23 February 2023 | 10:30 - 12:30 (GMT+1)
Open Session - HYBRID
Room: Hörsaal 7
Session Conveners: Yuanxin Zhang (Japan Agency for Marine-Earth Science and Technology, Japan); Marit Reigstad (UiT The Arctic University of Norway, Norway); Mariko Hatta (Japan Agency for Marine-Earth Science and Technology, Japan)
Session Description:
Approaches to studying and predicting the biogeochemistry of the Arctic Ocean on Pan-Arctic and regional scales include models, remote sensing, and field-based observations. Increased efforts are taken to improve models and observations to lead to a better understanding of the status and the future scenarios of both the Arctic regions and the Arctic as part of a global system. But is this enough for our mutual benefit?
Current gaps between modeling and observational research are caused by differences in scales and their approaches. To increase the synergy of the two complementary approaches, we need not only to identify the key questions, parameters, and biogeochemical processes but also to recognize what are the limitations, uncertainties, and challenges. Do observations fill the model needs, and do the models deliver robust results, upscaling, and test facilities to observers?
We invite contributions from younger and experienced scientists who can present the latest research in the Arctic Ocean inflow regions, and/or answer similarities, differences, and connections of the Arctic seas, and identify needs from observers and modelers that will help to fill gaps between modeling and observational research.
Presentations:
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unfold_more10:30 - 10:35: Opening
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unfold_more10:35 - 10:55: The importance of lateral carbon and nutrient fluxes for the Arctic Ocean biogeochemistry - Keynote Presentation
Jens Terhaar
Woods Hole Oceanographic InstitutionAbstract:
The unique Arctic Ocean ecosystem and fisheries are experiencing large changes caused among others by ocean acidification and changing net primary production. In this rapidly changing Arctic Ocean, reliable projections of these processes are essential for effective and proactive stewardship. The main tools for these projections are global Earth System Models (ESMs). Unfortunately, these ESMs struggle to represent Arctic Ocean primary production and ocean acidification despite continuous model development and increased model resolution. The large inter-model differences mainly occur because ocean biogeochemical models embedded in ESMs are developed to represent the open ocean and often do not include or greatly simplify local-scale processes that are important and observed in the Arctic Ocean such as carbon and nutrients fluxes from adjacent oceans through small-scale passages, carbon and nutrients fluxes from rivers and coastal erosion, lability and remineralization of (terrestrial) organic matter in the water column, and remineralization and burial in coastal sediments. In this presentation, I will first show how present ESMs can be used in combination with observations to extract the best possible information. In a second part, I will present future lines of research that will help to improve these projections in the next generations of ESMs. At a time when more high-quality observations in the Arctic are available and high-resolution earth system modeling becomes computationally feasible, this presentation will show how the gap between Arctic Ocean observations and Earth system modeling can be bridged to better represent the special Arctic biogeochemical conditions in ESMs and to provide more robust projections.
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unfold_more10:55 - 11:15: Multi-year phytoplankton predictability in the Barents Sea - Keynote Presentation
Filippa Fransner1,2; Annette Samuelsen2, 3; Are Olsen1, 2; Marius Årthun1, 2; François Counillon2, 3; Jerry Tjiputra2, 4; Noel Keenlyside1, 2
1University of Bergen; 2Bjerknes Centre for Climate Research; 3Nansen Environmental and Remote Sensing Centre; 4NORCE Norwegian Research CentreAbstract:
The Barents Sea is a highly biologically productive Arctic shelf sea with several commercially important fish stocks. Near-time forecasts, or predictions, of its ecosystem would therefore be valuable for marine resource management. Here, we demonstrate that the abundance of phytoplankton, the base of the marine food web, can be predicted up to five years in advance in the Barents Sea with the Norwegian Climate Prediction Model (NorCPM1) that includes the biogeochemical model HAMOCC. We identify two different mechanisms giving rise to this predictability; 1) in the southern ice-free Atlantic domain, skillful prediction is a result of the advection of waters with anomalous nitrate concentrations from the Subpolar North Atlantic; 2) in the northern Polar domain, phytoplankton predictability is a result of the skillful prediction of the summer ice concentration, which influences the light availability. The skillful prediction of the phytoplankton abundance by NorCPM1 opens up for development of numerical ecosystem predictions of the Barents Sea.
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unfold_more11:15 - 11:30: Seasonal cycling of inorganic carbon and nutrients in the Barents Sea: implications for ocean acidification
Elizabeth Jones
Institute of Marine ResearchAbstract:
In order to better predict effects of warming and sea-ice loss on biogeochemical cycling and ocean acidification in the Barents Sea it is essential to understand the carbon and nutrient dynamics in a region already experiencing ‘’Atlantification’’. Seasonality in carbon and nutrient cycling was investigated in the Arctic and Atlantic Water inflow regions of the Barents Sea during the Nansen Legacy project. In summer (August 2019), primary production had reduced concentrations of nutrients and dissolved inorganic carbon (CT), particularly in ice-free waters. Sea-ice meltwater lowered total alkalinity (AT), the buffering capacity of seawater, through dilution. By early winter (December 2019), mixing and remineralisation of organic matter increased concentrations of nutrients and CT in the water column. Winter-spring (March 2021) had greatest sea ice cover and a well-mixed water column rich in AT, carbon and nutrients. Following the transition to spring (April-May 2021), biological activity and ice melt was evident by small reductions in carbon, nutrients and AT in surface waters. The central Barents Sea exhibited low seasonality, where Arctic-like conditions persisted and likely increased the vulnerability of the water column to future acidification. In contrast, incursions of Atlantic Water eroded the ice cover and supplied the surface layer with nutrients and AT, driving biological uptake of CT and increasing the AT buffering capacity. Future ‘’Atlantification’’ may enhance biological activity, reduce meltwater effects and counteract acidification in the Barents Sea. The observations revealed the importance of seasonal and spatial studies in order to capture the variability in dynamic regions to improve the use of models.
