cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.966718
title: Glacier mass balance Jamtalferner, Silvretta, Austria, 2022/2023

description: The glacier mass balance of Jamtalferner has been measured annually since 1988/1989 with the direct/glaciological method. Winter mass balance has been determined for 1 May in all years. The mass balance records are complemented by precipitation measurements at a gauge close to the glacier tongue and climate data recorded at the village of Galtür. The project is supported by the Federal Government of Tyrol. Research results are also provided within the Environmental Education Centre Jamtal (http://www.umweltbildung-jamtal.info/). Jamtalferner is a LTER site and part of WMO's Global Crosphere Watch watch program as well as a WGMS benchmark glacier.
DOI: 10.1594/pangaea.939836
title: Surface elevation change rates of most glaciers on Franz Josef Land, Severnaya Zemlya and Novaya Zemlya between 2010 and 2017

description: Glaciers in the Russian High Arctic have been subject to large environmental changes due to global warming. Here we provide surface elevation change rates of most glaciers on Franz Josef Land, Severnaya Zemlya and Novaya Zemlya between 2010 and 2017.The dataset includes glacier elevation change maps of glaciers of the Russian Arctic archipelagos (Franz Josef Land, Severnaya Zemlya & Novaya Zemlya) for the period winter 2010/11 to winter 2016/17. Elevation change rates (unit: m/a) are calculated from differencing interferometric Digital Elevation Models (DEMs) of the TanDEM-X satellite mission. Glacier areas are derived from the Randolph Glacier Inventory V6.0 (09_rgi60_RussianArctic). All elevation change maps are provided as GeoTiffs with a spatial resolution of 30m (EPSG:3995). Additionally, raster files with the observation period in years per cell are included.
DOI: 10.1594/pangaea.945277
title: Uranium series ages of cold-water corals from east Equatorial Atlantic and Reykjanes Ridge

description: U-series ages of deep-sea corals from east Equatorial Atlantic and Reykjanes Ridge defined by laser ablation method. Depths of east Equatorial Atlantic corals was retrieved by ROV. Depths of Reykjanes Ridge corals corresponds to the mean depth of the dredge on and off bottom, and depth range is the depth interval between the dredge on and off bottom. Selection code column indicates samples included (accepted) and not included (rejected) on age distribution discussion.
description: Column "depth range" corresponds to the depths between the depths of the dredge on and off bottom. This column is only applicable for the Reykjanes Ridge coral samples, since corals from east Equatorial Atlantic were collected by ROV.
DOI: 10.1594/pangaea.979843
title: Emission Rate Estimates of Methane and Carbon Dioxide at Several Sectors in New York State in 2021

description: Aircraft measurements of methane and carbon dioxide mixing ratios were carried out by Champion X at several facilities in New York State in 2021. This dataset includes the calculated emission rates and uncertainties from each of the sampled facilites. The emission rate data includes all estimated CH4 and CO2 emission rates calculated by Champion X using a mass balance approach. It also includes the number of laps, wind direction (deg) and speed (m/s), start and end time, lowest and highest altitude measured (m), surface fraction, mean radius of the loop around the facility (m), temperature (C), and latitude and longitude coordinates. Measurements were made using a single-engine Mooney aircraft where ambient air was drawn in through the rearward-facing inlets mounted on the wing of the aircraft. In situ methane, carbon dioxide, and water vapor were recorded using a Picarro G2401 cavity ring down spectrometer at 1 Hz with calibrations done in-flight. Horizontal wind speed and direction are calculated following the method outlined in Conley et al. (2014), which combines pitot-static pressure airspeed measurement with GPS-calculated aircraft heading and ground speed. Meteorological parameters were measured using a Vaisala HMP60 probe and geographical coordinates recorded through a Hemisphere high-precision differential GPS. Further descriptions of the aircraft, analyzer precision and accuracy, and met data can be found elsewhere (Conley et al., 2017; Karion et al., 2015; Peischl et al., 2016; Ravikumar et al., 2024; Smith et al., 2015).
DOI: 10.1594/pangaea.966941
title: KOSMOS 2021 Gran Canaria mesocosm study on ocean alkalinity enhancement: water column biogeochemistry and pigments

