylls; Coloured dissolved organic matter; Estimates; Gulfs; Ocean colour; Optical properties; Phytoplankton; Red Sea; Remote sensing; Satellites; Validation
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2015.04.024

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing. •We validate four satellite chlorophyll algorithms in the Red Sea.•Results suggest that standard empirical algorithms overestimate chlorophyll.•The overestimation in chlorophyll may be related to higher levels of CDOM.•We develop regional chlorophyll algorithms for use in the Red Sea.•Results support the use of ocean colour data in the Red Sea.