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  • 1
    Publication Date: 2022-02-09
    Description: The meteorological data were recorded at Weißseespitze (3500 m) in the Ötztal Alps/Austria during the FWF project Cold Ice, P 29256-N36. This is the raw data as recorded, without quality control and without error corrections. Please be aware that before using the data the quality control is a necessary step before using the data in a scientific context. For example, at this high elevation site the albedo values recorded together with the radiation components contain values out of the range 0-1 because in the morning the sun directly shines into the lower sensors of the Hukseflux instruments which are designed to capture the reflected radiation. The AWS (Automatic Weather Station) was installed in October 2017 (46°50'46.56N, 10°43'4.59E, 3499 m) and mainly consists of Campbell Scientific (CS) components and a CR3000 data logger. Records of air temperature and humidity (Rotronic-HC2S3), air pressure (CS106 Vaisala PTB110), wind speed and direction (Young-05103-45), the energy balance (Hukseflux-NR01), snow accumulation and ice ablation by sonic ranging sensor (CS-SR50a) and ice temperatures in four different depths (CS225) are taken every minute and stored on ten-minute intervals with a UTC timestamp. The CS225 ice temperature sensors were initially installed at depths of -1m, -2m, -6m and -9m with reference to the 2017 ice surface as zero. The actual sensor depth thus depends on the ice ablation at the surface since 2017. Snow height is calculated as the difference between the SR50a instrument height and the measured distance to the surface. The instrument height is corrected and applied to the logger program regularly.
    Keywords: Alps; automatic weather station; energy balance; glaciers_austria; ice core; summit; Weißseespitze, Ötztaler Alpen, Austria; WSS
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 2
    Publication Date: 2022-02-23
    Description: TALDICE deep1 ice core chronology (years) for the TALDICE ice core for ice and gas matrix between 1438 m depth and 1548 m depth at 1 m resolution. The chronology is correlated with accumulation rate, thinning function and LIDIE (lock-in-depth in ice equivalent). The TALDICE deep1 chronology is defined for both gas and ice matrix between 1438 m depth and 1548 m depth with the application of the IceChrono1 model (Parrenin et al. 2015). The age scale is defined at 1 m resolution and gas and ice age ages (expressed in years) with their respective uncertainties. The chronology is correlated with accumulation rate, thinning function and LIDIE (lock-in-depth in ice equivalent).
    Keywords: 81Kr dating; Accumulation rate in ice equivalent per year; AGE; Age, standard deviation; Antarctica; BE-OI; Beyond EPICA - Oldest Ice; DEPTH, ice/snow; East Antarctica; Electromechanical drill; EMD; Gas age; Gas age, standard deviation; Ice core chronology; Lock-in depth in ice equivalent; TALDICE; Talos Dome; Talos Dome Ice Core; Thinning function
    Type: Dataset
    Format: text/tab-separated-values, 660 data points
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  • 3
    Publication Date: 2022-02-23
    Description: dD (permill) measured on TALDICE ice core at 5 cm resolution between 1438 m depth and 1619 m depth associated with ice age defined by the TALDICE 1a chronology. The dD measurements (permill) are performed between 1438 m depth until 1620 m depth at 5 cm and 10 cm resolution. Discrete samples at 10 cm-resolution between 1438 m and 1486 m depth are measured at the University of Venice using a Thermo Fisher Delta Plus Advantage mass spectrometer coupled with a HDO device. The precision of δD measurements is ± 0.7‰ (1σ). Below 1486 m depth, discrete 5 cm-resolution analyses are carried out the University of Venice and LSCE using the Cavity Ring Down Spectroscopy technique (CRDS). Analysis are performed using a Picarro isotope water analyser (L2130-i version) for both laboratories. The data are calibrated using a linear calibration with three lab-standards periodically calibrated vs V-SMOW.
    Keywords: 81Kr dating; AGE; Antarctica; BE-OI; Beyond EPICA - Oldest Ice; DEPTH, ice/snow; East Antarctica; Electromechanical drill; EMD; Ice core chronology; see abstract; TALDICE; Talos Dome; Talos Dome Ice Core; δ Deuterium, water
    Type: Dataset
    Format: text/tab-separated-values, 3115 data points
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  • 4
    Publication Date: 2022-02-25
    Description: Here we present the triple isotopic composition of atmospheric oxygen (Δ17O of O2) measured from EPICA Dome C (EDC) ice core, Antarctica, over 58.0-150.0, 233.2-238.1, and 445.6-796.3 ka, in order to reconstruct the past global biosphere productivity (Luz et al., 1999). The data were produced between Feb. 2019 and Oct. 2020 at Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif-sur-Yvette, France. The air samples trapped in EDC ice cores were extracted and purified by a semi-automated system of LSCE, following the identical principles of Barkan and Luz (2005).
    Keywords: Antarctic ice core chronology (AICC2012); calculated, 1 sigma; DEPTH, ice/snow; Dome C; Dome C, Antarctica; EDC; EPICA; EPICA Dome C; European Project for Ice Coring in Antarctica; Gas age; global oxygen biosphere productivity; ICEDRILL; Ice drill; Δ17O; Δ17O, uncertainty; Δ17O of O2
    Type: Dataset
    Format: text/tab-separated-values, 807 data points
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  • 5
    Publication Date: 2022-02-19
    Description: Air temperature and relative humidity (Vaisala HMP155A), as well as barometric pressure (Vaisala CS106), were measured at 1.5 m height above the initial snow surface.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_100; Akademik Fedorov; Arctic Ocean; DATE/TIME; Humidity, relative; Humidity-Temperature probe, Vaisala, HMP155A; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; Pressure, atmospheric; Pressure sensor, Vaisala, CS106; PS122/1_1-263; PS122/4; PS122/4_43-177; Sea ice mass balance; Temperature, air; UnIS; Unmanned ice station; Unmanned Ice Station
    Type: Dataset
    Format: text/tab-separated-values, 18459 data points
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  • 6
    Publication Date: 2022-02-24
    Description: Geographic position, barometric pressure, tilt and compass.
    Keywords: 2019T62; 2019T62, PRIC_09_01; Arctic Ocean; Compass bearing; Coring site; DATE/TIME; Heating rise; LATITUDE; LONGITUDE; MOSAiC; MOSAiC_ICE; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; Pressure, atmospheric; PS122/1; PS122/1_1-125; PS122/4; PS122/4_43-156; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; Temperature; Temperature, air; Tilt angle
    Type: Dataset
    Format: text/tab-separated-values, 66595 data points
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  • 7
    Publication Date: 2022-02-24
    Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 30 s.
    Keywords: 2019T62; 2019T62, PRIC_09_01; Arctic Ocean; Coring site; DATE/TIME; Heating rise; LATITUDE; LONGITUDE; MOSAiC; MOSAiC_ICE; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_1-125; PS122/4; PS122/4_43-156; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; Temperature; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 63173 data points
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  • 8
    Publication Date: 2022-02-24
    Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 120 s.
    Keywords: 2019T62; 2019T62, PRIC_09_01; Arctic Ocean; Coring site; DATE/TIME; Heating rise; LATITUDE; LONGITUDE; MOSAiC; MOSAiC_ICE; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_1-125; PS122/4; PS122/4_43-156; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; Temperature; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 63173 data points
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  • 9
    Publication Date: 2022-02-24
    Description: Temperature profile from atmosphere through snow and ice into the ocean.
    Keywords: 2019T62; 2019T62, PRIC_09_01; Arctic Ocean; Coring site; DATE/TIME; Heating rise; LATITUDE; LONGITUDE; MOSAiC; MOSAiC_ICE; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_1-125; PS122/4; PS122/4_43-156; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; Temperature; Temperature, technical
    Type: Dataset
    Format: text/tab-separated-values, 252936 data points
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  • 10
    Publication Date: 2022-02-19
    Description: The initial ice thickness and snow depth at the buoy deployment site were 1.53 and 0.15 m, respectively. The changes in ice thickness was determined using measurements by the underwater acoustic sounder. The measuring noise of the acoustic sounder has been removed. Since the acoustic sensor at the surface was invalid very soon after the deployment, the evolution of the air/snow interface was determined using the temperature profiles. Overall, the measurement accuracy was 0.1 K for temperature, 0.03 m for the snow or ice surface, and 0.01 m for the ice bottom, respectively. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_100; Akademik Fedorov; Arctic Ocean; DATE/TIME; Ice thickness; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1_1-263; PS122/4; PS122/4_43-177; Sea ice mass balance; Snow thickness; UnIS; Unmanned ice station; Unmanned Ice Station
    Type: Dataset
    Format: text/tab-separated-values, 12304 data points
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  • 11
    Publication Date: 2022-02-19
    Description: One unmanned ice station (UIS) has been deployed at the L3 site (85.13ºN, 135.68ºE) of the Distributed Network (DN) of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign on 10 October 2019. The measurement of the UIS ice unit lasted until 15 June 2020 when the buoy drifted to 82.28°N; while the ocean unit lasted until 28 September 2020 and finally failed at 74.09°N.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_100; Akademik Fedorov; Arctic Ocean; CT package; DATE/TIME; LATITUDE; LONGITUDE; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1_1-263; PS122/4; PS122/4_43-177; Sea ice mass balance; UnIS; Unmanned ice station; Unmanned Ice Station
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 12
    Publication Date: 2022-02-19
    Description: The UIS ocean unit (CT package) consisted of five conductivity & temperature sensors (RBR duo CT), one conductivity, and temperature & depth (pressure) sensor (RBR concerto CTD). The ocean unit were used to measure upper ocean at the depths of about 5-40 m, with the initial depths of 5.4, 10.4, 15.4, 20.4, 25.4, and 40.4 m. The ice and ocean units of UIS were deployed 10 m apart. The changes in the depths of CT sensors were estimated based on their initial depths and the depth measured by the CTD at the bottom of CT package.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_100; Akademik Fedorov; Arctic Ocean; CT package; DATE/TIME; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; Pressure, water; PS122/1_1-263; PS122/4; PS122/4_43-177; RBR_CTD; RBR concerto CTD; RBR duo CT; Salinity; Temperature, water; UnIS; Unmanned ice station; Unmanned Ice Station
    Type: Dataset
    Format: text/tab-separated-values, 152334 data points
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  • 13
    Publication Date: 2022-04-14
    Description: We report the levels of airborne PCB concentrations from 180 samples from 18 locations, from 2011 to 2013 in the metropolitan Chicago area, Il, USA. Measurements were obtained using polyurethane foam passive air samplers (PUF-PAS), deployed for ~45 days. Effective volumes for individual PCB congeners were calculated from a previously published model and included here. Further, individual PCB congener masses from 24 laboratory blank PUFs are included, as well as the masses of the individual PCB congeners measured in the PUF-PAS.
