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

2021 ◽  
Author(s):  
Yetang Wang ◽  
Minghu Ding ◽  
Carleen H. Reijmer ◽  
Paul C. J. P. Smeets ◽  
Shugui Hou ◽  
...  

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.

2021 ◽  
Vol 13 (6) ◽  
pp. 3057-3074
Author(s):  
Yetang Wang ◽  
Minghu Ding ◽  
Carleen H. Reijmer ◽  
Paul C. J. P. Smeets ◽  
Shugui Hou ◽  
...  

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 radar (GPR). The dataset collects 3579 individual multi-year-averaged observations, 687 annually resolved time series from 675 sites extending back over the past 1000 years, and daily resolved records covering 245 years from 32 sites across the whole ice sheet. These records are derived from ice cores, snow pits, stakes/stake farms, and ultrasonic sounders. Furthermore, GPR multi-year-averaged measurements are included in the dataset, covering an area of 22 025 km2. This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual, and multi-year) resolutions from multiple types of measurement and 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. As a case of model estimation, records of the AntSMB dataset are used to assess the performance of ERA5 for temporal and spatial variability in SMB over Antarctica.


2019 ◽  
Vol 32 (20) ◽  
pp. 6899-6915 ◽  
Author(s):  
A. Gossart ◽  
S. Helsen ◽  
J. T. M. Lenaerts ◽  
S. Vanden Broucke ◽  
N. P. M. van Lipzig ◽  
...  

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.


2016 ◽  
Author(s):  
Bianca Kallenberg ◽  
Paul Tregoning ◽  
Janosch F. Hoffmann ◽  
Rhys Hawkins ◽  
Anthony Purcell ◽  
...  

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.


2019 ◽  
Author(s):  
Quentin Dalaiden ◽  
Hugues Goosse ◽  
François Klein ◽  
Jan T. M. Lenaerts ◽  
Max Holloway ◽  
...  

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.


2020 ◽  
Author(s):  
Christoph Kittel ◽  
Charles Amory ◽  
Cécile Agosta ◽  
Nicolas Jourdain ◽  
Stefan Hofer ◽  
...  

<p><span>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 compensate</span><span>s</span><span> 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 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°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.</span></p>


2021 ◽  
Vol 15 (8) ◽  
pp. 3751-3784
Author(s):  
Ruth Mottram ◽  
Nicolaj Hansen ◽  
Christoph Kittel ◽  
J. Melchior van Wessem ◽  
Cécile Agosta ◽  
...  

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.


2019 ◽  
Vol 11 (14) ◽  
pp. 1686
Author(s):  
Yihui Liu ◽  
Fei Li ◽  
Weifeng Hao ◽  
Jean-Pierre Barriot ◽  
Yetang Wang

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.


2012 ◽  
Vol 6 (5) ◽  
pp. 3667-3702 ◽  
Author(s):  
V. Favier ◽  
C. Agosta ◽  
S. Parouty ◽  
G. Durand ◽  
G. Delaygue ◽  
...  

Abstract. We present an updated and quality controlled surface mass balance (SMB) database for the Antarctic ice sheet. We retrieved a total of 5284 SMB data documented with important meta-data, to which a filter was applied to discard data with limited spatial and temporal representativeness, too small measurement accuracy, or lack of quality control. A total of 3438 reliable data was obtained, which is about four times more than by applying the same data filtering process to previously available databases. New important data with high spatial resolution are now available over long traverses, and at low elevation in some areas. However, the quality control led to a considerable reduction in the spatial density of data in several regions, particularly over West Antarctica. Over interior plateaus, where the SMB is low, the spatial density of measurements remained high. This quality controlled dataset was compared to results from ERA-Interim reanalysis to assess model representativeness over Antarctica, and also to identify large areas where data gaps impede model validation. Except for very few areas (e.g. Adelie Land), the elevation range between 200 m and 1000 m a.s.l. is not correctly sampled in the field, and measurements do not allow a thorough validation of models in regions with complex topography, where the highest scattering of SMB values is reported. Clearly, increasing the spatial density of field measurements at low elevations, in the Antarctic Peninsula and in West Antarctica remains a scientific priority.


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