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  • 1
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    About this title - Characterization, Prediction and Modelling of Crustal Present-DayIn-SituStresses (2023)
    In:  Characterization, Prediction and Modelling of Crustal Present-Day In-Situ Stresses | Geological Society special publication
    Details
    Publication Date: 2024-04-24
    Type: info:eu-repo/semantics/bookPart
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  • 2
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    Characterization, Prediction and Modelling of Crustal Present-Day In-Situ Stresses (2024)
    Geological Society of London
    In:  Geological Society Special Publication
    Details
    Publication Date: 2024-04-24
    Language: English
    Type: info:eu-repo/semantics/book
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  • 3
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    Synchronizing the Western Gotland Basin (Baltic Sea) and Lake Kälksjön (central Sweden) sediment records using common cosmogenic radionuclide production variations (2024)
    In:  Holocene
    Details
    Publication Date: 2024-04-24
    Description: Multi-archive studies of climate events and archive-specific response times require synchronous time scales. Aligning common variations in the cosmogenic radionuclide production rate via curve fitting methods provides a tool for the continuous synchronization of natural environmental archives down to decadal precision. Based on this approach, we synchronize 10Be records from Western Gotland Basin (WGB, Baltic Sea) and Lake Kälksjön (KKJ, central Sweden) sediments to the 14C production time series from the IntCal20 calibration curve during the Mid-Holocene period ~6400 to 5200 a BP. Before the synchronization, we assess and reduce non-production variability in the 10Be records by using 10Be/9Be ratios and removing common variability with the TOC record from KKJ sediments based on regression analysis. The synchronizations to the IntCal20 14C production time scale suggest decadal to multi-decadal refinements of the WGB and KKJ chronologies. These refinements reduce the previously centennial chronological uncertainties of both archives to about ± 20 (WGB) and ±40 (KKJ) years. Combining proxy time series from the synchronized archives enables us to interpret a period of ventilation in the deep central Baltic Sea basins from ~6250 to 6000 a BP as possibly caused by inter-annual cooling reducing vertical water temperature gradients allowing deep water formation during exceptionally cold winters.
    Type: info:eu-repo/semantics/article
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  • 4
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    The quest for high fidelity, accurate geomechanical models and the research leading to it (2024)
    In:  Characterization, Prediction and Modelling of Crustal Present-Day In-Situ Stresses | Geological Society special publication
    Details
    Publication Date: 2024-04-24
    Description: Geomechanics has a marked impact on the safe and sustainable use of the subsurface. This Special Publication contains contributions detailing the latest efforts in present-day in-situ stress characterization, prediction and modelling from the borehole to plate-tectonic scale. A particular emphasis is on the uncertainties that are often associated with geomechanics.
    Language: English
    Type: info:eu-repo/semantics/bookPart
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  • 5
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    Contribution of cryoconite holes in the supraglacial discharge of bioavailable iron in Larsemann Hills, East Antarctica (2024)
    In:  Polar Science
    Details
    Publication Date: 2024-04-24
    Description: Supraglacial discharge of limiting micronutrients such as iron (Fe) into high-nutrient low-chlorophyll (HNLC) regions like the Southern Ocean has recently drawn global attention. In this study, we aim to understand the contribution of cryoconite holes (comprising a meltwater column with an underlying layer of sediment) to the discharge of Fe through the glacier runoff. Cryoconite hole meltwater collected from the Larsemann Hills, East Antarctica showed a higher concentration of dissolved Fe (dFe: 71.2 μgL−1) and total Fe extractable from suspended sediments (exFe: 362.1 μgL−1) than in the adjacent streams (dFe: 30.5 μgL−1; exFe: 21.2 μgL−1) and melt pools (dFe: 42.3 μgL−1; exFe: 5.8 μgL−1). Predictive pathways (using PICRUSt2) show that cryoconite hole bacterial communities could acquire Fe and other trace elements using different mechanisms, such as the biosynthesis of siderophores, and transport proteins, therefore influencing the trace metal chemistry in these and other environments that drain cryoconite hole contents. Estimated discharge of dFe (11.4 kg km−2 a−1) and exFe (57.9 kg km−2 a−1) within cryoconite holes are 2 and 17 times higher, respectively than the discharge from the adjacent supraglacial streams, indicating that cryoconite holes are an important source of potentially bioavailable Fe to the HNLC region.
