scholarly journals Do climate models underestimate snow accumulation on the Antarctic plateau? A re-evaluation of/from in situ observations in East Wilkes and Victoria Lands

2009 ◽  
Vol 50 (50) ◽  
pp. 61-65 ◽  
Author(s):  
C. Genthon ◽  
O. Magand ◽  
G. Krinner ◽  
M. Fily
Keyword(s):  
Climate Models ◽  
Snow Accumulation ◽  
Surface Mass ◽  
Antarctic Plateau ◽  
Clear Sky ◽  
Quality Control Criteria ◽  
The Cost ◽  
Control Criteria ◽  
The Antarctic

AbstractIt has been suggested that meteorological and climate models underestimate snow accumulation on the Antarctic plateau, because accumulation (or surface mass balance (SMB)) is dominated by clear-sky precipitation while this process is not properly taken into account in the models. Here, we show that differences between model and field SMB data are much reduced when the in situ SMB reports used to evaluate the models are filtered through quality-control criteria and less reliable reports are subsequently left out. We thus argue that, although not necessarily unsupported, model biases and their interpretations in terms of clear-sky vs synoptic precipitation on the Antarctic plateau may have been overstated in the past. To avoid such misleading issues, it is important that in situ SMB reports of insufficient or unassessed reliability are discarded, even at the cost of a strong reduction in spatial sampling and coverage.

scholarly journals Estimation of the Antarctic surface mass balance using MAR (1979–2015) and identification of dominant processes

2018 ◽  
Author(s):  
Cécile Agosta ◽  
Charles Amory ◽  
Christoph Kittel ◽  
Anais Orsi ◽  
Vincent Favier ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Ice Sheet ◽  
Snow Accumulation ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Drifting Snow ◽  
The Antarctic

Abstract. The Antarctic ice sheet mass balance is a major component of the sea level budget and results from the difference of two fluxes of a similar magnitude: ice flow discharging in the ocean and net snow accumulation on the ice sheet surface, i.e. the surface mass balance (SMB). Separately modelling ice dynamics and surface mass balance is the only way to project future trends. In addition, mass balance studies frequently use regional climate models (RCMs) outputs as an alternative to observed fields because SMB observations are particularly scarce on the ice sheet. Here we evaluate new simulations of the polar RCM MAR forced by three reanalyses, ERA-Interim, JRA-55 and MERRA2, for the period 1979–2015, and we compare our results to the last outputs of the RCM RACMO2 forced by ERA-Interim. We show that MAR and RACMO2 perform similarly well in simulating coast to plateau SMB gradients, and we find no significant differences in their simulated SMB when integrated over the ice sheet or its major basins. More importantly, we outline and quantify missing processes in both RCMs. Along stake transects, we show that both models accumulate too much snow on crests, and not enough snow in valleys, as a result of erosion-deposition processes not included in MAR, where the drifting snow module has been switched off, and probably underestimated in RACMO2 by a factor of three. As a consequence, the amount of drifting snow sublimating in the atmospheric boundary layer remains a potentially large mass sink needed to be better constrained. Moreover, MAR generally simulates larger SMB and snowfall amounts than RACMO2 inland, whereas snowfall rates are significantly lower in MAR than in RACMO2 at the ice sheet margins. This divergent behaviour at the margins results from differences in model parameterisations, as MAR explicitly advects precipitating particles through the atmospheric layers and sublimates snowflakes in the undersaturated katabatic layer, whereas in RACMO2 precipitation is added to the surface without advection through the atmosphere. Consequently, we corroborate a recent study concluding that sublimation of precipitation in the low-level atmospheric layers is a significant mass sink for the Antarctic SMB, as it may represent ∼ 240 ± 25 Gt yr-1 of difference in snowfall between RACMO2 and MAR for the period 1979–2015, which is 10 % of the simulated snowfall loaded on the ice sheet and more than twice the surface snow sublimation as currently simulated by MAR.

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

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.

scholarly journals The growth of sublimation crystals and surface hoar on the Antarctic plateau

2014 ◽  
Vol 8 (4) ◽  
pp. 1205-1215 ◽  
Author(s):  
J.-C. Gallet ◽  
F. Domine ◽  
J. Savarino ◽  
M. Dumont ◽  
E. Brun
Keyword(s):  
Energy Budget ◽  
Temperature Drop ◽  
Snow Surface ◽  
Surface Mass ◽  
Antarctic Plateau ◽  
Time Variations ◽  
Sunny Weather ◽  
Frost Flowers ◽  
Snow Model ◽  
The Antarctic

