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  • PANGAEA  (36,135)
  • American Institute of Physics  (29,928)
  • American Association for the Advancement of Science (AAAS)  (10,832)
  • Cambridge University Press  (9,824)
  • American Institute of Physics (AIP)
  • Cell Press
  • 2020-2024  (35,436)
  • 1980-1984  (58,440)
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  • 1
  • 2
    Publication Date: 2024-04-11
    Description: This dataset reports measurements from a laboratory incubation of soils sourced from a boreal peatland and surrounding habitats (Siikaneva Bog, Finland). In August 2021, soil cores were collected from three habitat zones: a well-drained upland forest, an intermediate margin ecotone, and a Sphagnum moss bog. The cores from each habitat were taken from surface to approximately 50cm below surface using an Eijelkamp peat corer and subdivided by soil horizon. The samples were then incubated anaerobically for 140 days in three temperature treatment groups (0, 4, 20°C). Subsamples of the incubations headspace (250 µL) were measured on a gas chromatograph (7890A, Agilent Technologies, USA) with flame ionization detection (FID) for CO2 and CH4 concentrations. The rate of respiration from the samples were calculated per gram carbon and per gram soil as described in the method of Robertson., et al. (1999) and reported here, along with other relevant parameters.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 3
    Publication Date: 2024-03-08
    Description: The Falkland Shelf is a highly productive ecosystem in the Southwest Atlantic Ocean. It is characterized by upwelling oceanographic dynamics and displays a wasp-waist structure, with few intermediate trophic-level species and many top predators that migrate on the shelf for feeding. One of these resident intermediate trophic-level species, the Patagonian longfin-squid Doryteuthis gahi, is abundant and plays an important role in the ecosystem. We used two methods to estimate the trophic structure of the Falkland Shelf food web, focusing on the trophic niche of D. gahi and its impacts on other species and functional groups to highlight the importance of D. gahi in the ecosystem. First, stable isotope measurements served to calculate trophic levels based on an established nitrogen baseline. Second, an Ecopath model was built to corroborate trophic levels derived from stable isotopes and inform about trophic interactions of D. gahi with other functional groups. The results of both methods placed D. gahi in the centre of the ecosystem with a trophic level of ∼ 3. The Ecopath model predicted high impacts and therefore a high keystoneness for both seasonal cohorts of D. gahi. Our results show that the Falkland Shelf is not only controlled by species feeding at the top and the bottom of the trophic chain. The importance of species feeding at the third trophic level (e.g. D. gahi and Patagonotothen ramsayi) and observed architecture of energy flows confirm the ecosystem's wasp-waist structure with middle-out control mechanisms at play.
    Type: Article , PeerReviewed
    Format: text
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  • 4
    Publication Date: 2024-06-27
    Description: Non-technical summary Scenarios compatible with the Paris agreement's temperature goal of 1.5 °C involve carbon dioxide removal measures - measures that actively remove CO2 from the atmosphere - on a massive scale. Such large-scale implementations raise significant ethical problems. Van Vuuren et al. (2018), as well as the current IPCC scenarios, show that reduction in energy and or food demand could reduce the need for such activities. There is some reluctance to discuss such societal changes. However, we argue that policy measures enabling societal changes are not necessarily ethically problematic. Therefore, they should be discussed alongside techno-optimistic approaches in any kind of discussions about how to respond to climate change. Technical summary The 1.5 °C goal has given impetus to carbon dioxide removal (CDR) measures, such as bioenergy combined with carbon capture and storage, or afforestation. However, land-based CDR options compete with food production and biodiversity protection. Van Vuuren et al. (2018) looked at alternative pathways including lifestyle changes, low-population projections, or non-CO2 greenhouse gas mitigation, to reach the 1.5 °C temperature objective. Underlined by the recently published IPCC AR6 WGIII report, they show that demand-side management measures are likely to reduce the need for CDR. Yet, policy measures entailed in these scenarios could be associated with ethical problems themselves. In this paper, we therefore investigate ethical implications of four alternative pathways as proposed by Van Vuuren et al. (2018). We find that emission reduction options such as lifestyle changes and reducing population, which are typically perceived as ethically problematic, might be less so on further inspection. In contrast, options associated with less societal transformation and more techno-optimistic approaches turn out to be in need of further scrutiny. The vast majority of emission reduction options considered are not intrinsically ethically problematic; rather everything rests on the precise implementation. Explicitly addressing ethical considerations when developing, advancing, and using integrated assessment scenarios could reignite debates about previously overlooked topics and thereby support necessary societal discourse. Social media summary Policy measures enabling societal changes are not necessarily as ethically problematic as commonly presumed and reduce the need for large-scale CDR
    Type: Article , PeerReviewed
    Format: text
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  • 5
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    American Association for the Advancement of Science (AAAS)
    In:  EPIC3Science, American Association for the Advancement of Science (AAAS), 383(6685), pp. 884-890, ISSN: 0036-8075
    Publication Date: 2024-03-21
    Description: Much of our understanding of Cenozoic climate is based on the record of δ18O measured in benthic foraminifera. However, this measurement reflects a combined signal of global temperature and sea level, thus preventing a clear understanding of the interactions and feedbacks of the climate system in causing global temperature change. Our new reconstruction of temperature change over the past 4.5 million years includes two phases of long-term cooling, with the second phase of accelerated cooling during the Middle Pleistocene Transition (1.5 to 0.9 million years ago) being accompanied by a transition from dominant 41,000-year low-amplitude periodicity to dominant 100,000-year high-amplitude periodicity. Changes in the rates of long-term cooling and variability are consistent with changes in the carbon cycle driven initially by geologic processes, followed by additional changes in the Southern Ocean carbon cycle. 〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 6
    Publication Date: 2024-04-05
    Description: Seismic Rayleigh wave ellipticity measurements are the horizontal-to-vertical ratio of the Rayleigh wave particle motion, and are sensitive to the subsurface structure beneath a seismic station. H/V ratios measured from the ambient vibrations of the Earth are being increasingly used in glaciological applications to determine glacier and ice sheet thickness, seismic velocities and firn properties. Using the newly developed degree-of-polarisation (DOP-E) method which exploits the polarisation properties of seismic noise, we identify and extract Rayleigh waves from seismic stations in Greenland, and relate them to sea ice processes and the geology of the upper crust. Finally, we provide some suggestions for future applications of DOP-E method to gain greater insight into seasonal and long-term variability of sea ice formation and breakup as well as the monitoring of ice sheet thickness, subglacial environment and firn layers in the poles.
    Description: Published
    Description: 3-7
    Description: OST1 Alla ricerca dei Motori Geodinamici
    Description: JCR Journal
    Keywords: 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 7
    Publication Date: 2024-05-29
    Description: We developed a high-resolution magnetochronology of the Pleistocene stratigraphy of the Monte Netto hillock, a tectonically uplifted struc ture in the Po Plain of northern Italy. Our data allowed reconstructing the depositional age of the sequence and assessing rates of defor mation and rock uplift of the neotectonic structure, thus providing constraints on the tectono-sedimentary evolution of this seismically active part of the buried Southern Alps. Using a combination of magnetostratigraphy and paleosecular variation analysis, we generated an age-depth model for the Monte Netto stratigraphy that encompasses, from the top, Upper Pleistocene (11–72 ka) loess-paleosols over laying fluvial sediments spanning the Brunhes-Matuyama boundary (773 ka) and the top of the Jaramillo (990 ka). The identification of the same magneto-chronostratigraphic surfaces in nearby drill cores from regions of the Po Plain that have not been affected by neotectonic deformation allowed estimating a mean rate of tectonic uplift of the hillock relative to the neighboring plain of 11.3 ± 1.5 cm/ka, and an absolute uplift relative to sea level of ∼19.3 cm/ka. Finally, our paleomagnetic analyses from the uppermost loess sequence disclosed the complexity of the tectonic evolution of the Monte Netto structure, which shows evidence of a two-phase rotational deformation linked to coseismic surface faulting due to recent seismic activity.
