ANTARCTIC ICE SHEET SURFACE MASS BALANCE ESTIMATES FROM 2003 TO 2015 USING ICESAT AND CRYOSAT-2 DATA

An assessment of Antarctic ice sheet surface mass balance from 2003 to 2015 has been carried out using a combination of ICESat data from 2003 to 2009 and CryoSat-2 data from 2010 to 2015. Both data sets are of L2 and are currently processed separately using different models. First, a repeat-track processing method that includes terms accounting for the trend and the first order fit of topography is applied to repeat-track measurements of all ICESat Campaigns. It uses the Least Squares fitting of the model to all observations in a box of 500 m x 500 m. The estimated trends in these boxes are then averaged inside a 30 km x 30 km cell. Similarly, the cells are used to estimate basin and ice sheet level surface elevation change trends. Mass balance calculating is performed at the cell level by multiplying the ice density by the volume change and then extended to the basin and the ice sheet level. Second, in CryoSat-2 data processing we applied a model within a cell of 5 km x 5 km considering that CryoSat-2 does not maintain repeated tracks. In this model the elevation trend, and a higher order topography are solved in an iterative way using the least squares technique. The mass change is computed at the cell level in the same way as the ICESat data. GIA correction is applied for both ICESat and CryoSat-2 estimates. Detailed information about the data processing, elevation and mass balance changes, and comparison with other studies will be introduced.

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Impact Of Snow Drift On The Antarctic Ice Sheet Surface Mass Balance: Possible Sensitivity To Snow-Surface Properties

Boundary-Layer Meteorology ◽

10.1023/a:1018776422809 ◽

2001 ◽

Vol 99 (1) ◽

pp. 1-19 ◽

Cited By ~ 150

Author(s):

Hubert Gallée ◽

Gilbert Guyomarc'h ◽

Eric Brun

Keyword(s):

Mass Balance ◽

Surface Properties ◽

Ice Sheet ◽

Surface Mass Balance ◽

Snow Surface ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Sheet Surface ◽

Snow Drift ◽

The Antarctic

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An Evaluation of Surface Climatology in State-of-the-Art Reanalyses over the Antarctic Ice Sheet

Journal of Climate ◽

10.1175/jcli-d-19-0030.1 ◽

2019 ◽

Vol 32 (20) ◽

pp. 6899-6915 ◽

Cited By ~ 6

Author(s):

A. Gossart ◽

S. Helsen ◽

J. T. M. Lenaerts ◽

S. Vanden Broucke ◽

N. P. M. van Lipzig ◽

...

Keyword(s):

Relative Humidity ◽

Surface Temperature ◽

Mass Balance ◽

Ice Sheet ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Near Surface ◽

Surface Mass ◽

Atmospheric Rivers ◽

The Antarctic

Abstract In this study, we evaluate output of near-surface atmospheric variables over the Antarctic Ice Sheet from four reanalyses: the new European Centre for Medium-Range Weather Forecasts ERA-5 and its predecessor ERA-Interim, the Climate Forecast System Reanalysis (CFSR), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The near-surface temperature, wind speed, and relative humidity are compared with datasets of in situ observations, together with an assessment of the simulated surface mass balance (approximated by precipitation minus evaporation). No reanalysis clearly stands out as the best performing for all areas, seasons, and variables, and each of the reanalyses displays different biases. CFSR strongly overestimates the relative humidity during all seasons whereas ERA-5 and MERRA-2 (and, to a lesser extent, ERA-Interim) strongly underestimate relative humidity during winter. ERA-5 captures the seasonal cycle of near-surface temperature best and shows the smallest bias relative to the observations. The other reanalyses show a general temperature underestimation during the winter months in the Antarctic interior and overestimation in the coastal areas. All reanalyses underestimate the mean near-surface winds in the interior (except MERRA-2) and along the coast during the entire year. The winds at the Antarctic Peninsula are overestimated by all reanalyses except MERRA-2. All models are able to capture snowfall patterns related to atmospheric rivers, with varying accuracy. Accumulation is best represented by ERA-5, although it underestimates observed surface mass balance and there is some variability in the accumulation over the different elevation classes, for all reanalyses.

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Supplementary material to "Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections"

10.5194/tc-2019-188-supplement ◽

2019 ◽

Author(s):

Heiko Goelzer ◽

Brice P. Y. Noel ◽

Tamsin L. Edwards ◽

Xavier Fettweis ◽

Jonathan M. Gregory ◽

...

Keyword(s):

Mass Balance ◽

Sea Level ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Sea Level Change ◽

Surface Mass Balance ◽

Surface Mass ◽

Sheet Surface ◽

Level Change ◽

Supplementary Material

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Greenland ice sheet surface mass balance 1991–2000: Application of Polar MM5 mesoscale model and in situ data

Journal of Geophysical Research Atmospheres ◽

10.1029/2003jd004451 ◽

2004 ◽

Vol 109 (D16) ◽

Cited By ~ 126

Author(s):

Jason E. Box

Keyword(s):

Mass Balance ◽

Mesoscale Model ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Mass Balance ◽

Surface Mass ◽

Sheet Surface ◽

In Situ Data

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Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models

The Cryosphere ◽

10.5194/tc-6-1275-2012 ◽

2012 ◽

Vol 6 (6) ◽

pp. 1275-1294 ◽

Cited By ~ 88

Author(s):

J. G. L. Rae ◽

G. Aðalgeirsdóttir ◽

T. L. Edwards ◽

X. Fettweis ◽

J. M. Gregory ◽

...

