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  • 1
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Today's surface ocean is saturated with respect to calcium carbonate, but increasing atmospheric carbon dioxide concentrations are reducing ocean pH and carbonate ion concentrations, and thus the level of calcium carbonate saturation. Experimental evidence suggests that if these trends ...
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2023-06-08
    Type: Dataset
    Format: application/pdf, 2.1 MBytes
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  • 3
    Publication Date: 2024-02-01
    Description: The JGOFS International Collection Volume 2: Integrated Data Sets CD is a coherent, organised compilation of existing data sets produced by member countries which participated in JGOFS. In most cases, the data were gathered from the JGOFS International Collection, Volume 1: Discrete Datasets DVD. To produce Vol. 1 data were taken from the original sources and copied “as is” on the DVD. For Vol. 2 data and metadata have been harmonized using the conversion software PanTool and the import routine of PANGAEA checking for completeness of metadata and defining the relations between data and metadata. Prior to the import, data had performed a technical quality control, i.e. format and readability of the file, availability and combination of parameters and units, range of values.
    Keywords: JGOFS; Joint Global Ocean Flux Study
    Type: Dataset
    Format: application/octet-stream, 607.6 MBytes
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  • 4
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    PANGAEA
    In:  Supplement to: Fischer, Gerhard; Karakas, Gökay; Blaas, M; Ratmeyer, Volker; Nowald, Nicolas; Schlitzer, Reiner; Helmke, Peer; Davenport, Robert; Donner, Barbara; Neuer, Susanne; Wefer, Gerold (2009): Mineral ballast and particle settling rates in the coastal upwelling system off NW Africa and the South Atlantic. International Journal of Earth Sciences, 98(2), 281-298, https://doi.org/10.1007/s00531-007-0234-7
    Publication Date: 2024-02-02
    Description: The ocean off NW Africa is the second most important coastal upwelling system with a total annual primary production of 0.33 Gt of carbon per year (Carr in Deep Sea Res II 49:59-80, 2002). Deep ocean organic carbon fluxes measured by sediment traps are also fairly high despite low biogenic opal fluxes. Due to a low supply of dissolved silicate from subsurface waters, the ocean off NW Africa is characterized by predominantly carbonate-secreting primary producers, i.e. coccolithophorids. These algae which are key primary producers since millions of years are found in organic- and chlorophyll-rich zooplankton fecal pellets, which sink rapidly through the water column within a few days. Particle flux studies in the Mauretanian upwelling area (Cape Blanc) confirm the hypothesis of Armstrong et al. (Deep Sea Res II 49:219-236, 2002) who proposed that ballast availability, e.g. of carbonate particles, is essential to predict deep ocean organic carbon fluxes. The role of dust as ballast mineral for organic carbon, however, must be also taken into consideration in the coastal settings off NW Africa. There, high settling rates of larger particles approach 400 m day**-1, which may be due to a particular composition of mineral ballast. An assessment of particle settling rates from opal-production systems in the Southern Ocean of the Atlantic Sector, in contrast, provides lower values, consistent with the assumptions of Francois et al. (Global Biogeochem Cycles 16(4):1087, 2002). Satellite chlorophyll distributions, particle distributions and fluxes in the water column off NW Africa as well as modelling studies suggest a significant lateral flux component and export of particles from coastal shelf waters into the open ocean. These transport processes have implications for paleo-reconstructions from sediment cores retrieved at continental margin settings.