    Description: Published
    Description: 191-205
    Description: JCR Journal
    Keywords: Magnetochronology ; Pleistocene ; Paleosecular variations ; Loess-paleosols ; Neotectonic deformation ; Po Plain
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
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    American Association for the Advancement of Science (AAAS)
    In:  EPIC3Sci Adv, American Association for the Advancement of Science (AAAS), 10(20), pp. eadl5904-eadl5904, ISSN: 2375-2548
    Publication Date: 2024-05-22
    Description: Marine heatwaves are increasing in frequency and intensity as climate change progresses, especially in the highly productive Arctic regions. Although their effects on primary producers will largely determine the impacts on ecosystem services, mechanistic understanding on phytoplankton responses to these extreme events is still very limited. We experimentally exposed Arctic phytoplankton assemblages to stable warming, as well as to repeated heatwaves, and measured temporally resolved productivity, physiology, and composition. Our results show that even extreme stable warming increases productivity, while the response to heatwaves depends on the specific scenario applied and is not predictable from stable warming responses. This appears to be largely due to the underestimated impact of the cool phase following a heatwave, which can be at least as important as the warm phase for the overall response. We show that physiological and compositional adjustments to both warm and cool phases drive overall phytoplankton productivity and need to be considered mechanistically to predict overall ecosystem impacts.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 9
    Publication Date: 2024-06-13
    Description: All Rights Reserved
    Description: Predicting coastal change depends upon our knowledge of postglacial relative sea-level variability, partly controlled by glacio-isostatic responses to ice-sheet melting. Here, we reconstruct the postglacial relative sea-level changes along the Caribbean and Pacific coasts of northwestern South America by numerically solving the sea-level equation with two scenarios of mantle viscosity: global standard average and high viscosity. Our results with the standard model (applicable to the Pacific coast) agree with earlier studies by indicating a mid-Northgrippian high stand of ~2 m. The high-viscosity simulation (relevant to the Caribbean coast) shows that the transition from far- to intermediate-field influence of the Laurentide Ice Sheet occurs between Manzanillo del Mar and the Gulf of Morrosquillo. South of this location, the Colombian Caribbean coast has exhibited a still stand with a nearly constant Holocene relative sea level. By analyzing our simulations considering sea-level indicators, we argue that tectonics is more prominent than previously assumed, especially along the Caribbean coast. This influence prevents a simplified view of regional relative sea-level changes on the northwestern South American coast.
    Description: Published
    Description: 28-43
    Description: OSA4: Ambiente marino, fascia costiera ed Oceanografia operativa
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
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    American Association for the Advancement of Science (AAAS)
    In:  EPIC3Science Advances, American Association for the Advancement of Science (AAAS), 10(23), pp. eadn6056-, ISSN: 2375-2548
    Publication Date: 2024-07-05
    Description: 〈jats:p〉Extensive ice coverage largely prevents investigations of Antarctica’s unglaciated past. Knowledge about environmental and tectonic development before large-scale glaciation, however, is important for understanding the transition into the modern icehouse world. We report geochronological and sedimentological data from a drill core from the Amundsen Sea shelf, providing insights into tectonic and topographic conditions during the Eocene (~44 to 34 million years ago), shortly before major ice sheet buildup. Our findings reveal the Eocene as a transition period from >40 million years of relative tectonic quiescence toward reactivation of the West Antarctic Rift System, coinciding with incipient volcanism, rise of the Transantarctic Mountains, and renewed sedimentation under temperate climate conditions. The recovered sediments were deposited in a coastal-estuarine swamp environment at the outlet of a >1500-km-long transcontinental river system, draining from the rising Transantarctic Mountains into the Amundsen Sea. Much of West Antarctica hence lied above sea level, but low topographic relief combined with low elevation inhibited widespread ice sheet formation.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 11
    Publication Date: 2024-01-03
    Keywords: AGE; Antarctic Circumpolar Current; Clay; DEPTH, sediment/rock; Diatoms; Giant piston corer (Calypso); GPC-C; Grain size, Mastersizer S, Malvern Instrument Inc.; magnetic parameters; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Silt; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 498 data points
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  • 12
    Publication Date: 2024-01-03
    Keywords: AGE; Anhysteretic susceptibility/magnetic susceptibility; Antarctic Circumpolar Current; Cryogenic magnetometer, 2G Enterprises; DEPTH, sediment/rock; Giant piston corer (Calypso); GPC-C; magnetic parameters; Magnetic susceptibility; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 320 data points
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  • 13
    Publication Date: 2024-01-03
    Keywords: AGE; Antarctic Circumpolar Current; calculated, 1 sigma; DEPTH, sediment/rock; Giant piston corer (Calypso); GPC-C; magnetic parameters; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Reconstructed from the percentage of Neogloboquadrina pachyderma sinistral; Reconstructed from the percentage of planktic foraminifera; Sea surface temperature, summer; Sea surface temperature, summer, standard deviation; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 186 data points
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  • 14
    Publication Date: 2024-02-02
    Description: The onset of the first sustained Antarctic glaciation at the Eocene-Oligocene Transition (~34 Ma; EOT) was marked by several changes in calcareous nannofossils coinciding with long-term cooling and modifications in the sea-surface water structure. Here, we combined a high-resolution calcareous nannofossil assemblage data (%) with bulk geochemical data from IODP Site U1509 (New Caledonia Trough, Tasman Sea) in order to give an overview of the paleoclimatic and palaeoceanographic evolution of the study area.
    Keywords: 371-U1509A; Calcareous nannofossils; Calcium carbonate; DEPTH, sediment/rock; DSDP/ODP/IODP sample designation; Eocene-Oligocene Transition.; Exp371; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; IODP Depth Scale Terminology; Isotope ratio mass spectrometry; Joides Resolution; Sample code/label; Tasman Frontier Subduction Initiation and Paleogene Climate; Tasman Sea; δ13C, carbonate; δ18O, carbonate
    Type: Dataset
    Format: text/tab-separated-values, 732 data points
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  • 15
    Publication Date: 2024-02-01
    Description: Marine heat flow data from RV Meteor cruise M186. The GEOMAR project name is Azores Hot Vents. We used the 6 m Bremen heat probe with 21 channels @ 0.26 m spacing.
    Keywords: Azores; Center for Marine Environmental Sciences; heatflow; MARUM
    Type: Dataset
    Format: application/zip, 10 datasets
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  • 16
    Publication Date: 2024-03-01
    Description: This data set contains airborne gravity data across central Dronning Maud Land, East Antarctica, acquired during the austral summer of 2009/2010 and within the project 'West-East Gondwana Amalgamation and its Separation' (WEGAS). The data span the offshore Astrid Ridge, and parts of the Nivl and Lazarev ice shelves. The survey was conducted using a ZLS Ultrasys Lacoste & Romberg Air/Sea gravimeter S56 installed into - and operated with - the research aircraft Polar 5. Base readings were performed with a handheld gravity meter at the base station Novolazarevskaja and in Cape Town. A ground speed of 130 knots and a time-domain filter of 220 s leads to a spatial resolution of around 7 km. The average crossover error after bias adjustment is 4.2 mGal. When citing this data set, please also cite the associated manuscript: Eisermann, H., Eagles, G. & Jokat, W. Coastal bathymetry in central Dronning Maud Land controls ice shelf stability. Sci Rep 14, 1367 (2024). https://doi.org/10.1038/s41598-024-51882-2.
