cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.973396
title: Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2016T37

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2016T37 (a.k.a. Awi_83) is an autonomous instrument that was installed on drifting sea ice in the Antarctic Ocean (Polarstern PS96 (ANT31/2, FROSN) in 2015/16) as part of the project Sea Ice Physics @ AWI (AWI_SeaIce). Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2016-01-15T17:00:39 and 2016-04-03T17:00:40. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.973397
title: Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2016T36

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2016T36 (a.k.a. Awi_82) is an autonomous instrument that was installed on drifting sea ice in the Antarctic Ocean (Polarstern PS96 (ANT31/2, FROSN) in 2015/16) as part of the project Sea Ice Physics @ AWI (AWI_SeaIce). Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2016-01-15T19:00:39 and 2017-04-21T07:00:39. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.973398
title: Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2016T42

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2016T42 (a.k.a. Awi_88) is an autonomous instrument that was installed on drifting sea ice in the Antarctic Ocean (Polarstern PS96 (ANT31/2, FROSN) in 2015/16) as part of the project Advanced Remote Sensing – Ground-Truth Demo and Test Facilities (ACROSS), Sea Ice Physics @ AWI (AWI_SeaIce). Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2016-01-18T14:00:39 and 2016-12-23T08:00:39. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.941610
title: Coccolith export fluxes and environmental data from sediment trap M4U
DOI: 10.1594/pangaea.937435
title: Ammonium (NH4+) raw data in the RECAP ice core, East Greenland, for the past 5000 years

description: This dataset presents the fire proxy ammonium (NH4+) measured in the RECAP ice core, in coastal East Greenland. The datasets cover a period of 5000 years. Ammonium (NH4+) has been measured by fluorescence within the Continuous Flow Analysis setup.
DOI: 10.1594/pangaea.935027
title: Stable oxygen (δ18O) and hydrogen (δD) isotopes in precipitation from Inuvik in the western Canadian Arctic (2015-2018)

description: Precipitation was collected in the city of Inuvik (68.3°N, 133.5°W) in the western Canadian Arctic over 37 months between August 2015 and August 2018. The regular sampling of meteoric water for subsequent stable isotope analysis was conducted at the Aurora Research Institute (Western Arctic Research Centre, 191 Mackenzie Road, Inuvik, NT X0E 0T0, Canada). The samples obtained resulted in 134 valid measurements of the isotopic composition of both snow and rain. The oxygen (δ18O) and hydrogen (δD) stable isotope compositions of precipitation were measured in the Stable Isotope Facility of the Alfred Wegener Institute in Potsdam (Germany), using a Finnigan MAT Delta-S mass spectrometer. Values are given as per mil (‰) difference from the Vienna Standard Mean Ocean Water (VSMOW) standard. Deuterium excess (d) was calculated as: d = δD – 8*δ18O.The goal of this data collection is to present a new local meteoric water line (LMWL) from Inuvik in the western Canadian Arctic. This data set fills a gap in the western Arctic, where isotopic data of precipitation are scarce and stem mostly from before the year 2000. Regional studies of meteorology, hydrology, environmental geochemistry and paleoclimate may benefit from this dataset and the new Inuvik LMWL.
DOI: 10.1594/pangaea.937687
title: Raster land cover product derived from TerraSAR-X imagery for the Komakuk Beach study site on the Beaufort Coast, Canada

description: The dataset contains a high-resolution (5m) land cover classification product for the Komakuk Beach study site located on the Beaufort Coast, Canada. Land cover types were classified using a Random Forest classifier with predictors derived from the Kennaugh elements K0 and K1 of seven dual-polarimetric HH/HV TerraSAR-X images acquired between July and December 2019. Land cover in-situ data were collected in August 2019 and upscaled to image objects (314 to 4766 m2) using segmentation of a WorldView-3 image and ArcticDEM elevation data. The SAR pixel values within these objects were used as reference data for the land cover classification. This dataset was produced to examine the potential of the Kennaugh Element Framework applied on dual-pol SAR data for Arctic tundra land cover classification.
description: TerraSAR-X data were made available by DLR through PI agreement 3645.
DOI: 10.1594/pangaea.974859
title: Bulk total organic carbon content and its isotope composition and biomarker data of sediment core YC22_MR_7 off Herschel island (Yukon Coast 2022)

description: In July 2022 within the framework of an Alfred-Wegener-Institute-managed expedition and the Nunataryuk project, sediment core YC22_MR_7 was taken off the coast of Herschel Island, Canada, using a hand corer. Data sets were obtained to investigate carbon feedback from the sediments to the water column and atmosphere, using DIC concentrations and isotopic values. The local sediments are supplied primarily by organic carbon previously stored in adjacent permafrost soils (biomarker and bulk data), which erode and redeposit quickly (age model) on the ocean floor.The acquired data includes:1) Sediment data: Bulk total organic carbon content (Lamping et al., 2021) and its isotopic values for 13C (Brodie et al., 2011; Werner & Brand, 2001) and 14C (Mollenhauer et al., 2021).2) Biomarker data: Quantifying alkanes (CPI) , and fatty acids (TAR ratio) as described by Wei et al. (2020), Glycerol dialkyl glycerol tetraethers (GDGTs basis for BIT-Index) after Hopmans et al. (2016), Hopanes (fßß) following instructions by Meyer et al., (2019), and Sterols (Dinosterol) after Dauner et al. (2022).
DOI: 10.1594/pangaea.933089
title: KOSMOS 2018 Gran Canaria mesocosm study: particle flux data from sediment trap