    Keywords: airborne concentration; Chicago; effective volumes; PCB congeners; PUF-PAS
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 14
    Publication Date: 2022-04-23
    Description: The database reports the results of bulk rock geochemical measurements realized on 105 ultramafic lithologies (harzburgites and dunites) samples collected from Holes CM1A (46 samples) and CM2B (59 samples) drilled in the Wadi Tayin massif in the SE of the ophiolite during Phase 2 of the ICDP OmanDP (Nov. 2017-Jan. 2018) (Kelemen et al. [2020]). The studied samples were selected following two strategies. First, a homogeneous sample was selected every 10 m downhole cores during the OmanDP Phase 2 drilling operations, onsite in Oman, in order to get a petrological and geochemical overview continuously along the cores. Second, additional samples have been selected during the daily ChikyuOman Leg 3 sampling meetings in consultation with the core description teams, to focus on more specific facies or levels. These samples are referred to as onsite samples and shipboard samples respectively. Adjacent to each onsite and shipboard sample an oriented thin section billet was taken for mineralogical and lithological characterization. Geochemical data of onsite and shipboard samples were measured both aboard the D/V Chikyu during the ChikyuOman Phase 2 Leg 3 for major element and volatile contents for part of the samples, and at Institute of Earth Science, Academia Sinica, Taiwan (IES-AS), the University of Edinburgh, Scotland (EU), Université Toulouse III - Paul Sabatier, France (TU), and Niigata University, Japan (NU) for trace element contents and additional major element and volatile contents. The purpose of the study was to obtain a high-density and high analytical quality bulk geochemical characterization along continuous cores recovered from OmanDP Holes CM1A and CM2B, from the crust to the mantle through the crust-mantle transition zone. Loss on ignition (LOI) of all onsite and shipboard samples were determined onboard the D/V Chikyu, using the OHTI (Ocean High Technology Institute, Inc., Tokyo, Japan) motion compensated balance system into a pre-weighed ceramic crucible using a spatula (that was never in contact with lithium metaborate flux). Duplicate LOI measurements were done on the onsite samples at EU, following the same steps and procedures. Major element abundances (wt.% oxides) in powdered rock samples were determined using the RIGAKU Supermini wavelength dispersive X-ray fluorescence spectrometer equipped with a 200 W Pd anode tube at 50 kV and 4 mA onboard DV Chikyu during OmanDP Phase 2 Leg 3. Major element analyses were determined to be acceptable if the sum of the anhydrous oxide concentrations totaled to between 99 and 101 wt.%. Precision and accuracy are better than 2.5 % for all oxides except for TiO2 for reference materials DTS-2B and JP-1 (better than 11%) and Na2O, P2O5 and K2O for JGb-2 (3.40, 17.60, and 7.49% respectively). Duplicates of onsite samples whole rock major element analyses were performed at EU, using the Panalytical PW2404 wavelength-dispersive sequential X-ray spectrometer. Gas chromatographic separation was undertaken on non-ignited powders to determine their volatile element contents (total carbon, CTotal and water recalculated from hydrogen) using the Thermo Finnigan™ FlashEA® 1112 elemental analyzers (EA) onboard D/V Chikyu. Whole rock trace element analyses were measured by ICP-MS using acid digestion of powder samples after ChikyuOman 2018 Leg 3. Sample powders were divided into three batches. One batch was sent to each IES-AS, TU and NU laboratory for trace element measurements. The measurements were conducted at IES-AS using an Agilent 7500s inductively coupled plasma‐mass spectrometer (ICP‐MS); at TU using a Thermo Scientific™ Element XR™ HR-ICP-MS; and at NU using Yokogawa HP4500 ICP-MS. To compare the accuracy and the precision in the three different laboratories, trace element measurements were performed on a selection of duplicate samples, and on the same reference materials (DTS-2B and JP-1a).
    Keywords: Dunites; Geochemistry; Harzburgites; Holes CM1A and CM2B; ICDP Oman Drilling Project; OmanDP; Oman Drilling Project; Oman ophiolite Crust-Mantle transition; Peridotite Carbonation; serpentinite; trace element
    Type: Dataset
    Format: application/zip, 6 datasets
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  • 15
    Publication Date: 2022-04-21
    Description: In order to investigate how quickly salt marsh foraminifera respond to rapid sea-level rise, we observed the foraminiferal response to the tidal restoration of the Ni'les-tun marsh (NM), Bandon Marsh National Wildlife Refuge (Oregon). The data sets contain: (1) Census counts of Recent Rose Bengal stained and dead benthic foraminifera. These surface (0-1cm) samples were taken prior tidal restoration in August 2011 and in the six years after tidal restoration until August 2017 the Ni'les-tun marsh. A total of eight station were investigated (NM stations 1 to 8) (2) Grainsize and geochemical analyses prior to and during the first year after tidal restoration (August 2011-August 2012). For grainsize and geochemical analyses, another set of surface samples (0-1 cm) were taken at the eight NM stations used for benthic foraminiferal analyzes. (3) Fossil benthic foraminiferal data from the upper 5 cm of a short core, taken by hand at surface NM station 1 in March 2016. The core was taken to investigate how the recent benthic foraminiferal record was transferred into the fossil record at NM station 1.
    Keywords: Benthic foraminifera; restoration; salt marsh
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 16
    Publication Date: 2022-04-21
    Description: These data was the paleomagnetic results, including the relative paleointennsity (RPI) and directions data since about ~90 kyr retrieved from the a lake sediments, Qinghai lake. This lake located on the Tengchong district, Yunan province of China (25°08′06″ - 25°07′44″N, 98°34′11″ - 98°34′26″E). Two cores were taken from the lake in 2016 and 2018 year respectively, and the detailed paleomagnetic works were performed for the core sediments. The age-depth model of two cores were reconstructed based on the correlation of delta Dwax isotope and radiocarbon ages. The RPI data Natural remanent magnetization (NRM), anhysteretic remanence (ARM) and saturation isothermal remanence (SIRM) of all samples were stepwise demagnetized and measured on a fully automated 2G-Rapid system (QH4 samples) or 2G-760 system (QH17A samples) using peak fields of 0-80 mT. RPI was reconstructed respectively and stacked based on the NRM/SIRM values of two cores. The characteristic remanence (ChRM) directions were isolated from the remaneces between 10 and 60 mT.
    Keywords: Flux Lobe; lake; Non-Dipole Field; relative paleointensity; Secular Variations
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 17
    Publication Date: 2022-04-21
    Keywords: Age model; ChRM, Declination; ChRM, Inclination; Core; CORE; DEPTH, sediment/rock; Flux Lobe; Geomagnetic field directions; lake; lake sediments; Maximum angular deviation; non-dipole earth magnetic; Non-Dipole Field; Reconstructed; relative paleointensity; Sample ID; Secular Variations; Tengchongq_Qinghai_Lake_QH4; Yunnan, China
    Type: Dataset
    Format: text/tab-separated-values, 2922 data points
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  • 18
    Publication Date: 2022-04-21
    Keywords: Age model; ChRM, Declination; ChRM, Inclination; Core; CORE; DEPTH, sediment/rock; Flux Lobe; Geomagnetic field directions; lake; lake sediments; Maximum angular deviation; non-dipole earth magnetic; Non-Dipole Field; Reconstructed; relative paleointensity; Sample ID; Secular Variations; TCQH17A; Tengchongq_Qinghai_Lake_QH17A; Yunnan, China
    Type: Dataset
    Format: text/tab-separated-values, 5323 data points
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  • 19
    Publication Date: 2022-04-21
    Keywords: Bandon Marsh National Wildlife Refuge, Oregon; Benthic foraminifera; Carbon, total; Carbon/Nitrogen ratio; Clay; DATE/TIME; DEPTH, sediment/rock; Elevation of event; Event label; Latitude of event; Longitude of event; Nitrogen, total; NM_Station_1; NM_Station_2; NM_Station_3; NM_Station_4; NM_Station_5; NM_Station_6; NM_Station_7; NM_Station_8; restoration; salt marsh; Sand; Silt; SURF_S; Surface sample; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 808 data points
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  • 20
    Publication Date: 2022-04-21
    Keywords: Age model; Core; CORE; Flux Lobe; Geomagnetic field directions; Intensity, relative; lake; lake sediments; non-dipole earth magnetic; Non-Dipole Field; Reconstructed; relative paleointensity; Secular Variations; Tengchongq_Qinghai_Lake_QH4; Yunnan, China
    Type: Dataset
    Format: text/tab-separated-values, 1082 data points
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  • 21
    Publication Date: 2022-04-21
    Keywords: Age model; Core; CORE; Flux Lobe; Geomagnetic field directions; Intensity, relative; lake; lake sediments; non-dipole earth magnetic; Non-Dipole Field; Reconstructed; relative paleointensity; Secular Variations; TCQH17A; Tengchongq_Qinghai_Lake_QH17A; Yunnan, China
    Type: Dataset
    Format: text/tab-separated-values, 1867 data points
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  • 22
    Publication Date: 2022-04-21
    Keywords: Age model; Flux Lobe; Geomagnetic field directions; Intensity, relative; lake; lake sediments; non-dipole earth magnetic; Non-Dipole Field; Reconstructed; relative paleointensity; Secular Variations; Standard error
    Type: Dataset
    Format: text/tab-separated-values, 1869 data points
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  • 23
    Publication Date: 2022-04-21
    Description: LADCP measurements from METEOR cruise M148/1 used a two-instrument configuration with two Teledyne RDI 300 kHz workhorse ADCPs mounted in down- and up-looking positions. Data collection and processing was performed according to recommendations in the GO-SHIP manual (Thurnherr et al., 2010).