    Keywords: AC; airborne gravity; Aircraft; Antarctica; Antarctica, East; Astrid Ridge; DATE/TIME; Event label; Free-air gravity anomaly; Gravity; Height; LATITUDE; Lazarev Ice Shelf; Line; LONGITUDE; Nivl Ice Shelf; PGM17 (NGA's Preliminary Geopotential Model 2017); POLAR 5; WEGAS_2009/10; WEGAS_2009/10_02; WEGAS_2009/10_03; WEGAS_2009/10_04; WEGAS_2009/10_05; WEGAS_2009/10_06; WEGAS_2009/10_07; WEGAS_2009/10_08; WEGAS_2009/10_09; WEGAS_2009/10_10; WEGAS_2009/10_11; WEGAS_2009/10_12; WEGAS_2009/10_13; WEGAS_2009/10_14; WEGAS_2009/10_16; WEGAS_2009/10_17; WEGAS_2009/10_18; WEGAS_2009/10_19; WEGAS_2009/10_20; WEGAS_2009/10_21; WEGAS offshore
    Type: Dataset
    Format: text/tab-separated-values, 128088 data points
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  • 17
    Publication Date: 2024-03-01
    Description: Attached data comprise a bathymetric model of central Dronning Maud Land, including the seabed beneath the Nivl Ice Shelf and the Lazarev Ice Shelf, as well as the offshore Astrid Ridge and adjacent parts of the Riiser-Larsen Sea. Here, this model is embedded within the larger Antarctic-wide bathymetric compilation IBCSOV2 (Dorschel et al., 2022). This is an addition to the stand-alone bathymetric model here: https://doi.org/10.1594/PANGAEA.961492. The embedded model gives seabed depths relative to WGS84 at a resolution of 2.5 km. It is generated by complementing existing topographic data sets - such as seismic data, ice penetrating radar data, and shipborne hydroacoustic data - with the inversion of airborne gravity data towards bathymetry. The airborne gravity data used for the inversion consist of data acquired during aerogeophysical campaigns VISA from the early 2000s and WEGAS from the austral summer of 2009/2010. When citing this model, please also cite the associated manuscript: Eisermann, H., Eagles, G. & Jokat, W. Coastal bathymetry in central Dronning Maud Land controls ice shelf stability. Sci Rep 14, 1367 (2024). https://doi.org/10.1038/s41598-024-51882-2.
    Keywords: Antarctica; Bathymetry; BathymetryModel_cDronningMaudLan; Bed elevation; Coordinate, x, relative; Coordinate, y, relative; Dronning Maud Land; Dronning Maud Land, Antarctica; gravity inversion; LATITUDE; Lazarev Ice Shelf; LONGITUDE; Model; Nivl Ice Shelf; water column
    Type: Dataset
    Format: text/tab-separated-values, 206742 data points
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  • 18
    Publication Date: 2024-03-05
    Keywords: 138-846B; 138-846C; AGE; Alkenone; Aluminium oxide; Barium sulfate; Calcium carbonate; Calibrated after Weltje & Tjallingi (2008); Date/Time of event; Depth, composite; DRILL; Drilling/drill rig; Eastern Equatorial Pacific; Event label; Iron oxide, Fe2O3; Joides Resolution; Latitude of event; Leg138; Longitude of event; Manganese oxide; ODP Site 846; Sample code/label; Sea surface temperature; Silicon dioxide; South Pacific Ocean; Titanium dioxide
    Type: Dataset
    Format: text/tab-separated-values, 75384 data points
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  • 19
    Publication Date: 2024-03-05
    Keywords: 138-846; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Joides Resolution; Leg138; ODP Site 846; Sea surface temperature; South Pacific Ocean
    Type: Dataset
    Format: text/tab-separated-values, 1056 data points
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  • 20
    Publication Date: 2024-03-05
    Keywords: 138-849; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Joides Resolution; Leg138; North Pacific Ocean; ODP Site 846; Sea surface temperature
    Type: Dataset
    Format: text/tab-separated-values, 388 data points
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  • 21
    Publication Date: 2024-03-05
    Keywords: 321-U1338; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Exp321; Joides Resolution; ODP Site 846; Pacific Equatorial Age Transect II / Juan de Fuca; Sea surface temperature
    Type: Dataset
    Format: text/tab-separated-values, 422 data points
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  • 22
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 22236 data points
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  • 23
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 257782 data points
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  • 24
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 25033 data points
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  • 25
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23254 data points
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  • 26
    Publication Date: 2024-02-29
    Description: Dinoflagellate cysts have been determined in sediments of core DP30PC on a resolution of 1 sample per 2.5 mm core depth (representing approximately 3 year) and 119.65 - 180.4 cm core depth. These data form the basis of high temporal resolution temperature and precipitation reconstructions for Roman times between about 200 BCE and 600 CE (ca. 205 BCE - 605 CE).
    Keywords: 64PE297; Age; Ataxiodinium choane; Bitectatodinium tepikiense; Center for Marine Environmental Sciences; Counting, dinoflagellate cysts; DEPTH, sediment/rock; Dinoflagellate cyst, other; Dinoflagellate cyst, warm water/cold water, ratio; Dinoflagellate cyst reworked; Discharge index; DP30PC; elements; Impagidinium aculeatum; Impagidinium paradoxum; Impagidinium patulum; Impagidinium plicatum; Impagidinium sphaericum; Impagidinium strialatum; Lingulodinium polyedrum; MARUM; Mediterranean; Nematosphaeropsis labyrinthus; Operculodinium israelianum; PC; Pelagia; Piston corer; Polysphaeridium zoharyi; Pseudoschizea spp.; Pyxidinopsis reticulata; Roman Climate Optimum; Spiniferites elongatus; Spiniferites mirabilis; Spiniferites ramosus; Tectatodinium pellitum; Temperature, water; Tuberculodinium vancampoae; volcanic glass shards
    Type: Dataset
    Format: text/tab-separated-values, 6092 data points
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  • 27
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 27270 data points
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  • 28
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 29012 data points
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  • 29
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 267840 data points
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  • 30
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 24245 data points
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  • 31
    Publication Date: 2024-03-12
    Keywords: Aluminium oxide; Ardmore; Area/locality; Barium oxide; Barr_Creek; Calcium oxide; Cerium; Chromium(III) oxide; Depth, description; DEPTH, sediment/rock; DTREE; Duchess; Dysprosium; Erbium; Europium; Event label; Gadolinium; Georgina Basin; Hole; Holmium; Iron oxide, Fe2O3; Lanthanum; Laser Ablation; LATITUDE; Lily_Creek; LONGITUDE; Loss on ignition; Lutetium; Magnesium oxide; Manganese oxide; Neodymium; Paradise_North; Paradise_South; Phosphate_Hill; Phosphorite; Phosphorus pentoxide; Potassium oxide; Praseodymium; Rare-earth elements; ROCK; Rock sample; Samarium; Sample code/label; Sherrin_Creek; Silicon dioxide; Sodium oxide; Strontium oxide; Terbium; Thorium; Thulium; Titanium dioxide; Total; Uranium; Whole rock geochemistry; Ytterbium; Yttrium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 1327 data points
    Location Call Number Expected Availability
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  • 32
    Publication Date: 2024-03-12
    Keywords: Aluminium; Aluminium oxide; Barium; Barium oxide; Calcium; Calcium oxide; Cerium; Cerium oxid; Chlorine; Date of determination; Electron micro probe analyser (EMPA); Fluorine; Gadolinium; Gadolinium oxide; Georgina Basin; Iron; Iron oxide, Fe2O3; Lanthanum; Lanthanum oxide; Laser Ablation; LATITUDE; LONGITUDE; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Mineral name; Neodymium; Neodymium oxid; Oxygen; Phosphorite; Phosphorus; Phosphorus pentoxide; Sample ID; Silicon; Silicon dioxide; Site; Sodium; Sodium oxide; Strontium; Strontium oxide; Sulfur; Sulfur trioxide; Total; Whole rock geochemistry; Yttrium; Yttrium oxide
    Type: Dataset
    Format: text/tab-separated-values, 1764 data points
    Location Call Number Expected Availability
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  • 33
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-12
    Description: We continuously measured aerosol size distributions in the range between 18 nm and 820 nm in 64 bit per decade resolution by means of a Scanning Mobility Particle Sizer (SMPS, TSI, i.e. a Series 3080 Electrostatic Classifier equipped with a Differential Mobility Analyzer DMA 3081). The measurements were conducted at the Air Chemistry Observatory (SPUSO) at Neumayer III Station (Antarctica) between 4 August 2023 and 31 December 2023. The data are based on an original 10-minute temporal resolution, submitted as 60-minute averages. Aerosol size distribution measurements are part of the air chemistry long-term observations at Neumayer III. Details about the instrument can be found under "resources" of the corresponding metadata link: https://hdl.handle.net/10013/sensor.81ece554-068a-4c6e-8de5-1ef1944c0156
    Keywords: aerosol; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; AWI_Glac; DATE/TIME; Date/time end; Dronning Maud Land, Antarctica; Glaciology @ AWI; HEIGHT above ground; Log-normal particle size distribution, normalized concentration at particle diameter 101.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 105.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 109.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 113.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 117.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 121.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 126.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 131 nm; Log-normal particle size distribution, normalized concentration at particle diameter 135.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 140.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 145.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 151.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 156.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 162.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 168.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 174.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 18.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 18.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 181.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 187.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 19.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 194.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 20.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 20.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 201.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 209.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 21.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 216.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 22.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 224.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 23.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 232.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 24.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 241.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 250.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 259.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25 nm; Log-normal particle size distribution, normalized concentration at particle diameter 26.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 269 nm; Log-normal particle size distribution, normalized concentration at particle diameter 27.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 278.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 28.