description: The data set compiles sinking flux data collected during a KOSMOS mesocosm experiment carried out in the frame work of the Ocean Artificial Upwelling project. The experiment was performed in the North-East Atlantic Ocean off the coast of Gran Canaria in autumn 2018 and lasted for 39 days. In this study we investigated the effect of different intensities of artificial upwelling combined with two upwelling modes (recurring additions versus one singular addition) on POC export and its potential transfer efficiency to depth. The data set includes the amounts of surface water that were exchanged with nutrient-rich deep water (from ~300 m depth). It also contains particle flux data, i.e. POC flux, PON flux, BSi flux and the corresponding C:N and C:Si ratios, as well as the carbon-specific remineralization rates, sinking velocities, porosities and remineralization length scales of sinking particles.
DOI: 10.1594/pangaea.974231
title: Bulk total organic carbon content and its isotope composition data of sediment core YC22_MR_8 off Herschel island (Yukon Coast 2022)

description: In July 2022 within the framework of an Alfred-Wegener-Institute-managed expedition and the Nunataryuk project, sediment core YC22_MR_8 was taken off the coast of Herschel Island, Canada, using a hand corer. Data sets were obtained to investigate carbon feedback from the sediments to the water column and atmosphere, using DIC concentrations and isotopic values. The local sediments are supplied primarily by organic carbon previously stored in adjacent permafrost soils (biomarker and bulk data), which erode and redeposit quickly (age model) on the ocean floor.The acquired data includes sediment data of bulk total organic carbon content (Lamping et al., 2021) and its isotopic values for 13C (Brodie et al., 2011; Werner & Brand, 2001) and 14C (Mollenhauer et al., 2021).
DOI: 10.1594/pangaea.910583
title: Physical oceanography during POSEIDON cruise POS534
DOI: 10.1594/pangaea.950497
title: Observational carbon and nitrogen zooplankton stable isotope and environmental data in the North Atlantic Ocean from 2009-2018

description: Calanus (copepod) sampled by the Continuous Plankton Recorder (CPR) survey (https://www.cprsurvey.org/) in the North Atlantic from 2009-2018 were analysed for stable carbon (d13C) and nitrogen (d15N) isotopes. The stable isotope analysis was done by the Scottish Universities Environmental Research Centre (SUERC) as part of National Environmental Isotope Facility (NEIF). Samples were loaded into an Elementar (Hanau, Germany) Pyrocube elemental analyser, which converted carbon and nitrogen in the samples to carbon dioxide (CO2) and nitrogen (N2) gases. δ13C and δ15N of evolved gases were measured on a Thermo-Fisher-Scientific (Bremen, Germany) Delta XP Plus isotope ratio mass spectrometer. The system was calibrated using laboratory standards and then independently checked for accuracy using USGS 40 glutamic acid reference material (Qi et al., 2003; Coplen et al., 2006). Measurement precision was assessed by running replicates of laboratory standards and resulted in a standard deviation (SD) consistently &lt; 0.1‰ and 0.2‰ for δ13C and δ15N, respectively.This observational dataset was used together with environmental variables (sea surface temperature, mixed layer depth, chlorophyll a, wind speed) to develop Bayesian spatial models and to produce yearly and seasonal isoscapes (spatial modelling of stable isotope ratio) for 1998-2020 (Espinasse 2022).
DOI: 10.1594/pangaea.914798
title: Physical oceanography from two CTD casts during a SponGES cruise with RV G.O. Sars in Sognefjord, Norway
DOI: 10.1594/pangaea.957073
title: Input data of Foraminifera 14C ages, tie-points, reservoir age and calculation settings to generate the age-depth model of ODP Site 202-1235
DOI: 10.1594/pangaea.903177
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during December, 2012
DOI: 10.1594/pangaea.957085
title: SST Proxies of ODP Hole 175-1078C
DOI: 10.1594/pangaea.902740
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during November, 2018
DOI: 10.1594/pangaea.903195
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during August, 2013
DOI: 10.1594/pangaea.903272
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during September, 2016
DOI: 10.1594/pangaea.903214
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during February, 2014
DOI: 10.1594/pangaea.903288
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during December, 2017
DOI: 10.1594/pangaea.931638
title: (Table 1) Sedimentation rate and mean accumulation rate of sediment and dust at Nussloch, Germany

