Empirical methods based on band ratios to infer chlorophyll-a concentration by satellite do not perform well over the optically complex waters of the St. Lawrence Estuary and Gulf. Using a dataset of 93 match-ups, we explore an alternative method relying on empirical orthogonal functions (EOF) to develop an algorithm that relates the satellite-derived remote sensing reflectances to in situ chlorophyll-a concentration for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Results show that an accuracy of 41% at retrieving chlorophyll-a concentration can be reached using the EOF method compared to 140% for the widely-used Ocean Chlorophyll 4 (OC4v4) empirical algorithm, 53% for the Garver-Siegel-Maritorena (GSM01) and 54% for the Generalized Inherent Optical Property (GIOP) semi-analytical algorithms. This result is possible because the EOF approach is able to extract region-specific radiometric features from the satellite remote sensing reflectances that are related to absorption properties of optical components (water, coloured dissolved organic matter and chlorophyll-a) using the visible SeaWiFS channels. The method could easily be used with other ocean-colour satellite sensors (e.g., MODIS, MERIS, VIIRS, OLCI) to extend the time series for the St. Lawrence Estuary and Gulf waters.

Previous studies have shown that the properties of optically significant water constituents (phytoplankton, suspended matter, and colored dissolved organic matter (CDOM)) in Hudson Bay are different from other Arctic regions. A new bio‐optical data set collected in summer 2010 shows that this region also presents seasonal variability of the light absorption coefficients by the different constituents, with a higher relative proportion of CDOM absorption in summer than in the fall as a result of decreased phytoplankton absorption in summer. The slope of the exponential function describing nonalgal particles and CDOM spectral absorption shows little variability between fall and summer. Seasonal variability of light absorption coefficients and water optical constituents is more pronounced near the coast, while less variability is observed in the central part of the bay. Very low summertime chlorophyll‐specific absorption coefficients by phytoplankton, among the lowest reported in the literature, are attributed to the high proportion of large size phytoplankton (microphytoplankton) and important packaging effect. There is also a smaller contribution of accessory pigments to total pigments in the summer than in the fall, resulting in a lower blue‐to‐red phytoplankton absorption ratio. These results emphasize that it is necessary to take into account the seasonal variability of light absorption properties in bio‐optical models for further remote sensing applications in Hudson Bay.

This study investigated the relationships between the concentration of biogeochemical parameters and particulate beam attenuation (c_p), scattering (b_p), and backscattering (b_bp) in Hudson Bay. Results showed that most of the variability resulted from the presence of a deep chlorophyll maximum. c_p, b_p, and b_bp were all adequate proxies to estimate total suspended matter (TSM) but were mostly sensitive to particulate inorganic matter (PIM) in the surface layer, and particulate organic matter (POM) at the chlorophyll maximum depth. The backscattering ratio varied in the range of 0.005–0.05 and was inversely related to the POM : TSM ratio. According to the Twardowski et al. (2001) model, the PSD slope ξ well represented and bulk refractive index in relation to particulate composition. For inorganic particulate dominated waters, both and had a larger range and a higher mean value than at organic particulate dominated waters. This knowledge on the optical properties related to the PSD and particulate composition provides valuable information for further investigation and broadens our understanding of ocean optics in high latitude waters leading to potential improvements of regional scale remote sensing algorithms.

28 years of satellite data were used to calculate sea surface temperature (SST) climatologies covering Canada's 3 surrounding oceans and the Great Lakes. Results show the imprint of major circulation features on the spatial distribution of the SST. Together with the Gulf Stream, the Labrador Current generates a strong spatial variability of SST on the east coast. Most of the Canadian Arctic, with the exception of Hudson Bay and the coastal Beaufort Sea region, is characterized by very small seasonal SST amplitude. Lake Erie is the water body having the largest seasonal SST amplitude, but for the oceanic regions, it is the southern Gulf of St. Lawrence and the adjacent Scotian Shelf. A trend analysis showed that many regions are undergoing rapid warming of the sea surface. However, warming is not spatially uniform. The strongest warming was detected in Baffin Bay and appears to result from the decreasing ice cover. Lake Superior is also showing a strong warming trend. These results have important implications for fisheries management because SST affects many species. Regions with small yearly amplitudes and warming trends might act as future cool water oases for some species.