cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.940805
title: 87Sr/86Sr and Sr/Ca measured in the otoliths of catfish (Carlarius parkii and Chrysichthys nigrodigitatus) caught in the estuaries of the Gambia River, Sine-Saloum, and Volta River, 2017

description: Modern sub-surface water samples and the otoliths of catfish (Carlarius parkii and Chrysichthys nigrodigitatus) collected from the estuaries of the Gambia River (The Gambia), Sine-Saloum (Senegal), and Volta River (Ghana) in 2017 were analysed to investigate relationships between the Sr geochemistry and salinity. 87Sr/86Sr, Sr concentration, and salinity measured in water samples collected along the estuarine salinity gradients were used to establish mixing models describing their relationships. Bulk catfish otolith 87Sr/86Sr measurements were used to estimate habitat salinity of the fish based on these mixing models. Catch data (total length, fork length, weight) of catfish were recorded and used to estimate their age. Fish ages were further estimated based on otolith annuli.
DOI: 10.1594/pangaea.943744
title: Ridge snow oxygen and hydrogen isotope data MOSAiC Leg 4 (PS122/4)

description: Oxygen (dO18) and hydrogen (dH) isotope ratio data from snow samples taken during MOSAiC leg 4 (PS122.4). Snow samples were taken from several locations around the central observatory (main ice floe. They were collected using a metal density cutter, placed in plastic cups with lids and melted at room temperature. Once completely melted, ~20 ml sub-samples were poured into 20 ml glass or plastic vials with lids and sealed with parafilm tape for isotope analyses. These samples were stored at +4°C. After the sub-samples were taken, bulk salinity was measured on the remaining water sample using a calibrated YSI 30 conductivity meter (practical salinity scale, unitless).The stable oxygen isotopic compositions of the melted snow samples (δ18O) were determined in the central laboratory of the Swiss Federal Institute for Forest, Snow and Landscape, Birmensdorf, Switzerland with an Isotopic Water Analyzer IWA-45-ER (ABB - Los Gatos Research Inc., US). Measurement uncertainty for δ18O is ±1‰, the precision ± 0.5‰. All samples were measured in duplicate and averaged. 169 The quality control was conducted with three standards for δ18O at 0.00‰, -12.34‰ and -55.50‰ and are presented as per mil difference relative to VSMOW (‰, Vienna Standard Mean Ocean Water).
DOI: 10.1594/pangaea.947831
title: Historical and projected (RCP8.5) temperatures and ice depths simulated with the Alfred Wegener Institute Earth System Model (AWI-ESM)

description: This dataset contains the results of a simulation using the global climate model AWI-ESM coupled with the interactive ice sheet model PISM. The simulation consists of a historical run (1850-2014) and a future scenario using the Representative Concentration Pathways scenarios RCP8.5. This scenario spans the years 2006-2100 and was prolonged to the year 2299 with fixed greenhouse gas concentrations. The variables provided are temperature at 2 meters above surface and ice depth. The data are used for a mathematical model to describe long-term changes in extreme temperatures (Contzen, Dickhaus and Lohmann, 2023). This dataset contains spatial data on a regular lon lat grid (0.5°x0.5° horizontal resolution) using monthly time steps. All files are in the NetCDF format.
description: Monthly temperature at 2 meters above surface and ice depth from a run of the AWI Earth System Model (AWI-ESM) that consists of a historical simulation and a future scenario using the RCP8.5 scenario and that ranges from 1850 to 2299.
DOI: 10.34740/kaggle/dsv/7674495
title: WallStreetBets 2022
DOI: 10.1594/pangaea.947536
title: GIS dataset of high-resolution rebound surfaces and ice-free paleotopography of glaciated North America since the LGM based on the ICE-xG (VMy) models' predictions