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  • 6
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    Erdbebensicherheit von Hochwasserrückhaltebecken und Talsperren - Kompendium für Betreiber und Wasserbehörden (2016)
    LUBW Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg
    Details
    Publication Date: 2024-04-24
    Description: Die DIN 19700:2004-07 "Stauanlagen fordert für Hochwasserrückhaltebecken und Talsperren die Prüfung der Einwirkung von Erdbeben. Ausgehend von der Erdbebengefahr am Standort müssen Nachweise hinsichtlich der Zuverlässigkeit der Stauanlage im Erdbebenfall geführt werden. Für die Betreiber und die Wasserbehörden gibt das vorliegende Kompendium einen zusammenfassenden Überblick über die Grundlagen der Erdbebennachweisführung entsprechend den DIN-Vorgaben. Die Anforderungen an die Nachweisführung sowie eine Leistungsbeschreibung für die zu beauftragenden Fachbüros werden gegeben. Ferner werden Hinweise zum Betrieb der Stauanlage erläutert. Es wird dargestellt, wie die Stauanlagen in Hinsicht auf eine Erdbebeneinwirkung zu überwachen sind.
    Language: German
    Type: info:eu-repo/semantics/book
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  • 7
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    Persistent microbial communities in hyperarid subsurface habitats of the Atacama Desert: Insights from intracellular DNA analysis (2024)
    In:  PNAS Nexus
    Details
    Publication Date: 2024-04-24
    Description: Desert environments constitute one of the largest and yet most fragile ecosystems on Earth. Under the absence of regular precipitation, microorganisms are the main ecological component mediating nutrient fluxes by using soil components, like minerals and salts, and atmospheric gases as a source for energy and water. While most of the previous studies on microbial ecology of desert environments have focused on surface environments, little is known about microbial life in deeper sediment layers. Our study is extending the limited knowledge about microbial communities within the deeper subsurface of the hyperarid core of the Atacama Desert. By employing intracellular DNA extraction and subsequent 16S rRNA sequencing of samples collected from a soil pit in the Yungay region of the Atacama Desert, we unveiled a potentially viable microbial subsurface community residing at depths down to 4.20 m. In the upper 80 cm of the playa sediments, microbial communities were dominated by Firmicutes taxa showing a depth-related decrease in biomass correlating with increasing amounts of soluble salts. High salt concentrations are possibly causing microbial colonization to cease in the lower part of the playa sediments between 80 and 200 cm depth. In the underlying alluvial fan deposits, microbial communities reemerge, possibly due to gypsum providing an alternative water source. The discovery of this deeper subsurface community is reshaping our understanding of desert soils, emphasizing the need to consider subsurface environments in future explorations of arid ecosystems.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 8
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    Increasing accuracy of 3-D geomechanical-numerical models (2024)
    In:  Geophysical Journal International
    Details
    Publication Date: 2024-04-24
    Description: The current crustal stress field is of key importance to understand geodynamic processes and to assess stability aspects during subsurface usage. To provide a 3-D continuous description of the stress state, linear elastic forward geomechanical-numerical models are used. These models solve the equilibrium of forces between gravitational volume forces and surfaces forces im- posed mainly by plate tectonics. The latter are responsible for the horizontal stress anisotropy and impose the inverse problem to estimate horizontal displacement boundary conditions that provide a fit best to horizontal stress magnitude data within the model volume. Ho wever , horizontal stress magnitude data have high uncertainties and they are sparse, clustered and not necessaril y representati ve for a larger rock v olume. Even w hen Bay esian statistics are incor - porated and additional stress information such as borehole failure observations or formation integrity test are used to further constrain the solution space, this approach may result in a low accuracy of the model results, that is the result is not correct. Here, we present an alternative approach that removes the dependence of the solution space based on stress magnitude data to avoid potential low accuracy . Initially , a solution space that contains all stress states that are physically reasonable is defined. Stress magnitude data and the additional stress information are then used in a Bayesian framework to e v aluate which solutions are more likely than others. We first show and validate our approach with a generic truth model and then apply it to a case study of the Molasse foreland basin of the Alps in Southern Germany. The results show that the model’s ability to predict a reliable stress state is increasing while the number of likely solutions may also increase, and that outlier of stress magnitude data can be identified. This alternative approach results in a substantial increase in computational speed as we perform most of the calculations anal yticall y.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 9
