Evaluations of SeaWiFS and MODIS Chlorophyll a algorithms in summer season for the Northern South Ch.pdf

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Evaluations of SeaWiFS and MODIS Chlorophyll a algorithms in summer season for the Northern South Ch.pdf

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Evaluations of SeaWiFS and MODIS Chlorophyll a algorithms in summer season for the Northern South Ch

doi: 10.3319/TAO.2010.02.11.01(Oc) * Corresponding author E-mail: lingzistdl@126.com Evaluation of the SeaWiFS and MODIS Chlorophyll a Algorithms Used for the Northern South China Sea during the Summer Season Yanli Pan1, 2, Danling Tang1, 2, *, and Dehe Weng 2, 3 1 Research Center of Remote Sensing on Marine Ecology and Environment, LED, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301,China 2 The Graduate School of Chinese Academy of Sciences, Beijing 100039, China 3 Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China Received 9 October 2009, accepted 11 February 2010 ABSTRACT The present study made evaluations of SeaWiFS-derived and MODIS-derived Chlorophyll a (Chl a) concentrations in the Northern South China Sea (NSCS), using in situ data collected during two research cruises which were conducted during the summer of 2004 (from September 18 to October 8) and 2007 (from August 10 to 29). The data of ±48 h and 3 × 3 pixels were used for the comparison between satellite and in situ Chl a data, and the results reveal a systematic overestimation of Chl a concentration by National and Space Administration (NASA) global algorithms (OC2v4, OC4v4, and OC3M). The RMSEs of the selected algorithms are larger than 0.35 except OC2_D’Ortenzio (one regional algorithm for the Mediterranean Sea). The overestimation seems to correlate with numerous (≈77%) low Chl a concentration ( 0.1 mg m-3) due to the oligotrophic characteristics of the South China Sea (SCS) in summer, and to correlate with the error in atmosphere correction introduced by aerosols. Therefore, the OC2 and OC4 algorithms for SeaWiFS and OC3M algorithm for MODIS are adapted to NSCS by fitting the satellite data set to in situ Chl a data in NSCS. With the new coefficients based on our field data, the regional ver- sion of the three algorithms (TP series) showed good performance with RMSE values of 0.24