description: This data was collected as a part of a mesocosm study to investigate the ecosystem impacts of ocean alkalinity enhancement, within the EU H2020 OceanNETs project. Nine mesocosms were deployed in Taliarte Harbour (Gran Canaria, Spain) and were regularly sampled using integrated water samplers between 10th September-25th October 2021. A gradient design was used in this experiment with a total of nine different alkalinity concentrations. Seawater alkalinity ranged between ambient (0 µeq kg-1 added alkalinity, OAE0) and 2400 µeq kg-1 additional alkalinity (OAE2400). The alkalinity levels increased in equal intervals of 300 µeq kg-1 across nine mesocosms (OAE0, OAE300, OAE600, OAE900, OAE1200, OAE1500, OAE1800, OAE2100, OAE2400). This data set contains water column biogeochemistry variables (inorganic nutrients, carbonate chemistry, particulate matter) as well as pigment concentrations from these nine mesocosms.
description: values marked with ? = questionable value i.e. potential sample contamination, or analytical issues
DOI: 10.1594/pangaea.971786
title: Glacier velocity maps over 2014-2019 on the Kenai Peninsula, Alaska

description: We used the Python Glacier Evolution Model (PyGEM) to model monthly glacier-wide climatic mass balance and runoff for all glaciers on the Peninsula from 2005 to 2019. It estimates the climatic mass balance (the sum of accumulation, melt, and refreezing) for each glacier using ~10 m elevation bins, the ice thickness, and a monthly time step forced with near-surface air temperature and precipitation data. The model is calibrated by the Geodetic mass balance data and validated by the in-situ data from US Geological Survey Benchmark Glaciers datasets (https://doi.pangaea.de/10.1594/PANGAEA.970133). We also used the Sentinel-1 data basing offset tracking method to derive velocity maps for glaciers on the Kenai Peninsula from Oct 2014 to Dec 2019 (this dataset).
DOI: 10.1594/pangaea.979845
title: Raw Aerial Observations of Methane and Carbon Dioxide at Several Sectors in New York State in 2021

description: Aircraft measurements of methane and carbon dioxide mixing ratios were carried out by Champion X at several facilities in New York State in 2021. This dataset includes the observed raw methane and carbon dioxide mixing ratios of the sampled facilites. Measurements were made using a single-engine Mooney aircraft where ambient air was drawn in through the rearward-facing inlets mounted on the wing of the aircraft. In situ methane, carbon dioxide, and water vapor were recorded using a Picarro G2401 cavity ring down spectrometer at 1 Hz with calibrations done in-flight. Horizontal wind speed and direction are calculated following the method outlined in Conley et al. (2014), which combines pitot-static pressure airspeed measurement with GPS-calculated aircraft heading and ground speed. Meteorological parameters were measured using a Vaisala HMP60 probe and geographical coordinates recorded through a Hemisphere high-precision differential GPS. Further descriptions of the aircraft, analyzer precision and accuracy, and met data can be found elsewhere (Conley et al., 2017; Karion et al., 2015; Peischl et al., 2016; Ravikumar et al., 2024; Smith et al., 2015).
DOI: 10.1594/pangaea.945279
title: Uranium series dated cold-water corals from Tropic Seamount, Reykjanes Ridge, and East Equatorial Atlantic

description: Uranium series dated cold-water corals from Tropic Seamount, Reykjanes Ridge, and East Equatorial Atlantic. Ages are reported in years before present (BP; where present is the year of 1950 CE) both uncorrected and corrected for initial 232Th. Some samples did not pass our quality control. Selection code column indicates samples not included on age distribution discussion: [238U] &lt;2 ppm (Low U), [232Th] &gt;6 ppb (High Th), [δ234Ui] &gt;157‰ (High δU) and lowest quality sub-sample (duplicate).
DOI: 10.1594/pangaea.970133
title: Glacier mass balance and runoff over 2005-2019 on the Kenai Peninsula, Alaska

description: We used the Python Glacier Evolution Model (PyGEM) to model monthly glacier-wide climatic mass balance and runoff for all glaciers on the Peninsula from 2005 to 2019. It estimates the climatic mass balance (the sum of accumulation, melt, and refreezing) for each glacier using ~10 m elevation bins, the ice thickness, and a monthly time step forced with near-surface air temperature and precipitation data. The model is calibrated by the Geodetic mass balance data and validated by the in-situ data from US Geological Survey Benchmark Glaciers datasets (this dataset). We also used the Sentinel-1 data basing offset tracking method to derive velocity maps for glaciers on the Kenai Peninsula from Oct 2014 to Dec 2019 (https://doi.pangaea.de/10.1594/PANGAEA.971786).
DOI: 10.1594/pangaea.945723
title: Compilation of cold-water coral dated by U-series or radiocarbon of Northeast Atlantic Ocean

