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  • 1
    Online Resource
    Online Resource
    Copernicus GmbH ; 2023
    In:  Geoscientific Model Development Vol. 16, No. 22 ( 2023-11-28), p. 6875-6897
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 16, No. 22 ( 2023-11-28), p. 6875-6897
    Abstract: Abstract. We present a framework that links in situ observations from the Biogeochemical Argo (BGC-Argo) array to biogeochemical models. The framework minimizes the technical effort required to construct a Lagrangian-type 1D modelling experiment along BGC-Argo tracks. We utilize the Argo data in two ways: (1) to drive the model physics and (2) to evaluate the model biogeochemistry. BGC-Argo physics data are used to nudge the model physics closer to observations to reduce the errors in the biogeochemistry stemming from physics errors. This allows us to target the model biogeochemistry and, by using the Argo biogeochemical dataset, we identify potential sources of model errors, introduce changes to the model formulation, and validate model configurations. We present experiments for the Nordic seas and showcase how we identify potential BGC-Argo buoys to model, prepare forcing, design experiments, and approach model improvement and validation. We use the ECOSMO II(CHL) model as the biogeochemical component and focus on chlorophyll a. The experiments reveal that ECOSMO II(CHL) requires improvements during low-light conditions, as the comparison to BGC-Argo reveals that ECOSMO II(CHL) simulates a late spring bloom and does not represent the deep chlorophyll maximum layer formation in summer periods. We modified the productivity and chlorophyll a relationship and statistically documented decreased bias and error in the revised model when using BGC-Argo data. Our results reveal that nudging the model temperature and salinity closer to BGC-Argo data reduces errors in biogeochemistry, and we suggest a relaxation time period of 1–10 d. The BGC-Argo data coverage is ever-growing and the framework is a valuable asset, as it improves biogeochemical models by performing efficient 1D model configurations and evaluation and then transferring the configurations to a 3D model with a wide range of use cases at the operational, regional/global and climate scales.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2456725-5
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  • 2
    Online Resource
    Online Resource
    Elsevier BV ; 2020
    In:  Progress in Oceanography Vol. 187 ( 2020-08), p. 102380-
    In: Progress in Oceanography, Elsevier BV, Vol. 187 ( 2020-08), p. 102380-
    Type of Medium: Online Resource
    ISSN: 0079-6611
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 1497436-8
    detail.hit.zdb_id: 4062-9
    SSG: 21,3
    SSG: 14
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  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Marine Science Vol. 9 ( 2022-3-24)
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 9 ( 2022-3-24)
    Abstract: Deep-sea sponges inhabit multiple areas of the deep North Atlantic at depths below 250 m. Living in the deep ocean, where environmental properties below the permanent thermocline generally change slowly, they may not easily acclimatize to abrupt changes in the environment. Until now consistent monitoring timeseries of the environment at deep sea sponge habitats are missing. Therefore, long-term simulation with coupled bio-physical models can shed light on the changes in environmental conditions sponges are exposed to. To investigate the variability of North Atlantic sponge habitats for the past half century, the deep-sea conditions have been simulated with a 67-year model hindcast from 1948 to 2014. The hindcast was generated using the ocean general circulation model HYCOM, coupled to the biogeochemical model ECOSMO. The model was validated at known sponge habitats with available observations of hydrography and nutrients from the deep ocean to evaluate the biases, errors, and drift in the model. Knowing the biases and uncertainties we proceed to study the longer-term (monthly to multi-decadal) environmental variability at selected sponge habitats in the North Atlantic and Arctic Ocean. On these timescales, these deep sponge habitats generally exhibit small variability in the water-mass properties. Three of the sponge habitats, the Flemish Cap, East Greenland Shelf and North Norwegian Shelf, had fluctuations of temperature and salinity in 4–6 year periods that indicate the dominance of different water masses during these periods. The fourth sponge habitat, the Reykjanes Ridge, showed a gradual warming of about 0.4°C over the simulation period. The flux of organic matter to the sea floor had a large interannual variability, that, compared to the 67-year mean, was larger than the variability of primary production in the surface waters. Lateral circulation is therefore likely an important control mechanism for the influx of organic material to the sponge habitats. Simulated oxygen varies interannually by less than 1.5 ml/l and none of the sponge habitats studied had oxygen concentrations below hypoxic levels. The present study establishes a baseline for the recent past deep conditions that future changes in deep sea conditions from observations and climate models can be evaluated against.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2757748-X
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  • 4
    Online Resource
    Online Resource
    Copernicus GmbH ; 2022
    In:  Geoscientific Model Development Vol. 15, No. 9 ( 2022-05-13), p. 3901-3921
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 9 ( 2022-05-13), p. 3901-3921
    Abstract: Abstract. ECOSMO II is a fully coupled bio-physical model of 3D hydrodynamics with an intermediate-complexity NPZD (nutrient, phytoplankton, zooplankton, detritus) type biology including sediment-water column exchange processes originally formulated for the North Sea and Baltic Sea. Here we present an updated version of the model incorporating chlorophyll a as a prognostic state variable: ECOSMO II(CHL). The version presented here is online coupled to the HYCOM ocean model. The model is intended to be used for regional configurations for the North Atlantic and the Arctic incorporating coarse to high spatial resolutions for hind-casting and operational purposes. We provide the full descriptions of the changes in ECOSMO II(CHL) from ECOSMO II and provide the evaluation for the inorganic nutrients and chlorophyll a variables, present the modelled biogeochemistry of the Nordic Seas and the Arctic, and experiment on various parameterization sets as use cases targeting chlorophyll a dynamics. We document the performance of each parameter set objectively analysing the experiments against in situ, satellite and climatology data. The model evaluations for each experiment demonstrated that the simulations are consistent with the large-scale climatological nutrient setting and are capable of representing regional and seasonal changes. Explicitly resolving chlorophyll a allows for more dynamic seasonal and vertical variations in phytoplankton biomass to chlorophyll a ratio and improves model chlorophyll a performance near the surface. Through experimenting with the model performance, we document the general biogeochemisty of the Nordic Seas and the Arctic. The Norwegian and Barents seas primary production show distinct seasonal patterns with a pronounced spring bloom dominated by diatoms and low biomass during winter months. The Norwegian Sea annual primary production is around double that of the Barents Sea while also having an earlier spring bloom.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
    Location Call Number Limitation Availability
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  • 5
    In: Progress in Oceanography, Elsevier BV, Vol. 217 ( 2023-09), p. 103084-
    Type of Medium: Online Resource
    ISSN: 0079-6611
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1497436-8
    detail.hit.zdb_id: 4062-9
    SSG: 21,3
    SSG: 14
    Location Call Number Limitation Availability
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  • 6
    In: Journal of Operational Oceanography, Informa UK Limited, Vol. 12, No. sup1 ( 2019-06-30), p. S1-S123
    Type of Medium: Online Resource
    ISSN: 1755-876X , 1755-8778
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2019
    detail.hit.zdb_id: 2428097-5
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