description: The postglacial rebound is component of the glacial isostatic adjustment which causes the Earth's crust to rebound in regions formerly covered by or adjacent to ice sheets, and subside beneath ocean basins. In North America, the observed postglacial rebound is mainly the result of the Laurentide Ice Sheet deglaciation after it reached its maximum thickness and extent at the Last Glacial Maximum (26.5-19 ka). Global-scale numerical models of glacial isostatic adjustment faithfully reproduce past and current changes in postglacial rebound, but the integration their predictions in a geographic information system to facilitate high-resolution paleotopographic reconstructions remains challenging. We therefore present high-resolution raster datasets of land-deformation and ice-free paleotopography of glaciated North America for several time slices since the Last Glacial Maximum to support geological, paleoenvironmental and archeological studies.
DOI: 10.1594/pangaea.954826
title: HALO wind lidar (level 1) data of the University of Trier for MOSAiC

description: Wind lidar measurements of the atmospheric boundary layer (ABL) were performed during the Multidisciplinary drifting Observatory for Study of Arctic Climate (MOSAiC) from September 2019 to October 2020. A “Halo-Photonics Streamline” (HPS) scanning wind lidar was used, which operates at a wavelength of 1.5 μm. The lidar can operate with a maximum range of 10km and is a programmable scanner, which enables vertical scans in all hemispheric directions. The scan patterns are the vertical azimuth display (VAD), the range-height indicator (RHI), and scans in one direction (STARE). The VAD is used for the determination of wind profiles above the lidar. The RHI scans are performed with different elevation angles. This allows for measurements of cross-sections, but also for the estimation of turbulent kinetic energy (TKE) profiles. Vertical STARE data can be used to compute the vertical wind variance profile. The HALO lidar measurements were performed in cooperation with the University of Leeds (PI Ian Brooks, Brooks 2022a), where the same quality control procedure was applied to the raw data of both HALO wind lidars of the University of Leeds and the University of Trier leading to the level 1 data of this data publication. The lidar raw data are high resolution (~3m along-beam and a few seconds temporal) measurements of lidar backscatter ratio and along-beam Doppler velocity. Data is only available where sufficient particles are available to backscatter the laser beam. The Doppler velocities were corrected for lidar orientation (pitch/roll/heading) and the drift speed of the ice. The result are true earth-relative velocities. The Level 1 data are the data for single beams, and are the basis for the calculation of derived quantities such as the vertical wind profile and wind variances. For the calculation of wind profiles from the single beams of the data e.g. as in Zentek et al. (2018), the lidar_heading must be taken into account. The horizontal direction is the sum of the variables [azimuth_true]+[lidar_heading]. Wind profiles will be published in a separate data publication. Data are provided only for the drift periods. Major data gaps occurred for 14 Feb. 2020 - 17 March 2020 and for 25 March 2020 - 28 March 2020.
description: Variables and units are documented in the Netcdf data.
DOI: 10.1594/pangaea.956209
title: Loss-on-ignition in Hashilan Wetland sediment core, western Iran

description: The proxy data reported here are measured from a sediment core collected from the Hashilan Wetland in the Zagros Mountains of western Iran. For Loss-on-Ignition (LOI), samples with 1 cm3 volume were dried overnight at 105 °C and weighed. The dry samples were combusted at 550 °C for 4 hrs and at 950 °C for 2 hrs to determine OM and CaCO3 contents of the samples, respectively. The percentage of non-carbonate mineral matter (NCMM: LOI residue) was calculated using the following formula: 100 – LOI (in %). The analyses were carried out at the Faculty of Geography, University of Tehran.
DOI: 10.1594/pangaea.956221
title: X-Ray fluorescence analysis of Hashilan Wetland sediment core, western Iran

