Evaluation of ocean chlorophyll-a remote sensing algorithms using in situ fluorescence data in Southern Brazilian Coastal Waters

A performance evaluation of ocean color chlorophyll-a algorithms was conducted based on the in situ fluorescence chlorophyll concentration (Fchl) measured by a sensor on the buoy SiMCosta-SC01 in coastal waters of South Brazil. The operational algorithms are used in MODIS and VIIRS sensors to deriv...

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Bibliographic Details
Main Authors: Gabriel Serrato de Mendonça Silva, Carlos Alberto Eiras Garcia
Format: Article
Language:English
Published: Instituto Oceanográfico da Universidade de São Paulo 2024-04-01
Series:Ocean and Coastal Research
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Online Access:https://journals.usp.br/ocr/article/view/224229
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Summary:A performance evaluation of ocean color chlorophyll-a algorithms was conducted based on the in situ fluorescence chlorophyll concentration (Fchl) measured by a sensor on the buoy SiMCosta-SC01 in coastal waters of South Brazil. The operational algorithms are used in MODIS and VIIRS sensors to derive satellite chlorophyll concentration (Csat). Fchl values were successfully corrected for nonphotochemical quenching (NPQ) by an interpolation of sunrise and sunset daily measurements. A laboratory-derived calibration coefficient was applied to convert the unquenching Fchl values into chlorophyll concentration (Cflu). Overall, linear regression analysis between Cflu and Csat for both sensors showed good results, with the coefficient of determination (R²) varying between 0.88 and 0.96, slopes between 0.92 and 1.02 and intercepts between -0.17 and 0.13. The MODIS algorithm (R² = 0.96, slope = 1.02, RMSE = 0.16 mg m-3, BIAS = 0.16 mg m-3, for N = 222 and time interval ±1 h) presented slightly better performance than VIIRS (R² = 0.92, slope = 0.96, RMSE = 0.25 mg m-3, BIAS = -0.25 mg m-3, for N = 284 and time interval ±1 h). These results represent the most comprehensive satellite data analysis for this region, suggesting that the approach may be applicable to other SiMCosta buoys
ISSN:2675-2824