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    (Table 3) Fatty acid and fatty alcohol composition of neutral lipids of Calanus finmarchicus CV at the northern Mid-Atlantic Ridge (2010)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Keywords: 6,9,12,15-Hexadecatetraenoic acid of total fatty acids; 6,9,12-Hexadecatrienoic acid of total fatty acids; 9-Tetradecenoic acid of total fatty acids; all-cis-3,6,9,12,15-Octadecapentaenoic acid of total fatty acids; all-cis-4,7,10,13,16,19-Docosahexaenoic acid of total fatty acids; all-cis-5,8,11,14,17-Eicosapentaenoic acid of total fatty acids; all-cis-5,8,11,14-Eicosatetraenoic acid of total fatty acids; all-cis-6,9,12,15-Octadecatetraenoic acid of total fatty acids; all-cis-7,10,13,16,19-Docosapentaenoic acid of total fatty acids; all-cis-8,11,14,17-Eicosatetraenoic acid of total fatty acids; all-cis-9,12,15-Octadecatrienoic acid of total fatty acids; all-cis-9,12-Octadecadienoic acid of total fatty acids; cis-11-Docosenoic acid of total fatty acids; cis-11-Hexadecenoic acid of total fatty acids (IUPAC: (11Z)-hexadec-11-enoic acid); cis-11-Icosenoic acid of total fatty acids; cis-13-Docosenoic acid of total fatty acids; cis-13-Icosenoic acid of total fatty acids; cis-7-Hexadecenoic acid of total fatty acids; cis-9-Hexadecenoic acid of total fatty acids (IUPAC: (9Z)-hexadec-9-enoic acid); cis-9-Icosanoic acid of total fatty acids; cis-9-Octadecenoic acid of total fatty acids (IUPAC: Octadec-9-enoic acid); CTD, Seabird; CTD-R; DATE/TIME; Docosanoic acid of total fatty acids; Event label; Fatty acids; Fatty acids, standard deviation; Fatty alcohols; Fatty alcohols, standard deviation; Gas chromatography, Agilent 6890 N GC System, Agilent Technologies; Hexadecanoic acid of total fatty acids; Hexadecanol of total fatty alcohols; High Performance Liquid Chromatography (HPLC); Latitude of event; Longitude of event; Octadecanoic acid of total fatty acids; Percentage; Ratio; ReykjanesR_St10; ReykjanesR_St12; ReykjanesR_St18; ReykjanesR_St20; ReykjanesR_St4; ReykjanesR_St8; Sample amount; Sample type; South Atlantic Ocean; Species; Standard deviation; Tetradecanoic acid of total fatty acids; Tetradecanol of total alcohols
    Type: Dataset
    Format: text/tab-separated-values, 468 data points
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  • 10
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    Benthic fauna counts of ROV dive INDEX2016_16ROV (2018)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Keywords: Alviniconcha marisindica; Austinograea rodriguezensis; Bathymodiolus septemdierum; Chiridota; File name; INDEX2016; INDEX2016_16ROV; Maractis; Munidopsis pallida; Neolepas marisindica; Phymorhynchus; Pourquoi Pas ? (2005); Rimicaris kairei; South East Indian Ridge; Total counts; Uniform resource locator/link to image; VICTOR; Victor6000 ROV; Zoarcidae
    Type: Dataset
    Format: text/tab-separated-values, 1703 data points
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  • 11
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    Silt and age analysis from sediment core KNP178-56JPC (2019)
    PANGAEA
    In:  Woods Hole Oceanographic Institution, Department of Geology & Geophysics
    Details
    Publication Date: 2024-04-24
    Keywords: Age; AGE; Atlantic meridional overturning circulation; ATLAS; A Trans-Atlantic assessment and deep-water ecosystem-based spatial management plan for Europe; deep water formation; Depth, composite; DEPTH, sediment/rock; Intercore correlation; Knorr; KNR178; KNR178-56JPC; PC; Piston corer; smoothed; sortable silt; Sortable-silt mean; subsurface ocean temperatures
    Type: Dataset
    Format: text/tab-separated-values, 369 data points
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  • 12
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    Spheroidal carbonaceous particle from sediment core KNR178-56JPC (2019)
    PANGAEA
    In:  Woods Hole Oceanographic Institution, Department of Geology & Geophysics
    Details
    Publication Date: 2024-04-24
    Keywords: Atlantic meridional overturning circulation; ATLAS; A Trans-Atlantic assessment and deep-water ecosystem-based spatial management plan for Europe; deep water formation; Depth, bottom/max; Depth, corrected; DEPTH, sediment/rock; Depth, top/min; Knorr; KNR178; KNR178-56JPC; PC; Piston corer; sortable silt; Spheroidal carbonaceous particle, per unit sediment dry mass; subsurface ocean temperatures
    Type: Dataset
    Format: text/tab-separated-values, 72 data points
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  • 13
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    Age analysis from sediment core KNR178-48JPC (2019)
    PANGAEA
    In:  Woods Hole Oceanographic Institution, Department of Geology & Geophysics
    Details
    Publication Date: 2024-04-24
