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.
The timing of spring phytoplankton blooms is crucial to many species that have adapted their development to benefit from the enhanced feeding opportunity they offer. Any change to their timing may affect the productivity of an entire ecosystem. This study explores the relationship between the ocean climate, the timing of the spring bloom and the secondary production on the Newfoundland and Labrador shelf. It is found that over interannual cycles, the ocean climate is significantly correlated with the timing of the bloom and the abundance of Calanus finmarchicus, a key zooplankton species for the ecosystem. It also appears that the spring bloom is initiated by the onset of ocean re‐stratification following winter mixing. Understanding how annual variation in climate relates to the timing of the spring bloom and zooplankton abundance, that is, the base of the marine food web, can inform the development of ecosystem‐informed models for higher trophic levels.
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