7 datasets found
  1. Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2...

    • zenodo.org
    nc
    Updated Nov 18, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters; JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters (2022). Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2 melt pond volume [Dataset]. http://doi.org/10.5281/zenodo.7334047
    Explore at:
    ncAvailable download formats
    Dataset updated
    Nov 18, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters; JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters
    Description

    Data set of yearly regional atmospheric climate model RACMO2.3p2 data over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 6 hours from 1979-2021. The model is run at 27 km horizontal resolution for the entire Antarctic ice sheet, which constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation is also active.
    To simulate the recent past (1950-2014) and the future (2015-2100) we use RACMO2.3p2 at 27 km resolution to dynamically downscale one historical and three future projections emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Detailed CESM2 description and latest updates are provided in Danabasoglu et., al 2020 and an evaluation over Greenland in Van Kampenhout et al., 2020.

    These data are then used to fit exponential and power-law relations of annual total liquid water production (melt + rain) and snow accumulation (snowfall - sublimation) to calculate MoA sensitivity as a function of annual average 2 m temperature. A comparison with Sentinel-2 melt pond observations can then be performed.

    Data set includes:

    RACMO2.3p2-ERA5-3H - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1979-2021 in mm w.e per year, and yearly average 2 m temperature in K, forced by 3 hourly ERA5 reanalysis data.

    RACMO2.3p2-hist_r567 - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1950-2014 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 historical data.

    RACMO2.3p2-SSP''126,245,585''_r567 - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 2015-2100 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 future scenario (SSP1-2.6, SSP2-4.5, SSP5-8.5) data.

    TT_ALL.nc - Antarctic threshold temperature \(T_T\) for MoA = 0.7 as described in the Methods section.

    dT_ALL.nc - Uncertainty in Antarctic threshold temperature \(T_T\) for MoA = 0.7 as described in the Methods section.

    TT_IS.nc - Antarctic threshold temperature \(T_T\) for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.

    dT_IS.nc - Uncertainty in Antarctic threshold temperature \(T_T\) for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.

    S2_meltpondvolume_v3.nc - Sentinel-2 melt pond volume as described in the Methods section.

    Height_latlon_ANT27.nc - Grids of latitude, longitude, surface elevation (height), land/ice mask (mask2d), grounded land/ice mask (maskgrounded2d), aspect ratio, and surface slope.

  2. a

    SMMR and SSM/I derived dates of Arctic sea ice surface melt/freeze

    • arcticdata.io
    • dataone.org
    • +2more
    Updated May 15, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    H. Eicken; R. Gradinger; T. Heinrichs; M. Johnson; A. Lovecraft; Mette Kaufman (2020). SMMR and SSM/I derived dates of Arctic sea ice surface melt/freeze [Dataset]. http://doi.org/10.18739/A2PW70
    Explore at:
    Dataset updated
    May 15, 2020
    Dataset provided by
    Arctic Data Center
    Authors
    H. Eicken; R. Gradinger; T. Heinrichs; M. Johnson; A. Lovecraft; Mette Kaufman
    Time period covered
    Jan 1, 1979 - Dec 31, 2008
    Area covered
    Arctic,
    Description

    Yearly maps of onset of early melt (earliest observed melt conditions), melt (melt conditions observed throughout from this point until freeze), early freeze (earliest observed freeze conditions), and freeze (freeze conditions observed throughout from this point on) for the surface of sea ice derived from scanning multichannel microwave radiometer (SMMR) - special sensor microwave/imager (SSM/I) data. See [Markus et al. 2009] for further details. Original data prepared in a polar stereographic projection, with 25 km grid spacing; data has been reprojected into a northern hemispheric Equal-Area Scalable Earth (EASE) grid [see: http://nsidc.org/data/ease/ for further details] with 25 km grid spacing. Reference: Markus, T., J. C. Stroeve, and J. Miller (2009), Recent changes in Arctic sea ice melt onset, freezeup, and melt season length, J. Geophys. Res., 114, C12, doi:10.1029/2009JC005436.*****These data were compiled in conjunction with the Sunlight and the Arctic atmosphere-ice-ocean system (Synthesis of Arctic System Science, SASS) project.***** Data Citation: Eicken, H., R. Gradinger, T. Heinrichs, M. Johnson, A. Lovecraft, and M. Kaufman. (Jan. 5, 2010, Updated May 9, 2012). SMMR and SSM/I derived dates of Arctic sea ice surface melt/freeze (SIZONET). UCAR/NCAR – CISL – ACADIS. http://dx.doi.org/10.5065/D6KW5CXQ