Abstract. On the Antarctic plateau, precipitation quantities are so low that the surface mass budget is for an important part determined by exchanges of water vapor between the snow surface and the atmosphere surface. At Dome C (75° S, 123° E), we have frequently observed the growth of crystals on the snow surface under calm sunny weather. Here we present the time variations of specific surface area (SSA) and density of these crystals. Using the detailed snow model Crocus, we conclude that the formation of these crystals was very likely due to the nighttime formation of surface hoar crystals and to the daytime formation of sublimation crystals. These latter crystals form by processes similar to those involved in the formation of frost flowers on young sea ice. The formation of these crystals impacts the albedo, mass and energy budget of the Antarctic plateau. In particular, the SSA variations of the surface layer can induce an instantaneous forcing at the snow surface up to −10 W m−2 at noon, resulting in a surface temperature drop of 0.45 K. This result confirms that snow SSA is a crucial variable to consider in the energy budget and climate of snow-covered surfaces.

scholarly journals Temporal and spatial variability of surface mass balance at Dome Fuji, East Antarctica, by the stake method from 1995 to 2006

2008 ◽  
Vol 54 (184) ◽  
pp. 107-116 ◽  
Author(s):  
Takao Kameda ◽  
Hideaki Motoyama ◽  
Shuji Fujita ◽  
Shuhei Takahashi
Keyword(s):  
Mass Balance ◽  
Ice Core ◽  
Snow Accumulation ◽  
East Antarctica ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Frequency Distributions ◽  
Temporal And Spatial Variability ◽  
The Antarctic ◽  
Height Data

AbstractThe surface mass balance (SMB) at Dome Fuji, East Antarctica, was estimated using 36 bamboo stakes (grid of 6 × 6, placed at 20 m intervals) from 1995 to 2006. The heights of the stake tops from the snow surface were measured at 0.5 cm resolution twice monthly in 1995, 1996, 1997 and 2003, and once a year for the rest of the study period. To account for snow settling, the average snow density at the stake base during the measurements was used for converting the stake-height data to SMB. The annual SMB from 1995 to 2006 at Dome Fuji was 27.3 ± 1.5 kg m−2 a−1. This result agrees well with the annual SMB from AD 1260 to 1993 (26.4 kg m−2 a−1) estimated from volcanic signals in the Dome Fuji ice core. Over the period 1995–2006, there were 37 (8.6% of the measurements) negative or zero annual SMB results. Variation in the multi-year averages of annual SMB decreased with the square root of the number of observation years, and 10 years of observations of a single stake allowed the estimation of annual SMB at ±10% accuracy. The frequency distributions of annual and monthly SMB were examined. The findings clarify the complex behavior of the annual and monthly SMB at Dome Fuji, which will be common phenomena in areas of low snow accumulation of the interior of the Antarctic ice sheet.

scholarly journals Evaluation of CloudSat snowfall rate profiles by a comparison with in situ micro-rain radar observations in East Antarctica

2019 ◽  
Vol 13 (3) ◽  
pp. 943-954 ◽  
Author(s):  
Florentin Lemonnier ◽  
Jean-Baptiste Madeleine ◽  
Chantal Claud ◽  
Christophe Genthon ◽  
Claudio Durán-Alarcón ◽  
...  
Keyword(s):  
Climate Models ◽  
Water Reservoir ◽  
Dronning Maud Land ◽  
Antarctic Continent ◽  
Unknown Area ◽  
The Antarctic ◽  
Vertical Level ◽  
Rain Radar ◽  
Precipitation Events

Abstract. The Antarctic continent is a vast desert and is the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote-sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the space–time-averaged observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRRs), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station located in the Dronning Maud Land escarpment zone. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10 km of the station and we compared these two different datasets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the two stations. Using different CloudSat and MRR vertical levels, we obtain 10 km space-scale and short-timescale (a few seconds) CloudSat uncertainties from −13 % up to +22 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset.

scholarly journals Snow melting bias in microwave mapping of Antarctic snow accumulation

2008 ◽  
Vol 2 (2) ◽  
pp. 255-273
Author(s):  
O. Magand ◽  
G. Picard ◽  
L. Brucker ◽  
M. Fily ◽  
C. Genthon
Keyword(s):  
Reasonable Agreement ◽  
Snow Accumulation ◽  
Snow Melting ◽  
Surface Mass ◽  
Surface Emission ◽  
Continental Scale ◽  
Antarctic Snow ◽  
In Situ Observations ◽  
Microwave Sensors

Abstract. Satellite records of microwave surface emission have been used to interpolate in-situ observations of Antarctic surface mass balance (SMB) and build continental-scale maps of accumulation. Using a carefully screened subset of accumulation measurements in the 90°–180° E sector, we show a reasonable agreement with microwave-based accumulation map in the dry-snow regions, but large discrepancies in the coastal regions where melt occurs during summer. Using an emission microwave model, we explain the failure of microwave sensors to retrieve accumulation by the presence of layers created by melt/re-freeze cycles. We conclude that regions potentially affected by melting should be masked-out in microwave-based interpolation schemes.

scholarly journals GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

2020 ◽  
Author(s):  
Xavier Fettweis ◽  
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Cores ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Meltwater Runoff

