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  • Articles  (13)
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  • 1
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    Impact of model resolution on simulated wind, drifting snow and surface mass balance in Terre Adelie, East Antarctica (2012)
    Cambridge University Press
    Details
    Publication Date: 2012-10-06
    Print ISSN: 0022-1430
    Electronic ISSN: 1727-5652
    Topics: Geography , Geosciences
    Published by Cambridge University Press on behalf of The International Glaciological Society (IGS).
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    PAPER CURRENT
  • 2
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    Spatial variability in sub-photic zone nitrate δ15N and surface mass balance across East Antarctica (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: Geographic information, surface mass balance (SMB) data, and sub-photic zone (〉0.3 m) nitrate concentration and nitrogen isotopic composition (δ15NNO3) for 135 sites across East Antarctica. This database was used to examine and define the relationship between δ15NNO3 and SMB in Antarctica as part of the SCADI (Snow Core Accumulation from Delta-15N Isotopes) and EAIIST (East Antarctic International Ice Sheet Traverse) projects. Of these 135 sites, 92 are newly reported here while the other site data were previously published and are cited accordingly. Snow bearing nitrate was sampled from snow pits and firn/ice cores at different dates depending on the original scientific campaign, but predominately between 2010 and 2020, with the earliest sampling occurring in 2004. Nitrate was later extracted from the snow, concentrated, and analyzed for δ15NNO3. Surface mass balance data comes from a combination of previous ground-based observations (e.g., stakes, ice core data) and the output from Modèle Atmosphérique Régional version 3.6.4 with European Centre for Medium-Range Weather Forecasts “Interim” re-analysis data (ERA-interim) data, adjusted for observed model SMB biases. Elevation data were extracted from the Reference Elevation Model of Antarctica (REMA, https://doi.org/10.5194/tc-13-665-2019).
    Keywords: ABN1314-103 ice core; Ant_ABN-1314; Ant_ABN-DL1; Ant_ABN-DL2; Ant_ABN-P4; Ant_ABN-P5; Ant_AGO5; Ant_asuma.2016.1; Ant_asuma.2016.2; Ant_CHIC-01; Ant_CHIC-04; Ant_CHIC-05; Ant_CHIC-07; Ant_CHIC-10; Ant_CHIC-11; Ant_CHIC-13; Ant_CHIC-15; Ant_CHIC-18; Ant_CHIC-20; Ant_cph.d17; Ant_cph.d24; Ant_cph.d5; Ant_cph1516; Ant_DA2005; Ant_DC04; Ant_DC07-1; Ant_DC07-2; Ant_DC07-3; Ant_dc14; Ant_dc2010pits; Ant_DF1; Ant_DF2; Ant_dml.pit.a; Ant_dml.pit.b; Ant_eaiist.stop01; Ant_eaiist.stop02; Ant_eaiist.stop03; Ant_eaiist.stop04; Ant_eaiist.stop05; Ant_eaiist.stop06; Ant_eaiist.stop07; Ant_eaiist.stop08a; Ant_eaiist.stop08b; Ant_eaiist.stop09; Ant_eaiist.stop10; Ant_eaiist.stop11; Ant_eaiist.stop12; Ant_eaiist.stop13a; Ant_eaiist.stop13b; Ant_eaiist.stop14; Ant_eaiist.stop19; Ant_eaiist.stop20; Ant_eaiist.stop21; Ant_eaiist.stop22; Ant_eaiist.stop23; Ant_eaiist.stop24; Ant_eaiist.stop25; Ant_eaiist.stop26; Ant_Fuji_Pass; Ant_H108; Ant_H128; Ant_H42; Ant_H68; Ant_H88; Ant_IM0; Ant_IV; Ant_MD590; Ant_NDF; Ant_NMD304; Ant_Paleo; Ant_Plateau_S; Ant_posteaiist.asuma01; Ant_posteaiist.asuma02; Ant_posteaiist.asuma03; Ant_posteaiist.asuma04; Ant_posteaiist.asuma05; Ant_posteaiist.asuma06; Ant_posteaiist.asuma07; Ant_posteaiist.asuma08; Ant_posteaiist.asuma09; Ant_posteaiist