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 ◽  
...  

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.

2013 ◽  
Vol 10 (6) ◽  
pp. 4383-4404 ◽  
Author(s):  
M. Ardyna ◽  
M. Babin ◽  
M. Gosselin ◽  
E. Devred ◽  
S. Bélanger ◽  
...  

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.


2014 ◽  
Vol 11 (12) ◽  
pp. 3131-3147 ◽  
Author(s):  
A. Matsuoka ◽  
M. Babin ◽  
D. Doxaran ◽  
S. B. Hooker ◽  
B. G. Mitchell ◽  
...  

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 (a&amp;varphi;(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 a&amp;varphi;(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.


2015 ◽  
Vol 19 (2) ◽  
pp. 1-18 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte

Abstract The authors examine five recent reanalysis products [NCEP Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis Project (JRA-25), Interim ECMWF Re-Analysis (ERA-Interim), and Arctic System Reanalysis (ASR)] for 1) trends in near-surface radiation fluxes, air temperature, and humidity, which are important indicators of changes within the Arctic Ocean and also influence sea ice and ocean conditions, and 2) fidelity of these atmospheric fields and effects for an extreme event: namely, the 2007 ice retreat. An analysis of trends over the Arctic for the past decade (2000–09) shows that reanalysis solutions have large spreads, particularly for downwelling shortwave radiation. In many cases, the differences in significant trends between the five reanalysis products are comparable to the estimated trend within a particular product. These discrepancies make it difficult to establish a consensus on likely changes occurring in the Arctic solely based on results from reanalyses fields. Regarding the 2007 ice retreat event, comparisons with remotely sensed estimates of downwelling radiation observations against these reanalysis products present an ambiguity. Remotely sensed observations from a study cited herewith suggest a large increase in downwelling summertime shortwave radiation and decrease in downwelling summertime longwave radiation from 2006 and 2007. On the contrary, the reanalysis products show only small gains in summertime shortwave radiation, if any; however, all the products show increases in downwelling longwave radiation. Thus, agreement within reanalysis fields needs to be further checked against observations to assess possible biases common to all products.


2014 ◽  
Vol 11 (2) ◽  
pp. 293-308 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
Y. Aksenov ◽  
A. C. Coward ◽  
T. R. Anderson

Abstract. The Arctic Ocean is a region that is particularly vulnerable to the impact of ocean acidification driven by rising atmospheric CO2, with potentially negative consequences for calcifying organisms such as coccolithophorids and foraminiferans. In this study, we use an ocean-only general circulation model, with embedded biogeochemistry and a comprehensive description of the ocean carbon cycle, to study the response of pH and saturation states of calcite and aragonite to rising atmospheric pCO2 and changing climate in the Arctic Ocean. Particular attention is paid to the strong regional variability within the Arctic, and, for comparison, simulation results are contrasted with those for the global ocean. Simulations were run to year 2099 using the RCP8.5 (an Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) scenario with the highest concentrations of atmospheric CO2). The separate impacts of the direct increase in atmospheric CO2 and indirect effects via impact of climate change (changing temperature, stratification, primary production and freshwater fluxes) were examined by undertaking two simulations, one with the full system and the other in which atmospheric CO2 was prevented from increasing beyond its preindustrial level (year 1860). Results indicate that the impact of climate change, and spatial heterogeneity thereof, plays a strong role in the declines in pH and carbonate saturation (Ω) seen in the Arctic. The central Arctic, Canadian Arctic Archipelago and Baffin Bay show greatest rates of acidification and Ω decline as a result of melting sea ice. In contrast, areas affected by Atlantic inflow including the Greenland Sea and outer shelves of the Barents, Kara and Laptev seas, had minimal decreases in pH and Ω because diminishing ice cover led to greater vertical mixing and primary production. As a consequence, the projected onset of undersaturation in respect to aragonite is highly variable regionally within the Arctic, occurring during the decade of 2000–2010 in the Siberian shelves and Canadian Arctic Archipelago, but as late as the 2080s in the Barents and Norwegian seas. We conclude that, for future projections of acidification and carbonate saturation state in the Arctic, regional variability is significant and needs to be adequately resolved, with particular emphasis on reliable projections of the rates of retreat of the sea ice, which are a major source of uncertainty.


2017 ◽  
Author(s):  
Sang Heon Lee ◽  
Jang Han Lee ◽  
Howon Lee ◽  
Jae Joong Kang ◽  
Jae Hyung Lee ◽  
...  