    Keywords: Calculated; CTD/Rosette; CTD 001; CTD 002; CTD 003; CTD 004; CTD 005; CTD 006; CTD 007; CTD 008; CTD 010; CTD 011; CTD 012; CTD 013; CTD 014; CTD 015; CTD 016; CTD 017; CTD 018; CTD 019; CTD 020; CTD 021; CTD 022; CTD 023; CTD 024; CTD 025; CTD 026; CTD 027; CTD 028; CTD 029; CTD 030; CTD 031; CTD 032; CTD 033; CTD 034; CTD 035; CTD 036; CTD 037; CTD 038; CTD 039; CTD 041; CTD 042; CTD 043; CTD 044; CTD 045; CTD 046; CTD 047; CTD 048; CTD 049; CTD 050; CTD 051; CTD 052; CTD 053; CTD 054; CTD 055; CTD 056; CTD 057; CTD 058; CTD 059; CTD 060; CTD 061; CTD 062; CTD 063; CTD 064; CTD 065; CTD 066; CTD 067; CTD 069; CTD 070; CTD 071; CTD 072; CTD 073; CTD 074; CTD 075; CTD 076; CTD 077; CTD 078; CTD 079; CTD 080; CTD 081; CTD 082; CTD 083; CTD 084; CTD 085; CTD 086; CTD 087; CTD 088; CTD 089; CTD 090; CTD 091; CTD 092; CTD 093; CTD 094; CTD 095; CTD 096; CTD 097; CTD 098; CTD 099; CTD 100; CTD 101; CTD 102; CTD 103; CTD-RO; Current velocity, east-west; Current velocity, north-south; Date/Time of event; DEPTH, water; Error, absolute; Event label; Latitude of event; Longitude of event; Lowered Acoustic Doppler Current Profiler (LADCP); M148/1; M148/1_100-1; M148/1_10-1; M148/1_102-1; M148/1_104-1; M148/1_106-1; M148/1_108-1; M148/1_1-1; M148/1_110-1; M148/1_112-1; M148/1_114-1; M148/1_116-1; M148/1_118-1; M148/1_12-1; M148/1_126-1; M148/1_128-1; M148/1_130-1; M148/1_13-1; M148/1_132-1; M148/1_134-1; M148/1_136-1; M148/1_137-1; M148/1_139-1; M148/1_140-1; M148/1_14-1; M148/1_142-1; M148/1_143-1; M148/1_148-1; M148/1_150-1; M148/1_15-1; M148/1_152-1; M148/1_154-1; M148/1_16-1; M148/1_166-1; M148/1_168-1; M148/1_170-1; M148/1_17-1; M148/1_171-1; M148/1_172-1; M148/1_173-1; M148/1_174-1; M148/1_175-1; M148/1_176-1; M148/1_177-1; M148/1_178-1; M148/1_179-1; M148/1_180-1; M148/1_18-1; M148/1_181-1; M148/1_183-1; M148/1_184-1; M148/1_185-1; M148/1_186-1; M148/1_187-1; M148/1_188-1; M148/1_19-1; M148/1_2-1; M148/1_21-1; M148/1_23-1; M148/1_24-1; M148/1_26-1; M148/1_29-1; M148/1_31-1; M148/1_33-1; M148/1_35-1; M148/1_37-1; M148/1_39-1; M148/1_41-1; M148/1_44-1; M148/1_46-1; M148/1_48-1; M148/1_50-1; M148/1_5-1; M148/1_53-1; M148/1_55-1; M148/1_57-1; M148/1_59-1; M148/1_6-1; M148/1_61-1; M148/1_63-1; M148/1_65-1; M148/1_69-1; M148/1_7-1; M148/1_71-1; M148/1_73-1; M148/1_75-1; M148/1_77-1; M148/1_79-1; M148/1_80-1; M148/1_8-1; M148/1_82-1; M148/1_83-1; M148/1_84-1; M148/1_85-1; M148/1_88-1; M148/1_90-1; M148/1_9-1; M148/1_92-1; M148/1_94-1; M148/1_95-1; M148/1_97-1; Meteor (1986); SACUS/SACUS-II; Southwest African Coastal Upwelling System and Benguela Niños
    Type: Dataset
    Format: text/tab-separated-values, 64395 data points
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  • 24
    Publication Date: 2022-04-14
    Keywords: airborne concentration; Chicago; effective volumes; Gas chromatography, coupled with tandem mass spectrometer (GC-MS/MS); Method comment; PCB congeners; Polychlorinated biphenyl in polyurethane foam; PUF-PAS; Sample code/label
    Type: Dataset
    Format: text/tab-separated-values, 3792 data points
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  • 25
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from August 2012 to August 2013 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-12; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; POS437/1; Poseidon; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 261455 data points
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  • 26
    Publication Date: 2022-04-09
    Description: Roosevelt Island Climate Evolution (RICE) ice core calcium (Ca) data, measured using continuous flow analysis (CFA), covering last glacial period 83000-26000 years BP is presented here. RICE is a 764-m long ice core retrieved from Roosevelt Island, a coastal dome in the vicinity of Ross Sea, West Antarctica. The measurements were made at Centre for Ice and Climate, University of Copenhagen, Denmark in 2015 and posses annual resolution. A three-point calibration was used for the measurements.
    Keywords: AGE; Antarctica; Calcium; CFA; Continuous Flow Analysis; Glaciochemistry; ICEDRILL; Ice drill; Last glacial period; RICE; RICE ice core; Roosevelt Island, Antarctica; Roosevelt Island Climate Evolution Project
    Type: Dataset
    Format: text/tab-separated-values, 40859 data points
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  • 27
    Publication Date: 2022-04-09
    Keywords: (9E)-2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyliden)pentadeca-9-ene, per unit mass organic carbon; 2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyl)pentadecane per unit mass total organic carbon; AGE; AMD16_1a; AMD16-117Q; AMD16-117Q-BC1-1; Baffin Bay; BC; biogenic silica; Biogenic silica, flux; Box corer; Calypso square corer; Carbon, organic, total; CASQ; CCGS Amundsen; DEPTH, sediment/rock; foraminifera abundance; foraminifera flux; GreenEdge/ArcticNet; Holocene; lipid biomarkers; North Water Polynya; productivity; Quaanaaq; Sulfur, total; total organic carbon (TOC)
    Type: Dataset
    Format: text/tab-separated-values, 721 data points
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  • 28
    Publication Date: 2022-04-06
    Description: The 26,000-year long time-series analyzed in a marine sediment core from the northern Bay of Bengal includes Mg/Ca-based SST estimates, Ba/Ca-based mixed layer salinity estimates, and estimates of ice-volume corrected d18O of the mixed layer. The data are provide new insights into the control of Indian Summer Monsoon over the last 26,000 years, including a strong influence of zonal and meridional SST gradient changes within the tropical Indian Ocean on Indian Summer Monsoon variability.
    Keywords: Ba/Ca-based salinitt estimates; Bay of Bengal; Holocene climate variability; Indian Monsoon; Indian Ocean Dipole; last deglaciation; Last Glacial Maximum; Mg/Ca-based paleotemperatures; runoff; Salinity; Temperature
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 29
    Publication Date: 2022-04-16
    Description: Dry bulk densities, organic carbon content, organic nitrogen content and the C:N-ratio of surface sediments were determined on 27 box cores from the shallow North Sea . The box corer used was supplied with a lid which closes the box during retrieval of the core. In this way disturbance of the surface layer of the core as a result of movements of the overlying water column is minimised. If a core showed cracks or disturbance structures at its surface it was discarded and a new core was taken. Of the undisturbed box cores (max length: 55 cm, diameter: 50 cm), the overlying bottom water was siphoned off and subsequently subsamples were made by slowly inserting wet PVC liners (diameter: 9 cm). After the subsampling the liners were stored upright at 4° C. Dry bulk densities were determined by taking subsamples of 5 cm3 wet sediment which were weighed, dried for 72 hours and reweighed. Dry bulk densities were calculated from the dry weight and the initial volume of the samples. Dry bulk densities were corrected for compaction during subsampling and storage by measuring the compaction of the sediments in the liners (if any) and assuming linear compaction over the whole sediment column. Total organic carbon and nitrogen contents of the same set of subsamples were determined using a Carlo Erba NAl500 series 2 Nitrogen Carbon Sulphur analyzer with sample preparation according to the method of Verardo et al. (1990). Depending on the grain size of the sediment, and the expected organic carbon contents, 20-40 mg of dry sediment was weighed into tin sample containers. Calcium carbonate was removed using sulphurous acid. Since sandy sediments have a low specific surface area; the amount of organic matter per weight unit of sediment is much lower in sands than in clayey sediments. As a result it proved to be impossible to determine reliable organic nitrogen values for the sandy sediments of the North Sea. The published data are supplementary to de Haas et al. (1997).