description: Compilation of cold-water coral dated by U-series or radiocarbon of Northeast Atlantic Ocean. Age column corresponds to reported U-series corrected ages or calendar 14C ages re-calculated. Re-calibrated 14C ages column corresponds to 14C ages calculated using CALIB8.10 software, Marine20 calibration curve, and age offset with Marine20 indicated at column "Local offset with Marine20".
DOI: 10.1594/pangaea.938228
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T62

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.938234
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T68

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.938232
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T66

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.973140
title: Pb isotope composition in the ferromanganese crust PS75/247-2

description: Lead (Pb) isotope measurements are performed in the ferromanganese crust PS75/247-2, dredged on the southern flank of Haxby Seamount in the Pacific sector of the SO, using laser ablation coupled to a MC-ICP-MS (LA-MC-ICP-MS). The measurement is targeted at the bulk sample in this crust. We used smaller laser spot sizes (each integrating about 8 kyr of growth) to resolve glacial-interglacial cyclic Pb isotope variations in the youngest part of our record. We also used larger laser spot sizes to integrate a sampling interval of approximately 40 kyr of growth (i.e., one early Pleistocene glacial cycle) in order to detect long-term changes beyond orbital cyclicity throughout the past 20 Ma. In order to verify the laser ablation-based Pb isotope data, the Pb isotope compositions of samples from 10 different depths in crust Haxby was also analysed by conventional solution-based method. The depth in the sample list represents the distance from the measurement spot to the sample surface.Pb isotope is a sensitive water mass tracer and our data reveal that the Antarctic Circumpolar Current (ACC) has experienced five stable circulation states since the early Miocene which were separated by four major transitions observed at 17.5-14.6, 12, 10 and 5 Ma. According to our data the modern ACC configuration formed 5 million years ago, likely in response to the closure of the Panama Seaway. Our data also show that changes in the latitudinal position of the ACC were linked to the middle Miocene waxing and waning of the Antarctic ice sheets, which emphasizes the ACC's critical role as a key control of Antarctic glaciation.
DOI: 10.1594/pangaea.938229
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T63

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.938239
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T74

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.914118
title: Surface elevation changes of glaciers in the European Alps between 2000 and 2014

description: Glaciers in the European Alps are known to be strongly affected by global climate change. Here we provide temporally consistent changes in glacier area, surface elevation and ice mass over the entire European Alps between 2000 and 2014. Our measurements show strong glacier surface lowering throughout the European Alps with regional variability in average ice thickness changes (-0.5 to -0.9 ma-1). For the entire Alps we estimate a mass loss of 1.3±0.2 Gta-1 (2000-2014). Our results provide important information for future socio-economic research, such as water resource management, tourism and risk assessment, and for the calibration and validation of glacier change projections.The dataset includes glacier elevation change maps (GeoTiffs) of the entire European Alps for the periods 2000-2012 and 2000-2014. Elevation changes are derived from differencing Digital Elevation Models (DEMs) of the SRTM and TanDEM-X satellite missions. Average surface elevation change rates (ma-1) were calculated based on specifically generated glacier outlines (2000, 2011 & 2014) and outlines of the Randolph Glacier Inventory (V6.0 Central Europe). Elevation change maps are cropped to Randolph Glacier Inventory outlines and the spatial union of specific glacier outlines from 2000 and 2011 (for elevation change 2000-2012) and 2000 and 2014 (for elevation change 2000-2014), respectively. See the associated publication for further details regarding the datasets and calculation of surface elevation change and geodetic mass change with a temporal mean area. All elevation change maps are provided as GeoTiffs with a spatial resolution of approximately 30m. Please note that the provided elevation change measurements are not filtered (no outlier removal applied).The observation period of each raster cell is measured in years between the respective TanDEM-X DEM and the SRTM reference DEM. As reference date the mean date of the SRTM mission (2000-02-16) is used.
DOI: 10.1594/pangaea.938241
title: Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T76

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.