Abstract:Seasonal, interannual, and decadal variations in the Arctic ice‐algal productivity for 1980–2009 are investigated using daily outputs from five sea ice‐ocean ecosystem models participating in the Forum for Arctic Modeling and Observational Synthesis project. The models show a shelf‐basin contrast in the spatial distribution of ice‐algal productivity (ice‐PP). The simulated ice‐PP substantially varies among the four subregions (Chukchi Sea, Canada Basin, Eurasian Basin, and Barents Sea) and among the five model… Show more
“…The seasonal ice zone is defined here as the area where sea ice is present seasonally. The spatial pattern of the peak concentration shows a shelf basin contrast similar to modeled ice algal biomass distribution (Watanabe et al, 2019); the peak concentration range is 100–1,000 μmol S m −3 in shelf regions, while its range is much lower (1–10 μmol m −3 ) in the basins. There are only a few measurements of DMS within Arctic sea ice reported in Levasseur (2013): 30 μmol S m −3 in the Central Arctic in August 1994, 769 μmol S m −3 in the Beaufort Sea (year unknown), and 2,000 μmol S m −3 in the Resolute Bay in June 2012.…”
Field observations suggest that oceanic emissions of dimethylsulfide (DMS) may play a dominant role in the production of Arctic aerosols and clouds and therefore modulate the surface irradiance, during spring and summer. DMS is produced not only in the water column but also in various sea ice habitats. The ongoing recession of Arctic sea ice is expected to enhance DMS emissions, but the magnitude of this increase is highly uncertain. Here we investigate the spatiotemporal variability in bottom ice and sea surface DMS concentrations and fluxes using a regional sea ice-ocean physical-biogeochemical model. Model results indicate that the observed accelerated decline of Arctic sea ice extent since the beginning of the 21st century is associated with upward trends in May-August pan-Arctic-averaged sea surface DMS concentration and sea-to-air DMS flux. On the other hand, strong interannual variability and statistically insignificant trends are found for bottom ice DMS concentration and ice-to-sea DMS flux, owing to the counteracting effects of the shrinking horizontal extent and the vertical thinning of sea ice on ice algal production. The pan-Arctic DMS climatology products based on model simulation and satellite algorithms provide dynamically based spatial details that are absent in the in situ measurement-based climatology due to limited spatiotemporal data coverage and inevitable extrapolation bias. Lastly, model results indicate that the bottom ice DMS and its precursor dimethylsulfoniopropionate production can be the only local source of oceanic DMS emissions into the atmosphere during May prior to pelagic blooms, suggesting that it may be a key component of the biological control on Arctic climate at that time.
“…The seasonal ice zone is defined here as the area where sea ice is present seasonally. The spatial pattern of the peak concentration shows a shelf basin contrast similar to modeled ice algal biomass distribution (Watanabe et al, 2019); the peak concentration range is 100–1,000 μmol S m −3 in shelf regions, while its range is much lower (1–10 μmol m −3 ) in the basins. There are only a few measurements of DMS within Arctic sea ice reported in Levasseur (2013): 30 μmol S m −3 in the Central Arctic in August 1994, 769 μmol S m −3 in the Beaufort Sea (year unknown), and 2,000 μmol S m −3 in the Resolute Bay in June 2012.…”
Field observations suggest that oceanic emissions of dimethylsulfide (DMS) may play a dominant role in the production of Arctic aerosols and clouds and therefore modulate the surface irradiance, during spring and summer. DMS is produced not only in the water column but also in various sea ice habitats. The ongoing recession of Arctic sea ice is expected to enhance DMS emissions, but the magnitude of this increase is highly uncertain. Here we investigate the spatiotemporal variability in bottom ice and sea surface DMS concentrations and fluxes using a regional sea ice-ocean physical-biogeochemical model. Model results indicate that the observed accelerated decline of Arctic sea ice extent since the beginning of the 21st century is associated with upward trends in May-August pan-Arctic-averaged sea surface DMS concentration and sea-to-air DMS flux. On the other hand, strong interannual variability and statistically insignificant trends are found for bottom ice DMS concentration and ice-to-sea DMS flux, owing to the counteracting effects of the shrinking horizontal extent and the vertical thinning of sea ice on ice algal production. The pan-Arctic DMS climatology products based on model simulation and satellite algorithms provide dynamically based spatial details that are absent in the in situ measurement-based climatology due to limited spatiotemporal data coverage and inevitable extrapolation bias. Lastly, model results indicate that the bottom ice DMS and its precursor dimethylsulfoniopropionate production can be the only local source of oceanic DMS emissions into the atmosphere during May prior to pelagic blooms, suggesting that it may be a key component of the biological control on Arctic climate at that time.