    Keywords: 64PE94_VVA; 64PE94_VVAII; 64PE95_VVA; BC; Box corer; Calculated; Carbon, organic, total; Carbon/Nitrogen ratio; Comment; Date/Time of event; Density, dry bulk; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; dry bulk density; Dry mass; Element analyser CNS, Carlo Erba NA1500 series 2; Elevation of event; Event label; Latitude of event; Longitude of event; Mass; Mass balance; nitrogen; Nitrogen, organic, total; North Sea; organic carbon; Pelagia; sediment; VVA94-1; VVA94-2; VVA94-4; VVA94-5; VVA94-6; VVA94-7; VVA94-8; VVA94II-1; VVA94II-10; VVA94II-11; VVA94II-12; VVA94II-2; VVA94II-3; VVA94II-4; VVA94II-5; VVA94II-6; VVA94II-7; VVA94II-9; VVA95-1; VVA95-10; VVA95-11; VVA95-12; VVA95-13; VVA95-3; VVA95-4; VVA95-5; VVA95-6; VVA95-7; VVA95-8; VVA95-9; Weight loss after drying; Wet mass
    Type: Dataset
    Format: text/tab-separated-values, 1392 data points
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  • 30
    Publication Date: 2022-04-16
    Keywords: #435; #436; #437; #439; #440; #441; Elevation of event; Event label; hydrothermal deep sea vents; in-situ mineral geochemistry; Latitude of event; Lead-206/Lead-204 ratio; Lead-207/Lead-204 ratio; Lead-208/Lead-204 ratio; Location; Longitude of event; Pb isotopes; Remote operated vehicle; ROV; Sample code/label; SO263; SO263_068; SO263_070; SO263_082; SO263_090; SO263_097; SO263_103; SO263_110; Sonne_2; Sulfur isotopes; Television-Grab; Tonga Rift; TVG; Type; δ34S
    Type: Dataset
    Format: text/tab-separated-values, 168 data points
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  • 31
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 15 minutes. The data was collected from August 2005 to July 2006 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-05; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 157850 data points
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  • 32
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from August 2013 to July 2014 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-13; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 238330 data points
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  • 33
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from July 2014 to June 2015 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-14; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; POS471/2; Poseidon; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 245595 data points
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  • 34
    Publication Date: 2022-04-15
    Description: Empirical study of the isotopic features of river runoff were carried out at three hydrological posts in 3 different river basins: the Zakza river in the southwest of the Moscow region, the Dubna river in the north of the Moscow region and the Sosna river in the Voronezh region. Samples of river water, groundwater and precipitation were collected at weekly intervals from September 2019 to October 2021. The analysis was performed by a Picarro L2130-i isotope analyzer. The accuracy was 0.04‰ for δ18О and 0.1‰ for δ2Н. The values are calibrated in the VSMOW-VSLAP scale.
    Keywords: groundwater; precipitation; runoff; stable isotope composition of oxygen and hydrogen
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 35
    Publication Date: 2022-04-15
    Description: Peat properties from an ombrotrophic bog (Store Mosse bog) located in south-central Sweden. The data include peat bulk density analysis, peat accumulation rates (peat-AR), and an age model based on 16 radiocarbon dates, on a 678 cm long peat sequence which was collected in November 2018 (using a Russian corer) and reaches almost 10000 cal years BP in basal age. The peat sequence is based on 9 consecutive peat cores (of 1 m each) obtained from two alternating holes in the southern part of Store Mosse bog. The peat cores were subsampled into 1 cm slices and then stored in a cold room before analysis. The bulk density analysis was made at a 1 cm resolution by taking a cube of peat (roughly 1 cubic cm) from each subsampled slice to be freeze-dried, then weighed and measured (using a caliper) to calculate its density - these values were then used to align the cores to obtain one composite peat sequence with a depth of 678 cm. The age model was created using R_Bacon which utilizes the IntCa13.14C calibration curve, based on 16 radiocarbon age dates of hand-picked plant macrofossil remains. Using the bulk density data and the ages from the age model, the peat accumulation rates (peat-AR) were calculated at 1 cm resolution by dividing the total mass (g/m²) by time between each sample, presented as g/m²/a.
    Keywords: Accumulation model; Accumulation rate, net, peat; Accumulation rate, standard deviation; Age, 14C calibrated, IntCal13 (Reimer et al., 2013); Calculated; Calendar age, maximum/old; Calendar age, mean; Calendar age, median; Calendar age, minimum/young; Density, dry bulk; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Mass; Mass, flux, total; palaeoecology; peat accumulation rate; peat basal ages and dates; PEATC; Peat corer; peatlands; plant macrofossil; Sample, dry mass; Sample volume; SM-A2018; sphagnum; Store Mosse Bog, Sweden; Sweden; Weight, total, wet; Weight loss during freeze-drying
    Type: Dataset
    Format: text/tab-separated-values, 12014 data points
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  • 36
    Publication Date: 2022-04-15
    Description: We measured dissolved and particular inorganic nitrogen concentrations in the Ems estuary (Germany). The sampling campaign was conducted on three days in August 2014 (05.08.2014– 07.08.2014) on board of the German research vessel Ludwig Prandtl. Water samples were taken regularly along the salinity gradient of the estuary irrespective of the state of the tide 2 m below the surface. For stations S276 to S280, only the Ferrybox measurements were taken 2 m below the surface. The water samples were taken by a Niskin-Bottle 2 m above the bottom. The water samples were filtered immediately and stored frozen for analysis of dissolved inorganic nutrient and nitrate stable isotope composition. Filtered samples for suspended particular matter (SPM) concentration, particular carbon and nitrogen content of SPM and nitrogen stable isotope composition of SPM were dried at 50°C and also stored frozen. An onboard membrane pump provided the on-line in situ FerryBox system with water from 2 m below the surface. It continuously measured oxygen, salinity, and temperature during our cruise. More information can be found in Sanders and Laanbroek (2018). The aims of the cruise were 1) to study spatial segregation of nitrogen turnover, 2) to identify the dominant nitrogen turnover processes in the water column and 3) to investigate controlling factors of the nitrogen cycle along the Ems estuary.
    Keywords: Carbon, total, particulate; Carbon/Nitrogen ratio; Continuous flow analyser (AA3, Seal Analytics, Germany); Date/Time of event; DEPTH, water; Elemental analyser; Element analyser, Carlo Erba NA2500, coupled with an isotope ratio mass spectrometerFinnigan MAT 252; Ems estuary; Event label; Helmholtz-Zentrum Hereon; Hereon; Latitude of event; Longitude of event; LP201408; LP201408_S274; LP201408_S275; LP201408_S276; LP201408_S277; LP201408_S278; LP201408_S279; LP201408_S280; LP201408_S281; LP201408_S282; LP201408_S283; LP201408_S284; LP201408_S285; LP201408_S286; LP201408_S287; LP201408_S288; LP201408_S289; LP201408_S290; Ludwig Prandtl; Measurement as N2O using isotope-ratio mass spectrometry (IRMS). Bacterial conversion to N2O, so called Denitrifier-method (according to Sigman et al. 2001; Casciotti et al. 2002). Average of the measurement of 2 replicates; Nitrogen, particulate; Nitrogen in ammonium; Nitrogen in nitrate; Nitrogen in nitrite; On-line-in-situ FerryBox-System (Pertersen et al. 2001); Oxygen; Salinity; Sample ID; Sample method; Station label; Suspended particulate matter; Temperature, water; Water sample; WS; δ15N; δ15N, nitrate; δ18O, nitrate
    Type: Dataset
    Format: text/tab-separated-values, 366 data points
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  • 37
    Publication Date: 2022-04-15
    Description: We measured dissolved and particular inorganic nitrogen and dissolved nitrous oxide concentration in the Ems estuary (Germany). The sampling campaign was conducted on two consecutive days in June 2020 (11.06.2020– 12.06.2020) on board of the German research vessel Ludwig Prandtl. Water samples were taken approximately every 20 min during ebb tide from the North Sea around the island Borkum upstream to Papenburg. The discrete water samples were used to measure dissolved inorganic nutrient, nitrate stable isotope composition, suspended particular matter (SPM) concentration, particular carbon and nitrogen content of SPM and nitrogen stable isotope composition of SPM. An onboard membrane pump provided the on-line in situ FerryBox system with water from 2 m below the surface. It continuously measured oxygen, salinity, and temperature during our cruise. A N2O analyzer coupled (Model 914-0022, Los Gatos Res. Inc., San Jose, CA, USA) with a sea water/gas equilibrator using off-axis cavity output spectroscopy continuously detected dry mole fraction of dissolved nitrous oxide along the estuary. The aims of the study were 1) to investigate spatial dynamics in nitrogen turnover processes along the Ems estuary, 2) to identify their relation to nitrous oxide production and 3) to unravel controlling factors of the nitrogen circle.