  3. Data publication for "Bathymetry-constrained impact of relative sea-level...

    • zenodo.org
    zip
    Updated Feb 7, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Moritz Kreuzer; Moritz Kreuzer; Lena Nicola; Lena Nicola; Torsten Albrecht; Torsten Albrecht (2025). Data publication for "Bathymetry-constrained impact of relative sea-level change on basal melting in Antarctica" by Kreuzer et al. 2025 [Dataset]. http://doi.org/10.5281/zenodo.14824284
    Explore at:
    zipAvailable download formats
    Dataset updated
    Feb 7, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Moritz Kreuzer; Moritz Kreuzer; Lena Nicola; Lena Nicola; Torsten Albrecht; Torsten Albrecht
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Antarctica
    Description

    This archive documents all relevant output data and compute scripts of the publications (citation handles currently refer to preprint versions of the manuscript and will be updated at a later stage, when the manuscripts are published):

    - part A:

    Nicola, L., Reese, R., Kreuzer, M., Albrecht, T., and Winkelmann, R.: Oceanic gateways to Antarctic grounding lines – Impact of critical access depths on sub-shelf melt, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2583, 2023.

    - part B:

    Kreuzer, M., Albrecht, T., Nicola, L., Reese, R., and Winkelmann, R.: Oceanic gateways in Antarctica – Impact of relative sea-level change on sub-shelf melt, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2737, 2023.


    It also includes the scripts used to produce the figures of the `part B` publication.

  4. The distribution of volatile and metallic elements in the Macquarie Island...

    • researchdata.edu.au
    Updated Sep 15, 2004
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    KAMENETSKY, DIMA (2004). The distribution of volatile and metallic elements in the Macquarie Island glasses and melt inclusions [Dataset]. http://doi.org/10.4225/15/548925146CA3B
    Explore at:
    Dataset updated
    Sep 15, 2004
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    KAMENETSKY, DIMA
    Time period covered
    Jan 1, 1997 - Jun 30, 2004
    Area covered
    Description

    Primary sulfur abundances and the oxidation state of sulfur in the Macquarie Island glasses and melt inclusions: implications for the sulfur budget during seafloor alteration.

    The distribution of volatile and metallic elements in the Macquarie Island glasses and melt inclusions: Implications for fractional crystallisation and degassing during seafloor basaltic magmatism.

    Macquarie Island basaltic glasses and melt inclusions represent the products of mantle melting, crystal fractionation and degassing in mid-ocean ridge environment. State-of-art analytical techniques will be employed to quantify systematics of volatile and ore-forming elements in different magmatic processes. Implications for the origin of seafloor massive sulphide deposits are expected.

    1. Spreadsheet 'MacIsl-glasses' contains chemical analyses of the Macquarie Island glasses rows 4-8 - radiogenic isotope ratios (Nd, Sr, Pb) - see analytical details in Kamenetsky, V.S., and Maas, R., 2002, Mantle-melt evolution (dynamic source) in the origin of a single MORB suite: a perspective from magnesian glasses of Macquarie Island: Journal of Petrology, v. 43, p. 1909-1922. rows 10-25 - major petrogenetic elements in weight %. rows 29-57 and 60-83 - trace elements in ppm (parts per million).

    2. Spreadsheet 'MI_in_Sp' contains chemical analyses (major elements + chlorine + sulfur) of homogenised and quenched melt inclusions in chromites from Macquarie Island picrites. The concentrations are in weight %.

    3. Spreadsheet 'MI_in_Sp-GEO' contains compositions (trace elements by SIMS) of homogenised and quenched melt inclusions in chromites from Macquarie Island picrite #38277

    rows 3-16 - major petrogenetic elements in weight %. rows 19-43 - trace elements in ppm (parts per million).

    The specific equipment used to analyse the data were 1. Electron microprobes Cameca SX-50 (University of Tasmania) and JEOL Superprobe 8200 (Max-Planck-Institut fur Chemie, Mainz, Germany); 2. Fourier-transform infrared spectroscopy (University of Tasmania); 3. Laser-ablation inductively-coupled plasma mass-spectrometry (ANU, Canberra and CODES, University of Tasmania); 4. Secondary ion mass-spectroscopy, Cameca 3f ion probe (Institute of Microelectronics, Russia) 5. Finnigan MAT262 multicollector mass-spectrometer (La Trobe University, Melbourne)

    The samples were collected from Macquarie Island. The exact position of the samples is shown on Fig. 1b in Kamenetsky, V.S., Everard, J.L., Crawford, A.J., Varne, R., Eggins, S.M., and Lanyon, R., 2000, Enriched end-member of primitive MORB melts: petrology and geochemistry of glasses from Macquarie Island (SW Pacific): Journal of Petrology, v. 41, p. 411-430.

