cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.938233
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T67

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.958402
title: Heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2020T84: 120 s after the heating cycle

description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 120 s.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.1594/pangaea.958401
title: Heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2020T84: 30 s after the heating cycle

description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 30 s.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.1594/pangaea.958416
title: Auxiliary data from SIMBA-type sea ice mass balance buoy 2020T81

description: Geographic position, barometric pressure, tilt and compass.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.1594/pangaea.942679
title: Nano- and microplankton in the northern Patagonian shelf (SW South Atlantic) during austral spring and summer

description: The species composition and structure (e.g. abundance and biomass) of protistan plankton (cell size &gt; 5 µm) and in situ chorophyll a were assessed in a shallow (&lt;50 m depth) inner shelf area of the Argentine Shelf called El Rincón (38º-41°S). Surface water samples (5 m depth) for plankton quantification were taken with Niskin bottles during four oceanographic cruises (two in early austral spring and two in late austral summer- early fall), onboard the vessel B. Houssay accounting for a total of 36 sampling stations. These samples were analyzed under optical microscopy following the inverted microscope technique with sedimentation chambers. Cells enumeration and identification was made up to species, genus or family level, which were afterward categorized in taxonomical groups: diatoms, dinoflagellates, coccolithophores and nanoflagellates. Carbon content was calculated following the method of Menden-Deuer et al. (2000) in which biovolume was estimated assigning a geometrical shape to each species (Hillebrand et al., 1999). The biomass is the result of multiplying the carbon content of a species by its abundance in the sample. The studied area supports important fishes of commercial interest, therefore plankton biodiversity records are neccesary to understand possible shifts at the population and community levels that might have cascading effects on marine ecosystems' productivity.
DOI: 10.1594/pangaea.958442
title: Heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2020T78: 120 s after the heating cycle

description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 120 s.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.1594/pangaea.984741
title: ANT 2016/17: AWI airborne ultra-wideband radar data over the Jutulstraumen Glacier, western Dronning Maud Land, East Antarctica (MABAJU 2 project), Version 2

description: This dataset contains airborne radar data acquired using the AWIs multi-channel ultra-wideband radar system (AWI UWB) during the Antarctic season of 2016/17. The profiles are located near the grounding line of the Jutulstraumen Glacier in western Dronning Maud Land, East Antarctica as well as over the Halvfarryggen ice rise. The data are available as netCDF files (including waveforms and metadata), KML files of the profile line locations, and quicklook images of the radargrams.
description: New Version 2, 2025-09-04 (V1: doi:10.1594/PANGAEA.982758)--Project: MABAJU 2Region: Jutulstraumen ice stream & HalvfarryggenOwner / PI: Angelika Humbert (angelika.humbert@awi.de)Email address of the provider:daniel.steinhage@awi.deveit.helm@awi.deInstrument used: AWI UWB (MCoRDS 5)Data products: CSARP_standard (SAR focussed), CSARP_qlook (unfocussed)Data product documentation: https://data.cresis.ku.edu/data/rds/rds_readme.pdfMethod of navigation : GPS data was acquired by four NovAtel DL-V3 GPS receivers operating at 20Hz--The netCDF files contain the following variables:altitude: Platform altitude (WGS84) in metersbed_elevation: Bed elevation for each trace (without applying a firn correction and permitivity of ice: 3.15) in metersbed_pick: picked Bed location for each trace, expressed as twt in seconds from time zerodata: Radar data (Values in dBm after DC conversion)data_agc: Scaled radar data using automatic gain control (AGC)distance: Along-track distance in metersice_thickness: Ice thickness for each trace (without applying a firn correction and permitivity of ice: 3.15) in meterslat: Latitude in decimal degrees (WGS84)lon: Longitude in decimal degrees (WGS84)range: Range between sensor and surface in metersspacing: Along-track trace to trace spacing in meterssurface: Surface elevation derived from radar (WGS84) in meterssurface_pick: Picked surface reflection in two-way travel time in secondstime: Seconds of daytwt: Two-way travel time (twt) in seconds--Note that the surface picks were quality-checked for the standard product. For the qlook product only an auto-tracked surface pick is available.
DOI: 10.1594/pangaea.958417
title: Temperature measurements from SIMBA-type sea ice mass balance buoy 2020T81

description: Temperature profile from atmosphere through snow and ice into the ocean.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.1594/pangaea.938240
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T75