    Keywords: Carbon, organic, particulate; Carbon, total, particulate; Carbon/Nitrogen ratio; Continuous flow analyser (AA3, Seal Analytics, Germany); Date/Time of event; DEPTH, water; Elemental analyser; Element analyser, Carlo Erba NA2500, coupled with an isotope ratio mass spectrometerFinnigan MAT 252; Ems estuary; Event label; Helmholtz-Zentrum Hereon; Hereon; Latitude of event; Longitude of event; LP20200602; LP20200602_Underway_station_700; LP20200602_Underway_station_701; LP20200602_Underway_station_702; LP20200602_Underway_station_703; LP20200602_Underway_station_704; LP20200602_Underway_station_705; LP20200602_Underway_station_706; LP20200602_Underway_station_707; LP20200602_Underway_station_708; LP20200602_Underway_station_709; LP20200602_Underway_station_710; LP20200602_Underway_station_711; LP20200602_Underway_station_712; LP20200602_Underway_station_713; LP20200602_Underway_station_716; LP20200602_Underway_station_717; LP20200602_Underway_station_718; LP20200602_Underway_station_719; LP20200602_Underway_station_720; LP20200602_Underway_station_721; LP20200602_Underway_station_722; LP20200602_Underway_station_723; LP20200602_Underway_station_724; LP20200602_Underway_station_725; LP20200602_Underway_station_726; LP20200602_Underway_station_727; LP20200602_Underway_station_728; Ludwig Prandtl; Measurement as N2O using isotope-ratio mass spectrometry (IRMS). Bacterial conversion to N2O, so called Denitrifier-method (according to Sigman et al. 2001; Casciotti et al. 2002). Average of the measurement of 2 replicates; N2O analyzer (Los Gatos Research, Model 914-0022, LGR); Nitrogen, particulate; Nitrogen in ammonium; Nitrogen in nitrate; Nitrogen in nitrite; Nitrous oxide; Nitrous oxide saturation; On-line-in-situ FerryBox-System (Pertersen et al. 2001); Oxygen; Phosphorus in orthophosphate; Salinity; Sample ID; Sample method; Silicate, dissolved; Suspended particulate matter; Temperature, water; Water sample; WS; δ15N; δ15N, nitrate; δ18O, nitrate
    Type: Dataset
    Format: text/tab-separated-values, 682 data points
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  • 38
    Publication Date: 2022-04-15
    Description: Wet bulk density, dry bulk density, porosity, water content and water saturation of sediments from the Norwegian Trough were determined on short cores taken between 1992 and 1996. On the cruises 17-25 July 1992 (station 2-55) and 1-6 July 1993 (station 56-75) in the easternmost part of the Skagerrak, cores were taken with a Niemistö corer. Plastic liners (length 76 cm, outer diameter 63 mm, inner diameter 59 mm) were placed in the corer with holes drilled every five centimetres downwards. These holes were sealed with tape before sampling. After the sample was taken, the tape was removed. In most cases, there was water along the inside of the plastic liner. This water was allowed to drain before sub-samples were taken. Then plastic syringes without a tip were carefully inserted into each hole, and 10 ml of wet sediment was taken out. The sub-samples were then pressed out of the syringes into plastic bags that had been weighed in advance and stored in a refrigerator until they were measured in the laboratory. Upon arrival at the laboratory, the plastic bags with samples were weighed, the weight of the plastic bags was deducted, and the weight of 10 ml of the wet sample was noted. The weight of the dry sample was found by transferring the sample material onto a pre-weighted ceramic bowl before it was weighed again, then drying the bowl with sample in drying cabinet at 70 degrees C for 24 hours, and finally weighing the bowl with sample after drying. The weight of 10 ml of dry sample corresponds to the difference before and after drying. On the cruises 5-16 June 1994 (stations 76-133), 17-24 July 1995 (stations 135-180) and 9-19 September 1996 (stations 181-286), cores were taken with a multicorer. Plastic liners (length 61 cm, outer diameter 63 mm, inner diameter 59 mm) were placed in the corer, which after sampling was closed at both ends with rubber caps to prevent water in the core and on top of the core from leaking out or to evaporate. The cores were then transported to the laboratory in an upright position and stored as such until they were opened. After removing the rubber cap on top of the core, the water was drained by drilling holes in the plastic liner just above the top of the sediment. Lying in a rack, the core was then divided lengthwise with a circular saw by sawing through the plastic liner on both sides of the core. A thin string was then pulled in the saw gap through the sediment and the core split in two halves. Metal rings of known weight and volume were used to take sub-samples. The ring (approx. 2 cm in diameter) was gently pressed into the sediment at certain depths in the middle of one of the core halves, until the ring was full, and then gently tilted out with a spatula. The ends were levelled with a wire saw or spatula, and the excess sediment was discarded. The wet sample plus ring was weighed immediately after the sediment on the outside of the metal ring was removed. The sample was then pressed out into a pre-weighed porcelain bowl. Then the weight of bowl plus wet sample was measured, and the weight of wet sample was determined. The sample was dried in a porcelain bowl in a heating cabinet at 105 degrees C for 24 hours, before the sample plus bowl was weighed again and the dry weight was determined. More details on the methods can be found in Rise and Bøe (1995) and Bøe and Rise (1997).
    Keywords: 10; 100; 101; 102; 103; 104; 105; 106; 107; 108; 109; 11; 110; 111; 112; 113; 114; 115; 116; 117; 118; 119; 12; 120; 121; 122; 123; 127; 128; 129; 13; 130; 131; 132; 133; 135; 136; 137; 138; 139; 14; 140; 141; 142; 143; 144; 145; 146; 147; 148; 149; 15; 150; 151; 152; 153; 154; 155; 156; 157; 158; 16; 160; 161; 162; 163; 164; 165; 166; 166B; 167; 169; 17; 170; 171; 172; 173; 175; 176; 177; 178; 179; 18; 180; 181; 182; 183; 184; 185; 186; 188; 189; 19; 190; 191; 192; 193; 194; 195; 196; 197; 198; 199; 2; 200; 201; 203; 205; 206; 207; 208; 209; 21; 210; 211; 212; 213; 214; 215; 216; 22; 220; 221; 222; 223; 224; 225; 226; 227; 228; 229; 23; 230; 231; 232; 235; 236; 237; 238; 239; 24; 240; 241; 242; 243; 244; 245; 246; 247; 25; 251; 252; 253; 254; 255; 256; 257; 258; 259; 26; 260; 261; 262; 263; 264; 268; 269; 27; 270; 271; 272; 273; 274; 275; 276; 277; 28; 280; 281; 282; 283; 284; 285; 286; 29; 3; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 4; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 5; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 6; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 7; 70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 8; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 9; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; Date/Time of event; Density, dry bulk; Density, wet bulk; DEPTH, sediment/rock; dry bulk density; Event label; Håkon Mosby; HM9205; HM9205_10; HM9205_11; HM9205_12; HM9205_13; HM9205_14; HM9205_15; HM9205_16; HM9205_17; HM9205_18; HM9205_19; HM9205_2; HM9205_21; HM9205_22; HM9205_23; HM9205_24; HM9205_25; HM9205_26; HM9205_27; HM9205_28; HM9205_29; HM9205_3; HM9205_30; HM9205_31; HM9205_32; HM9205_33; HM9205_34; HM9205_35; HM9205_36; HM9205_37; HM9205_38; HM9205_39; HM9205_4; HM9205_40; HM9205_41; HM9205_42; HM9205_43; HM9205_44; HM9205_45; HM9205_46; HM9205_47; HM9205_48; HM9205_49; HM9205_5; HM9205_50; HM9205_51; HM9205_52; HM9205_53; HM9205_54; HM9205_55; HM9205_6; HM9205_7; HM9205_8; HM9205_9; HM9307; HM9307_56; HM9307_57; HM9307_58; HM9307_59; HM9307_60; HM9307_61; HM9307_62; HM9307_63; HM9307_64; HM9307_65; HM9307_66; HM9307_67; HM9307_68; HM9307_69; HM9307_70; HM9307_71; HM9307_72; HM9307_73; HM9307_74; HM9307_75; HM9404; HM9404_100; HM9404_101; HM9404_102; HM9404_103; HM9404_104; HM9404_105; HM9404_106; HM9404_107; HM9404_108; HM9404_109; HM9404_110; HM9404_111; HM9404_112; HM9404_113; HM9404_114; HM9404_115; HM9404_116; HM9404_117; HM9404_118; HM9404_119; HM9404_120; HM9404_121; HM9404_122; HM9404_123; HM9404_127; HM9404_128; HM9404_129; HM9404_130; HM9404_131; HM9404_132; HM9404_133; HM9404_76; HM9404_77; HM9404_78; HM9404_79; HM9404_80; HM9404_81; HM9404_82; HM9404_83; HM9404_84; HM9404_85; HM9404_86; HM9404_87; HM9404_88; HM9404_89; HM9404_90; HM9404_91; HM9404_92; HM9404_93; HM9404_94; HM9404_95; HM9404_96; HM9404_97; HM9404_98; HM9404_99; HM9506; HM9506_135; HM9506_136; HM9506_137; HM9506_138; HM9506_139; HM9506_140; HM9506_141; HM9506_142; HM9506_143; HM9506_144; HM9506_145; HM9506_146; HM9506_147; HM9506_148; HM9506_149; HM9506_150; HM9506_151; HM9506_152; HM9506_153; HM9506_154; HM9506_155; HM9506_156; HM9506_157; HM9506_158; HM9506_160; HM9506_161; HM9506_162; HM9506_163; HM9506_164; HM9506_165; HM9506_166; HM9506_166B; HM9506_167; HM9506_169; HM9506_170; HM9506_171; HM9506_172; HM9506_173; HM9506_175; HM9506_176; HM9506_177; HM9506_178; HM9506_179; HM9506_180; HM9606; HM9606_181; HM9606_182; HM9606_183; HM9606_184; HM9606_185; HM9606_186; HM9606_188; HM9606_189; HM9606_190; HM9606_191; HM9606_192; HM9606_193; HM9606_194; HM9606_195; HM9606_196; HM9606_197; HM9606_198; HM9606_199; HM9606_200; HM9606_201; HM9606_203; HM9606_205; HM9606_206; HM9606_207; HM9606_208; HM9606_209; HM9606_210; HM9606_211; HM9606_212; HM9606_213; HM9606_214; HM9606_215; HM9606_216; HM9606_220; HM9606_221; HM9606_222; HM9606_223; HM9606_224; HM9606_225; HM9606_226; HM9606_227; HM9606_228; HM9606_229; HM9606_230; HM9606_231; HM9606_232; HM9606_235; HM9606_236; HM9606_237; HM9606_238; HM9606_239; HM9606_240; HM9606_241; HM9606_242; HM9606_243; HM9606_244; HM9606_245; HM9606_246; HM9606_247; HM9606_251; HM9606_252; HM9606_253; HM9606_254; HM9606_255; HM9606_256; HM9606_257; HM9606_258; HM9606_259; HM9606_260; HM9606_261; HM9606_262; HM9606_263; HM9606_264; HM9606_268; HM9606_269; HM9606_270; HM9606_271; HM9606_272; HM9606_273; HM9606_274; HM9606_275; HM9606_276; HM9606_277; HM9606_280; HM9606_281; HM9606_282; HM9606_283; HM9606_284; HM9606_285; HM9606_286; Latitude of event; Longitude of event; MUC; MultiCorer; NC; Niemistoe corer; North Sea; Norwegian Trough, North Sea; porosity; Porosity; Saturation; Skagerrak; Station label; water content; Water content, sediment; water saturation; wet bulk density
    Type: Dataset
    Format: text/tab-separated-values, 6366 data points
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  • 39
    Publication Date: 2022-04-14
    Description: This data set collection provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 to 20 minutes. The data was collected between 2005 to 2015 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array is to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Denmark Strait; DS2-05; DS2-07; DS2-08; DS2-09; DS2-11; DS2-12; DS2-13; DS2-14; Greenland Sea; M85/2; M85/2_919-1; Maria S. Merian; Meteor (1986); MOOR; Mooring; MSM05/4; MSM12/1; NACLIM; North Atlantic; North Atlantic Climate; Overflow; POS437/1; POS471/2; Poseidon; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: application/zip, 8 datasets
    Location Call Number Expected Availability
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  • 40
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from July 2008 to June 2009 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-08; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 223880 data points
    Location Call Number Expected Availability
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  • 41
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from August 2011 to June 2012 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-11; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; M85/2; M85/2_919-1; Meteor (1986); MOOR; Mooring; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 211670 data points
    Location Call Number Expected Availability
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  • 42
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 20 minutes. The data was collected from June 2009 to July 2010 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-09; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; Maria S. Merian; MOOR; Mooring; MSM12/1; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 142845 data points
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  • 43
    Publication Date: 2022-04-14
    Description: Multiparameter measurement of biogeochemical properties of the sea surface microlayer (SML), 0.5-meter depth, underlying water (ULW) at 1-meter depth and near surface ocean at 1.5-meter depth during cruise FK1911120 onboard RV Falkor. The pH, temperature and conductivity were measured both in the SML and ULW with two VWR model MU 6100H. The salinity values were calculated from the conductivity and corrected with discrete water samples measured with a salinometer in the lab. The temperature reported comes from the conductivity sensors. The pH (0m) and pH (1m) were measured in surface and bulk water (approximated 0.5 and 1.5 m depth) with a flowthrough sensor manufactured by SubCtech and with two AMT pH sensors. Fluorescent dissolved organic matter (fDOM) in SML and ULW was measured with two TriOs MicroFlu sensors. All the meteorological data comes from a Davis Instrument Vantage Pro2 located on the top of the sea surface scanner (S3) mast. Discrete samples for surfactants analysis were taken with the S3 and analysed in the laboratory with voltammetry. More details about the S3 and the sensors on it are described in Ribas-Ribas et al., 2017 (https://doi.org/10.1175/JTECH-D-17-0017.1). The S3 was deployed during 17 stations between the 20 November 2019 and the 17 December 2019 in the Pacific Ocean.