.asuma10; Ant_posteaiist.asuma11; Ant_posteaiist.samba; Ant_posteaiist.stop27; Ant_posteaiist.stop28; Ant_posteaiist.stop29; Ant_posteaiist.stop30; Ant_posteaiist.stop31; Ant_posteaiist.stop32; Ant_posteaiist.stop33; Ant_posteaiist.stop34; Ant_posteaiist.stop35; Ant_posteaiist.stop36; Ant_posteaiist.stop37; Ant_posteaiist.stop38; Ant_preeaiist.01; Ant_preeaiist.02; Ant_preeaiist.03; Ant_preeaiist.04; Ant_preeaiist.05; Ant_preeaiist.06; Ant_preeaiist.07; Ant_preeaiist.08; Ant_preeaiist.09; Ant_preeaiist.10; Ant_preeaiist.11; Ant_preeaiist.12; Ant_preeaiist.13; Ant_preeaiist.14; Ant_preeaiist.15; Ant_preeaiist.16; Ant_preeaiist.17; Ant_preeaiist.18; Ant_S1; Ant_S2; Ant_S3; Ant_S30-JARE; Ant_S4; Ant_S80core; Ant_S80pit; Ant_V09-1; Ant_V09-2; Ant_VI; Ant_VIII; Ant_X; Ant_XII; Ant_XIV; Ant_XVI; Ant_XVIII; Ant_Z2; Ant_ZtoA-P1; Ant_ZtoA-P2; Ant_ZtoA-P3; Ant_ZtoA-P4; Ant_ZtoA-P5; Ant_ZtoA-P7; Antarctica; Bias-adjusted MAR output; Campaign; Category; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; Colorimetry and/or ion chromatography; Comment; East Antarctica; ELEVATION; Event label; Extracted from REMA; GPS in field; IC; Ice core; Ice corer; isotope; LATITUDE; LONGITUDE; MAR output; Mass spectrometer, Finnigan, MAT 253; nitrate; Nitrate; nitrogen isotope ratio (δ15N); Physical measurement and observations; Reference/source; Site; SNOW; Snow/ice sample; Snow pits/firn core/ice core; surface mass balance; Surface mass balance; Transect; Type; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 1904 data points
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    DATA PANGAEA
  • 3
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    Nitrate δ15N values and ice density-based surface mass balance from the ABN1314-103 ice core, Aurora Basin North, Antarctica (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: Nitrate concentration and isotopic (δ15NNO3) data, ice density, and surface mass balance estimates from the ABN1314-103 ice core. This 103 m long core was drilled beginning on 07 January 2014 as one of three ice cores at Aurora Basin North, Antarctica (-71.17, 111.37, 2679 m.a.s.l), in the 2013-2014 field season. The age-depth model for ABN1314-103 was matched through ion profiles from an annually-resolved model (ALC01112018) originally developed for one of the other ABN cores through seasonal ion and water isotope cycles and constrained by volcanic horizons. Each 1 m segment of the core was weighed and measured for ice density calculations, and then sampled for nitrate at 0.33 m resolution. Nitrate concentrations were taken on melted ice aliquots with ion chromatography, while isotopic analysis was achieved through bacterial denitrification and MAT 253 mass spectrometry after concentrating with anionic resin. Using the density data and the age-depth model's dates for the top and bottom of each 1 m core segment, we reconstructed a history of surface mass balance changes as recorded in ABN1314-103. Additionally, we also estimated the effect of upstream topographic changes on the ice core's surface mass balance record through a ground penetrating radar transect that extended 11.5 km against the direction of glacial ice flow. The modern SMB changes along this upstream transect were linked to ABN1314-103 core depths by through the local horizontal ice flow rate (16.2 m a-1) and the core's age-depth model, and included here for comparative analysis. See Akers et al., 2022 for more analytical details.