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unfold_more11:35 - 11:50: Detection of the Arctic Ocean biogeochemical model biases through reanalysis system
Tsuyoshi Wakamatsu1, 2; Jiping Xie1, 2; Annette Samuelsen1, 2; Caglar Yumruktepe1, 2; Laurent Bertino1, 2
1Nansen Environmental and Remote Sensing Center; 2Bjerknes Centre for Climate ResearchAbstract:
In this presentation, we report model biases in the Arctic Ocean biogeochemical model detected through production of the Arctic Ocean biogeochemical reanalysis and discuss efforts towards future update of the system.Arctic Ocean biogeochemical reanalysis product is now available through the Copernicus Marine Service. The operational system for the reanalysis data production is based on a fixed-lag ensemble Kalman smoother data assimilation with joint state-parameter estimation and a physical-biogeochemical coupled ocean model. Satellite chlorophyll-a and in-situ nutrients: nitrate, silicate and phosphate are assimilated and biogeochemical model states are estimated jointly with eight global biogeochemical model parameters. Significant model bias is detectedin phytoplankton phenology characterized by late onset of spring bloom with too short duration and too strong bloom at its peak in the Barents Sea and Norwegian Sea without data assimilation. The model biasis successfully corrected by data assimilation,but still emerges during the next eight days forecast. This bias in phytoplankton phenology led our reanalysis system introduce new analysis masks based on sea ice concentration, mixed layer depth and nitrate concentration which are main sources of the model bias in the spring bloom onset timing in our model settings. The evaluation against in situ nutrients in the Barents Sea and the Norwegian Sea shows a reduced overestimation of silicate and nitrate, but validation of nutrients is difficult in general over the Arctic Ocean due to lack of in-situ data. Currently, multiple efforts to update the reanalysis system areon going focusing on reduction of the model biases and increasing effective number of observations.
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unfold_more11:50 - 12:05: Transport processes of seafloor sediment from the Chukchi shelf to the western Arctic basin
Eiji Watanabe1; Motoyo Itoh1; Jonaotaro Onodera1; Kohei Mizobata2
1Japan Agency for Marine-Earth Science and Technology; 2Tokyo University of Marine Science and TechnologyAbstract:
The processes of seafloor sediment transport from the Chukchi shelf to the western Arctic basin were investigated using a pan-Arctic sea ice‒ocean model and sediment-trap measurements at four mooring stations: North of Barrow Canyon, North of Hanna Canyon, Northwind Abyssal Plain, and Chukchi Abyssal Plain. The available sediment-trap data verified that the sinking flux of lithogenic material (LM) originally resuspended from the seafloor for 2010‒2020 was simulated reasonably well in the four mooring areas. The model results were analyzed to quantify the spatiotemporal variability of LM and to reveal its background mechanisms. Analysis indicated that the Barrow Canyon throughflow, Chukchi Slope Current (CSC), and mesoscale eddies played important roles in LM redistribution. The CSC controlled the westward transport of LM from the mouth of Barrow Canyon to the Chukchi Borderland. The mesoscale eddies generated north of Barrow Canyon efficiently transported shelf-origin LM toward the southern Canada Basin. The sinking flux of particulate organic carbon (POC) averaged from September 2010 to August 2020, which was estimated statistically from the simulated LM flux, was 0.13‒0.30 gC/m2/yr at 200-m depth in the southern Canada Basin. This finding reveals that lateral transport of sediment from the Chukchi shelf bottom has a considerable effect on the sinking flux of POC in the western Arctic basin, and suggests that the western Arctic marine biogeochemical cycle is strongly influenced by shelf–basin exchange that depends on the relative strength of the CSC and mesoscale eddy activity.
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unfold_more12:05 - 12:15: Dissolved Aluminium distribution in the Arctic Ocean
Mariko Hatta1; Christopher Measures2
1Japan Agency for Marine-Earth Science and Technology; 2University of HawaiiAbstract:
The Arctic Ocean shows one of the most elevated deep-water enrichments of dissolved Al in the any ocean basin. A correlation between dissolved Si and Al within the water column and a small amount of Al is incoprated into the biogenic shells were invoked to imply as a control mechanism of the Al distribution in the ocean, but it is highly variable or non-existent in many places. As a result of its perennial ice cover has one of the lowest vertical fluxes of biogenic particles, it is hard to describe the enrichment mechanism of Al in the Arctic by the vertical transport and remineralization of the biogenic Si phase. With the most updated Al data set in the Arctic Ocean, we will show that the enrichment in the intermediate waters along the shelf slope in the European Arctic, especially near Barents and Kara Seas, and in contrast, the value is lower along the shelf slope near Laptiv Sea and Canada Basin. This distribution of dissolved Al in the intermediate water of the Arctic appears to be tracing direct continental inputs to the ocean in much the same manner that surface water values reflect the input of wind-blown and riverine-transported continental materials to the surface ocean. The difference of dissolved Al value in the regions can be used as a tracer to identify the geochemical transport of the material from the continental boundary to the water interior.
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unfold_moreDiscussion