scholarly journals Trends in Winter Light Environment Over the Arctic Ocean: A Perspective From Two Decades of Ocean Color Data

2020 ◽  
Vol 47 (16) ◽  
Author(s):  
Bror F. Jönsson ◽  
Shubha Sathyendranath ◽  
Trevor Platt
Keyword(s):  
Arctic Ocean ◽  
Ocean Color ◽  
Light Environment ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Color Data

scholarly journals A synthesis of light absorption properties of the Arctic Ocean: application to semianalytical estimates of dissolved organic carbon concentrations from space

2014 ◽  
Vol 11 (12) ◽  
pp. 3131-3147 ◽  
Author(s):  
A. Matsuoka ◽  
M. Babin ◽  
D. Doxaran ◽  
S. B. Hooker ◽  
B. G. Mitchell ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Arctic Ocean ◽  
Ocean Color ◽  
The Arctic ◽  
Data Sets ◽  
Absorption Coefficients ◽  
Absorption Properties ◽  
Chl A ◽  
The Arctic Ocean ◽  
Color Data

Abstract. In addition to scattering coefficients, the light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the data sets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database of the Arctic Ocean by pooling the majority of published data sets and merging new data sets. Our results show that the total nonwater absorption coefficients measured in the eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aϕ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semianalytical CDOM absorption algorithm is based on chl a-specific aϕ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Based on statistics, derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semianalytical algorithm for estimating DOC concentrations for river-influenced coastal waters of the Arctic Ocean is presented and applied to satellite ocean color data.

scholarly journals Parameterization of vertical chlorophyll <i>a</i> in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal and annual primary production estimates

2013 ◽  
Vol 10 (1) ◽  
pp. 1345-1399 ◽  
Author(s):  
M. Ardyna ◽  
M. Babin ◽  
M. Gosselin ◽  
E. Devred ◽  
S. Bélanger ◽  
...  
Keyword(s):  
Primary Production ◽  
Arctic Ocean ◽  
Empirical Model ◽  
Ocean Color ◽  
The Arctic ◽  
Winter Period ◽  
Substantial Impact ◽  
Near Surface ◽  
Chl A ◽  
The Arctic Ocean

Abstract. Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e. 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (chl a) according to: (1) the shelf-offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface chl a concentration (chl asurf; 0.7–30 mg m−3) throughout the open water period, the chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when chl asurf is low (0–0.5 mg m−3). By applying our empirical model to annual chl asurf time series, instead of the conventional method assuming vertically homogenous chl a, we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e. pre-bloom, post-bloom > 0.05 mg m−3 and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e. post-bloom < 0.05 mg m−3). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.

scholarly journals An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll‐ a based models

2015 ◽  
Vol 120 (9) ◽  
pp. 6508-6541 ◽  
Author(s):  
Younjoo J. Lee ◽  
Patricia A. Matrai ◽  
Marjorie A. M. Friedrichs ◽  
Vincent S. Saba ◽  
David Antoine ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Chlorophyll A ◽  
Primary Productivity ◽  
Ocean Color ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Satellite Ocean Color

scholarly journals Parameterization of vertical chlorophyll <i>a</i> in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates

2013 ◽  
Vol 10 (6) ◽  
pp. 4383-4404 ◽  
Author(s):  
M. Ardyna ◽  
M. Babin ◽  
M. Gosselin ◽  
E. Devred ◽  
S. Bélanger ◽  
...  
Keyword(s):  
Primary Production ◽  
Arctic Ocean ◽  
Empirical Model ◽  
Ocean Color ◽  
The Arctic ◽  
Winter Period ◽  
Substantial Impact ◽  
Near Surface ◽  
Chl A ◽  
The Arctic Ocean

Abstract. Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (Chl a) according to (1) the shelf–offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom, and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl asurf; 0.7–30 mg m−3) throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl asurf is low (0–0.5 mg m−3). By applying our empirical model to annual Chl asurf time series, instead of the conventional method assuming vertically homogenous Chl a, we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m−3, and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom < 0.5 mg m−3). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.

scholarly journals A synthesis of light absorption properties of the Pan-Arctic Ocean: application to semi-analytical estimates of dissolved organic carbon concentrations from space

2013 ◽  
Vol 10 (11) ◽  
pp. 17071-17115 ◽  
Author(s):  
A. Matsuoka ◽  
M. Babin ◽  
D. Doxaran ◽  
S. B. Hooker ◽  
B. G. Mitchell ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Arctic Ocean ◽  
Light Absorption ◽  
Ocean Color ◽  
The Arctic ◽  
Absorption Coefficients ◽  
Absorption Properties ◽  
Chl A ◽  
Color Data

Abstract. The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aφ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific aφ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC vs. CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

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