    Keywords: Antarctica; density; Ice core; nitrate; nitrogen isotope ratio (δ15N); surface mass balance
    Type: Dataset
    Format: application/zip, 2 datasets
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    DATA PANGAEA
  • 4
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    Ice density-based surface mass balance from the ABN1314-103 ice core, Aurora Basin North, Antarctica (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Calculated from density and age-depth model; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; density; Density, ice; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; IC; Ice core; Ice corer; nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years
    Type: Dataset
    Format: text/tab-separated-values, 774 data points
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    DATA PANGAEA
  • 5
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    Nitrate concentration, isotopic δ15N and surface mass balance from the ABN1314-103 ice core, Aurora Basin North, Antarctica (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; Colorimetry and/or ion chromatography; density; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; Ground-penetrating radar (GPR); IC; Ice core; Ice corer; Mass spectrometer, Finnigan, MAT 253; nitrate; Nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years; δ15N; δ15N, standard error
    Type: Dataset
    Format: text/tab-separated-values, 3207 data points
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    DATA PANGAEA
  • 6
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    Snowfall and Water Stable Isotope Variability in East Antarctica Controlled by Warm Synoptic Events (2020)
    AMER GEOPHYSICAL UNION
    In:  EPIC3Journal of Geophysical Research: Atmospheres, AMER GEOPHYSICAL UNION, 125(17), ISSN: 2169-897X
    Details
    Publication Date: 2020-09-18
    Description: Understanding climate proxy records that preserve physical characteristics of past climate is a prerequisite to reconstruct long‐term climatic conditions. Water stable isotope ratios (δ18O) constitute a widely used proxy in ice cores to reconstruct temperature and climate. However, the original climate signal is altered between the formation of precipitation and the ice, especially in low‐accumulation areas such as the East Antarctic Plateau. Atmospheric conditions under which the isotopic signal is acquired at Aurora Basin North (ABN), East Antarctica, are characterized with the regional atmospheric model Modèle Atmosphérique Régional (MAR). The model shows that 50% of the snow is accumulated in less than 24 days/year. Snowfall occurs throughout the year and intensifies during winter, with 64% of total accumulation between April and September, leading to a cold bias of −0.86°C in temperatures above inversion compared to the annual mean of −29.7°C. Large snowfall events are associated with high‐pressure systems forcing warm oceanic air masses toward the Antarctic interior, which causes a warm bias of +2.83°C. The temperature‐δ18O relationship, assessed with the global atmospheric model ECHAM5‐wiso, is primarily constrained by the winter variability, but the observed slope is valid year‐round. Three snow δ18O records covering 2004–2014 indicate that the anomalies recorded in the ice core are attributable to the occurrence of warm winter storms bringing precipitation to ABN and support the interpretation of δ18O in this region as a marker of temperature changes related to large‐scale atmospheric conditions, particularly blocking events and variations in the Southern Annular Mode.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
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    Mass balance of the Greenland Ice Sheet from 1992 to 2018 (2020)
    In:  EPIC3Nature, 579(7798), pp. 233-239
    Details
    Publication Date: 2020-08-03
    Description: The Greenland Ice Sheet has been a major contributor to global sea-level rise in recent decades1,2, and it is expected to continue to be so3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the magnitude and trajectory of the ice sheet’s mass imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. The ice sheet was close to a state of balance in the 1990s, but annual losses have risen since then, peaking at 345 ± 66 billion tonnes per year in 2011. In all, Greenland lost 3,902 ± 342 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.8 ± 0.9 millimetres. Using three regional climate models, we show that the reduced surface mass balance has driven 1,964 ± 565 billion tonnes (50.3 per cent) of the ice loss owing to increased meltwater runoff. The remaining 1,938 ± 541 billion tonnes (49.7 per cent) of ice loss was due to increased glacier dynamical imbalance, which rose from 46 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. The total rate of ice loss slowed to 222 ± 30 billion tonnes per year between 2013 and 2017, on average, as atmospheric circulation favoured cooler conditions15 and ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the rates predicted by the Intergovernmental Panel on Climate Change for their high-end climate warming scenario17, which forecast an additional 70 to 130 millimetres of global sea-level rise by 2100 compared with their central estimate.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 8