Keyword(s):

Mass Balance ◽

Sea Level ◽

Climate Models ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Regional Climate Models ◽

Surface Mass Balance ◽

Surface Mass ◽

Sheet Surface

Abstract. Four high-resolution regional climate models (RCMs) have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB), and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution general circulation models (GCMs). This is the first time an intercomparison has been carried out of RCM results for Greenland climate and SMB. Output from RCM simulations for the recent past with the four RCMs is evaluated against available observations. The evaluation highlights the importance of using a detailed snow physics scheme, especially regarding the representations of albedo and meltwater refreezing. Simulations with three of the RCMs for the 21st century using SRES scenario A1B from two GCMs produce trends of between −5.5 and −1.1 Gt yr−2 in SMB (equivalent to +0.015 and +0.003 mm sea level equivalent yr−2), with trends of smaller magnitude for scenario E1, in which emissions are mitigated. Results from one of the RCMs whose present-day simulation is most realistic indicate that an annual mean near-surface air temperature increase over Greenland of ~ 2°C would be required for the mass loss to increase such that it exceeds accumulation, thereby causing the SMB to become negative, which has been suggested as a threshold beyond which the ice sheet would eventually be eliminated.

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A new approach to estimate ice dynamic rates using satellite observations in East Antarctica

10.5194/tc-2016-269 ◽

2016 ◽

Author(s):

Bianca Kallenberg ◽

Paul Tregoning ◽

Janosch F. Hoffmann ◽

Rhys Hawkins ◽

Anthony Purcell ◽

...

Keyword(s):

Mass Balance ◽

Satellite Altimetry ◽

Ice Sheet ◽

East Antarctica ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Elevation Changes ◽

Ice Sheet Mass Balance ◽

The Antarctic

Abstract. Mass balance changes of the Antarctic ice sheet are of significant interest due to its sensitivity to climatic changes and its contribution to changes in global sea level. While regional climate models successfully estimate mass input due to snowfall, it remains difficult to estimate the amount of mass loss due to ice dynamic processes. It's often been assumed that changes in ice dynamic rates only need to be considered when assessing long term ice sheet mass balance; however, two decades of satellite altimetry observations reveal that the Antarctic ice sheet changes unexpectedly and much more dynamically than previously expected. Despite available estimates on ice dynamic rates obtained from radar altimetry, information about changes in ice dynamic rates are still limited, especially in East Antarctica. Without understanding ice dynamic rates it is not possible to properly assess changes in ice sheet mass balance, surface elevation or to develop ice sheet models. In this study we investigate the possibility of estimating ice dynamic rates by removing modelled rates of surface mass balance, firn compaction and bedrock uplift from satellite altimetry and gravity observations. With similar rates of ice discharge acquired from two different satellite missions we show that it is possible to obtain an approximation of ice dynamic rates by combining altimetry and gravity observations. Thus, surface elevation changes due to surface mass balance, firn compaction and ice dynamic rates can be modelled and correlate with observed elevation changes from satellite altimetry.

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Surface Mass Balance of the Antarctic Ice Sheet and its link with surface temperature change in model simulations and reconstructions

10.5194/tc-2019-111 ◽

2019 ◽

Cited By ~ 3

Author(s):

Quentin Dalaiden ◽

Hugues Goosse ◽

François Klein ◽

Jan T. M. Lenaerts ◽

Max Holloway ◽

...

Keyword(s):

Surface Temperature ◽

Mass Balance ◽

Regional Scale ◽

Ice Sheet ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Model Simulations ◽

Surface Temperatures ◽

The Antarctic

Abstract. Improving our knowledge of the temporal and spatial variability of the Antarctic Ice Sheet (AIS) Surface Mass Balance (SMB) is crucial to reduce the uncertainties of past, present and future Antarctic contributions to sea level rise. Here, we show that Global Climate Models (GCMs) can reproduce the present-day (1979–2005) AIS SMB and the temporal variations over the last two centuries. An examination of the surface temperature–SMB relationship in model simulations demonstrates a strong link between the two. Reconstructions based on ice cores display a weaker relationship, indicating a model-data discrepancy that may be due to model biases or to the non-climatic noise present in the records. We find that, on the regional scale, the modelled temperature-SMB relationship is stronger than the relationship between δ18O-temperature. This suggests that SMB data can be used to reconstruct past surface temperatures. Using this finding, we assimilate isotope-enabled model SMB and δ18O output with ice-core observations, to generate a new surface temperature reconstruction. Although an independent evaluation of the skill is difficult because of the short observational time series, this new reconstruction outperforms the previous reconstructions for the continental-mean temperature that were based on δ18O alone with a linear correlation coefficient with the observed surface temperatures (1958–2010 CE) of 0.73. The improvement is largest for the East Antarctic region, where the uncertainties are particularly large. Finally, we provide a spatial SMB reconstruction of the AIS over the last two centuries showing 1) large variability in SMB trends at regional scale; and 2) a large SMB increase (0.82 Gt year−2) in West Antarctica over 1957–2000 while at the same time, East Antarctica has experienced a large SMB decrease (−3.3 Gt year−2), which is consistent with a recent reconstruction.

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