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 289 nm; Log-normal particle size distribution, normalized concentration at particle diameter 299.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 30 nm; Log-normal particle size distribution, normalized concentration at particle diameter 31.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 310.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 32.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 322 nm; Log-normal particle size distribution, normalized concentration at particle diameter 33.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 333.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 34.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 346 nm; Log-normal particle size distribution, normalized concentration at particle diameter 35.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 358.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 37.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 371.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 38.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 385.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 399.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 40 nm; Log-normal particle size distribution, normalized concentration at particle diameter 41.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 414.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 42.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 429.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 44.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 445.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 46.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 461.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 47.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 478.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 49.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 495.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 51.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 514 nm; Log-normal particle size distribution, normalized concentration at particle diameter 53.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 532.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 55.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 552.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 57.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 572.5 nm; Log-normal particle size distribution, normalized
    Type: Dataset
    Format: text/tab-separated-values, 385097 data points
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  • 34
    Publication Date: 2024-03-12
    Keywords: Aluminium; Aluminium oxide; Antimony; Ardmore; Area/locality; Arsenic; Barium; Barr_Creek; Beryllium; Bismuth; Boron; Cadmium; Caesium; Calcium; Calcium oxide; Cerium; Chromium; Cobalt; Copper; DTREE; Duchess; Dysprosium; Erbium; Europium; Gadolinium; Georgina Basin; Hafnium; Holmium; Inductively coupled plasma - mass spectrometry (ICP-MS); Iron; Iron oxide, Fe2O3; Lanthanum; Laser Ablation; LATITUDE; Lead-208; Lily_Creek; Lithium; Lithium borate fusion; acid digestion; LONGITUDE; Lutetium; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Molybdenum; Neodymium; Nickel; Niobium; Paradise_North; Paradise_South; Phosphate_Hill; Phosphorite; Phosphorus; Phosphorus pentoxide; Potassium; Potassium oxide; Praseodymium; Rhenium; ROCK; Rock sample; Rock type; Rubidium; Samarium; Sample ID; Scandium; Sherrin_Creek; Silicon; Silicon dioxide; Sodium; Sodium oxide; Strontium; Tantalum; Tellurium; Terbium; Thallium; Thorium; Thulium; Tin; Titanium; Titanium dioxide; Total; Uranium; Vanadium; Whole rock geochemistry; Ytterbium; Yttrium; Zinc; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 837 data points
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  • 35
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-09
    Description: We operate a multi angle absorption photometer MAAP (Model 5012, Thermo Electron Corp.). which is in operation since March 2006 ongoing. This instrument measures atmospheric light absorption by aerosol (mainly caused by black carbon, BC). To this end, ambient aerosol was sampled on a glass filter tape. The measured absorption coefficients abs(637) refer to a wavelength of 637 nm. Raw data were originally sampled in one-minute resolution. Finally, hourly averaged MAAP data are presented here. We also provide BC concentrations (ng/m³) derived from the absorption coefficients using the specific BC attenuation cross section (QBC) of 6.6 m²/g.
    Keywords: aerosol; Aerosol absorption at 637 nm; AIRCHEM; Air chemistry observatory; Atmospheric chemistry; Atmospheric Chemistry @ AWI; AWI_AC; Black carbon, aerosol; DATE/TIME; Dronning Maud Land, Antarctica; Duration; HEIGHT above ground; Multi angle absorption spectrometer MAAP5012; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; Spuso; SPUSO
    Type: Dataset
    Format: text/tab-separated-values, 26274 data points
    Location Call Number Expected Availability
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  • 36
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-09
    Description: We continuously measured aerosol size distributions in the range between 90 nm and 5000 nm in 64 bit resolution with an optical particle sizer (TSI LAS3340). The measurements were conducted at the Air Chemistry Observatory (SPUSO) at Neumayer III Station (Antarctica) between 1 January 2023 and 10 July 2023. The data rely on an original 10-minute temporal resolution and are finally submitted as 60-minute averages. Aerosol size distribution measurements are part of the air chemistry long-term observations at Neumayer III. Details about the instrument can be found under "resources" of the corresponding metadata link: https://hdl.handle.net/10013/sensor.5d9a9253-e118-4744-be3a-05f31551314a.
    Keywords: aerosol; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; AWI_Glac; DATE/TIME; Date/time end; Dronning Maud Land, Antarctica; Glaciology @ AWI; HEIGHT above ground; las3340; Laser Aerosol Spectrometer TSI LAS3340; Log-normal particle size distribution, normalized concentration at particle diameter 1008.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 105.29 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1074.15 nm; Log-normal particle size distribution, normalized concentration at particle diameter 112.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1143.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 119.38 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1217.84 nm; Log-normal particle size distribution, normalized concentration at particle diameter 127.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1296.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 135.34 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1380.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 144.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1470.19 nm; Log-normal particle size distribution, normalized concentration at particle diameter 153.45 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1565.43 nm; Log-normal particle size distribution, normalized concentration at particle diameter 163.39 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1666.85 nm; Log-normal particle size distribution, normalized concentration at particle diameter 173.97 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1774.83 nm; Log-normal particle size distribution, normalized concentration at particle diameter 185.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1889.81 nm; Log-normal particle size distribution, normalized concentration at particle diameter 197.25 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2012.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 210.03 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2142.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 223.63 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2281.41 nm; Log-normal particle size distribution, normalized concentration at particle diameter 238.12 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2429.21 nm; Log-normal particle size distribution, normalized concentration at particle diameter 253.55 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2586.58 nm; Log-normal particle size distribution, normalized concentration at particle diameter 269.97 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2754.15 nm; Log-normal particle size distribution, normalized concentration at particle diameter 287.46 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2932.57 nm; Log-normal particle size distribution, normalized concentration at particle diameter 306.08 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3122.55 nm; Log-normal particle size distribution, normalized concentration at particle diameter 325.91 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3324.84 nm; Log-normal particle size distribution, normalized concentration at particle diameter 347.02 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3540.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 369.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3769.59 nm; Log-normal particle size distribution, normalized concentration at particle diameter 393.45 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4013.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 418.93 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4273.82 nm; Log-normal particle size distribution, normalized concentration at particle diameter 446.08 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4550.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 474.98 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4845.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 505.75 nm; Log-normal particle size distribution, normalized concentration at particle diameter 538.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 573.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 610.54 nm; Log-normal particle size distribution, normalized concentration at particle diameter 650.09 nm; Log-normal particle size distribution, normalized concentration at particle diameter 692.21 nm; Log-normal particle size distribution, normalized concentration at particle diameter 737.05 nm; Log-normal particle size distribution, normalized concentration at particle diameter 784.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 835.64 nm; Log-normal particle size distribution, normalized concentration at particle diameter 889.78 nm; Log-normal particle size distribution, normalized concentration at particle diameter 92.87 nm; Log-normal particle size distribution, normalized concentration at particle diameter 947.42 nm; Log-normal particle size distribution, normalized concentration at particle diameter 98.89 nm; Neumayer; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; size distribution; Spuso; SPUSO; Time in minutes
    Type: Dataset
    Format: text/tab-separated-values, 300234 data points
    Location Call Number Expected Availability
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  • 37
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    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-12
    Description: We operate a 7-wavelength aethalometer (Model AE33, Magee Scientific) which is in operation since 23 January 2019 ongoing. The Aethalometer model AE33 collects aerosol particles continuously by drawing the aerosol-laden air stream through a spot on the filter tape. It analyzes the aerosol by measuring the transmission of light through one portion of the filter tape containing the sample, versus the transmission through an unloaded portion of the filter tape acting as a reference area. This analysis is done at seven optical wavelengths spanning the range from the near-infrared to the near-ultraviolet. The Aethalometer calculates the instantaneous concentration of optically-absorbing aerosols from the rate of change of the attenuation of light transmitted through the particle-laden filter.
