Elevation Changes in Antarctica Mainly Determined by Accumulation Variability

Helsen, M. M.; Broeke, M. R. van den; Wal, R. S. W. van de; Berg, Willem Jan van de; Meijgaard, E. van; Davis, C.H.; Li, Yonghong; Goodwin, Ian

doi:10.1126/science.1153894

Cited by 158 publications

(240 citation statements)

References 23 publications

(37 reference statements)

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“…Another example is the slight increase in surface elevation that has been observed in the interior of the continent, suggesting a recent gain in mass (e.g. Helsen et al, 2008), whereas precipitation appears not to have undergone any significant change since the 1950s (Monaghan et al, 2006a). This contradiction highlights the uncertainty of SMB measurements and interpretations, which result in a high level of incertitude concerning the future contribution of Antarctic SMB to sea level rise (Meehl et al, 2007).…”

Section: Introductionmentioning

confidence: 88%

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

et al. 2012

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Abstract. The mass balance of ice sheets is an intensively studied topic in the context of global change and sealevel rise. However -particularly in Antarctica -obtaining mass balance estimates remains difficult due to various logistical problems. In the framework of the TASTE-IDEA (Trans-Antarctic Scientific Traverses Expeditions -Ice Divide of East Antarctica) program, an International Polar Year project, continuous ground penetrating radar (GPR) measurements were carried out during a traverse in Adelie Land (East Antarctica) during the 2008-2009 austral summer between the Italian-French Dome C (DC) polar plateau site and French Dumont D'Urville (DdU) coastal station. The aim of this study was to process and interpret GPR data in terms of snow accumulation, to analyse its spatial and temporal variability and compare it with historical data and modelling. The focus was on the last 300 yr, from the preindustrial period to recent times. Beta-radioactivity counting and gamma spectrometry were applied to cores at the LGGE laboratory, providing a depth-age calibration for radar measurements. Over the 600 km of usable GPR data, depth and snow accumulation were determined with the help of three distinct layers visible on the radargrams (≈ 1730(≈ , 1799(≈ and 1941. Preliminary results reveal a gradual increase in accumulation towards the coast (from ≈ 3 cm w.e. a −1 at Dome C to ≈ 17 cm w.e. a −1 at the end of the transect) and previously undocumented undulating structures between 300 and 600 km from DC. Results agree fairly well with data from previous studies and modelling. Drawing final conclusions on temporal variations is difficult because of the margin of error introduced by density estimation. This study should have various applications, including model validation.

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Section: Introductionmentioning

confidence: 88%

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

et al. 2012

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“…They are typically close to approximately 1.75 mm. change, H(t), and mass change, M(t), is complicated by the fact that the near-surface density of snow, firn, and ice can vary in space and in time (18). However, the surface-sensing techniques have much better spatial resolution than does GRACE or GPS.…”

Section: Discussionmentioning

confidence: 99%

Bedrock displacements in Greenland manifest ice mass variations, climate cycles and climate change

Bevis

Wahr

Khan³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

123

125

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The Greenland GPS Network (GNET) uses the Global Positioning System (GPS) to measure the displacement of bedrock exposed near the margins of the Greenland ice sheet. The entire network is uplifting in response to past and present-day changes in ice mass. Crustal displacement is largely accounted for by an annual oscillation superimposed on a sustained trend. The oscillation is driven by earth's elastic response to seasonal variations in ice mass and air mass (i.e., atmospheric pressure). Observed vertical velocities are higher and often much higher than predicted rates of postglacial rebound (PGR), implying that uplift is usually dominated by the solid earth's instantaneous elastic response to contemporary losses in ice mass rather than PGR. Superimposed on longer-term trends, an anomalous 'pulse' of uplift accumulated at many GNET stations during an approximate six-month period in 2010. This anomalous uplift is spatially correlated with the 2010 melting day anomaly.climate change | climate cycles | elasticity | crustal motion geodesy

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“…Firn compaction is currently linked with SMB through a simple correlation model (Zammit-Mangion et al, 2014). This approach could be further improved by adding a temperature dependence, along the lines of a simple firn compaction model (Helsen et al, 2008). Finally, another open question concerns the extent of present-day viscoelastic rebound in the ASE.…”

Section: Discussionmentioning

confidence: 99%

Simultaneous solution for mass trends on the West Antarctic Ice Sheet

et al. 2015

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Abstract. The Antarctic Ice Sheet is the largest potential source of future sea-level rise. Mass loss has been increasing over the last 2 decades for the West Antarctic Ice Sheet (WAIS) but with significant discrepancies between estimates, especially for the Antarctic Peninsula. Most of these estimates utilise geophysical models to explicitly correct the observations for (unobserved) processes. Systematic errors in these models introduce biases in the results which are difficult to quantify. In this study, we provide a statistically rigorous error-bounded trend estimate of ice mass loss over the WAIS from 2003 to 2009 which is almost entirely data driven. Using altimetry, gravimetry, and GPS data in a hierarchical Bayesian framework, we derive spatial fields for ice mass change, surface mass balance, and glacial isostatic adjustment (GIA) without relying explicitly on forward models. The approach we use separates mass and height change contributions from different processes, reproducing spatial features found in, for example, regional climate and GIA forward models, and provides an independent estimate which can be used to validate and test the models. In addition, spatial error estimates are derived for each field. The mass loss estimates we obtain are smaller than some recent results, with a time-averaged mean rate of −76 ± 15 Gt yr −1 for the WAIS and Antarctic Peninsula, including the major Antarctic islands. The GIA estimate compares well with results obtained from recent forward models (IJ05-R2) and inverse methods (AGE-1). The Bayesian framework is sufficiently flexible that it can, eventually, be used for the whole of Antarctica, be adapted for other ice sheets and utilise data from other sources such as ice cores, accumulation radar data, and other measurements that contain information about any of the processes that are solved for.

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Elevation Changes in Antarctica Mainly Determined by Accumulation Variability

Cited by 158 publications

References 23 publications

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

Bedrock displacements in Greenland manifest ice mass variations, climate cycles and climate change

Simultaneous solution for mass trends on the West Antarctic Ice Sheet

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