    Keywords: bulk water; CµC; Calculated; Carbon microcycle: CO2 gradients in the ocean surface; CATAMARAN; CATM; DATE/TIME; Dew/frost point; Erythemal dose, minimal; Event label; Falkor; FK191120; FK191120_1; FK191120_11; FK191120_13; FK191120_14; FK191120_15; FK191120_17; FK191120_18; FK191120_19; FK191120_20; FK191120_21; FK191120_22; FK191120_24; FK191120_25; FK191120_3; FK191120_4; FK191120_5; FK191120_9; Flowthrough system (SubCtech) with pH sensor (AMT); Fluorescence, dissolved organic matter; Handheld meter MU 6100 H, VWR; Heat index; Humidity, relative; LATITUDE; LONGITUDE; meteorological data; microFlu sensor, TriOS; near surface ocean; Number; Pacific Ocean; pH; Precipitation; Pressure; Quality flag, air temperature; Quality flag, fluorescence, dissolved organic matter; Quality flag, pH; Quality flag, salinity; Quality flag, water temperature; Salinity; sea surface microlayer; Short-wave downward (GLOBAL) radiation; Solar Energy; South Pacific Ocean; Station label; Surface active substances, standard deviation; Surfactants; Temperature, air; Temperature, water; Temperature humidity sun wind index; Temperature humidity wind index; Ultraviolet index; Voltammetry; Weather Station, Vantage Pro2, Davis; Wind direction description; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 656034 data points
    Location Call Number Expected Availability
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  • 44
    Publication Date: 2022-04-14
    Description: This data set provides quality controlled temperature, conductivity and pressure measurements from moored instrumentation (Seabird Microcat) in the Denmark Strait. Practical salinity was calculated from the measured quantities and is provided as well. Temporal resolution of the time series is 10 minutes. The data was collected from July 2007 to July 2008 at the location of mooring DS2. This mooring is part of the Denmark Strait Overflow array and maintained by the Institute of Oceanography, University Hamburg. The purpose of the array was to monitor the properties and variability of the dense Denmark Strait Overflow.
    Keywords: Calculated; Conductivity; DATE/TIME; DEPTH, water; DS2-07; Gear identification number; Greenland Sea; LATITUDE; LONGITUDE; Maria S. Merian; MOOR; Mooring; MSM05/4; NACLIM; North Atlantic; North Atlantic Climate; Overflow; Pressure, water; Salinity; Seabird Microcat mooring; Temperature, water; Temperature and Salinity; Thermohaline Overturning – at Risk?; THOR
    Type: Dataset
    Format: text/tab-separated-values, 272865 data points
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  • 45
    Publication Date: 2022-04-09
    Description: Data was collected as part of the SOCPacific project. Dealing with challenges of the pandemic and travel restrictions, project participants aimed to develop a typology of reef passages based on visual interpretation of freely available satellite imagery. Nine islands of different sizes and shapes surrounded by coral reef structures were selected based on previous field expertise. Reef passages were mapped in GoogleEarth and further processed in QGIS (version 3.16) and R (version 3.5.3). In addition, outlines for the selected islands were downloaded from the GADM database (gadm.org). Parameters distance to coast, minimal width of the passage and the assigned type were added to the dataset. Passages were assigned one of three types defined in Breckwoldt et al. (in review) - Coastal, Lagoon or Open Ocean - depending on the geomorphological appearance of the reef and distance to the coast.
    Keywords: coral reefs; Distance to shore; Event label; Identification; LATITUDE; Location; LONGITUDE; Obtained from Geographic Information System (GIS); reef passages; satellite image analysis; Satellite imagery; satellite remote sensing; SATI; SOCP-001; SOCP-002; SOCP-003; SOCP-004; SOCP-005; SOCP-006; SOCP-007; SOCP-008; SOCP-009; SOCPacific; SOCPacific - A Sea of Connections; SOCP-FJ-Cicia; SOCP-FJ-Gau; SOCP-FJ-Kadavu; SOCP-FJ-Kanacea; SOCP-FJ-Makogai; SOCP-FJ-Yadua; SOCP-NC-GT; SOCP-VU-Efate; SOCP-VU-Malekula; South Pacific; Type; typology; visual interpretation; Width
    Type: Dataset
    Format: text/tab-separated-values, 565 data points
    Location Call Number Expected Availability
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  • 46
    Publication Date: 2022-03-12
    Description: To investigate the lithostratigraphic position and frictional behavior of the shallow plate boundary fault at the northern Cascadia subduction zone, we conducted laboratory friction experiments on sediments recovered at IODP Site U1301. We used a single-direct shear device under room temperature conditions with 3.5% simulated seawater to perform cohesion tests, plate rate tests and velocity step tests (VST). Friction data from VSTs were inversly modelled to obtain rate- and state friction (RSF) parameters.
    Keywords: Cascadia Basin; earthquake; fault; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Juan de Fuca plate; laboratory friction experiments; subduction zone input
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 47
    Publication Date: 2022-03-12
    Keywords: 301-U1301C; 301-U1301D; Cascadia Basin; Coefficient of peak friction; Coefficient of sliding friction; Cohesion coefficient; Condition; DEPTH, sediment/rock; DRILL; Drilling/drill rig; earthquake; Effective normal stress; Event label; Exp301; Experiment; fault; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; Juan de Fuca Hydrogeology; Juan de Fuca plate; Juan de Fuca Ridge, North Pacific Ocean; laboratory friction experiments; Sample code/label; Shearing velocity; subduction zone input; Test type
    Type: Dataset
    Format: text/tab-separated-values, 231 data points
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  • 48
    Publication Date: 2022-03-12
    Keywords: 301-U1301C; 301-U1301D; Cascadia Basin; Comment; Condition; Critical slip distance dc1; Critical slip distance dc1, standard deviation; Critical slip distance dc2; Critical slip distance dc2, standard deviation; DEPTH, sediment/rock; DRILL; Drilling/drill rig; earthquake; Event label; Exp301; Experiment; fault; Friction direct effect; Friction direct effect, standard deviation; Friction evolutionary effect, b1; Friction evolutionary effect, b2; Friction evolutionary effect b1, standard deviation; Friction evolutionary effect b2, standard deviation; Initial friction coefficient; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; Juan de Fuca Hydrogeology; Juan de Fuca plate; Juan de Fuca Ridge, North Pacific Ocean; laboratory friction experiments; Linear term; Sample code/label; Sliding velocity, final; Sliding velocity, initial; Stiffness; subduction zone input; Velocity-dependent friction parameter
    Type: Dataset
    Format: text/tab-separated-values, 1228 data points
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  • 49
    Publication Date: 2022-03-17
    Keywords: Altai Mountains, Mongolia; compound-specific biomarker isotopes; DEPTH, soil; Depth, soil, maximum; Depth, soil, minimum; Event label; GASC; Gas chromatograph; KN_2H_A1; KN_2H_A10; KN_2H_A11; KN_2H_A12; KN_2H_A13; KN_2H_A2; KN_2H_A3; KN_2H_A4; KN_2H_A5; KN_2H_A6; KN_2H_A7; KN_2H_A8; KN_2H_A9; lake surface sediments; LATITUDE; LONGITUDE; Mongolia; n-Alkane C27, δD; n-Alkane C27, δD, standard deviation; n-Alkane C31, δD; n-Alkane C31, δD, standard deviation; Sample ID; SOIL; Soil profile; topsoils
    Type: Dataset
    Format: text/tab-separated-values, 65 data points
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  • 50
    Publication Date: 2022-03-17
    Description: The RECAP ice core was drilled on the Renland Ice Cap (71° 18′18′′ N, 26° 43′24′′ W; 2315 m a.s.l.), coastal East Greenland, in 2015. This repository contains ice core values of d^18^O of the upper ca. 530 meter section of the core, corresponding to the ca. 11,000 years of the Holocene. The time series is smoothed using a 100-yr Gaussian kernel. The data are from Hughes et al., 2020: High-frequency climate variability in the Holocene from a coastal-dome ice core in east-central Greenland.
