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 Bay of Fundy is a highly productive ecosystem within the Northwest Atlantic where extreme tides and strong currents result in a large gradient of sediment concentrations across and along the bay. We processed daily satellite data from the MODerate resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite from 2003 to 2021 at 300-m resolution to understand and quantify spatial and temporal trends in chlorophyll-a concentration (chl-a, a measure of phytoplankton biomass), and suspended particulate matter concentration (SPM) in the Bay of Fundy surface waters. To account for high sediment loading (up to 100’s g m⁻³) and moderate chl-a (median in situ chl-a of 1.5 mg m⁻³ from 2003 to 2021), coefficients of the OC3M chl-a algorithm were regionally tuned using in situ chl-a data, and satellite-derived SPM was incorporated within the chl-a retrieval algorithm to account for possible bias. The updated new algorithm was denoted as OC_X-SPMCor. Chl-a computed using OC_X-SPMCor showed better performance against in situ chl-a than the generic OC3M with a coefficient of determination that increased from 0.01 to 0.28 and a root mean square logarithmic error that decreased by 35%. Unlike previous remote sensing studies, OC_X-SPMCor correctly predicted the particular chl-a seasonality in the Bay of Fundy, which does not follow the typical occurrence of spring/fall blooms as observed in the adjacent Gulf of Maine and Scotian Shelf. For the first time, satellite-predicted chl-a aligned with the phenology of in situ chl-a, where chl-a continually increased from April to June and remained high all summer, with a small secondary summer peak before decreasing in the fall. SPM seasonality followed an opposite trend where SPM reached a maximum in winter and a minimum in summer. A small number of matchups and high temporal variability on the hourly time scale precluded a robust assessment of the satellite-derived SPM. However, comparisons between time series of remotely sensed and in situ SPM demonstrated the ability of the satellite-derived SPM to capture temporal variations, though the absolute values may be slightly underestimated. Accurate maps of phytoplankton biomass and sediment concentrations are essential variables required for effective management and conservation of marine ecosystems in the Bay of Fundy.

Phytoplankton spring blooms in the Labrador Sea are dominated by diatoms, with Phaeocystis spp. (hereafter Phaeocystis ) contributing more than 25% to total phytoplankton biomass. However, in 2015 and 2022, large blooms of Phaeocystis were observed, contributing up to 90% of the surface phytoplankton biomass. In this study, we quantified shifts in the absorption coefficient of phytoplankton (a _PHY ), colored dissolved organic matter (a _CDOM ), and non‐algal particles (a _NAP ) within four different oceanographic regimes along a Labrador Sea monitoring line spanning from the southeast Labrador to the southwest Greenland coast. Pigment‐based chemotaxonomy showed that from 2014 to 2022, diatoms and Phaeocystis were the dominant taxonomic groups in the spring. Analysis of absorption coefficients of optically active components informed on the bio‐optical status of the Labrador Sea. Regimes dominated by diatoms and other non‐ Phaeocystis groups were identified as Case‐2 waters with high a _CDOM coefficients, and an absence of correlation with a _PHY . Diatom‐dominated waters exhibited the lowest chlorophyll‐specific absorption (a* _PHY ). In summer, when chlorophyll‐a concentration (chl‐a) was low, a* _PHY was highest; however, a* _PHY decreased as Phaeocystis biomass increased. In contrast to typical conditions, when Phaeocystis biomass was 80% or more of total chl‐a, a _PHY , a _NAP , and a _CDOM positively and significantly correlated with significant increases in a _PHY . The linear slope of a _PHY between 470 and 518 nm was higher and positively correlated with Phaeocystis, and lower and negatively correlated to diatom biomass. Information on a _PHY spectral shape and magnitude supports the development of hyperspectral‐based reflectance models to detect Phaeocystis blooms in the Labrador Sea from space.

Net primary productivity (NPP) plays a central role in biological carbon pump (BCP) and global carbon cycling, but NPP estimates in high-latitude regions remain highly uncertain despite their disproportional contribution to the global carbon sink. Previous studies identified discrepancies among satellite- and in situ-derived NPP estimates, but the drivers of disagreement remain poorly resolved due to limited high-frequency observations. Here, we present continuous depth-resolved estimates of in situ NPP from the Central Labrador Sea (56°N) in the subpolar Northwest Atlantic, reconstructed from daily bio-optical profiles collected between May and November 2016, and a 40-year dataset of photosynthesis parameters derived from ¹⁴C photosynthesis-irradiance (P-I) incubation experiments. Comparing with two satellite-based models showed satellite models overestimated NPP by factors of 2.5–4 from the study period. Statistical analyses identified the P-I parameterization as the most influential contributor to the disagreement between satellite and in situ NPP estimates. Given the importance of NPP to estimates of the biological carbon pump, our findings highlight the need for regionally appropriate P-I parameterization in NPP models, particularly in high-latitude regions.