description: Our study focuses on European loess sequences, particularly the eolian intervals in between the observed pedogenic units. The classical concept of soil formation from parent material is reformulated to estimate of the duration and the associated sedimentation rate (SR) and mass accumulation rate (MAR) of these paleodust intervals. We show that the Greenland Stadial (GS) duration in European loess deposits includes the thickness of the overlying pedogenic unit, which in fact developed downward into the upper part of the eolian unit. The lower stratigraphical limit of the eolian unit overlying the pedogenic unit corresponds to the restart of the dust sedimentation of the younger GS. We illustrate this interpretation first by computing both SRs and MARs first for the Nussloch key sequence, the most complete European series. The correlation between Nussloch and other European loess sequences, located along a 1,800 km longitudinal transect, allows computation of SR and MAR for several identified GS events. Comparing GS from marine and ice core records, our study shows that the two last Bond cycles are preserved in every European eolian record. Bulk SR and MAR are estimated and compared for these two Bond cycles, showing the highest SRs and MARs in western Europe. These indices also indicate that the last stadials, embedding an Henrich event, were not the dustiest in every Bond cycle. Our estimated MAR also differ from previously published computations, which did not take into account the various pedogenic units present in the studied loess sequences. The bulk SR and MAR estimates computed for the two last Bond Cycles from Chinese sequences from the Loess Plateau indicate lower atmospheric dust than in Europe during the Last Glacial Maximum. SR and MAR estimates computed from the fine-grained material for European records fit with Earth System model reconstructions.
DOI: 10.1594/pangaea.931652
title: (Table 3) Sedimentation rate and mean accumulation rate of sediment in China
DOI: 10.1594/pangaea.931659
title: (Table 4) Grain size dependent mean accumulation rate of sediments in Europe
DOI: 10.1594/pangaea.903337
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during February, 2019
DOI: 10.1594/pangaea.903334
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during January, 2019
DOI: 10.1594/pangaea.903144
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during August, 2011
DOI: 10.1594/pangaea.903156
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during January, 2012
DOI: 10.1594/pangaea.903261
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during March, 2016
DOI: 10.1594/pangaea.903163
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during May, 2012
DOI: 10.1594/pangaea.903176
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during November, 2012
DOI: 10.1594/pangaea.903186
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during February, 2013
DOI: 10.1594/pangaea.903293
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during March, 2018
DOI: 10.1594/pangaea.903297
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during May, 2018
DOI: 10.1594/pangaea.903300
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during June, 2018
DOI: 10.1594/pangaea.931282
title: Raw data from Pure-rotational and Vibro-rotational Raman Lidar signals from MDPI-Sensors 1074075 and retrieved aerosol optical and extiction coefficients

description: The data correspond to measurements along a vertical line of sight carried out by the multiwavelength Raman / elastic EARLINET/ACTRIS lidar at Universitat Politècnica de Catalunya (UPC, Barcelona, Spain) on March, 11th 2020 and on March 21th 2020.sensors-20210202T183221Z-001_Input_files are the raw data files in netCDF format generated by the multiwavelength Raman / elastic EARLINET/ACTRIS lidar at Universitat Politècnica de Catalunya (UPC, Barcelona, Spain) submitted as input to the EARLINET Single Calculus Chain (SCC, https://scc.imaa.cnr.it/) centralized software processing the data and retrieving, among other products, range-resolved aerosol extinction and backscatter coefficients.sensors-1074075_Output_ files contain the netCDF files containing the aerosol extinction and backscatter coefficients retrieved by the SCC.
DOI: 10.1594/pangaea.903161
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during April, 2012
DOI: 10.1594/pangaea.903243
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during February, 2015
DOI: 10.1594/pangaea.903299
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during June, 2018
DOI: 10.1594/pangaea.903278
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during February, 2017
DOI: 10.1594/pangaea.903242
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during February, 2015
DOI: 10.1594/pangaea.903246
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during April, 2015
DOI: 10.1594/pangaea.903264
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during May, 2016
DOI: 10.1594/pangaea.903271
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during August, 2016
DOI: 10.1594/pangaea.903283
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during July, 2017
DOI: 10.1594/pangaea.911151
title: Bottom trawl positions from year 2002 to 2013 of the EU NAFO groundfish surveyon boards R/V Vizconde de Eza

description: Tows from year 2002 to 2013 of the EU NAFO groundfish survey, with biomass data of different invertebrates (Sponges, Sea Pens, Large Gorgonians and small Gorgonias) and presence of pennatulaceans. Gear used was a Bottom trawl. Since 2003, all surveys were conducted using the Spanish R/V Vizconde de Eza. Until 2005, the invertebrate data collection was non systematic (it was sporadic) and only few sponge data was collected. The "-" means that there is NO DATA AVAILABLE.. EU NAFO groundfish surveys (NAFO Div. 3MNLO) has been co-funded by the European Union through the European Maritime and Fisheries Fund within the National Program. Data Citation: Reports of bottom trawl surveys (2007-2017) on boards R/V Vizconde de Eza