    The particular isotope stated was used to measure the element. Total elemental concentration is reported.

    The fields in this dataset are:

    SiO2 TiO2 Al2O3 FeO MnO MgO CaO Na2O K2O P2O5 Cl S Cr2O3 Potassium Cesium Lithium Beryllium Boron Scandium Titanium Vandium Gallium Rubidium Strontium Yttrium Zirconium Niobium Barium Lanthanum Cerium Neodymium Samarium Europium Gadolinium Dysprosium Erbium Ytterbium Lutetium Tantalum Thorium Uranium Chromium Cobalt Nickel Copper Zinc Arsenic Molybdenum Cadmium Tin Antimony Hafnium Tantalum Tungsten Thallium Lead Bismuth

  5. Data from: Melt ponds and leads water sampling for biogeochemical parameters...

    • doi.pangaea.de
    html, tsv
    Updated Mar 25, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hanno Meyer; Daiki Nomura; Yuhong Li; Elise Sayana Droste; Alison L Webb; Emelia Chamberlain; Masaki Yoshimura; Bruno Delille (2024). Melt ponds and leads water sampling for biogeochemical parameters during expedition PS122/5 (MOSAiC Leg 5) to the central Arctic in August-September 2020 [Dataset]. http://doi.org/10.1594/PANGAEA.966787
    Explore at:
    tsv, htmlAvailable download formats
    Dataset updated
    Mar 25, 2024
    Dataset provided by
    PANGAEA
    Authors
    Hanno Meyer; Daiki Nomura; Yuhong Li; Elise Sayana Droste; Alison L Webb; Emelia Chamberlain; Masaki Yoshimura; Bruno Delille
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Aug 22, 2020 - Sep 14, 2020
    Area covered
    Variables measured
    Site, LATITUDE, Salinity, DATE/TIME, LONGITUDE, Event label, Sample type, DEPTH, water, δ18O, water, Carbon dioxide, and 3 more
    Description

    Melt ponds water sampling for biogeochemical parameters such as dissolved inorganic carbon (DIC), total alkalinity (TA), oxygen isotopes were examined from August to September 2020. To obtain discrete water samples from the melt ponds and leads, we checked the vertical structure and depth of the meltwater layer from the same hole used for the RINKO Profiler by attaching a conductivity sensor (Cond 315i, WTW GmbH, Germany) to a 2-m-long ruler and inserting the ruler into the lead water until the salinity measured with the Cond 315i increased at the meltwater–seawater interface (Nomura et al., 2024) . Water was pumped up with a peristaltic pump through a 2-m-long PTFE tube (L/S Pump Tubing, Masterflex, USA) at depths corresponding to meltwater (surface), the interface between meltwater and seawater (interface), and seawater (bottom). Salinity was measured at each depth by attaching a Cond 315i conductivity sensor to the bottom of the ruler. The tube intake was likewise attached to the bottom of the ruler. Seawater was subsampled into a 250-mL glass vial (Duran Co., Ltd., Germany) for measurement of dissolved inorganic carbon (DIC) and total alkalinity (TA) and a 50-mL glass, screw-cap, narrow-neck vial (VWR international LLC, Germany) for measurement of the oxygen isotopic ratio (δ18O) of the water. Immediately after subsampling for measurement of DIC and TA, a 6.0% (wt.) mercuric chloride (HgCl2) solution (100 µL) was added to stop biological activity. Samples for DIC and TA were stored at +4°C on the R/V Polarstern. Samples for δ18O were stored at room temperature (20°C). During the discrete water sampling, the CO2 concentration in the water column was measured directly on site by passing the water through an equilibrator Liqui-Cel® (G542, S/N: 132462, 3M Company, USA) connected to an infrared gas analyzer (LI-8100A, LI-COR Inc., USA). The analyzer was calibrated with standard gases containing 0.0, 299.3, and 501.3 ppm CO2 before MOSAiC Leg 5. RMS (root means square) noise at 370 ppm with 1 sec signal averaging is <1 ppm (https://www.licor.com/env/products/soil-flux/LI-8100a). The equilibrator was connected in the loop for water sampling (vide supra), and a 2-m-long ruler was inserted into the water and kept at that depth until the CO2 was equilibrated with air (about 1 minute) by monitoring the CO2 values. The CO2 concentration was measured at each depth (i.e., surface, interface, and bottom). […]

  6. f

    Data from: Magmatic volatile distribution as recorded by rhyolitic melt...