description: The proxy data reported here are measured from a sediment core collected from the Hashilan Wetland in the Zagros Mountains of western Iran. For X-Ray Fluorescence (XRF) core scanning, samples were dried, ground and measured individually with an ITRAX XRF core-scanner (Cox Analytics) (Croudace et al., 2006; Croudace et al., 2019) following the approach of Profe and Ohlendorf (2019) for measuring discrete samples. Analyses were carried out with the Molybdenum (Mo) X-ray tube with a voltage of 30 kV, a current of 40 mA, and 100 s exposure time. Analyses were carried out in the GEOPOLAR lab at the University of Bremen.
DOI: 10.1594/pangaea.956085
title: Chlorine oxyacids in the Arctic atmosphere measured during MOSAiC campaign in 2020

description: This dataset contains HClO3 and HClO4 (30min-averaged) data, measured with a nitrate-chemical ionization atmospheric pressure interface time-of-flight mass spectrometry (CI-APi-TOF), during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from 15 January 2020 to 30 June 2020. These measurements were performed in the Swiss container on board of Research Vessel Polarstern during the MOSAiC campaign. The data columns include the Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, and the unit of the data has been indicated in each data column.
DOI: 10.1594/pangaea.956087
title: Hydrogen bromide and sulfuric acid in the Arctic atmosphere measured during MOSAiC campaign in 2020

description: This dataset contains 30min-averaged data of HBr (normalized signal) and H2SO4, obtained from nitrate-chemical ionization atmospheric pressure interface time-of-flight mass spectrometry (CI-APi-TOF) for period of 22 February 2020 to 30 April 2020 during the MOSAiC campaign. These measurements were performed in the Swiss container on board of Research Vessel Polarstern during the MOSAiC campaign. The data columns include the Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, and the unit of the data has been indicated in each data column.
DOI: 10.1594/pangaea.956282
title: Mineralogical analysis by X-Ray diffraction of Hashilan Wetland sediment core, western Iran

description: For mineralogical analysis by X-Ray Diffraction (XRD), samples of ~ 1 gram were dried at 50 °C for 48 hours. The dried samples were ground and homogenized using mortar and pestle. XRD analyses were carried out at the Crystallography and Geomaterials Group, Dept. of Geosciences, University of Bremen. The X-ray diffractograms have been measured on a Philips X'Pert Pro multipurpose diffractometer equipped with a Cu-tube (kα 1.541, 45 kV, 40 mA), a fixed divergence slit of ¼°, a 16 samples changer, a secondary Ni-Filter, and the X'Celerator detector system. Measurements were performed as a continuous scan from 3–65° 2θ, with a calculated step size of 0.016° 2θ (calculated time per step was 100 s). Minerals were identified with the Philips/Panalytical software X'Pert HighScore™, which can also give a semi-quantitative value for each identified mineral on the basis of Relative Intensity Ratio (R.I.R)-values. The R.I.R.-values are calculated as the ratio between the intensity of the most intense reflex of a specific mineral phase and the intensity of the most intense reflex of pure corundum (I/Ic) referring to as the "matrix-flushing method" after Chung (1974).
DOI: 10.1594/pangaea.957750
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2021-12-04

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958520
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2021-12-05

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958909
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-07

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958910
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-12

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958911
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-10

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958912
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-13

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958913
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-11

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958915
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-15

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958916
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-14

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958917
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-17

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958918
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-16

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958919
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-18

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958920
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-23

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958921
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-20

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958922
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-19

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958923
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-22

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958924
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-21

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958926
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-27

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958927
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-24

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958928
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-28

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958929
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-29

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958930
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-06-30

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958931
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-18

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958932
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-23

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958933
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-22

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958934
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-21

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958935
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-20

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958936
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-27

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958937
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-26

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958938
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-24

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958939
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-25

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958940
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-29

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958941
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-05-31

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).
DOI: 10.1594/pangaea.958670
title: Video In Situ Snowfall Sensor (VISSS) data for Ny-Ålesund on 2022-01-19

description: The VISSS is a camera system recording precipitating snowfall from two perspectives. Here, movies and images of falling precipitation particles are provided for one day at station Ny-Ålesund. For further details on the VISS Sensor see Maahn et al. (2023).