    Keywords: Age, comment; Age, dated; Age, dated standard error; Atlantic meridional overturning circulation; ATLAS; A Trans-Atlantic assessment and deep-water ecosystem-based spatial management plan for Europe; Calendar age; deep water formation; DEPTH, sediment/rock; Fraction modern carbon; Fraction modern carbon, error; Knorr; KNR178; KNR178-48JPC; PC; Piston corer; Sample code/label; Sample ID; sortable silt; subsurface ocean temperatures; Taxon/taxa
    Type: Dataset
    Format: text/tab-separated-values, 44 data points
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  • 14
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    XRF and biogeochemical characteristics of sediment core PG2201 from Lake Malaya Chabyda, Central Yakutia (2021)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Keywords: Aluminium, area, total counts; Aluminium, calibrated elemental proportions; Aluminium, chi-square; Aluminium, standard deviation; AWI_Envi; AWI Arctic Land Expedition; Bismuth, area, total counts; Bismuth, chi-square; Bismuth, proportion; Bismuth, standard deviation; Bromine, area, total counts; Bromine, chi-square; Bromine, proportion; Bromine, standard deviation; Calcium, area, total counts; Calcium, chi-square; Calcium, proportion; Calcium, standard deviation; Calcium/Titanium ratio; Carbon; Carbon, inorganic, total; Carbon, organic, total; Carbon, organic, total/Nitrogen, total ratio; Carbon and Nitrogen and sulfur (CNS) isotope element analyzer, Elementar, Elementar Vario MAX Cube; Chloride, area, total counts; Chlorine, chi-square; Chlorine, proportion; Chlorine, standard deviation; Chromium, area, total counts; Chromium, chi-square; Chromium, proportion; Chromium, standard deviation; COMPCORE; Composite Core; Copper, area, total counts; Copper, chi-square; Copper, proportion; Copper, standard deviation; Density; Density, dry bulk; DEPTH, sediment/rock; Elemental analyzer, Vario SoilTOC cube; File name; Gallium, area, total counts; Gallium, chi-square; Gallium, proportion; Gallium, standard deviation; Holocene; Iron, area, total counts; Iron, chi-square; Iron, proportion; Iron, standard deviation; Iron/Calcium ratio; Iron/Manganese ratio; Iron/Titanium ratio; Lake Malaya Chabyda, Yakutia, Russia; Lake sediment core; Late Pleistocene; Lead, area, total counts; Lead, chi-square; Lead, proportion; Lead, standard deviation; Manganese, area, total counts; Manganese, chi-square; Manganese, proportion; Manganese, standard deviation; Manganese/Iron ratio; Manganese/Titanium ratio; Mass; Mass spectrometer ThermoFisher Delta V Advantage; Molybdenum, area, total counts; Molybdenum, chi-square; Molybdenum, proportion; Molybdenum, standard deviation; Niobium, area, total counts; Niobium, chi-square; Niobium, proportion; Niobium, standard deviation; Nitrogen, total; organic carbon; Paleolimnology; PG2201_site; Phosphorus, area, total counts; Phosphorus, chi-square; Phosphorus, proportion; Phosphorus, standard deviation; Polar Terrestrial Environmental Systems @ AWI; Porosity, fractional; Potassium, area, total counts; Potassium, chi-square; Potassium, proportion; Potassium, standard deviation; Rhenium, area, total counts; Rhenium, chi-square; Rhenium, proportion; Rhenium, standard deviation; Rubidium, area, total counts; Rubidium, chi-square; Rubidium, standard deviation; RU-Land_2013_Yakutia; Sample code/label; Sample mass; Sample volume; Siberian permafrost; Silicon, area, total counts; Silicon, chi-square; Silicon, proportion; Silicon, standard deviation; Silicon/Titanium ratio; stable carbon isotopes δ13C; Strontium, area, total counts; Strontium, chi-square; Strontium, proportion; Strontium, standard deviation; Sulfur, area, total counts; Sulfur, chi-square; Sulfur, proportion; Sulfur, standard deviation; Titanium, area, total counts; Titanium, chi-square; Titanium, proportion; Titanium, standard deviation; Water content, wet mass; X-ray fluorescence (XRF); X-ray fluorescence core scanner (XRF), Avaatech; Yakutia2013; Yttrium, area, total counts; Yttrium, chi-square; Yttrium, proportion; Yttrium, standard deviation; Zinc, area, total counts; Zinc, chi-square; Zinc, proportion; Zinc, standard deviation; Zirconium, area, total counts; Zirconium, chi-square; Zirconium, standard deviation; Zirconium/Rubidium ratio; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 68144 data points
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  • 15
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    Temperature, electrical conductivity, DOC, CDOM, stable water isotopes and major ions of Lena River water from April 2018 to April 2019 (2020)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: A number of studies expect an increase of carbon export by rivers to the Arctic Ocean due to rapidly changing climate in the Arctic One possible reason for the increase of carbon export is thawing permafrost, which can lead to a mobilization of previously frozen dissolved organic matter (DOM). Scarce measurements of DOC and the coloured fraction of DOM (CDOM) (〈 8 samples/year) were previously used to estimate fluxes to the Arctic Ocean for the whole year. Here, we present a new high frequency sampling program and its viability to monitor export fluxes of DOM and its biogeochemistry in the Lena River. This dataset