    Keywords: aerosol; Aerosol absorption at 370 nm; Aerosol absorption at 470 nm; Aerosol absorption at 520 nm; Aerosol absorption at 590 nm; Aerosol absorption at 660 nm; Aerosol absorption at 880 nm; Aerosol absorption at 950 nm; aerosol absorption coefficient; Aethalometer, AE33, Magee Scientific; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; DATE/TIME; Dronning Maud Land, Antarctica; Duration; HEIGHT above ground; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; Neumayer Station; Spuso; SPUSO
    Type: Dataset
    Format: text/tab-separated-values, 131400 data points
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  • 38
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Code; DATE/TIME; Dew/frost point; Germany; HYGRO; Hygrometer; LIN; Lindenberg; Monitoring station; MONS; Past weather1; Past weather2; Present weather; Pressure, atmospheric; Station pressure; Temperature, air; Thermometer; Total cloud amount; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 6265 data points
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  • 39
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: Baseline Surface Radiation Network; BSRN; Cloud base height; DATE/TIME; Germany; LIN; Lindenberg; Monitoring station; MONS
    Type: Dataset
    Format: text/tab-separated-values, 3422 data points
    Location Call Number Expected Availability
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  • 40
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; DATE/TIME; Dew/frost point; Germany; LIN; Lindenberg; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Vaisala, RS41; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 782989 data points
    Location Call Number Expected Availability
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  • 41
    facet.materialart.
    Unknown
    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-03-08
    Keywords: Baseline Surface Radiation Network; BSRN; DATE/TIME; IZA; Izaña; Monitoring station; MONS; Ozone total; Tenerife, Spain
    Type: Dataset
    Format: text/tab-separated-values, 1663 data points
    Location Call Number Expected Availability
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  • 42
    facet.materialart.
    Unknown
    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-03-08
    Keywords: Baseline Surface Radiation Network; BSRN; DATE/TIME; HEIGHT above ground; IZA; Izaña; Monitoring station; MONS; Tenerife, Spain; Ultraviolet-a global; Ultraviolet-a global, maximum; Ultraviolet-a global, minimum; Ultraviolet-a global, standard deviation; Ultraviolet-b global; Ultraviolet-b global, maximum; Ultraviolet-b global, minimum; Ultraviolet-b global, standard deviation; UV-Radiometer, Kipp & Zonen, UVB1, SN 970839, WRMC No. 61007; UV-Radiometer, Kipp & Zonen, UV-S-A-T, SN 080005, WRMC No. 61006
    Type: Dataset
    Format: text/tab-separated-values, 356432 data points
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  • 43
    facet.materialart.
    Unknown
    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-03-08
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; DATE/TIME; Dew/frost point; IZA; Izaña; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Vaisala, RS92; Temperature, air; Tenerife, Spain; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 1318328 data points
    Location Call Number Expected Availability
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  • 44
    facet.materialart.
    Unknown
    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-03-08
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Code; DATE/TIME; Dew/frost point; Geopotential of a standard isobaric surface; High cloud; HYGRO; Hygrometer; IZA; Izaña; Low/middle cloud amount; Low cloud; Middle cloud; Monitoring station; MONS; Past weather1; Past weather2; Present weather; Station pressure; Temperature, air; Tenerife, Spain; Thermometer; Total cloud amount; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 996 data points
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  • 45
    Publication Date: 2024-02-27
    Description: This data set includes biogeochemical proxy data analysed on sediment core TAN1106-28 in 2021 at the University of Tasmania, The Australian Nuclear Science and Technology Organisation, National Taiwan University, and the University of Southampton. This sediment core was collected in 2011 by the RV Tangaroa, in the Solander Trough, south of New Zealand (-48.372°S, 165.659°E). The data spans from 71–0 ka, and is comprised of sea surface temperatures, thorium normalised fluxes of iron, lithogenic material, total organic carbon, chlorins, CaCO3, and excess barium, as well as formanifera-bound nitrogen isotopic compositions, authigenic uranium and excess manganese concentrations, and Benthic-Planktic 14C offsets (yrs).
    Keywords: biogeochemistry; dust; Export Production; iron fertilization; Millennial scale variability; Southern Ocean; SST
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 46
    Publication Date: 2024-02-27
    Description: Current velocities of the upper water column along the cruise track of R/V Maria S. Merian cruise MSM112/1 were collected by a vessel-mounted 75 kHz RDI Ocean Surveyor ADCP. The ADCP transducer was located at 6.0 m below the water line. The instrument was operated in narrowband mode (WM10) with a bin size of 8.00 m, a blanking distance of 8.00 m, and a total of 100 bins, covering the depth range between 22.0 m and 814.0 m. Heading, pitch and roll data from the ship's motion reference unit and the navigation data from the Global Positioning systems were used by the data acquisition software VmDAS internally to convert ADCP velocities into earth coordinates. Single-ping data were screened for bottom signals and, where appropriate, a bottom mask was manually processed. The ship's velocity was calculated from position fixes obtained by the Global Positioning System (GPS). Accuracy of the ADCP velocities mainly depends on the quality of the position fixes and the ship's heading data. Further errors stem from a misalignment of the transducer with the ship's centerline. Data post-processing included water track calibration of the misalignment angle (-47.4056° +/- 0.6284°) and scale factor (1.0037 +/- 0.0102) of the Ocean Surveyor signal. The velocity data were averaged in time using an average interval of 60 s. Velocity quality flagging is based on different threshold criteria: Depth cells with ensemble-averaged percent-good values below 25% are marked as 'bad data'. Depth cells with velocities above 2.0 m/s are flagged as 'bad data'. Depth cells with a root-mean-square deviation between the measured ensemble-average velocity and a cell-wise running-mean velocity above 0.5 m/s are flagged as 'probably bad data'.
    Keywords: Current velocity, east-west; Current velocity, north-south; DAM_Underway; DAM Underway Research Data; DATE/TIME; DEPTH, water; Echo intensity, relative; LATITUDE; LONGITUDE; Maria S. Merian; MSM112; MSM112_0_Underway-3; Pings, averaged to a double ensemble value; Quality flag, current velocity; RM ROFI; Seadatanet flag: Data quality control procedures according to SeaDataNet (2010); Vessel mounted Acoustic Doppler Current Profiler [75 kHz]; VMADCP-75
    Type: Dataset
    Format: text/tab-separated-values, 4385480 data points
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  • 47
    facet.materialart.