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    Mass balance of the Antarctic Ice Sheet from 1992 to 2017 (2019)
    Details
    Publication Date: 2019-01-25
    Description: Analysis | Published: 13 June 2018 Mass balance of the Antarctic Ice Sheet from 1992 to 2017 The IMBIE team Naturevolume 558, pages219–222 (2018) | Download Citation Abstract The Antarctic Ice Sheet is an important indicator of climate change and driver of sea-level rise. Here we combine satellite observations of its changing volume, flow and gravitational attraction with modelling of its surface mass balance to show that it lost 2,720 ± 1,390 billion tonnes of ice between 1992 and 2017, which corresponds to an increase in mean sea level of 7.6 ± 3.9 millimetres (errors are one standard deviation). Over this period, ocean-driven melting has caused rates of ice loss from West Antarctica to increase from 53 ± 29 billion to 159 ± 26 billion tonnes per year; ice-shelf collapse has increased the rate of ice loss from the Antarctic Peninsula from 7 ± 13 billion to 33 ± 16 billion tonnes per year. We find large variations in and among model estimates of surface mass balance and glacial isostatic adjustment for East Antarctica, with its average rate of mass gain over the period 1992–2017 (5 ± 46 billion tonnes per year) being the least certain.
    Description: Published
    Description: 219-222
    Description: 5A. Paleoclima e ricerche polari
    Description: JCR Journal
    Keywords: Antarctica ; Ice sheet mass balance ; 02.02. Glaciers ; 04.03. Geodesy
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
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    Acceleration of dynamic ice loss in Antarctica from satellite gravimetry (2021)
    Frontiers
    In:  EPIC3Frontiers in Earth Science, Frontiers, 9, pp. 1266, ISSN: 9
    Details
    Publication Date: 2022-06-20
    Description: The dynamic stability of the Antarctic Ice Sheet is one of the largest uncertainties in projections of future global sea-level rise. Essential for improving projections of the ice sheet evolution is the understanding of the ongoing trends and accelerations of mass loss in the context of ice dynamics. Here, we examine accelerations of mass change of the Antarctic Ice Sheet from 2002 to 2020 using data from the GRACE (Gravity Recovery and Climate Experiment; 2002–2017) and its follow-on GRACE-FO (2018-present) satellite missions. By subtracting estimates of net snow accumulation provided by re-analysis data and regional climate models from GRACE/GRACE-FO mass changes, we isolate variations in ice-dynamic discharge and compare them to direct measurements based on the remote sensing of the surface-ice velocity (2002–2017). We show that variations in the GRACE/GRACE-FO time series are modulated by variations in regional snow accumulation caused by large-scale atmospheric circulation. We show for the first time that, after removal of these surface effects, accelerations of ice-dynamic discharge from GRACE/GRACE-FO agree well with those independently derived from surface-ice velocities. For 2002–2020, we recover a discharge acceleration of -5.3 ± 2.2 Gt yr−2 for the entire ice sheet; these increasing losses originate mainly in the Amundsen and Bellingshausen Sea Embayment regions (68%), with additional significant contributions from Dronning Maud Land (18%) and the Filchner-Ronne Ice Shelf region (13%). Under the assumption that the recovered rates and accelerations of mass loss persisted independent of any external forcing, Antarctica would contribute 7.6 ± 2.9 cm to global mean sea-level rise by the year 2100, more than two times the amount of 2.9 ± 0.6 cm obtained by linear extrapolation of current GRACE/GRACE-FO mass loss trends.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 10
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    Projected land ice contributions to twenty-first-century sea level rise (2021)
    In:  EPIC3Nature, 593(7857), pp. 74-82, ISSN: 0028-0836
    Details
    Publication Date: 2022-09-26
    Description: The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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