Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea
The use of ocean colour remote sensing to facilitate the monitoring of phytoplankton biomass in coastal waters is hampered by the high variability in absorption and scattering from substances other than phytoplankton. The eastern Arabian Sea coastal shelf is influenced by river run-off, winter conve...
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Published in | Continental shelf research Vol. 65; pp. 14 - 26 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
15.08.2013
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Abstract | The use of ocean colour remote sensing to facilitate the monitoring of phytoplankton biomass in coastal waters is hampered by the high variability in absorption and scattering from substances other than phytoplankton. The eastern Arabian Sea coastal shelf is influenced by river run-off, winter convection and monsoon upwelling. Bio-optical parameters were measured along this coast from March 2009 to June 2011, to characterise the optical water type and validate three Chlorophyll-a (Chla) algorithms applied to Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-Aqua) data against in situ measurements. Ocean Colour 3 band ratio (OC3M), Garver–Siegel–Maritorena Model (GSM) and Generalized Inherent Optical Property (GIOP) Chla algorithms were evaluated. OC3M performed better than GSM and GIOP in all regions and overall, was within 11% of in situ Chla. GSM was within 24% of in situ Chla and GIOP on average was 55% lower. OC3M was less affected by errors in remote sensing reflectance Rrs(λ) and by spectral variations in absorption coefficient (aCDOM(λ)) of coloured dissolved organic material (CDOM) and total suspended matter (TSM) compared to the other algorithms. A nine year Chla time series from 2002 to 2011 was generated to assess regional differences between OC3M and GSM. This showed that in the north eastern shelf, maximum Chla occurred during the winter monsoon from December to February, where GSM consistently gave higher Chla compared to OC3M. In the south eastern shelf, maximum Chla occurred in June to July during the summer monsoon upwelling, and OC3M yielded higher Chla compared to GSM. OC3M currently provides the most accurate Chla estimates for the eastern Arabian Sea coastal waters.
•Bio-optical properties of eastern Arabian Sea coast were determined from 2009 to 2011.•Three MODIS-Aqua Chla algorithms (OC3M, GSM, GIOP) were validated.•The most accurate algorithms were used to generate a nine year Chla time series. |
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AbstractList | The use of ocean colour remote sensing to facilitate the monitoring of phytoplankton biomass in coastal waters is hampered by the high variability in absorption and scattering from substances other than phytoplankton. The eastern Arabian Sea coastal shelf is influenced by river run-off, winter convection and monsoon upwelling. Bio-optical parameters were measured along this coast from March 2009 to June 2011, to characterise the optical water type and validate three Chlorophyll-a (Chla) algorithms applied to Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-Aqua) data against in situ measurements. Ocean Colour 3 band ratio (OC3M), Garver–Siegel–Maritorena Model (GSM) and Generalized Inherent Optical Property (GIOP) Chla algorithms were evaluated. OC3M performed better than GSM and GIOP in all regions and overall, was within 11% of in situ Chla. GSM was within 24% of in situ Chla and GIOP on average was 55% lower. OC3M was less affected by errors in remote sensing reflectance Rrs(λ) and by spectral variations in absorption coefficient (aCDOM(λ)) of coloured dissolved organic material (CDOM) and total suspended matter (TSM) compared to the other algorithms. A nine year Chla time series from 2002 to 2011 was generated to assess regional differences between OC3M and GSM. This showed that in the north eastern shelf, maximum Chla occurred during the winter monsoon from December to February, where GSM consistently gave higher Chla compared to OC3M. In the south eastern shelf, maximum Chla occurred in June to July during the summer monsoon upwelling, and OC3M yielded higher Chla compared to GSM. OC3M currently provides the most accurate Chla estimates for the eastern Arabian Sea coastal waters.
•Bio-optical properties of eastern Arabian Sea coast were determined from 2009 to 2011.•Three MODIS-Aqua Chla algorithms (OC3M, GSM, GIOP) were validated.•The most accurate algorithms were used to generate a nine year Chla time series. |
Author | Tilstone, Gavin H. Menon, Harilal B. Lotliker, Aneesh A. Suresh, T. Ragavan, B.R. Miller, Peter I. Kumar, T. Srinivasa Ashraf, P. Muhamed |
Author_xml | – sequence: 1 givenname: Gavin H. surname: Tilstone fullname: Tilstone, Gavin H. email: ghti@pml.ac.uk organization: Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1 3DH, UK – sequence: 2 givenname: Aneesh A. surname: Lotliker fullname: Lotliker, Aneesh A. organization: Indian National Centre for Ocean Information Services (INCOIS), “Ocean Valley”, P.B. No. 21, IDA Jeedimetla P.O., Hyderabad 500 055, India – sequence: 3 givenname: Peter I. surname: Miller fullname: Miller, Peter I. organization: Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1 3DH, UK – sequence: 4 givenname: P. Muhamed surname: Ashraf fullname: Ashraf, P. Muhamed organization: Central Institute of Fisheries Technology, Willingdon Island, Matsyapuri P.O., Cochin 682 029, India – sequence: 5 givenname: T. Srinivasa surname: Kumar fullname: Kumar, T. Srinivasa organization: Indian National Centre for Ocean Information Services (INCOIS), “Ocean Valley”, P.B. No. 21, IDA Jeedimetla P.O., Hyderabad 500 055, India – sequence: 6 givenname: T. surname: Suresh fullname: Suresh, T. organization: National Institute of Oceanography (NIO), Dona Paula 403 004, Goa, India – sequence: 7 givenname: B.R. surname: Ragavan fullname: Ragavan, B.R. organization: Mangalore University, Mangalagangotri, Mangalore 574 199, Karnataka, India – sequence: 8 givenname: Harilal B. surname: Menon fullname: Menon, Harilal B. organization: Goa University, Taleigao Plateau, Goa 403 206, India |
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