Sea ice phenology and timing of primary production pulses in the Arctic Ocean

2012 ◽  
Vol 19 (3) ◽  
pp. 734-741 ◽  
Author(s):  
Rubao Ji ◽  
Meibing Jin ◽  
Øystein Varpe
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.


2016 ◽  
Vol 12 (11) ◽  
pp. 20160223 ◽  
Author(s):  
Mati Kahru ◽  
Zhongping Lee ◽  
B. Greg Mitchell ◽  
Cynthia D. Nevison

The influence of decreasing Arctic sea ice on net primary production (NPP) in the Arctic Ocean has been considered in multiple publications but is not well constrained owing to the potentially large errors in satellite algorithms. In particular, the Arctic Ocean is rich in coloured dissolved organic matter (CDOM) that interferes in the detection of chlorophyll a concentration of the standard algorithm, which is the primary input to NPP models. We used the quasi-analytic algorithm (Lee et al . 2002 Appl. Opti. 41 , 5755−5772. ( doi:10.1364/AO.41.005755 )) that separates absorption by phytoplankton from absorption by CDOM and detrital matter. We merged satellite data from multiple satellite sensors and created a 19 year time series (1997–2015) of NPP. During this period, both the estimated annual total and the summer monthly maximum pan-Arctic NPP increased by about 47%. Positive monthly anomalies in NPP are highly correlated with positive anomalies in open water area during the summer months. Following the earlier ice retreat, the start of the high-productivity season has become earlier, e.g. at a mean rate of −3.0 d yr −1 in the northern Barents Sea, and the length of the high-productivity period has increased from 15 days in 1998 to 62 days in 2015. While in some areas, the termination of the productive season has been extended, owing to delayed ice formation, the termination has also become earlier in other areas, likely owing to limited nutrients.


2013 ◽  
Vol 10 (2) ◽  
pp. 2937-2965 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
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, negatively impacting calcifying organisms such as coccolithophorids and foraminiferans. In this study, we use an ocean general circulation model, with embedded biogeochemistry and a full description of the carbon cycle, to study the response of pH and saturation states of calcite and aragonite to 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 RCP 8.5 (the highest IPCC AR5 CO2 emission scenario). The separate impacts of the direct increase in atmospheric CO2 and indirect effects via climate feedbacks (changing temperature, stratification, primary production and fresh water fluxes) were examined by undertaking two simulations, one with the full system and the other in which ocean-atmosphera exchange of CO2 was prevented from increasing beyond the flux calculated for year 2000. Results indicate that climate feedbacks, and spatial heterogeneity thereof, play 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 weakening stratification associated with diminishing ice cover led to greater mixing and primary production. As a consequence, the predicted onset of undersaturation 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, in order to make future projections of acidification and carbon saturation state in the Arctic, regional variability needs to be adequately resolved, with particular emphasis on reliable predictions of the rates of retreat of the sea-ice which are a major source of uncertainty.


2010 ◽  
Vol 7 (4) ◽  
pp. 5557-5620 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
A. C. Coward ◽  
Y. K. Aksenov ◽  
S. G. Alderson ◽  
...  

Abstract. Until recently, the Arctic Basin was generally considered to be a low productivity area and was afforded little attention in global- or even basin-scale ecosystem modelling studies. Due to anthropogenic climate change however, the sea ice cover of the Arctic Ocean is undergoing an unexpectedly fast retreat, exposing increasingly large areas of the basin to sunlight. As indicated by existing Arctic phenomena such as ice-edge blooms, this decline in sea-ice is liable to encourage pronounced growth of phytoplankton in summer and poses pressing questions concerning the future of Arctic ecosystems. It thus provides a strong impetus to modelling of this region. The Arctic Ocean is an area where plankton productivity is heavily influenced by physical factors. As these factors are strongly responding to climate change, we analyse here the results from simulations of the 1/4° resolution global ocean NEMO (Nucleus for European Modelling of the Ocean) model coupled with the MEDUSA (Model for Ecosystem Dynamics, carbon Utilisation, Sequestration and Acidification) biogeochemical model, with a particular focus on the Arctic Basin. Simulated productivity is consistent with the limited observations for the Arctic, with significant production occurring both under the sea-ice and at the thermocline, locations that are difficult to sample in the field. Results also indicate that a substantial fraction of the variability in Arctic primary production can be explained by two key physical factors: (i) the maximum penetration of winter mixing, which determines the amount of nutrients available for summer primary production, and (ii) short-wave radiation at the ocean surface, which controls the magnitude of phytoplankton blooms. A strong empirical correlation was found in the model output between primary production these two factors, highlighting the importance of physical processes in the Arctic Ocean.