    Unknown
    PANGAEA
    In:  Instituto de Geofísica, Universidad Nacional Autónoma De México
    Publication Date: 2024-02-27
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Mexico; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP22, SN 160484, WRMC No. 83003; Pyranometer, Kipp & Zonen, CMP22, SN 160486, WRMC No. 83001; Pyrgeometer, Kipp & Zonen, CGR4, SN 140084, WRMC No. 83004; Pyrheliometer, Kipp & Zonen, CHP 1, SN 140189, WRMC No. 83002; SEL; Selegua, Mexico Solarimetric Station; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Thermometer; UV-Biometer, Solar Light 501A, SN 19489, WRMC No. 83007
    Type: Dataset
    Format: text/tab-separated-values, 1202633 data points
    Location Call Number Expected Availability
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  • 48
    facet.materialart.
    Unknown
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Publication Date: 2024-02-21
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; DATE/TIME; Dew/frost point; Japan; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Meisei, iMS; TAT; Tateno; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 32168 data points
    Location Call Number Expected Availability
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  • 49
    facet.materialart.
    Unknown
    PANGAEA
    In:  GeoSphere Austria
    Publication Date: 2024-02-23
    Keywords: Amount of cloud layer 1; Amount of cloud layer 2; Amount of cloud layer 3; Anemometer; Austria; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cloud base height code, layer 1; Cloud base height code, layer 2; Cloud layer 1; Cloud layer 2; Cloud layer 3; Code; DATE/TIME; Dew/frost point; High cloud; HYGRO; Hygrometer; Low/middle cloud amount; Low cloud; Middle cloud; Monitoring station; MONS; Past weather1; Past weather2; Present weather; SON; Sonnblick; Station pressure; Temperature, air; Thermometer; Total cloud amount; Visibility sensor; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 5511 data points
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  • 50
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    PANGAEA
    In:  GeoSphere Austria
    Publication Date: 2024-02-23
    Keywords: Amount of cloud layer 1; Amount of cloud layer 2; Amount of cloud layer 3; Anemometer; Austria; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cloud base height code, layer 1; Cloud base height code, layer 2; Cloud base height code, layer 3; Cloud layer 1; Cloud layer 2; Cloud layer 3; Code; DATE/TIME; Dew/frost point; High cloud; HYGRO; Hygrometer; Low/middle cloud amount; Low cloud; Middle cloud; Monitoring station; MONS; Past weather1; Past weather2; Present weather; SON; Sonnblick; Station pressure; Temperature, air; Thermometer; Total cloud amount; Visibility sensor; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 5214 data points
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  • 51
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    PANGAEA
    In:  GeoSphere Austria
    Publication Date: 2024-02-23
    Keywords: Air temperature at 2 m height; Austria; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Hukseflux, SR30, SN 2302, WRMC No. 75040; Pyranometer, Hukseflux, SR30, SN 6355, WRMC No. 75039; Pyrgeometer, Kipp & Zonen, CGR4, SN 100175, WRMC No. 75041; Pyrheliometer, Hukseflux, DR02-T2-10, SN 9119, WRMC No. 75038; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; SON; Sonnblick; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 832913 data points
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  • 52
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    PANGAEA
    In:  GeoSphere Austria
    Publication Date: 2024-02-23
    Keywords: Amount of cloud layer 1; Amount of cloud layer 2; Amount of cloud layer 3; Anemometer; Austria; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cloud base height code, layer 1; Cloud base height code, layer 2; Cloud base height code, layer 3; Cloud layer 1; Cloud layer 2; Cloud layer 3; Code; DATE/TIME; Dew/frost point; High cloud; HYGRO; Hygrometer; Low/middle cloud amount; Low cloud; Middle cloud; Monitoring station; MONS; Past weather1; Past weather2; Present weather; SON; Sonnblick; Station pressure; Temperature, air; Thermometer; Total cloud amount; Visibility sensor; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 5666 data points
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  • 53
    Publication Date: 2024-02-29
    Description: Concentrations of volcanic glass shards of the sediment size fraction between 45 - 100 micrometer of sediments of core DP30PC (southeastern Gulf of Taranto) have been determined by polar light microscopy. Based on these results the positions of cryptotephras can be determined. This forms the basis for the establishment of the tephra-chronologic age model of core DP30PC that is based on the elemental analysis of selected shards from these crypto-tephra.
    Keywords: 64PE297; Age; Age, tephra-chronostratigraphy; Center for Marine Environmental Sciences; DEPTH, sediment/rock; DP30PC; elements; MARUM; Mediterranean; PC; Pelagia; Piston corer; Polarisation microscopy; Roman Climate Optimum; Volcanic glass; volcanic glass shards
    Type: Dataset
    Format: text/tab-separated-values, 699 data points
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  • 54
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    PANGAEA
    In:  National Meteorological Office of Algeria
    Publication Date: 2024-02-29
    Keywords: Algeria; ALTITUDE; Baseline Surface Radiation Network; BSRN; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Vaisala, RS92; TAM; Tamanrasset; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 3650 data points
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  • 55
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 259082 data points
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  • 56
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 253409 data points
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  • 57
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 264341 data points
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  • 58
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Meisei, iMS; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 24497 data points
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  • 59
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Meisei, iMS; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23263 data points
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  • 60
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Meisei, iMS; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 22391 data points
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  • 61
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    PANGAEA
    In:  National Meteorological Office of Algeria
    Publication Date: 2024-02-29
    Keywords: Algeria; Amount of cloud layer 1; Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cloud base height code, layer 1; Cloud layer 1; Code; DATE/TIME; Dew/frost point; High cloud; HYGRO; Hygrometer; Low/middle cloud amount; Low cloud; Middle cloud; Monitoring station; MONS; Past weather1; Past weather2; Present weather; Station pressure; TAM; Tamanrasset; Temperature, air; Thermometer; Total cloud amount; Visibility sensor; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 3943 data points
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  • 62
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 263041 data points
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  • 63
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    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23112 data points
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  • 64
    Publication Date: 2024-02-29
    Description: Here we present annual linear extension rates of modern Porites corals recovered at Tahiti that grew between 1996 and 2008.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; Extension rate; IODP; MARUM; Sampling by diver; Sr/Ca; Tahiti; TIAREI-A1
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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  • 65
    Publication Date: 2024-02-29
    Description: Here we present annual linear extension rates of modern Porites corals recovered at Tahiti that grew between 1996 and 2008.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; Extension rate; IODP; MARAA-7; MARUM; Sampling by diver; Sr/Ca; Tahiti
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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  • 66
    Publication Date: 2024-02-29
    Description: Here we present annual linear extension rates of modern Porites corals recovered at Tahiti that grew between 1996 and 2008.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; Extension rate; IODP; MARAA-8; MARUM; Sampling by diver; Sr/Ca; Tahiti
    Type: Dataset
    Format: text/tab-separated-values, 4 data points
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  • 67
    Publication Date: 2024-02-29
    Description: Here we present annual linear extension rates of modern Porites corals recovered at Tahiti that grew between 1996 and 2008.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; Extension rate; IODP; MARUM; Sampling by diver; Sr/Ca; Tahiti; TIAREI-3B
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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  • 68
    Publication Date: 2024-02-29
    Description: Here we present annual linear extension rates of modern Porites corals recovered at Tahiti that grew between 1996 and 2008.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; Extension rate; IODP; MARUM; Sampling by diver; Sr/Ca; Tahiti; TIAREI-4
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 69
    Publication Date: 2024-02-29
    Description: Here we present monthly resolved geochemical proxy data (Sr/Ca, Mg/Ca, δ18O, δ13C) extracted along the growth axes of Porites modern corals ecovered at Tahiti that grew between 1996 and 2008 and serve as a modern-day benchmark.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; ICP-OES (Agilent 720); IODP; MARUM; Mass spectrometer Finnigan MAT 251; Porites sp., Magnesium/Calcium ratio; Porites sp., Strontium/Calcium ratio; Porites sp., δ13C; Porites sp., δ18O; Sampling by diver; Sr/Ca; Tahiti; TIAREI-A1
