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  • 1
    Publikationsdatum: 2021-02-08
    Beschreibung: The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 22 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017.
    Materialart: Article , PeerReviewed
    Format: text
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    Publikationsdatum: 2023-07-01
    Beschreibung: The data set of the marine sediment core PS97/72-1 from the Bransfield Strait, Antarctic Peninsula, contains data from analyses of a 1012 cm core covering the age from recent to 13.8 ka BP. The piston core was retrieved 2016 during R/V Polarstern cruise PS97. The purpose of this data was a study for the reconstruction of Deglacial and Holocene sea ice and climate dynamics in the Bransfield Strait, Northern Antarctic Peninsula, which was published in Climate of the Past. Dataset 1 contains details of the radiocarbon ages. Dataset 2 are the geochemical bulk parameters including sedimentation rate, total organic carbon, biogenic opal, C/N ration, d13C of organic carbon, branched and isoprenoid tetraether index BIT and ice rafted debris. Dataset 3 is information on biomarkers with highly branched isoprenoids diene and triene (IPSO25), the phytoplankton biomarker IPSO25 index, d13C of IPSO25, branched and isoprenoid tetraether index BIT, sub-surface ocean temperature (based on branched GDGTs), diatom derived sea ice probability and diatom derived summer sea surface temperature. Dataset 4 contains all diatom counts including groupings of diatoms indication seasonal sea ice and open ocean cold and warm species.
    Schlagwort(e): Antarctica; Biomarker; Holocene; IPSO25; Marine Sediment Core; Sea ice
    Materialart: Dataset
    Format: application/zip, 4 datasets
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 3
    Publikationsdatum: 2023-07-01
    Schlagwort(e): Age, 14C AMS; Age, 14C calibrated; Age, dated; Age, dated material; Age, dated standard error; Age model; Antarctica; ANT-XXXI/3; Biomarker; calculated, 1 sigma; calculated, 2 sigma; Calendar age; Calendar age, standard error; DEPTH, sediment/rock; Holocene; IPSO25; Laboratory code/label; Marine Sediment Core; PC; Piston corer; Polarstern; PS97; PS97/072-1; Reservoir effect/correction; Sample code/label; Scotia Sea; Sea ice
    Materialart: Dataset
    Format: text/tab-separated-values, 88 data points
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 4
    Publikationsdatum: 2023-07-01
    Schlagwort(e): (9Z)-2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyliden)pentadeca-9-ene, per unit mass total organic carbon; 2,10,14-Trimethyl-6-enyl-7-(3-methylpent-1-enyl)pentadecene, per unit mass total organic carbon; AGE; Antarctica; ANT-XXXI/3; Biomarker; Branched and isoprenoid tetraether index; Calculated; DEPTH, sediment/rock; Diatoms, sea-ice; Gas chromatography - Mass spectrometry (GC-MS); Holocene; IPSO25; Marine Sediment Core; Modern analog technique (MAT), D274/28/4an; PC; Phytoplankton biomarker IPSO25 index; Piston corer; Polarstern; PS97; PS97/072-1; Scotia Sea; Sea ice; Sea surface temperature, summer; SOTOH, SOT based on RI-OH caculated after Lü et al., 2015 (Eq. 13 and 14); Sub-surface ocean temperature; Tetraether index of 86 carbon atoms, low-temperature region; Transfer function, IKM – D336/29/3q; δ13C; δ13C, standard error
    Materialart: Dataset
    Format: text/tab-separated-values, 955 data points
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 5
    Publikationsdatum: 2023-07-01
    Schlagwort(e): AGE; Antarctica; ANT-XXXI/3; Biomarker; Branched and isoprenoid tetraether index; Carbon, organic, total; Carbon/Nitrogen ratio; DEPTH, sediment/rock; Holocene; Ice rafted debris; IPSO25; Marine Sediment Core; Opal, biogenic silica; PC; Piston corer; Polarstern; PS97; PS97/072-1; Scotia Sea; Sea ice; Sedimentation rate; δ13C, organic carbon; δ13C, organic carbon, standard error
    Materialart: Dataset
    Format: text/tab-separated-values, 1714 data points
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 6
    Publikationsdatum: 2023-07-10
