Evolution of the Antarctic ice sheet throughout the last deglaciation: A study with a new coupled climate—north and south hemisphere ice sheet model

2006 ◽  
Vol 248 (3-4) ◽  
pp. 750-758 ◽  
Author(s):  
G PHILIPPON ◽  
G RAMSTEIN ◽  
S CHARBIT ◽  
M KAGEYAMA ◽  
C RITZ ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Last Deglaciation ◽  
Antarctic Ice Sheet ◽  
The Last Deglaciation ◽  
The Antarctic ◽  
North And South

Impact of ice sheet reconstructions on the deglacial climate in iLOVECLIM

2021 ◽  
Author(s):  
Nathaelle Bouttes ◽  
Didier Roche ◽  
Fanny Lhardy ◽  
Aurelien Quiquet ◽  
Didier Paillard ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Last Deglaciation ◽  
Antarctic Ice Sheet ◽  
Intermediate Complexity ◽  
Climate Evolution ◽  
The Last Deglaciation ◽  
The Antarctic ◽  
The Impact

<p>The last deglaciation is a time of large climate transition from a cold Last Glacial Maximum at 21,000 years BP with extensive ice sheets, to the warmer Holocene 9,000 years BP onwards with reduced ice sheets. Despite more and more proxy data documenting this transition, the evolution of climate is not fully understood and difficult to simulate. The PMIP4 protocol (Ivanovic et al., 2016) has indicated which boundary conditions to use in model simulations during this transition. The common boundary conditions should enable consistent multi model and model-data comparisons. While the greenhouse gas concentration evolution and orbital forcing are well known and easy to prescribe, the evolution of ice sheets is less well constrained and several choices can be made by modelling groups. First, two ice sheet reconstructions are available: ICE-6G (Peltier et al., 2015) and GLAC-1D (Tarasov et al., 2014). On top of topographic changes, it is left to modelling groups to decide whether to account for the associated bathymetry and land-sea mask changes, which is technically more demanding. These choices could potentially lead to differences in the climate evolution, making model comparisons more complicated.</p><p>We use the iLOVECLIM model of intermediate complexity (Goosse et al., 2010) to evaluate the impact of different ice sheet reconstructions and the effect of bathymetry changes on the global climate evolution during the Last deglaciation. We test the two ice sheet reconstructions (ICE-6G and GLAC-1D), and have implemented changes of bathymetry and land-sea mask. In addition, we also evaluate the impact of accounting for the Antarctic ice sheet evolution compared to the Northern ice sheets only.</p><p>We show that despite showing the same long-term changes, the two reconstructions lead to different evolutions. The bathymetry plays a role, although only few changes take place before ~14ka. Finally, the impact of the Antarctic ice sheet is important during the deglaciation and should not be neglected.</p><p>References</p><p>Goosse, H., et al., Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633, https://doi.org/10.5194/gmd-3-603-2010, 2010</p><p>Ivanovic, R. F., et al., Transient climate simulations of the deglaciation 21–9 thousand years before present (version 1) – PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, 2016</p><p>Peltier, W. R., Argus, D. F., and Drummond, R., Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model, J. Geophys. Res.-Sol. Ea., 120, 450–487, doi:10.1002/2014JB011176, 2015</p><p>Tarasov,L.,  et al., The global GLAC-1c deglaciation chronology, melwater pulse 1-a, and a question of missing ice, IGS Symposium on Contribution of Glaciers and Ice Sheets to Sea-Level Change, 2014</p>

Antarctic warmth in the last interglacial driven by Northern insolation and deglaciation

2021 ◽  
Author(s):  
Takashi Obase ◽  
Ayako Abe-Ouchi ◽  
Fuyuki Saito
Keyword(s):  
Mass Loss ◽  
Northern Hemisphere ◽  
Ice Sheet ◽  
Last Deglaciation ◽  
Orbital Eccentricity ◽  
Last Interglacial ◽  
Antarctic Ice Sheet ◽  
The Last Deglaciation ◽  
The Difference ◽  
The Antarctic

<p>The global mean sea level in the last interglacial (LIG, about 130,000 to 115,000 years before present) was very likely higher than the present level, driven mainly by mass loss of the Antarctic ice sheet. Some studies have suggested that this mass loss may have been caused by the warmer temperature over the Southern Ocean in the LIG compared with the present interglacial. However, the ultimate cause of the difference in Antarctic warming between the last and current interglacials has not been explained. Here, based on transient simulations of the last deglaciation using a fully coupled ocean–atmosphere model, we show that greater meltwater (by a factor of 1.5 relative to the last deglaciation) during the middle and later stages of the deglaciation could have produced the difference in Antarctic warmth. Northern Hemisphere ice sheet model experiments suggest that the difference in meltwater was caused by slightly smaller orbital eccentricity in our current interglacial than in the LIG, indicating that mass loss of the Antarctic ice sheet is influenced by the preceding northern summer insolation and disintegration of Northern Hemisphere ice sheets.</p>

Millennial-scale variability in Antarctic ice-sheet discharge during the last deglaciation