    Type: Dataset
    Format: text/tab-separated-values, 480 data points
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  • 70
    Publication Date: 2024-02-29
    Description: Here we present monthly resolved geochemical proxy data (Sr/Ca, Mg/Ca, δ18O, δ13C) extracted along the growth axes of Porites modern corals ecovered at Tahiti that grew between 1996 and 2008 and serve as a modern-day benchmark.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; ICP-OES (Agilent 720); IODP; MARUM; Mass spectrometer Finnigan MAT 251; Porites sp., Magnesium/Calcium ratio; Porites sp., Strontium/Calcium ratio; Porites sp., δ13C; Porites sp., δ18O; Sampling by diver; Sr/Ca; Tahiti; TIAREI-3B
    Type: Dataset
    Format: text/tab-separated-values, 455 data points
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  • 71
    Publication Date: 2024-02-29
    Description: Here we present monthly resolved geochemical proxy data (Sr/Ca, Mg/Ca, δ18O, δ13C) extracted along the growth axes of Porites modern corals ecovered at Tahiti that grew between 1996 and 2008 and serve as a modern-day benchmark.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; ICP-OES (Agilent 720); IODP; MARAA-8; MARUM; Mass spectrometer Finnigan MAT 251; Porites sp., Magnesium/Calcium ratio; Porites sp., Strontium/Calcium ratio; Porites sp., δ13C; Porites sp., δ18O; Sampling by diver; Sr/Ca; Tahiti
    Type: Dataset
    Format: text/tab-separated-values, 155 data points
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  • 72
    Publication Date: 2024-02-29
    Description: Here we present monthly resolved geochemical proxy data (Sr/Ca, Mg/Ca, δ18O, δ13C) extracted along the growth axes of Porites modern corals ecovered at Tahiti that grew between 1996 and 2008 and serve as a modern-day benchmark.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; ICP-OES (Agilent 720); IODP; MARAA-7; MARUM; Mass spectrometer Finnigan MAT 251; Porites sp., Magnesium/Calcium ratio; Porites sp., Strontium/Calcium ratio; Porites sp., δ13C; Porites sp., δ18O; Sampling by diver; Sr/Ca; Tahiti
    Type: Dataset
    Format: text/tab-separated-values, 480 data points
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  • 73
    Publication Date: 2024-02-29
    Description: Here we present monthly resolved geochemical proxy data (Sr/Ca, Mg/Ca, δ18O, δ13C) extracted along the growth axes of Porites modern corals ecovered at Tahiti that grew between 1996 and 2008 and serve as a modern-day benchmark.
    Keywords: Age; AGE; Center for Marine Environmental Sciences; Coral; d13C; d18O; DIVER; ICP-OES (Agilent 720); IODP; MARUM; Mass spectrometer Finnigan MAT 251; Porites sp., Magnesium/Calcium ratio; Porites sp., Strontium/Calcium ratio; Porites sp., δ13C; Porites sp., δ18O; Sampling by diver; Sr/Ca; Tahiti; TIAREI-4
    Type: Dataset
    Format: text/tab-separated-values, 395 data points
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  • 74
    Publication Date: 2024-02-27
    Description: We conducted a study on the Late Miocene-Early Pliocene Biogenic Bloom, a phase of increased marine biological productivity that occurred approximately between 9 and 3.5 Ma. This phenomenon was observed worldwide in various ocean locations and was attributed to either a rise in nutrient input or a significant reorganization of nutrients within the oceans. Our focus was on the Biogenic Bloom at Ocean Drilling Program (ODP) Site 1085 in the Atlantic Ocean. We provided new biostratigraphic data to develop an updated age model and subsequently examined the variations observed in benthic foraminiferal assemblages throughout the Biogenic Bloom. At Site 1085, the Biogenic Bloom occurred between 8.1 and 3.0 Ma and we studied it employing various proxies, including linear sedimentation rates, carbonate mass accumulation rates, benthic foraminifera assemblage data and associated indexes (such as benthic foraminifera accumulation rate and diversity). We identified four distinct intervals within the Biogenic Bloom based on paleoenvironmental changes inferred from the benthic foraminiferal assemblages. Two intervals within the Biogenic Bloom, spanning from 8.1 to 5.2 Ma and from 3.8 to 3.0 Ma, indicated oligotrophic conditions with highly seasonal phytoplankton blooms. Between 5.2 and 4.8 Ma, we observed short-term fluctuations between well-oxygenated oligotrophic conditions and phases of low-oxygen eutrophic conditions. From 4.8 to 3.8 Ma, we noted a transition to a higher input of food supply to the seafloor. Our findings indicate that the onset of the Biogenic Bloom coincided with well-dated global records and its conclusion aligned with other records from the Atlantic Ocean. Furthermore, our research supports the hypothesis that the Biogenic Bloom should not be viewed as a single productivity event but rather as a complex occurrence comprising several shorter-lived high-productivity periods driven by different factors.
    Type: Dataset
    Format: application/zip, 7 datasets
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  • 75
    Publication Date: 2024-02-27
    Keywords: AGE; Barium excess; Barium excess, flux; biogeochemistry; Calcium carbonate; Calcium carbonate, flux; Carbon, organic, total; Carbon, organic, total, flux; Chlorins; Chlorins, flux; DEPTH, sediment/rock; dust; Export Production; Iron; Iron, flux; iron fertilization; Lithogenic, flux; Lithogenic material; Manganese excess; Millennial scale variability; Sea surface temperature, annual mean; Southern Ocean; SST; TAN1106; TAN1106/28; Tangaroa; Thorium-230, activity; Thorium-230, activity, standard deviation; Thorium-232, activity; Thorium-232, activity, standard deviation; Uranium, authigenic; Uranium-238, activity; Uranium-238, activity, standard deviation; δ15N, foraminifera-bound organic matter
    Type: Dataset
    Format: text/tab-separated-values, 1755 data points
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  • 76
    Publication Date: 2024-02-27
    Keywords: AGE; Benthic-Planktic 14C offset; Benthic-Planktic 14C offset, standard deviation; biogeochemistry; DEPTH, sediment/rock; dust; Export Production; iron fertilization; Millennial scale variability; Southern Ocean; SST; TAN1106; TAN1106/28; Tangaroa
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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  • 77
    Publication Date: 2024-02-27
    Keywords: 175-1085A; 175-1085B; Benguela Current, South Atlantic Ocean; Date/Time of event; Depth, composite revised; Depth, logging; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Event label; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Longitude of event; Reference/source; Sample code/label; Sample comment
    Type: Dataset
    Format: text/tab-separated-values, 921 data points
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  • 78
    Publication Date: 2024-02-27
    Keywords: 175-1085A; 175-1085B; Amaurolithus delicatus; Amaurolithus primus; Benguela Current, South Atlantic Ocean; Calcidiscus macintyrei; Ceratolithus acutus; Ceratolithus atlanticus; Ceratolithus cristatus; Counting; Date/Time of event; Depth, composite revised; DEPTH, sediment/rock; Discoaster asymmetricus; Discoaster berggrenii; Discoaster brouweri; Discoaster hamatus; Discoaster pentaradiatus; Discoaster quinqueramus; Discoaster tamalis; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Event label; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Longitude of event; Nickilithus amplificus; Orthorhabdus rugosus; Reticulofenestra pseudoumbilicus; Sample code/label; Sphenolithus moriformis
    Type: Dataset
    Format: text/tab-separated-values, 1710 data points
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  • 79
    Publication Date: 2024-02-27
    Keywords: 175-1085A; 175-1085B; Abditodentrix pseudothalmanni; Age; Alabaminella weddellensis; Anomalinoides globulosus; Anomalinoides spp.; Benguela Current, South Atlantic Ocean; Bolivina spathulata; Bolivina spp.; Bolivina subaenariensis; Bulimina elongata; Bulimina spp.; Bulimina striata; Bulimina truncana; Cassidulina carapitana; Cassidulina carinata; Cassidulina havanensis; Cassidulina laevigata; Cassidulina minuta; Cassidulina sp.; Cassidulina spp.; Cibicides lobatulus; Cibicidoides bradyi; Cibicidoides cf. alazanensis; Cibicidoides cf. grimsdalei; Cibicidoides cf. pachyderma; Cibicidoides cicatricosus; Cibicidoides micrus; Cibicidoides mundulus; Cibicidoides robertsonianus; Cibicidoides spp.; Cibicidoides wuellerstorfi; Counting; Date/Time of event; Depth, composite revised; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Eggerella bradyi; Ehrenbergina carinata; Ehrenbergina glabra; Elevation of event; Epistominella exigua; Event label; Fissurina spp.; Foraminifera, benthic agglutinated; Frondicularia sp.; Gaudryina sp.; Gavelinopsis lobatulus; Globobulimina spp.; Globocassidulina crassa; Globocassidulina subglobosa; Gyroidinoides orbicularis; Gyroidinoides planulatus; Gyroidinoides soldanii; Gyroidinoides spp.; Hanzawaia ammophila; Hoeglundina elegans; IODP Depth Scale Terminology; Joides Resolution; Karreriella bradyi; Lagena spp.; Laticarinina altocamerata; Laticarinina pauperata; Latitude of event; Leg175; Lenticulina spp.; Longitude of event; Melonis barleeanus; Melonis pompilioides; Melonis spp.; Miliolidae; Nodosariidae; Nonionella spp.; Nonion spp.; Nuttallides umbonifera; Nuttallinella sp.; Obesopleurostomella bierigi; Oridorsalis umbonatus; Osangularia culter; Osangularia spp.; Pleurostomella spp.; Polymorphinidae; Pullenia bulloides; Pullenia quinqueloba; Pyrgo lucernula; Pyrgo murrhina; Quinqueloculina sp.; Rectuvigerina multicostata; Sample code/label; Sigmoilina schlumbergeri; Sphaeroidina bulloides; Spiroplectammina spectabilis; Spirosigmoilina spp.; Stilostomellidae; Textularia lythostrota; Textularia spp.; Uvigerina occidentalis; Uvigerina peregrina; Uvigerina proboscidea; Vulvulina sp.