“…Thus, fully comprehending HiLAT model shortcomings with respect to mixed layer nutrient concentrations will be important for understanding not only the overall response of production to climate change but its partitioning between the ice and ocean. HiLAT model estimate for annual Arctic (all analysis regions except the Bering Sea) ice‐algae primary production (2.4 Tg C) were in line with estimates from the UAF‐G model but significantly less than estimates from the other four model configurations (Watanabe et al, 2019). The HiLAT model and the UAF‐G model are both based on the biogeochemical module (Jin et al, 2012; Moore et al, 2004), which has been incorporated into CESM.…”
Section: Summary and Discussionsupporting
confidence: 60%
“…A reduction in snow and ice thickness will allow increased light penetration and thus a more suitable habitat for the growth of ice algae. However, a substantial reduction in ice cover will inevitability reduce the viable substrate and thus the contribution of ice algae to total production (Gosselin et al, 1997; Watanabe et al, 2019).…”
We use a modern Earth system model to approximate the relative importance of ice versus temperature on Arctic marine ecosystem dynamics. We show that while the model adequately simulates ice volume, water temperature, air‐sea CO2 flux, and annual primary production in the Arctic, itunderestimates upper water column nitrate across the region. This nitrate bias is likely responsible for the apparent underestimation of ice algae production. Despite this shortcoming, the model appears to be a useful tool for exploring the impacts of environmental change on phytoplankton production and carbon dynamics over the Arctic Ocean. Our experiments indicate that under a warmer climate scenario, the percentage of ocean warming that could be apportioned to a reduction in ice area ranged from 11% to 100%, while decreasing ice area could account for 22–100% of the increase in annual ocean primary production. The change to CO2 air‐sea flux in response to ice and temperature changes averaged an Arctic‐wide 5.5 Tg C yr−1 (3.5%) increase, into the ocean. This increased carbon sink may be short‐lived, as ice cover continues to decrease and the ocean warms. The change in carbon fixation from phytoplankton in response to increased temperatures and reduced ice was generally more than a magnitude larger than the changes to CO2 flux, highlighting the importance of fully considering changes to the marine ecosystem when assessing Arctic carbon cycle dynamics. Our work demonstrates the importance of ice dynamics in controlling ocean warming and production and thus the need for well‐behaved ice and BGC models within Earth system models if we hope to accurately predict Arctic changes.
“…Discharge and river water temperatures, simulated using the CHANGE model forced by three different meteorological datasets (Supplementary Materials), were used as riverine freshwater and heat fluxes in the COCO model experiments, which makes it possible to quantify the sensitivity of sea ice to the associated fluxes. Both COCO and CHANGE have been extensively used to simulate changes in sea ice–ocean processes associated with the Arctic sea-ice retreat ( 12 ) and long-term changes in river discharge and water temperatures from the pan-Arctic river system ( 1 , 17 ), respectively.…”
Arctic river discharge increased over the last several decades, conveying heat and freshwater into the Arctic Ocean and likely affecting regional sea ice and the ocean heat budget. However, until now, there have been only limited assessments of riverine heat impacts. Here, we adopted a synthesis of a pan-Arctic sea ice–ocean model and a land surface model to quantify impacts of river heat on the Arctic sea ice and ocean heat budget. We show that river heat contributed up to 10% of the regional sea ice reduction over the Arctic shelves from 1980 to 2015. Particularly notable, this effect occurs as earlier sea ice breakup in late spring and early summer. The increasing ice-free area in the shelf seas results in a warmer ocean in summer, enhancing ocean–atmosphere energy exchange and atmospheric warming. Our findings suggest that a positive river heat–sea ice feedback nearly doubles the river heat effect.
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