@article{RN229,
   author = {Brewin, Robert J. W. and Raitsos, Dionysios E. and Dall'Olmo, Giorgio and Zarokanellos, Nikolaos and Jackson, Thomas and Racault, Marie-Fanny and Boss, Emmanuel S. and Sathyendranath, Shubha and Jones, Burt H. and Hoteit, Ibrahim},
   title = {Regional ocean-colour chlorophyll algorithms for the Red Sea},
   journal = {Remote Sensing of Environment},
   volume = {165},
   pages = {64-85},
   abstract = {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.},
   keywords = {Phytoplankton
Ocean colour
Remote sensing
Chlorophyll
Red Sea
Validation
Coloured dissolved organic matter},
   ISSN = {0034-4257},
   DOI = {https://doi.org/10.1016/j.rse.2015.04.024},
   url = {https://www.sciencedirect.com/science/article/pii/S0034425715001662},
   year = {2015},
   type = {Journal Article}
}

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H.","Hoteit, I."],"bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Brewin"],"firstnames":["Robert","J.","W."],"suffixes":[]},{"propositions":[],"lastnames":["Raitsos"],"firstnames":["Dionysios","E."],"suffixes":[]},{"propositions":[],"lastnames":["Dall'Olmo"],"firstnames":["Giorgio"],"suffixes":[]},{"propositions":[],"lastnames":["Zarokanellos"],"firstnames":["Nikolaos"],"suffixes":[]},{"propositions":[],"lastnames":["Jackson"],"firstnames":["Thomas"],"suffixes":[]},{"propositions":[],"lastnames":["Racault"],"firstnames":["Marie-Fanny"],"suffixes":[]},{"propositions":[],"lastnames":["Boss"],"firstnames":["Emmanuel","S."],"suffixes":[]},{"propositions":[],"lastnames":["Sathyendranath"],"firstnames":["Shubha"],"suffixes":[]},{"propositions":[],"lastnames":["Jones"],"firstnames":["Burt","H."],"suffixes":[]},{"propositions":[],"lastnames":["Hoteit"],"firstnames":["Ibrahim"],"suffixes":[]}],"title":"Regional ocean-colour chlorophyll algorithms for the Red Sea","journal":"Remote Sensing of Environment","volume":"165","pages":"64-85","abstract":"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.","keywords":"Phytoplankton Ocean colour Remote sensing Chlorophyll Red Sea Validation Coloured dissolved organic matter","issn":"0034-4257","doi":"https://doi.org/10.1016/j.rse.2015.04.024","url":"https://www.sciencedirect.com/science/article/pii/S0034425715001662","year":"2015","bibtex":"@article{RN229,\r\n author = {Brewin, Robert J. W. and Raitsos, Dionysios E. and Dall'Olmo, Giorgio and Zarokanellos, Nikolaos and Jackson, Thomas and Racault, Marie-Fanny and Boss, Emmanuel S. and Sathyendranath, Shubha and Jones, Burt H. and Hoteit, Ibrahim},\r\n title = {Regional ocean-colour chlorophyll algorithms for the Red Sea},\r\n journal = {Remote Sensing of Environment},\r\n volume = {165},\r\n pages = {64-85},\r\n abstract = {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.},\r\n keywords = {Phytoplankton\r\nOcean colour\r\nRemote sensing\r\nChlorophyll\r\nRed Sea\r\nValidation\r\nColoured dissolved organic matter},\r\n ISSN = {0034-4257},\r\n DOI = {https://doi.org/10.1016/j.rse.2015.04.024},\r\n url = {https://www.sciencedirect.com/science/article/pii/S0034425715001662},\r\n year = {2015},\r\n type = {Journal Article}\r\n}\r\n\r\n","author_short":["Brewin, R. J. W.","Raitsos, D. 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