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

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

Decreasing Antarctic surface mass balance due to runoff-dominated ablation by 2100

10.5194/egusphere-egu2020-17355 ◽

2020 ◽

Author(s):

Christoph Kittel ◽

Charles Amory ◽

Cécile Agosta ◽

Nicolas Jourdain ◽

Stefan Hofer ◽

...

Keyword(s):

Mass Balance ◽

Sea Level Rise ◽

Sea Level ◽

Ice Sheet ◽

Surface Mass Balance ◽

Ice Shelf ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Ice Shelves ◽

The Antarctic

The surface mass balance (SMB) of the Antarctic ice sheet is often considered as a negative contributor to the sea level rise as present snowfall accumulation largely compensates for ablation through wind erosion, sublimation and runoff. The latter is even almost negligible since current Antarctic surface melting is limited to relatively scarce events over generally peripheral areas and refreezes almost entirely into the snowpack. However, melting can significantly affect the stability of ice shelves through hydrofracturing, potentially leading to their disintegration, acceleration of grounded ice and increased sea level rise. Although a large increase in snowfall is expected in a warmer climate, more numerous and stronger melting events could conversely lead to a larger risk of ice shelf collapse. In this study, we provide an estimation of the SMB of the Antarctic ice sheet for the end of the 21st&#160;century by forcing the state-of-the-art regional climate model MAR with three different global climate models. We chose the models (from both the Coupled Model Intercomparison Project Phase 5 and 6 - CMIP5 and CMIP6) providing the best metrics for representing the current Antarctic climate. While the increase in snowfall largely compensates snow ablation through runoff in CMIP5-forced projections, CMIP6-forced simulations reveal that runoff cannot be neglected in the future as it accounts for a maximum of 50% of snowfall and becomes the main ablation component over the ice sheet. Furthermore, we identify a tipping point (ie., a warming of 4&#176;C) at which the Antarctic SMB starts to decrease as a result of enhanced runoff particularly over ice shelves. Our results highlight the importance of taking into account meltwater production and runoff and indicate that previous model studies neglecting these processes yield overestimated SMB estimates, ultimately leading to underestimated Antarctic contribution to sea level rise. Finally, melt rates over each ice shelf are higher than those that led to the collapse of the Larsen A and B ice shelves, suggesting a high probability of ice shelf collapses all over peripheral Antarctica by 2100.

Download Full-text

What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates

The Cryosphere ◽

10.5194/tc-15-3751-2021 ◽

2021 ◽

Vol 15 (8) ◽

pp. 3751-3784

Author(s):

Ruth Mottram ◽

Nicolaj Hansen ◽

Christoph Kittel ◽

J. Melchior van Wessem ◽

Cécile Agosta ◽

...

Keyword(s):

Mass Balance ◽

Regional Climate ◽

Ice Sheet ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Substantial Impact ◽

Near Surface ◽

Surface Mass ◽

Ensemble Mean ◽

The Antarctic

Abstract. We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica.

Download Full-text

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

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b8-549-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 549-553 ◽

Cited By ~ 1

Author(s):

Huan Xie ◽

Gang Hai ◽

Lei Chen ◽

Shijie Liu ◽

Jun Liu ◽

...

Keyword(s):

Data Processing ◽

Least Squares ◽

Mass Balance ◽

Ice Sheet ◽

Surface Mass Balance ◽

Data Sets ◽

Cell Level ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Sheet Surface

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.

Download Full-text

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

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-549-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 549-553

Author(s):

Huan Xie ◽

Gang Hai ◽

Lei Chen ◽

Shijie Liu ◽

Jun Liu ◽

...

Keyword(s):

Data Processing ◽

Least Squares ◽

Mass Balance ◽

Ice Sheet ◽

Surface Mass Balance ◽

Data Sets ◽

Cell Level ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Sheet Surface

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.

Download Full-text

Review Surface Mass Balance of the Antarctic Ice Sheet and its link with surface temperature change in model simulations and reconstructions by Q. Delaiden et al.