    Schlagwort(e): Achnanthes brevipes; Actinocyclus actinochilus; Actinocyclus ingens; Amphora coffeaeformis; Amphora copulata; Antarctica; ANT-XXXI/3; Asteromphalus hookeri; Asteromphalus hyalinus; Azpeitia tabularis; Berkeleya spp.; Biomarker; Chaetoceros, resting spores; Cladogramma sp.; Cocconeis californica var. californica; Cocconeis californica var. kerguelensis; Cocconeis costata; Cocconeis dalmannii; Cocconeis fasciolata; Cocconeis imperatrix; Cocconeis melchioroides; Cocconeis sp.; Corethron pennatum; Coscinodiscus oculus-iridis; Denticulopsis spp.; DEPTH, sediment/rock; Diatoms; Diatoms, benthic; Diatoms, fossil; Diatoms, open ocean cold; Diatoms, open ocean warm; Diatoms, seasonal sea-ice; Diatoms indeterminata; Diatom valves, per unit sediment mass; Entopyla ocellata; Eucampia antarctica var. antarctica; Eucampia antarctica var. recta; Fallacia marnierii; Fragilariopsis curta; Fragilariopsis cylindrus; Fragilariopsis kerguelensis; Fragilariopsis nana; Fragilariopsis obliquecostata; Fragilariopsis peragallii; Fragilariopsis pseudonana; Fragilariopsis rhombica; Fragilariopsis ritscheri; Fragilariopsis separanda; Fragilariopsis sublinearis; Fragilariopsis vanheurckii; Gomphomenopsis littoralis; Grammatophora angulosa; Holocene; IPSO25; Licmophora gracilis; Marine Sediment Core; Melosira adeliae; Navicula directa; Navicula glaciei; Navicula imperfecta; Navicula perminuta; Nitzschia bicapitata; Nitzschia stellata; Nitzschia taeniiformis; Odontella weissflogii; Paralia sulcata; PC; Piston corer; Planothidium vicentii; Polarstern; Porosira glacialis; Porosira pseudodenticulata; Porosira spp.; Proboscia alata; Proboscia inermis; Proboscia spp.; PS97; PS97/072-1; Pseudogomphonema kamtschaticum; Pseudo-nitzschia turgiduloides; Rhizosolenia antennata forma antennata; Rhizosolenia antennata forma semispina; Rhizosolenia polydactyla forma polydactila; Rhizosolenia simplex; Rouxia constricta; Rouxia leventerae; Scotia Sea; Sea ice; Shionodiscus frenguelliopsis; Shionodiscus gracilis var. expectus; Shionodiscus gracilis var. gracilis; Shionodiscus oestrupii; Stellarima microtrias; Stephanopyxis turris; Synedra spp.; Synedropsis laevis; Synedropsis recta; Synedropsis sp.; Thalassiosira antarctica; Thalassiosira gravida; Thalassiosira lentiginosa; Thalassiosira maculata; Thalassiosira oliverana; Thalassiosira ritscheri; Thalassiosira scotia; Thalassiosira tumida; Thalassiothrix antarctica; Total; Trichotoxon reinboldii
    Materialart: Dataset
    Format: text/tab-separated-values, 7676 data points
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 7
    Publikationsdatum: 2021-05-03
    Beschreibung: 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.
    Beschreibung: This project has received funding from the European Union Horizon 2020 and Seventh Framework Programmes under grant agreement number 730960 SeaDataCloud.
    Beschreibung: Published
    Beschreibung: 611742
    Beschreibung: 4A. Oceanografia e clima
    Beschreibung: JCR Journal
    Schlagwort(e): 05.06. Methods
    Repository-Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Materialart: article
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 8
    Publikationsdatum: 2021-06-05
    Beschreibung: 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
    Materialart: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 9
    Publikationsdatum: 2022-05-25
    Beschreibung: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chemical Geology 493 (2018): 210-223, doi:10.1016/j.chemgeo.2018.05.040.
    Beschreibung: The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017. This article is part of a special issue entitled: Conway GEOTRACES - edited by Tim M. Conway, Tristan Horner, Yves Plancherel, and Aridane G. González.
    Beschreibung: We gratefully acknowledge financial support by the Scientific Committee on Oceanic Research (SCOR) through grants from the U.S. National Science Foundation, including grants OCE-0608600, OCE-0938349, OCE-1243377, and OCE-1546580. Financial support was also provided by the UK Natural Environment Research Council (NERC), the Ministry of Earth Science of India, the Centre National de Recherche Scientifique, l'Université Paul Sabatier de Toulouse, the Observatoire Midi-Pyrénées Toulouse, the Universitat Autònoma de Barcelona, the Kiel Excellence Cluster The Future Ocean, the Swedish Museum of Natural History, The University of Tokyo, The University of British Columbia, The Royal Netherlands Institute for Sea Research, the GEOMAR-Helmholtz Centre for Ocean Research Kiel, and the Alfred Wegener Institute.
    Schlagwort(e): GEOTRACES ; Trace elements ; Isotopes ; Electronic atlas ; IDP2017
    Repository-Name: Woods Hole Open Access Server
    Materialart: Article
    Standort Signatur Einschränkungen Verfügbarkeit
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