    Keywords: Age, relative, number of years; Arctic Sea Ice and Greenland Ice Sheet Sensitivity; Calculated; d18O; Holocene; ice2ice; ice core; ICEDRILL; Ice drill; RECAP; Renland; Renland Ice Cap, East Greenland; Sea ice; δ18O
    Type: Dataset
    Format: text/tab-separated-values, 222 data points
    Location Call Number Expected Availability
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  • 51
    Publication Date: 2022-03-17
    Description: This repository contains GISP2 ice core (Summit, Greenland) sodium concentrations of the upper ca. 1600 meter section of the core, corresponding to the ca. 11,000 years of the Holocene. The time series is smoothed using a 100-yr Gaussian kernel. The raw data are from O'Brien et al., 1995: Complexity of Holocene Climate as Reconstructed from a Greenland Ice Core.
    Keywords: Age, relative, number of years; Arctic Sea Ice and Greenland Ice Sheet Sensitivity; DRILL; Drilling/drill rig; GISP; GISP2; GISP2-D; Holocene; ice2ice; ice core; Renland; Sampling/drilling ice; Sea ice; smoothed; sodium; Sodium
    Type: Dataset
    Format: text/tab-separated-values, 9628 data points
    Location Call Number Expected Availability
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  • 52
    Publication Date: 2022-03-24
    Description: Time series of river-flow observations at Bomporto (coordinates 661919 E 4954652 N, WGS84 UTM 32 N; elevation 32 m asl) along Panaro River (Po River Valley, northern Italy). Recording time step 1 h. Starting from January 1923 to December 1983. Data collected by Servizio Idrografico Italiano (the former Italian hydrographic agency), by converting water stage observations into flow discharges by using a flow rating curve. Data were collected during the routinely monitoring of river-flows conducted by the Italian hydrographic agency. Only flood events are included, while baseflow periods are omitted.
    Keywords: Bomporto_1923-1983; DATE/TIME; derived from water stage record; Panaro River, Bomporto, Italy; Po River Valley; River discharge; river-flow; Time series
    Type: Dataset
    Format: text/tab-separated-values, 63299 data points
    Location Call Number Expected Availability
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  • 53
    Publication Date: 2022-03-29
    Description: Experimental study on the performance of the common sea star Asterias rubens subjected to heatwaves of different duration and frequency (No, Interrupted, Present-day, and Extended). Treatments are based on the climatological analysis of 22-year long temperature data. The study was conducted at GEOMAR, Helmholtz-Centre for Ocean Research Kiel (54.329979 N, 10.148013 E) in the Kiel Indoor Benthocosms (Pansch and Hiebenthal 2019) over 68 days from July 5th to September 10th, 2019. The temperature was measured with a handheld thermometer at least every three days (TTX 110 type T, Ebro, Ingolstadt, Germany). Salinity, pH, and oxygen concentration were also measured over the experimental period (Multi 3630 IDS, WTW, Kaiserslautern, Germany).
    Keywords: Asterias rubens; DATE/TIME; environmental variability; EXP; experiment; Experiment; heatwaves; Identification; KIB; Kiel-Indoor-Benthocosms; Oxygen; Oxygen saturation; pH; Replicate; Salinity; sea star; Temperature, water, experiment; Temperature sensor TTX 110 type T (Ebro, Ingolstadt); Treatment; WTW MULTI 3630 IDS hand probe
    Type: Dataset
    Format: text/tab-separated-values, 7476 data points
    Location Call Number Expected Availability
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  • 54
    Publication Date: 2022-03-29
    Description: Experimental study on the performance of the common sea star Asterias rubens subjected to heatwaves of different duration and frequency (No, Interrupted, Present-day, and Extended). Treatments are based on the climatological analysis of 22-year long temperature data. The study was conducted at GEOMAR, Helmholtz-Centre for Ocean Research Kiel (54.329979 N, 10.148013 E) in the Kiel Indoor Benthocosms (Pansch and Hiebenthal 2019) over 68 days from July 5th to September 10th, 2019. The temperature was logged over the entire experimental period (EnvLogger, ElectricBlue, Vairão, Portugal).
    Keywords: Asterias rubens; DATE/TIME; Date/Time local; environmental variability; EXP; experiment; Experiment; heatwaves; Identification; KIB; Kiel-Indoor-Benthocosms; sea star; Temperature, water, experiment; Temperature logger, EnvLogger (ElectricBlue); Treatment
    Type: Dataset
    Format: text/tab-separated-values, 420865 data points
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  • 55
    Publication Date: 2022-04-20
    Description: Point measurements of snow depth data were collected at approximately peak snow accumulation each winter for a 10-year period from 2005 to 2014 (2005-04-20; 2006-05-02; 2007-04-17; 2008-04-24; 2009-04-30; 2010-05-06; 2011-04-28; 2012-04-10; 2013-05-02; 2014-05-01) around the West Glacier Lake Watershed at GLEES (Glacier Lakes Ecosystem Experiments Site) (41.37255627, -106.2676067; 41.38350614, -106.2505978). Data were collected as part of the research by Dr. Douglas M. Hultstrand (https://mountainscholar.org/handle/10217/233658; https://mountainscholar.org/handle/10217/232572) and others. Snow depth was measured with an anodized aluminum depth probe and the location was measured with a hand-held Garmin Global Positioning System (GPS) unit. The data were collected by the Colorado State University (CSU) in conjunction with the United States Department of Agriculture U.S. Forest Service Rocky Mountain Research Station.
    Keywords: Anodized aluminum depth probe; DATE/TIME; DEPTH, ice/snow; Glacier Lakes Ecosystem Experiments Site; GLEES; GLEES (Glacier Lakes Ecosystem Experiments Site); Handheld GPS, Garmin; LATITUDE; LONGITUDE; Rocky Mountains; SNOW; Snow/ice sample; snow depth; Wyoming USA
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 56
    Publication Date: 2022-04-20
    Keywords: AC; Aircraft; Calculated; Course; DATE/TIME; LATITUDE; LONGITUDE; P5_228_FUEGO_21; P5_228_FUEGO_21_2111080101; POLAR 5; Speed
    Type: Dataset
    Format: text/tab-separated-values, 600 data points
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  • 57
    Publication Date: 2022-04-21
    Description: LADCP measurements from METEOR cruise M159 used a two-instrument configuration with two Teledyne RDI 300 kHz workhorse ADCPs mounted in down- and up-looking positions. Data collection and processing was performed according to recommendations in the GO-SHIP manual (Thurnherr et al., 2010).
    Keywords: Calculated; CTD/Rosette; CTD 001; CTD 002; CTD 003; CTD 004; CTD 005; CTD 006; CTD 007; CTD 008; CTD 009; CTD 010; CTD 011; CTD 012; CTD 013; CTD 014; CTD 015; CTD 017; CTD 018; CTD 019; CTD 020; CTD 021; CTD 022; CTD 023; CTD 024; CTD 025; CTD 026; CTD 027; CTD 028; CTD 029; CTD 030; CTD 031; CTD 032; CTD 033; CTD 034; CTD 035; CTD 036; CTD 037; CTD 038; CTD 039; CTD 040; CTD 041; CTD 042; CTD 043; CTD 044; CTD 045; CTD 046; CTD 047; CTD 048; CTD 049; CTD 050; CTD 051; CTD 052; CTD 053; CTD 054; CTD 055; CTD 057; CTD 058; CTD 059; CTD 060; CTD 061; CTD 062; CTD 063; CTD 064; CTD 065; CTD 066; CTD-RO; Current velocity, east-west; Current velocity, north-south; Date/Time of event; DEPTH, water; Error, absolute; Event label; Latitude of event; Longitude of event; Lowered Acoustic Doppler Current Profiler (LADCP); M159; M159_1-1; M159_11-1; M159_12-1; M159_13-1; M159_14-1; M159_15-1; M159_18-1; M159_19-1; M159_20-1; M159_23-1; M159_24-1; M159_27-1; M159_28-1; M159_29-1; M159_30-1; M159_31-1; M159_32-1; M159_33-1; M159_34-1; M159_35-1; M159_36-1; M159_37-1; M159_38-1; M159_39-1; M159_40-1; M159_4-1; M159_41-1; M159_42-1; M159_43-1; M159_44-1; M159_45-1; M159_46-1; M159_47-1; M159_48-1; M159_49-1; M159_50-1; M159_5-1; M159_51-1; M159_52-1; M159_53-1; M159_54-1; M159_55-1; M159_56-1; M159_57-1; M159_58-1; M159_59-1; M159_60-1; M159_6-1; M159_61-1; M159_62-1; M159_63-1; M159_64-1; M159_65-1; M159_66-1; M159_67-1; M159_68-1; M159_69-1; M159_70-1; M159_7-1; M159_71-1; M159_72-1; M159_73-1; M159_74-1; M159_75-1; Meteor (1986); RACE-II; Regional Atlantic Circulation and global Change II
    Type: Dataset
    Format: text/tab-separated-values, 64644 data points
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  • 58
    Publication Date: 2022-04-22
    Description: The negative of the vertical component of the atmospheric direct current (DC) electric field is referred to as the atmospheric electric potential gradient (PG). The PG depends on the actual ionospheric potential, local electric fields, and the electrical conductivity of the air at the place of the measurement. These factors are more or less directly connected to meteorological conditions. The overall state of the global network of large-scale electrical currents in the Earth-ionosphere system can be inferred from the PG when the weather is locally calm. This meteorological condition is traditionally referred to as “fair weather” and is characterized by allowed ranges of specified meteorological parameters. This is why information on the actual weather condition is supposed to be an inherent supplement of PG datasets. This dataset contains PG data recorded in the Széchenyi István Geophysical Observatory (NCK, 47.632°N, 16.718°E), Hungary from 1962, when the regular measurements were started, up to 2009. Throughout this time period, data were collected using practically the same instrument at the same location. The PG was measured by a locally developed radioactive apparatus which equalizes the atmospheric potential over the lowest 1 m thick air layer so that the potential difference between the sensing and grounded electrodes at ground level is the PG itself. Zero signal offset was determined daily and the instrument was calibrated in the ±250 V/m range weekly whenever it was possible. The instrument has a measuring range of −300 V/m to 300 V/m. The data were recorded photographically by a sensitive galvanometer. Hourly averages were then obtained from the photographical records via manual evaluation with an uncertainty of ±10 V/m. Hourly averaged PG data was included in this dataset when valid records from more than 30 minutes from a given hour were available. Records in the original dataset marked as unreliable or saturated have been omitted. Detailed characteristics of the instruments and the applied calibration technique as well as links to original data publications can be found in Bór et al., 2020 and the references therein. This dataset also contains hourly PG averages which have been corrected for the time-dependent bias caused by the electrostatic shielding effect of trees that were growing up not far from the measuring instrument over the decades. Note that this shielding effect largely dominates the long-term trends in the uncorrected data, so the original PG data must be interpreted with care. The uncertainty of the conversion is also provided. This uncertainty arises from unexact information on the age and growth rate of different trees near the measuring instrument. Detailed explanation of the correction can be found in Buzás et al., 2021. On-site measurements of temperature, total rainfall, relative humidity, resultant wind direction and speed, and global solar radiation are available after 2000. These parameters were measured by a Campbell meteorological station. The measured data was compiled using the factory calibration of the sensors throughout the included time interval. The original time resolution of the data is 10 minutes. The data was converted to hourly time resolution to comply with the PG records. In order to provide a possibility for examining the relation of PG to meteorology on the full time span of the PG records, meteorological parameters obtained in hourly time resolution from the ERA5 reanalysis framework are attached. The two horizontal components of wind speed at 10 m (to calculate the resultant wind speed and direction; see reference ERA5WindCalculation), temperature at 2 m, dew point temperature at 2 m (to calculate relative humidity according to Tetens (1930)), total precipitation, surface pressure, downwards surface solar radiation, snow cover, and snow depth were extracted from the ERA5-Land hourly data 1950 to present dataset (Muñoz Sabater, 2019). Total cloud cover, low cloud cover, and cloud base height between 1962 and 1978 were compiled from the ERA5 hourly data on single levels 1950-1978 (preliminary version) dataset (Bell et al., 2020). The latter parameter set in the 1979–2009 time period was compiled from the ERA5 hourly data on single levels 1979 to present dataset (Herschbach et al., 2018). Note that, due to the finite spatial resolution of the ERA5 framework, these values correspond to the whole area 47.6-47.7 °N latitude and 16.7-16.8 °E longitude (11 km x 11 km) in the case of the ERA5-Land hourly data dataset and 47.5-47.75 °N latitude and 16.5-16.75 °E longitude (28 km x 28 km) in the cases of ERA5 hourly data on single levels datasets. The observatory is located 4 km and 13 km from the center of the corresponding area in the case of higher and lower spatial resolution ERA5 datasets, respectively.