Nature ◽  
2014 ◽  
Vol 510 (7503) ◽  
pp. 134-138 ◽  
Author(s):  
M. E. Weber ◽  
P. U. Clark ◽  
G. Kuhn ◽  
A. Timmermann ◽  
D. Sprenk ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Last Deglaciation ◽  
Antarctic Ice Sheet ◽  
The Last Deglaciation ◽  
Millennial Scale

scholarly journals Simulated last deglaciation of the Barents Sea Ice Sheet primarily driven by oceanic conditions

2020 ◽  
Author(s):  
Michele Petrini ◽  
Colleoni Florence ◽  
Kirchner Nina ◽  
Hughes Anna L. C. ◽  
Camerlenghi Angelo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Last Deglaciation ◽  
Antarctic Ice Sheet ◽  
West Antarctic Ice Sheet ◽  
West Antarctic ◽  
The Barents Sea ◽  
The Last Deglaciation

<p>An interconnected complex of ice sheets, collectively referred to as the Eurasian ice sheets, covered north-westernmost Europe, Russia and the Barents Sea during the Last Glacial Maximum (around 21 ky BP), connecting to the Scandinavian Ice Sheet to the south. Due to common geological features, the Barents Sea component of this ice complex is seen as a paleo-analogue for the present-day West Antarctic Ice Sheet. Investigating key processes driving the last deglaciation of the Barents Sea Ice Sheet represents an important tool to interpret recent observations in Antarctica over the multi-millennial temporal scale of glaciological changes. We present results from a statistical ensemble of ice sheet model simulations of the last deglaciation of the Barents Sea Ice Sheet, all forced with transient atmospheric and oceanic conditions derived from AOGCM simulations. The ensemble of transient simulations is evaluated against the data-based DATED-1 reconstruction. We find that the simulated deglaciation of the Barents Sea Ice Sheet is primarily driven by the oceanic forcing, with sea level rise and surface melting amplifying the ice sheet sensitivity to ocean warming over relatively short intervals. Despite a large model/data mismatch at the western and eastern ice sheet margins, the simulated and DATED-1 deglaciation scenarios agree well on the timing of the deglaciation of the central and northern Barents Sea. The primary role played by ocean forcing in our simulations suggests that the long-term stability of the West Antarctic Ice Sheet could be at stake if the current trend in ocean warming will continue.</p>

scholarly journals Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) – Part 2: Parameter ensemble analysis

2020 ◽  
Vol 14 (2) ◽  
pp. 633-656 ◽  
Author(s):  
Torsten Albrecht ◽  
Ricarda Winkelmann ◽  
Anders Levermann
Keyword(s):  
Sea Level ◽  
Ice Sheet ◽  
Model Parameters ◽  
Last Deglaciation ◽  
Relevant Model ◽  
Ice Dynamics ◽  
Antarctic Ice Sheet ◽  
The Antarctic ◽  
Best Fit ◽  
Ensemble Analysis

Abstract. The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (≈210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation–age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model–data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016). This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4±4.1 m (or 6.5±2.0×106km3), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.

scholarly journals A Joint Inversion Estimate of Antarctic Ice Sheet Mass Balance Using Multi-Geodetic Data Sets

2019 ◽  
Vol 11 (6) ◽  
pp. 653 ◽  
Author(s):  
Chunchun Gao ◽  
Yang Lu ◽  
Zizhan Zhang ◽  
Hongling Shi
Keyword(s):  
Mass Balance ◽  
Joint Inversion ◽  
Ice Sheet ◽  
Mass Change ◽  
West Antarctica ◽  
Amundsen Sea ◽  
Antarctic Ice Sheet ◽  
Forward Models ◽  
Uplift Rates ◽  
The Antarctic

Many recent mass balance estimates using the Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry (including two kinds of sensors of radar and laser) show that the ice mass of the Antarctic ice sheet (AIS) is in overall decline. However, there are still large differences among previously published estimates of the total mass change, even in the same observed periods. The considerable error sources mainly arise from the forward models (e.g., glacial isostatic adjustment [GIA] and firn compaction) that may be uncertain but indispensable to simulate some processes not directly measured or obtained by these observations. To minimize the use of these forward models, we estimate the mass change of ice sheet and present-day GIA using multi-geodetic observations, including GRACE and Ice, Cloud and land Elevation Satellite (ICESat), as well as Global Positioning System (GPS), by an improved method of joint inversion estimate (JIE), which enables us to solve simultaneously for the Antarctic GIA and ice mass trends. The GIA uplift rates generated from our JIE method show a good agreement with the elastic-corrected GPS uplift rates, and the total GIA-induced mass change estimate for the AIS is 54 ± 27 Gt/yr, which is in line with many recent GPS calibrated GIA estimates. Our GIA result displays the presence of significant uplift rates in the Amundsen Sea Embayment of West Antarctica, where strong uplift has been observed by GPS. Over the period February 2003 to October 2009, the entire AIS changed in mass by −84 ± 31 Gt/yr (West Antarctica: −69 ± 24, East Antarctica: 12 ± 16 and the Antarctic Peninsula: −27 ± 8), greater than the GRACE-only estimates obtained from three Mascon solutions (CSR: −50 ± 30, JPL: −71 ± 30, and GSFC: −51 ± 33 Gt/yr) for the same period. This may imply that single GRACE data tend to underestimate ice mass loss due to the signal leakage and attenuation errors of ice discharge are often worse than that of surface mass balance over the AIS.

Sign in / Sign up

Export Citation Format

Share Document