2010 ◽  
Vol 7 (11) ◽  
pp. 3569-3591 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
A. C. Coward ◽  
Y. K. Aksenov ◽  
S. G. Alderson ◽  
...  

Abstract. Until recently, the Arctic Basin was generally considered to be a low productivity area and was afforded little attention in global- or even basin-scale ecosystem modelling studies. Due to anthropogenic climate change however, the sea ice cover of the Arctic Ocean is undergoing an unexpectedly fast retreat, exposing increasingly large areas of the basin to sunlight. As indicated by existing Arctic phenomena such as ice-edge blooms, this decline in sea-ice is liable to encourage pronounced growth of phytoplankton in summer and poses pressing questions concerning the future of Arctic ecosystems. It thus provides a strong impetus to modelling of this region. The Arctic Ocean is an area where plankton productivity is heavily influenced by physical factors. As these factors are strongly responding to climate change, we analyse here the results from simulations of the 1/4° resolution global ocean NEMO (Nucleus for European Modelling of the Ocean) model coupled with the MEDUSA (Model for Ecosystem Dynamics, carbon Utilisation, Sequestration and Acidification) biogeochemical model, with a particular focus on the Arctic basin. Simulated productivity is consistent with the limited observations for the Arctic, with significant production occurring both under the sea-ice and at the thermocline, locations that are difficult to sample in the field. Results also indicate that a substantial fraction of the variability in Arctic primary production can be explained by two key physical factors: (i) the maximum penetration of winter mixing, which determines the amount of nutrients available for summer primary production, and (ii) short-wave radiation at the ocean surface, which controls the magnitude of phytoplankton blooms. A strong empirical correlation was found in the model output between primary production and these two factors, highlighting the importance of physical processes in the Arctic Ocean.


2012 ◽  
Vol 69 (7) ◽  
pp. 1180-1193 ◽  
Author(s):  
Zachary W. Brown ◽  
Kevin R. Arrigo

Abstract Brown, Z. W., and Arrigo, K. R. 2012. Contrasting trends in sea ice and primary production in the Bering Sea and Arctic Ocean. – ICES Journal of Marine Science, 69: . Satellite remote sensing data were used to examine recent trends in sea-ice cover and net primary productivity (NPP) in the Bering Sea and Arctic Ocean. In nearly all regions, diminished sea-ice cover significantly enhanced annual NPP, indicating that light-limitation predominates across the seasonally ice-covered waters of the northern hemisphere. However, long-term trends have not been uniform spatially. The seasonal ice pack of the Bering Sea has remained consistent over time, partially because of winter winds that have continued to carry frigid Arctic air southwards over the past six decades. Hence, apart from the “Arctic-like” Chirikov Basin (where sea-ice loss has driven a 30% increase in NPP), no secular trends are evident in Bering Sea NPP, which averaged 288 ± 26 Tg C year−1 over the satellite ocean colour record (1998–2009). Conversely, sea-ice cover in the Arctic Ocean has plummeted, extending the open-water growing season by 45 d in just 12 years, and promoting a 20% increase in NPP (range 441–585 Tg C year−1). Future sea-ice loss will likely stimulate additional NPP over the productive Bering Sea shelves, potentially reducing nutrient flux to the downstream western Arctic Ocean.


2008 ◽  
Vol 21 (5) ◽  
pp. 866-882 ◽  
Author(s):  
Irina V. Gorodetskaya ◽  
L-Bruno Tremblay ◽  
Beate Liepert ◽  
Mark A. Cane ◽  
Richard I. Cullather

Abstract The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3. In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.


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