    Keywords: 1962-1978: ERA5 hourly data on single levels 1950-1978 (preliminary version) dataset (Bell et al., 2020), 1979-2009: derived from the ERA5 hourly data on single levels 1979 to present dataset (Herschbach et al., 2018); Air electric potential gradient; Air electric potential gradient, uncertainty; Air temperature at 2 m height; Calculated; Campbell meteorological station; Climate monitoring station; Cloud base height; Cloud cover; Cloud cover, low clouds; CMS; DATE/TIME; ERA5-Land hourly data 1950 to present dataset (Muñoz Sabater, 2019); Geophysical Observatory Reports; Humidity, relative; Hungary; Nagycenk; NCK; Precipitation; Pressure, atmospheric; Short-wave downward (GLOBAL) radiation; Snow coverage; Snow thickness; Wind direction; Wind direction, standard deviation; Wind speed; Wind speed, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 5288576 data points
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  • 59
    Publication Date: 2022-04-22
    Keywords: 230Th excess; 231Pa excess; Arctic Ocean; Calculated after Not and Hillaire-Marcel (2010); Carbonate; DEPTH, sediment/rock; Grain Size; Healy; Healy-Oden Trans Arctic Expedition 2005 (HOTRAX05); HLY0503; HLY0503-11MC; MUC; MultiCorer; Protactinium-231 excess; Protactinium-231 excess, standard deviation; Stable isotopes
    Type: Dataset
    Format: text/tab-separated-values, 44 data points
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  • 60
    Publication Date: 2022-04-22
    Keywords: 230Th excess; 231Pa excess; Arctic Ocean; Carbonate; Clay; DEPTH, sediment/rock; Grain Size; Healy; Healy-Oden Trans Arctic Expedition 2005 (HOTRAX05); HLY0503; HLY0503-11MC; MUC; MultiCorer; Particle size analyser; Sand; Stable isotopes
    Type: Dataset
    Format: text/tab-separated-values, 156 data points
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  • 61
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_4_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 1137 data points
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  • 62
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_9_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 1365 data points
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  • 63
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_2_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 1137 data points
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  • 64
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_5_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 909 data points
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  • 65
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_8_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 2046 data points
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  • 66
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_11_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 1593 data points
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  • 67
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_10_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 1821 data points
    Location Call Number Expected Availability
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  • 68
    Publication Date: 2022-04-05
    Description: Data from autonomous, drifting buoy with a floating chamber to measure insitu air-sea carbon dioxide (CO2) fluxes during RV Falkor cruise FK191120 in the southern Pacific during November-December 2019. The technique is described in detail in Ribas-Ribas et al. (2018) (https://doi.org/10.1525/elementa.275). The buoy is equipped with a sensor to measure aqueous and atmospheric partial pressure of CO2 (pCO2), and to monitor the increase or loss of CO2 inside the chamber. One complete cycle including two chamber measurements last 70 minutes. The buoy can be deployed for more than 15 hours, and at wind speeds of up to 10 m/s. Floating chambers are known to overestimate fluxes due to the creation of additional turbulence at the water surface. We check that by measuring turbulence with two Acoustic Doppler Velocimeter (ADV), one directly underneath the center of the floating chamber (equipped with an inertial motion unit) and the other one positioned sideways to measure turbulence outside the perimeter of the buoy.
    Keywords: Air-sea CO2 flux; Analytical method; Buoy; BUOY; CµC; Carbon dioxide, partial pressure; Carbon microcycle: CO2 gradients in the ocean surface; CO2 analyzer, LI-840x, LI-COR, OceanPackTM, SubCtech; DATE/TIME; Falkor; FK191120; FK191120_20_BUOY; gas exchange; gas transfer velocity; GPS data logger, GT-730FL-S, Canmore; LATITUDE; LONGITUDE; marine carbon cycle; ocean technology; Pacific Ocean; partial pressure of carbon dioxide; South Pacific Ocean; Station label
    Type: Dataset
    Format: text/tab-separated-values, 906 data points
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  • 69
    Publication Date: 2022-04-01
    Description: The relation of the stable oxygen isotope (δ¹⁸O) was measured in surface water and snowpatches of the northeast coast of Chukotka collected in 1987 and 2017. Data is compiled from Vasil'chuck 1992 (vol.1 & vol.2) and Vasil'chuk et al. 2021.
    Keywords: Chukotka, Russia; Chulcheveem_river; cryostratigraphy; Event label; Koolen_creek; Latitude of event; Lavrentia_bay; Lavrentia_lake; Lavrentia_Lorino_road; Lavrentia_settl_creek; Lavrentia_settl_glac; Lavrentia_settl_snow1; Lavrentia_settl_snow2; Lavrentia_settl_snow3; Lavrentia_settl_snow4; Location; Longitude of event; massive ice; Mass spectrometer Finnigan Delta-V; North-Eastern Chukotka; Sample comment; Sample ID; Sample material; SNOW; Snow/ice sample; Stable isotopes; stable isotopes of water; Surface water sample; SWS; δ18O, maximum; δ18O, minimum
    Type: Dataset
    Format: text/tab-separated-values, 57 data points
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  • 70
    Publication Date: 2022-04-01
    Keywords: Ammonium; Antarctic; cell respiration; DATE/TIME; energy budget; Experimental treatment; fish; hepatocytes; Nitrite; Salinity; Temperature; Temperature, technical; vertebrate
    Type: Dataset
    Format: text/tab-separated-values, 1520 data points
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  • 71
    Publication Date: 2022-03-04
    Description: Geographic position, barometric pressure, tilt and compass.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_89; Akademik Fedorov; Arctic Ocean; Compass bearing; DATE/TIME; distributed network; Heating rising; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020, AF122/1; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Pressure, atmospheric; PS122/1_1-226, 2019T65, PRIC_09_04; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; snow; Temperature; Temperature, air; Tilt angle
    Type: Dataset
    Format: text/tab-separated-values, 72160 data points
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  • 72
    Publication Date: 2022-03-04
    Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 120 s.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_89; Akademik Fedorov; Arctic Ocean; DATE/TIME; distributed network; Heating rising; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020, AF122/1; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-226, 2019T65, PRIC_09_04; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; snow; Temperature; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 57112 data points
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  • 73
    Publication Date: 2022-03-04
    Description: Temperature profile from atmosphere through snow and ice into the ocean.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_90; Akademik Fedorov; Arctic Ocean; DATE/TIME; distributed network; Heating rising; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020, AF122/1; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-224, 2019T63, PRIC_09_02; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; snow; Temperature; Temperature, technical
    Type: Dataset
    Format: text/tab-separated-values, 246840 data points
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  • 74
    Publication Date: 2022-03-04
    Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 30 s.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_90; Akademik Fedorov; Arctic Ocean; DATE/TIME; distributed network; Heating rising; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020, AF122/1; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-224, 2019T63, PRIC_09_02; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; snow; Temperature; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 62194 data points
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  • 75
    Publication Date: 2022-03-04
    Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 120 s.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_90; Akademik Fedorov; Arctic Ocean; DATE/TIME; distributed network; Heating rising; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020, AF122/1; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-224, 2019T63, PRIC_09_02; Quality flag, position; SAMS Ice Mass Balance buoy; Sea ice mass balance; SIMBA; snow; Temperature; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 62194 data points
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    Publication Date: 2022-03-04
    Description: Temperature profile from atmosphere through snow and ice into the ocean.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_89; Akademik Fedorov;