    Type: Dataset
    Format: text/tab-separated-values, 2871 data points
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  • 80
    Publication Date: 2024-02-27
    Keywords: 175-1085A; 175-1085B; Abditodentrix pseudothalmanni; Age; Alabaminella weddellensis; Benguela Current, South Atlantic Ocean; Bolivina spathulata; Bolivina subaenariensis; Bulimina elongata; Bulimina striata; Bulimina truncana; Calculated; Cassidulina carapitana; Cibicidoides bradyi; Cibicidoides mundulus; Cibicidoides wuellerstorfi; Cluster; Cluster analysis; Date/Time of event; Depth, composite revised; DEPTH, sediment/rock; Diversity; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Epistominella exigua; Event label; Fishers alpha index of diversity; Foraminifera, benthic, dysoxic/suboxic group; Foraminifera, benthic, epifaunal; Foraminifera, benthic, infaunal; Foraminifera, benthic, oxic fauna; Foraminifera, benthic agglutinated; Foraminifera, benthic calcareous; Globocassidulina crassa; Globocassidulina subglobosa; Hoeglundina elegans; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Longitude of event; Melonis barleeanus; Nuttallides umbonifera; Oridorsalis umbonatus; Relative abundance (counted and calculated); Sample code/label; Uvigerina occidentalis; Uvigerina peregrina; Uvigerina proboscidea
    Type: Dataset
    Format: text/tab-separated-values, 1221 data points
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  • 81
    Publication Date: 2024-02-27
    Description: We used the positions of the calcareous nannofossil events from this study, combined with shipboard data, as tie-points to develop the age model between 526.87 and 182.00 m. Between two successive tie-points, the sedimentation rate was assumed constant. The time scale used is the Geological Time Scale 2020 (GTS2020; Raffi et al. (2020, doi:10.1016/B978-0-12-824360-2.00029-2)) and is based on calcareous nannofossil biochronology provided in GTS2020.
    Keywords: 175-1085A; 175-1085B; Age; Age, error; Benguela Current, South Atlantic Ocean; Date/Time of event; Depth, composite revised; Depth, error; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Event label; Event layer type; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Longitude of event; Provenance/source; Reference/source; Sample code/label; Sample code/label 2; see description in data abstract
    Type: Dataset
    Format: text/tab-separated-values, 153 data points
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  • 82
    Publication Date: 2024-02-27
    Description: Carbonate mass accumulation rates (MARCarb) were calculated for Site 1085 following successive steps: first, we derived the carbonate content of our samples from Diester-Haass et al. (2004, doi:10.1029/2003PA000933) data using linear interpolation between 542.45 and 149.00 m. Secondly, we calculated the carbonate mass accumulation rates (MARCarb, expressed as g/m²/ka) for each sample, using the LSR (cm/ka) obtained, and the calcium carbonate content (wt% CaCO3) and the dry bulk density (DBD, g/cm3) interpolated from Diester-Haass et al. (2004). We applied the formula: MARCarb = %wtCaCO₃ * LSR * DBD. MARCarb from this study has been plotted with MARCarb from Diester-Haass et al. (2004), recalibrated using our age model.
    Keywords: 175-1085A; 175-1085B; Accumulation rate, calcium carbonate; Age; AGE; Benguela Current, South Atlantic Ocean; Calcium carbonate; Date/Time of event; Density, dry bulk; Depth, composite revised; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Event label; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Linear sedimentation rate; Longitude of event; Sample code/label; see description in data abstract
    Type: Dataset
    Format: text/tab-separated-values, 231 data points
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  • 83
    Publication Date: 2024-02-27
    Keywords: 175-1085A; 175-1085B; Accumulation rate, benthic foraminifera by number; Accumulation rate, calcareous benthic foraminifera by number; Age; Benguela Current, South Atlantic Ocean; Calculated (Herguera and Berger, 1991); Counted; Counting 〉63 µm fraction; Date/Time of event; Density, dry bulk; Depth, composite revised; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Elevation of event; Event label; Foraminifera, benthic; Foraminifera, benthic, wet mass; IODP Depth Scale Terminology; Joides Resolution; Latitude of event; Leg175; Linear sedimentation rate; Longitude of event; Sample code/label; Weighted
    Type: Dataset
    Format: text/tab-separated-values, 396 data points
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  • 84
    Publication Date: 2024-02-29
    Description: Volcanic glass shards have been selected from core DP30PC section 8, collected in the southeast Gulf of Taranto to establish a robust tephra chronology. In the core 4 Cryptotephras are observed. Selected glass shards from these Tephras contain elemental signals typical for Lipari outbreaks as well as of the Somma-Vesuvius.
    Keywords: 64PE297; Aluminium oxide; Calcium oxide; Center for Marine Environmental Sciences; Date; DEPTH, sediment/rock; DP30PC; elements; Elements, total; Iron oxide, FeO; Magnesium oxide; Manganese oxide; MARUM; Mediterranean; Normalized to VG-568 standard and to 100 wt% volatile-free; PC; Pelagia; Phosphorus pentoxide; Piston corer; Potassium oxide; Roman Climate Optimum; Sample comment; Sample ID; Silicon dioxide; Sodium and Potassium oxide; Sodium oxide; Titanium dioxide; volcanic glass shards
    Type: Dataset
    Format: text/tab-separated-values, 1170 data points
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  • 85
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 259050 data points
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  • 86
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23888 data points
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  • 87
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 266730 data points
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  • 88
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Meisei, iMS; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 26411 data points
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  • 89
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 267750 data points
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  • 90
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 28633 data points
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  • 91
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 24424 data points
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  • 92
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 265543 data points
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  • 93
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 266217 data points
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  • 94
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 28352 data points
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  • 95
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 241920 data points
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  • 96
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23738 data points
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  • 97
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 30029 data points
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  • 98
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 267297 data points
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  • 99
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 267711 data points
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  • 100
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 266999 data points
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