10.5194/tc-2019-111-rc1 ◽

2019 ◽

Author(s):

Anonymous

Keyword(s):

Surface Temperature ◽

Mass Balance ◽

Temperature Change ◽

Ice Sheet ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Surface Temperature Change ◽

Surface Mass ◽

Model Simulations ◽

The Antarctic

Download Full-text

The AntSMB dataset: a comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

10.5194/essd-2021-22 ◽

2021 ◽

Author(s):

Yetang Wang ◽

Minghu Ding ◽

Carleen H. Reijmer ◽

Paul C. J. P. Smeets ◽

Shugui Hou ◽

...

Keyword(s):

Mass Balance ◽

Ice Sheet ◽

Ice Cores ◽

Field Measurements ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Ground Penetrating ◽

The Antarctic ◽

Comprehensive Compilation

Abstract. A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of a variety of published field measurements of the Antarctic Ice Sheet SMB by means of stakes, snow pits, ice cores, ultrasonic sounders and ground-penetrating radars. The dataset collects 268 913 individual multi-year averaged observations, 687 annual resolved time series from 675 sites extending back the past 1000 years, and 78 968 records at daily resolution from 32 sites across the whole ice sheet. These records are derived from ice core, snow pits, stakes/stake farms, ultrasonic sounders and ground-penetrating radar measurements. This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual and multi-year) resolutions from multiple types of measurements, which is available at: https://doi.org/10.11888/Glacio.tpdc.271148 (Wang et al., 2021). The database has potentially wide applications such as the investigation of temporal and spatial variability in SMB, model validation, assessment of remote sensing retrievals and data assimilation.

Download Full-text

Evaluation of Synoptic Snowfall on the Antarctic Ice Sheet Based on CloudSat, In-Situ Observations and Atmospheric Reanalysis Datasets

Remote Sensing ◽

10.3390/rs11141686 ◽

2019 ◽

Vol 11 (14) ◽

pp. 1686

Author(s):

Yihui Liu ◽

Fei Li ◽

Weifeng Hao ◽

Jean-Pierre Barriot ◽

Yetang Wang

Keyword(s):

Mass Balance ◽

Ice Sheet ◽

Absolute Error ◽

Snow Accumulation ◽

Surface Mass Balance ◽

Antarctic Ice Sheet ◽

Surface Mass ◽

Weather Forecasts ◽

The Antarctic

Snowfall data are vital in calculating the surface mass balance of the Antarctic Ice Sheet (AIS), where in-situ and satellite measurements are sparse at synoptic timescales. CloudSat data are used to construct Antarctic snowfall data at synoptic timescales to compensate for the sparseness of synoptic snowfall data on the AIS and to better understand its surface mass balance. Synoptic CloudSat snowfall data are evaluated by comparison with daily snow accumulation measurements from ten automatic weather stations (AWSs) and the fifth generation of the European Centre for Medium-Range Weather Forecasts climate reanalysis (ERA5) snowfall. Synoptic snowfall data were constructed based on the CloudSat measurements within a radius of 1.41°. The results show that reconstructed CloudSat snowfall at daily and two-day resolutions cover about 28% and 29% of the area of the AIS, respectively. Daily CloudSat snowfall and AWS snow accumulation have similar trends at all stations. While influenced by stronger winds, >73.3% of extreme snow accumulation events correspond to snowfall at eight stations. Even if the CloudSat snowfall data have not been assimilated into the ERA5 dataset, the synoptic CloudSat snowfall data are almost identical to the daily ERA5 snowfall with only small biases (average root mean square error and mean absolute error < 3.9 mm/day). Agreement among the three datasets suggests that the CloudSat data can provide reliable synoptic snowfall data in most areas of the AIS. The ERA5 dataset captures a large number of extreme snowfall events at all AWSs, with capture rates varying from 56% to 88%. There are still high uncertainties in ERA5. Nevertheless, the result suggests that ERA5 can be used to represent actual snowfall events on the AIS at synoptic timescale.

Download Full-text