    • geolsoc.figshare.com
    txt
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Florence Bégué; Darren M. Gravley; Isabelle Chambefort; Chad D. Deering; Ben M. Kennedy (2023). Magmatic volatile distribution as recorded by rhyolitic melt inclusions in the Taupo Volcanic Zone, New Zealand [Dataset]. http://doi.org/10.6084/m9.figshare.3453779.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Geological Society of London
    Authors
    Florence Bégué; Darren M. Gravley; Isabelle Chambefort; Chad D. Deering; Ben M. Kennedy
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    The central Taupo Volcanic Zone (TVZ) is an actively rifting continental arc and is well known for its exceptionally high rate of rhyolitic magma generation and frequent caldera-forming eruptions. Two end-member types of rhyolites (R1 and R2) have been previously identified based on differences in their bulk-rock chemistry and mineral assemblage with hydrous phases crystallizing in the R1 type, which are not present or only rare in R2 rhyolites. Here we present new trace element and volatile data from rhyolitic melt inclusions measured in several representative eruptive deposits (R1 and R2 rhyolites) from the central TVZ to examine their volatile concentrations and origin. R1 and R2 show very distinct Cl concentrations, with R2 rhyolites being enriched in Cl by c. 1000 ppm. H2O is slightly higher in the R1 rhyolites, whereas CO2 concentrations are similar between the two end-member types. The origin of these volatile disparities between R1 and R2 melts is assigned to differences in the initial bulk volatile content of the parental magma, possibly associated with distinct input of fluids from the subduction zone. These disparities in bulk volatile concentrations can lead to variations in relative timing of exsolution of volatile phase(s) prior to melt inclusion entrapment.

  7. Parameters used and estimated uncertainties for the computation of melt...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Guilherme A. R. Gualda; Ayla S. Pamukcu; Mark S. Ghiorso; Alfred T. Anderson Jr; Stephen R. Sutton; Mark L. Rivers (2023). Parameters used and estimated uncertainties for the computation of melt inclusion faceting time as a function of inclusion radius (r). [Dataset]. http://doi.org/10.1371/journal.pone.0037492.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Guilherme A. R. Gualda; Ayla S. Pamukcu; Mark S. Ghiorso; Alfred T. Anderson Jr; Stephen R. Sutton; Mark L. Rivers
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    aApproximate values.bCalculated using the CORBA Phase Properties applet (http://ctserver.ofm-research.org/phaseProp.html). Retrieved Nov 12, 2007. Calculations based on data from [73].

  8. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters; JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters (2022). Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2 melt pond volume [Dataset]. http://doi.org/10.5281/zenodo.7334047
Organization logo

Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2 melt pond volume

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
ncAvailable download formats
Dataset updated
Nov 18, 2022
Dataset provided by
Zenodohttp://zenodo.org/
Authors
JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters; JM van Wessem; Michiel R. van den Broeke; Stef Lhermitte; Bert Wouters
Description

Data set of yearly regional atmospheric climate model RACMO2.3p2 data over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 6 hours from 1979-2021. The model is run at 27 km horizontal resolution for the entire Antarctic ice sheet, which constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation is also active.
To simulate the recent past (1950-2014) and the future (2015-2100) we use RACMO2.3p2 at 27 km resolution to dynamically downscale one historical and three future projections emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Detailed CESM2 description and latest updates are provided in Danabasoglu et., al 2020 and an evaluation over Greenland in Van Kampenhout et al., 2020.

These data are then used to fit exponential and power-law relations of annual total liquid water production (melt + rain) and snow accumulation (snowfall - sublimation) to calculate MoA sensitivity as a function of annual average 2 m temperature. A comparison with Sentinel-2 melt pond observations can then be performed.

Data set includes:

RACMO2.3p2-ERA5-3H - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1979-2021 in mm w.e per year, and yearly average 2 m temperature in K, forced by 3 hourly ERA5 reanalysis data.

RACMO2.3p2-hist_r567 - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1950-2014 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 historical data.

RACMO2.3p2-SSP''126,245,585''_r567 - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 2015-2100 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 future scenario (SSP1-2.6, SSP2-4.5, SSP5-8.5) data.

TT_ALL.nc - Antarctic threshold temperature \(T_T\) for MoA = 0.7 as described in the Methods section.

dT_ALL.nc - Uncertainty in Antarctic threshold temperature \(T_T\) for MoA = 0.7 as described in the Methods section.

TT_IS.nc - Antarctic threshold temperature \(T_T\) for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.

dT_IS.nc - Uncertainty in Antarctic threshold temperature \(T_T\) for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.

S2_meltpondvolume_v3.nc - Sentinel-2 melt pond volume as described in the Methods section.

Height_latlon_ANT27.nc - Grids of latitude, longitude, surface elevation (height), land/ice mask (mask2d), grounded land/ice mask (maskgrounded2d), aspect ratio, and surface slope.

Search
Clear search
Close search
Google apps
Main menu