    Keywords: Calcium carbonate, flux; Calculated, see reference(s); Cape Blanc; Carbon, organic, flux; CB13; CB13_trap; CB3_trap; CB4_trap; Center for Marine Environmental Sciences; Comment; DEPTH, water; Event label; Lithogenic, flux; M12/1; M16/2; MARUM; Meteor (1986); Opal, flux; Sample code/label; Total, flux per year; Trap; TRAP
    Type: Dataset
    Format: text/tab-separated-values, 39 data points
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  • 5
    Publication Date: 2021-05-03
    Description: We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to algorithmically support and partly automate the quality control of ocean data profiles are especially helpful for the gross errors in the data. Range filters, spike detection, and data distribution checks remove reliably the outliers and errors in the data, still wrong classifications occur. Various automated quality control procedures have been successfully implemented within the main international and EU marine data infrastructures (WOD, CMEMS, IQuOD, SDN) but their resulting data products are still containing data anomalies, bad data flagged as good and vice-versa. They also include visual inspection of suspicious measurements, which is a time consuming activity, especially if the number of suspicious data detected is large. A deep learning approach could highly improve our capabilities to quality assess big data collections and contemporary reducing the human effort. Our algorithm SalaciaML is meant to complement classical automated quality control procedures in supporting the time consuming visually inspection of data anomalies by quality control experts. As a first approach we applied the algorithm to a large dataset from the Mediterranean Sea. SalaciaML has been able to detect correctly more than 90% of all good and/or bad data in 11 out of 16 Mediterranean regions.
    Description: This project has received funding from the European Union Horizon 2020 and Seventh Framework Programmes under grant agreement number 730960 SeaDataCloud.
    Description: Published
    Description: 611742
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Keywords: 05.06. Methods
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 6
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    In:  EPIC3Geophysical Research Letters, 48(5), ISSN: 0094-8276
    Publication Date: 2021-03-15
    Description: Anaerobic microbial activity in the ocean causes losses of bioavailable nitrogen and emission of nitrous oxide to the atmosphere, but its predictability at global scales remains limited. Resource ratio theory suggests that anaerobic activity becomes sustainable when the ratio of oxygen to organic matter supply is below the ratio required by aerobic metabolisms. Here, we demonstrate the relevance of this framework at the global scale using three-dimensional ocean datasets, providing a new interpretation of existing observations. Evaluations of the location and extent of anoxic zones and a diagnostic rate of pelagic nitrogen loss are consistent with previous estimates. However, we demonstrate that a threshold based on substrate-supply fluxes is qualitatively different from a threshold based solely on the ambient oxygen concentration. This implies that use of the flux-based threshold in global biogeochemical models can result in different predictions of anaerobic activity and nitrogen loss.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 7
    Publication Date: 2021-06-05
    Description: We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to algorithmically support and partly automate the quality control of ocean data profiles are especially helpful for the gross errors in the data. Range filters, spike detection, and data distribution checks remove reliably the outliers and errors in the data, still wrong classifications occur. Various automated quality control procedures have been successfully implemented within the main international and EU marine data infrastructures (WOD, CMEMS, IQuOD, SDN) but their resulting data products are still containing data anomalies, bad data flagged as good and vice-versa. They also include visual inspection of suspicious measurements, which is a time consuming activity, especially if the number of suspicious data detected is large. A deep learning approach could highly improve our capabilities to quality assess big data collections and contemporary reducing the human effort. Our algorithm SalaciaML is meant to complement classical automated quality control procedures in supporting the time consuming visually inspection of data anomalies by quality control experts. As a first approach we applied the algorithm to a large dataset from the Mediterranean Sea. SalaciaML has been able to detect correctly more than 90% of all good and/or bad data in 11 out of 16 Mediterranean regions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 8
    Publication Date: 2019-07-16
    Description: We investigate CO2 uptake by the ocean with a three dimensional global inverse ocean model. The new approach lies in the calculation of spatially and temporally varying air-sea fluxes by assimilating water column carbon data, avoiding difficulties with changing gas-transfer velocities and their wind-speed dependencies. The model includes biological production near the surface and export particle remineralization below. Production and downward particle fluxes vary monthly following SeaWiFS chlorophyll data. Monthly DIC and DOC values are simulated. Starting air-sea fluxes are from Takahashi (2002).GLODAP DIC data are assimilated using the adjoint method, and CO2 air-sea fluxes are modified by the model until agreement with DIC data is optimal. In the present stage we are able to reduce DIC misfits by around 50%. The optimal air-sea fluxes are similar to those proposed by Takahashi. Differences are in larger flux-amplitudes and in the northern hemisphere.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 9
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    In:  EPIC3Dept. for Theoretical Physics / Dept. f. Meteorology, Eötvös Loránd University, Budapest, Hungary.
    Publication Date: 2019-07-16
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 10
    Publication Date: 2019-07-16
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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