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.958418
title: Heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2020T81: 30 s after the heating cycle

description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 30 s.
description: The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, position: The geographic position is flagged +1 if the drift velocity, as derived from the GPS longitude and latitude, exceeds a threshold of 10 deg latitude or 50 deg longitude per time step; +2 if the position exceeds extreme values, such as longitude &gt; 360 deg; +4 if the position is exactly 0.0.
DOI: 10.15468/dl.7vhvc8
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Imparfinis cochabambae",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009976-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.947631
title: Abundance of mesopelagic fish collected at different layers of the water column around the Iberian Peninsula

description: This file contains data on number of mesopelagic fish collected during the CSIC-SUMMER survey carried out in October 2020 in five zones around the Iberian Peninsula: Balears and Alboran in the western Mediterranean, and Cadiz, Lisboa and Galicia. The scientific midwater trawl Mesopelagos fitted with a Multisampler placed at the end of the net was used to collect specimens at seven layers of the water column. The depth of the net was controlled by a SCANMAR system. In the five zones, hauls were carried out day and night to study vertical migration patterns of mesopelagic fish. A total of 24 deployments were made (between 0 and 700 m), of which 14 discriminated water layers. Additionally, to more accurately sample the epipelagic layers 7 night hauls were restricted to the first 210 m of the water column. Fish were identified and counted on board, or frozen for later processes in the laboratory. These data were obtained within the European Union Project 'Sustainable Management of Mesopelagic Resources' (SUMMER, Grant Agreement 817806) as funded by the Horizon 2020 Research and Innovation Programme.
DOI: 10.7910/dvn/t0bclc
title: Apocynaceae

description: Conjunto de dados sobre a família botânica Apocynaceae, coletados a partir de diferentes projetos e parcerias em expedições botânicas na Amazônia brasileira, que auxilam a identificação da biodiversidade da flora amazônica.
DOI: 10.1594/pangaea.984879
title: Volume change calculations of glaciers in the Salzburg region, Austria: a new inventory (2008-2018)
DOI: 10.1594/pangaea.984881
title: Area change calculations of glaciers in the Salzburg region, Austria: a new inventory (2008-2018)
DOI: 10.1594/pangaea.984882
title: New glacier boundaries mapped from DEMs, Salzburg region, Austria
DOI: 10.1594/pangaea.986464
title: Stable Isotope Records and Mg/Ca Ratios of the RAT Speleothem from Menorca Island (387–209 ka)

description: This dataset comprises speleothem carbon and oxygen isotope records, Mg/Ca ratios results from the RAT speleothem. The data were used to reconstruct past climate variability in the western Mediterranean region over the interval 387 to 209 ka, encompassing several glacial terminations (TIV, TIII, and TIIIa). The speleothem was collected in winter 2011 from Murada Cave, located on Menorca Island (39°57′58″N; 3°57′53″E). Stable isotope analyses (δ¹³C and δ¹⁸O) were performed with 50 µg of carbonate powder using isotope ratio mass spectrometry (IRMS), and Mg/Ca ratios were measured by inductively coupled plasma mass spectrometry (ICP-MS) at the Scientific and Technological Centres of the University of Barcelona. Analytical uncertainties were ≤ 0.04‰ VPDB for δ¹³C and ≤ 0.08‰ VPDB for δ¹⁸O, NBS19 international standard (Coplen, 1996) was used for calibration.
DOI: 10.1594/pangaea.938227
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T58

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.938231
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T65

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.938235
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T69

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.938238
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T73

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.
DOI: 10.1594/pangaea.938242
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T77

description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.