Abstract
Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m−3) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.
Highlights
The product derived from satellite ocean colour that is the most used is undoubtedly chlorophyll-a concentration, an index of phytoplankton biomass, which has numerous applications in biogeochemical oceanography, such as phytoplankton ecology and phenology [1,2], carbon cycles [3], climate change, transfer of energy to higher trophic levels, and water quality [4]
Band ratio algorithms exploit the ratio of wavebands in the blue and green to retrieve chla; the Ocean Colour X (OCx) (x stands for 2, 3, or 4 and indicates the number of bands that were used in the algorithm) suite of empirical algorithms have been developed by the National Aeronautics and Space Administration (NASA) using a global dataset of in situ measurements of chla concentration fitted to remote sensing reflectance (NOMAD, the NASA bio-Optical Marine Algorithm Dataset [12]) and a fourth-degree polynomial expression
Regionalization of the OCx and Garver–Siegel Maritorena (GSM) algorithms was carried out using satellite-derived and in situ chla, which differs from the original algorithms where the coefficients of the models were derived using remote sensing reflectances and chla measured in situ
Summary
The product derived from satellite ocean colour that is the most used is undoubtedly chlorophyll-a (chla) concentration, an index of phytoplankton biomass, which has numerous applications in biogeochemical oceanography, such as phytoplankton ecology and phenology [1,2], carbon cycles [3], climate change, transfer of energy to higher trophic levels, and water quality [4]. Semi-analytical algorithms (e.g., Garver–Siegel Maritorena (GSM)) consist of optimizing bio-optical parameters (including chla concentration) in an approximate solution of the radiative transfer equation to match modelled reflectance to the reflectance measured by the satellite. This type of algorithm has the advantage of decoupling the contribution of the optically active components (i.e., phytoplankton, non-algal particles and coloured dissolved organic carbon) such that chla concentration should, in theory, be retrieved with higher accuracy than the band ratio algorithms. Note that the performance of algorithms that use remote sensing reflectance will be inherently dependent on the performance of the atmospheric correction procedure, which will not be addressed here
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