includes measurements of several water parameters, such as temperature, electric conductivity, dissolved organic carbon (DOC), spectral CDOM absorption (aCDOM), stable water isotopes and major ions. The high sampling frequency throughout the whole year facilitats the identification of the main drivers behind the seasonality of DOM concentration and biogeochemistry of the Lena River. The high number of samples throughout the whole year allows flux calculations that are independently from load models that likely lead to a large variation of earlier studies. Optical indices reveal changing composition and sources of DOM throughout the year. This dataset represents the first year (April 2018 to April 2019) of a planned long-term monitoring program at the Research Station Samoylov Island and provides a baseline data set against which future change of this large integrative system may be measured. A continuous sampling of Arctic River water will facilitate to identify intra and inter-annual trends with ongoing climate change.
    Keywords: Absorption coefficient, colored dissolved organic matter at given wavelength; Aluminium; AWI Arctic Land Expedition; Barium 2+; biogeochemistry; Bromide; Calcium; Calculated; Carbon, organic, dissolved; CDOM; Chloride; Conductivity, electrical; DATE/TIME; DEPTH, water; Deuterium excess; DOC; DOM; Fluoride; Handheld meter, WTW, 340i, Conductivity; Identification; Inductively coupled plasma optical emission spectrometry (ICP-OES), Perkin-Elmer, Optima 8300DV; Ion chromatography (Thermo-Fischer ICS 2100); Iron; Latitude of event; Lena 2018; Lena 2019; Longitude of event; Magnesium; major ions; Manganese; Mass spectrometer Finnigan Delta-S/equilibration device; Nitrate; Olenekskaya_Ch; Phosphate; Phosphorus; Potassium; RIVER; RU-Land_2018_Lena; RU-Land_2018_Lena_Olenekskaya; RU-Land_2019_Lena; RU-Land_2019_Lena_Olenekskaya; Sampling river; Shimadzu TOC-VCPH total organic carbon analyzer; Silicon; Sodium; Specific ultraviolet absorbance normalized to DOC; Spectrophotometer UV/VIS (PerkinElmer Lambda 950); stable water isotopes; Strontium 2+; Sulfate; Temperature, water; δ18O, water; δ Deuterium, water
    Type: Dataset
    Format: text/tab-separated-values, 42031 data points
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  • 16
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    Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition flight 20191130_01, version 1 (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.
    Keywords: 20191130_01; Airborne laser scanning; Arctic; Binary Object; DATE/TIME; Flight number; Freeboard; HELI; Helicopter; IceSense; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_9-98; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: text/tab-separated-values, 44 data points
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  • 17
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    Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition flight 20191119_01, version 1 (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.
    Keywords: 20191119_01; Airborne laser scanning; Arctic; Binary Object; DATE/TIME; Flight number; Freeboard; HELI; Helicopter; IceSense; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_8-23; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: text/tab-separated-values, 102 data points
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  • 18
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    Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition flight 20191228_01, version 1 (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.
    Keywords: 20191228_01; Airborne laser scanning; Arctic; Arctic Ocean; Binary Object; DATE/TIME; Flight number; Freeboard; HELI; Helicopter; IceSense; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/2; PS122/2_17-101; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: text/tab-separated-values, 282 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 19
    facet.materialart.
    Unknown
    Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition flight 20191224_01, version 1 (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.
    Keywords: 20191224_01; Airborne laser scanning; Arctic; Arctic Ocean; Binary Object; DATE/TIME; Flight number; Freeboard; HELI; Helicopter; IceSense; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/2; PS122/2_17-98; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: text/tab-separated-values, 390 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 20
    facet.materialart.
    Unknown
    Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition flight 20190928_01, version 1 (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-24
    Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.
    Keywords: Airborne laser scanning; Arctic; Binary Object; DATE/TIME; Flight number; Freeboard; HELI; Helicopter; IceSense; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122_1_2_45_2019092801; PS122/1; PS122/1_2-45; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: text/tab-separated-values, 58 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
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