Satellite chlorophyll off the British Columbia Coast, 1997-2010

Jackson, Jennifer M.; Thomson, Richard E.; Brown, Leslie; Willis, Peter G.; Borstad, Gary A.

doi:10.1002/2014jc010496

Cited by 43 publications

(43 citation statements)

References 57 publications

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“…The causality between PAR and Chl-a occurred in most regions of the Bohai Sea in winter (Figure 9h). These results, as shown in Figure 9, implied that the influences of environmental drivers (PAR and SST) on the Chl-a pattern were complex, which has been confirmed by previous studies [22,41,42]. At this stage, it should be stated that we investigated the causality between Chl-a and SST by mainly considering the indirect influences of SST on Chl-a.…”

Section: The Causality Between Chl-a Anomaly Sst Anomaly and Par Ansupporting

confidence: 84%

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

et al. 2017

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Abstract:Knowledge of the chlorophyll-a dynamics and their long-term changes is important for assessing marine ecosystems, especially for coastal waters. In this study, the spatial and temporal variability of sea surface chlorophyll-a concentration (Chl-a) in the Bohai Sea were investigated using 13-year (2000-2012) satellite-derived products from MODIS and SeaWiFS observations. Based on linear regression analysis, the results showed that the entire Bohai Sea experienced an increase in Chl-a on a long-term scale, with the largest increase in the central Bohai Sea and the smallest increase in the Bohai strait. Distinct seasonal patterns of Chl-a existed in different sub-regions of the Bohai Sea. A long-lasting Chl-a peak was observed from May to September in coastal waters (Liaodong bay, Qinhuangdao coast, and Bohai bay) and the central Bohai Sea, whereas Laizhou bay had relatively low Chl-a in early summer. In the Bohai strait, two pronounced Chl-a peaks occurred in March and September, but the lowest Chl-a was in summer. This pattern was quite different from those in other regions of the Bohai Sea. The water column condition (stratified or mixed) was likely an important physical factor that affects the seasonal pattern of Chl-a in the Bohai Sea. Meanwhile, increased human activity (e.g., river discharge) played a significant role in changing the Chl-a distribution in both coastal waters and the central Bohai Sea, especially in summer. The increasing trend of Chl-a in the Bohai Sea might be attributed to the increase in nutrient contents from riverine inputs. The Chl-a dynamics documented in this study provide basic knowledge for the future exploration of marine biogeochemical processes and ecosystem evolution in the Bohai Sea.

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Section: The Causality Between Chl-a Anomaly Sst Anomaly and Par Ansupporting

confidence: 84%

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

et al. 2017

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“…However, outlier or erroneous pixels, such as at undetected cloud edges [40], may have been introduced through the straylight flag reduction, or in scenes with low spatial coverage. Additionally, the removal of pixels exceeding 40.00 mg m −3 , while consistent with other remote sensing chla studies of the region [35,58], resulted in a distinctive distribution of input data (Figure 3). This led to a reduction of the global input dataset mean, and, as a result, chla rec concentrations above~20.0 mg m −3 were underestimated as data was reconstructed following a normal distribution of the input dataset anomaly (Section 2.3.1).…”

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confidence: 86%

Applications of DINEOF to Satellite-Derived Chlorophyll-a from a Productive Coastal Region

Hilborn

Costa

2018

Remote Sensing

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A major limitation for remote sensing analyses of oceanographic variables is loss of spatial data. The Data INterpolating Empirical Orthogonal Functions (DINEOF) method has demonstrated effectiveness for filling spatial gaps in remote sensing datasets, making them more easily implemented in further applications. However, the spatial and temporal coverage of the input image dataset can heavily impact the outcomes of using this method and, thus, further metrics derived from these datasets, such as phytoplankton bloom phenology. In this study, we used a three-year time series of MODIS-Aqua chlorophyll-a to evaluate the DINEOF reconstruction output accuracy corresponding to variation in the form of the input data used (i.e., daily or week composite scenes) and time series length (annual or three consecutive years) for a dynamic region, the Salish Sea, Canada. The accuracy of the output data was assessed considering the original chla pixels. Daily input time series produced higher accuracy reconstructing chla (95.08–97.08% explained variance, RMSExval 1.49–1.65 mg m−3) than did all week composite counterparts (68.99–76.88% explained variance, RMSExval 1.87–2.07 mg m−3), with longer time series producing better relationships to original chla pixel concentrations. Daily images were assessed relative to extracted in situ chla measurements, with original satellite chla achieving a better relationship to in situ matchups than DINEOF gap-filled chla, and with annual DINEOF-processed data performing better than the multiyear. These results contribute to the ongoing body of work encouraging production of ocean color datasets with consistent processing for global purposes such as climate change studies.

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“…Except at some small coastal locations where upwelling and mixing limit the yearly range of SST, the average seasonal warming for the entire northeast Pacific is quite spatially homogeneous at ∼ 8 • C. Another exception is the Georgia Strait where the amplitude is ∼ 14 • C. This is probably a result of the high vertical stability induced by the Fraser River freshwater outflow that keeps the heat in the surface layer. This area has been shown to have the highest annual chlorophyll concentration of the entire west coast, also possibly resulting from the stratification enhancement (Jackson et al 2015).…”

Section: Sst Extremes and Amplitudementioning

confidence: 95%

Canadian Coastal Seas and Great Lakes Sea Surface Temperature Climatology and Recent Trends

Larouche

Galbraith

2016

Canadian Journal of Remote Sensing

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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. Résumé. 28 années de données satellitaires ontété utilisées afin de calculer des climatologies des températures de surface de la mer «sea surface temperature» (SST) pour les 3 océans entourant le Canada ainsi que pour les Grands Lacs. Les résultats montrent l'empreinte des principaux courants océaniques sur la distribution spatiale des SST. Avec le Gulf Stream, le courant duLabrador génère une forte variabilité spatiale des SST sur la côte est. La plupart de l'arctique canadien, avec l'exception de la Baie d'Hudson et la zone côtière de la mer de Beaufort, est caractérisé par une très faible amplitude annuelle des SST. Le lacÉrié est la masse d'eau montrant la plus grande amplitude saisonnière, mais pour les régions océaniques, ce sont le sud du Golfe du Saint-Laurent et le plateau Néo-Écossais adjacent. Une analyse de tendances a montré que plusieurs régions sont soumisesà un accroissement rapide des températures de surface. Toutefois, le réchauffement n'est pas spatialement uniforme. Le plus fort réchauffement aété détecté dans la baie de Baffin et semble reliéà la décroissance de la couverture de glace. Le lac Supérieur montre aussi une forte tendance au réchauffement. Ces résultats ont d'importantes implications pour la gestion des pêches puisque la SST affecte plusieurs espèces. Les régions ayant une faible amplitude annuelle et un faible taux de réchauffement pourraient agir dans le futur comme des oasis froides pour certaines espèces.

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Satellite chlorophyll off the British Columbia Coast, 1997-2010

Cited by 43 publications

References 57 publications

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

Applications of DINEOF to Satellite-Derived Chlorophyll-a from a Productive Coastal Region

Canadian Coastal Seas and Great Lakes Sea Surface Temperature Climatology and Recent Trends

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