Abstract. The Laptev and East Siberian seas are the least biologically studied region in the Arctic Ocean, although they are highly dynamic in terms of active processing of organic matter impacting the transport to the deep Arctic Ocean. Field-measured carbon and nitrogen uptake rates of phytoplankton were conducted in the Laptev and East Siberian seas as part of the NABOS (Nansen and Amundsen Basins Observational System) program. Major inorganic nutrients were mostly depleted at 100–50 % light depths but were not depleted within the euphotic depths in the Laptev and East Siberian seas. The water column-integrated chl-a concentration in this study was significantly higher than that in the western Arctic Ocean (t-test, p > 0.01). Unexpectedly, the daily carbon and nitrogen uptake rates in this study (average ± S.D. = 110.3 ± 88.3 mg C m−2 d−1 and 37.0 ± 25.8 mg N m−2 d−1, respectively) are within previously reported ranges. Surprisingly, the annual primary production (13.2 g C m−2) measured in the field during the vegetative season is approximately one order of magnitude lower than the primary production reported from a satellite–based estimation. Further validation using field-measured observations is necessary for a better projection of the ecosystem in the Laptev and East Siberian seas responding to ongoing climate change.


Science ◽  
2020 ◽  
Vol 369 (6500) ◽  
pp. 198-202 ◽  
Author(s):  
K. M. Lewis ◽  
G. L. van Dijken ◽  
K. R. Arrigo

Historically, sea ice loss in the Arctic Ocean has promoted increased phytoplankton primary production because of the greater open water area and a longer growing season. However, debate remains about whether primary production will continue to rise should sea ice decline further. Using an ocean color algorithm parameterized for the Arctic Ocean, we show that primary production increased by 57% between 1998 and 2018. Surprisingly, whereas increases were due to widespread sea ice loss during the first decade, the subsequent rise in primary production was driven primarily by increased phytoplankton biomass, which was likely sustained by an influx of new nutrients. This suggests a future Arctic Ocean that can support higher trophic-level production and additional carbon export.


2020 ◽  
Vol 11 ◽  
Author(s):  
Lisa W. von Friesen ◽  
Lasse Riemann

The Arctic Ocean is the smallest ocean on Earth, yet estimated to play a substantial role as a global carbon sink. As climate change is rapidly changing fundamental components of the Arctic, it is of local and global importance to understand and predict consequences for its carbon dynamics. Primary production in the Arctic Ocean is often nitrogen-limited, and this is predicted to increase in some regions. It is therefore of critical interest that biological nitrogen fixation, a process where some bacteria and archaea termed diazotrophs convert nitrogen gas to bioavailable ammonia, has now been detected in the Arctic Ocean. Several studies report diverse and active diazotrophs on various temporal and spatial scales across the Arctic Ocean. Their ecology and biogeochemical impact remain poorly known, and nitrogen fixation is so far absent from models of primary production in the Arctic Ocean. The composition of the diazotroph community appears distinct from other oceans – challenging paradigms of function and regulation of nitrogen fixation. There is evidence of both symbiotic cyanobacterial nitrogen fixation and heterotrophic diazotrophy, but large regions are not yet sampled, and the sparse quantitative data hamper conclusive insights. Hence, it remains to be determined to what extent nitrogen fixation represents a hitherto overlooked source of new nitrogen to consider when predicting future productivity of the Arctic Ocean. Here, we discuss current knowledge on diazotroph distribution, composition, and activity in pelagic and sea ice-associated environments of the Arctic Ocean. Based on this, we identify gaps and outline pertinent research questions in the context of a climate change-influenced Arctic Ocean – with the aim of guiding and encouraging future research on nitrogen fixation in this region.


2015 ◽  
Vol 143 (6) ◽  
pp. 2363-2385 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich ◽  
Lesheng Bai ◽  
Cecilia M. Bitz ◽  
Jordan G. Powers ◽  
...  

Abstract The Polar Weather Research and Forecasting Model (Polar WRF), a polar-optimized version of the WRF Model, is developed and made available to the community by Ohio State University’s Polar Meteorology Group (PMG) as a code supplement to the WRF release from the National Center for Atmospheric Research (NCAR). While annual NCAR official releases contain polar modifications, the PMG provides very recent updates to users. PMG supplement versions up to WRF version 3.4 include modified Noah land surface model sea ice representation, allowing the specification of variable sea ice thickness and snow depth over sea ice rather than the default 3-m thickness and 0.05-m snow depth. Starting with WRF V3.5, these options are implemented by NCAR into the standard WRF release. Gridded distributions of Arctic ice thickness and snow depth over sea ice have recently become available. Their impacts are tested with PMG’s WRF V3.5-based Polar WRF in two case studies. First, 20-km-resolution model results for January 1998 are compared with observations during the Surface Heat Budget of the Arctic Ocean project. Polar WRF using analyzed thickness and snow depth fields appears to simulate January 1998 slightly better than WRF without polar settings selected. Sensitivity tests show that the simulated impacts of realistic variability in sea ice thickness and snow depth on near-surface temperature is several degrees. The 40-km resolution simulations of a second case study covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on midlatitude synoptic meteorology that develop within 2 weeks during a winter 2012 blocking event.


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