&lt;p&gt;The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 +/- 10 Gt/yr&lt;sup&gt;2&lt;/sup&gt; since the end of the 1990's, with around 60% of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980-2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 +/- 112 Gt/yr, but has decreased at an average rate of -7.3 Gt/yr&lt;sup&gt;2&lt;/sup&gt; (with a significance of 96%), mainly driven by an increase of 8.0 Gt/yr&lt;sup&gt;2&lt;/sup&gt; (with a significance of 98%) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. It is also interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models. Finally, results from MAR forced by ERA5 will be added in this intercomparison to evaluate the added value of using this new reanalysis as forcing vs the former ERA-Interim reanalysis (used in SMBMIP).&amp;#160;&lt;/p&gt;

scholarly journals Brief communication: Impact of common ice mask in surface mass balance estimates over the Antarctic ice sheet

2021 ◽  
Author(s):  
Nicolaj Hansen ◽  
Sebastian Bjerregaard Simonsen ◽  
Fredrik Boberg ◽  
Christoph Kittel ◽  
Andrew Orr ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Ice Sheet ◽  
Regional Climate Models ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Glacier Ice ◽  
High Precipitation ◽  
The Antarctic

Abstract. Regional climate models compute ice sheet surface mass balance (SMB) over a mask that defines the area covered by glacier ice, but ice masks have not been harmonised between models. Intercomparison studies of modelled SMB therefore use a common ice mask. The SMB in areas outside the common ice mask, which are typically coastal and high precipitation regions, are discarded. Ice mask differences change integrated SMB by between 40.5 to 140.6 Gt yr−1, (1.8 % to 6.0 % of ensemble mean SMB), equivalent to the entire Antarctic mass imbalance. We conclude there is a pressing need for a common ice mask protocol.

scholarly journals Evaluation of the CMIP5 models in the aim of regional modelling of the Antarctic surface mass balance

2015 ◽  
Vol 9 (3) ◽  
pp. 3113-3136 ◽  
Author(s):  
C. Agosta ◽  
X. Fettweis ◽  
R. Datta
Keyword(s):  
Mass Balance ◽  
Temperature Increase ◽  
Climate Models ◽  
Regional Climate ◽  
Cmip5 Models ◽  
Surface Mass Balance ◽  
Initial State ◽  
Sea Ice Extent ◽  
Surface Mass ◽  
The Antarctic

Abstract. The Antarctic surface mass balance (SMB) cannot be reliably deduced from global climate models (GCMs), both because their spatial resolution is insufficient and because their physics are not adapted for cold and snow-covered regions. By contrast, regional climate models (RCMs) adapted for polar regions can physically and dynamically downscale surface mass balance components over the ice-sheet using large scale forcing at their boundaries. Polar-oriented RCMs require appropriate GCM fields for forcing because the response of the cryosphere to a warming climate is dependent on its initial state and is not linear with respect to temperature increase. In this context, we evaluate current climate in 41 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset over Antarctica by focusing on forcing fields which may have the greatest impact on SMB components simulated by RCMs. Our inter-comparison includes 5 reanalyses, among which ERA-Interim reanalysis is chosen as a reference over 1979–2014. Model efficiency is assessed taking into account the multi-decadal variability of the fields over the 1850–1980 period. We show that less than 10 CMIP5 models show reasonable biases compared to ERA-Interim, among which ACCESS1-3 seems to be the most pertinent choice for regional climate modeling over Antarctica, followed by CMCC-CM, MIROC-ESM/MIROC-ESM-CHEM and NorESM1-M. Finally, climate change over the Southern Ocean is much more dependent on the initial state of winter sea-ice extent and on the local feedback between air temperature increase and winter sea-ice extent decrease than on the global warming signal.

scholarly journals Evaluation of the CMIP5 models in the aim of regional modelling of the Antarctic surface mass balance

2015 ◽  
Vol 9 (6) ◽  
pp. 2311-2321 ◽  
Author(s):  
C. Agosta ◽  
X. Fettweis ◽  
R. Datta
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Temperature Increase ◽  
Climate Models ◽  
Ice Sheet ◽  
Cmip5 Models ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
The Antarctic

Abstract. The surface mass balance (SMB) of the Antarctic Ice Sheet cannot be reliably deduced from global climate models (GCMs), both because their spatial resolution is insufficient and because their physics are not adapted for cold and snow-covered regions. By contrast, regional climate models (RCMs) adapted for polar regions can physically and dynamically downscale SMB components over the ice sheet using large-scale forcing at their boundaries. Polar-oriented RCMs require appropriate GCM fields for forcing because the response of the cryosphere to a warming climate is dependent on its initial state and is not linear with respect to temperature increase. In this context, we evaluate the current climate in 41 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) data set over Antarctica by focusing on forcing fields which may have the greatest impact on SMB components simulated by RCMs. Our inter-comparison includes six reanalyses, among which ERA-Interim reanalysis is chosen as a reference over 1979–2014. Model efficiency is assessed taking into account the multi-decadal variability of the fields over the 1850–1980 period. We show that fewer than 10 CMIP5 models show reasonable biases compared to ERA-Interim, among which ACCESS1-3 is the most pertinent choice for forcing RCMs over Antarctica, followed by ACCESS1-0, CESM1-BGC, CESM1-CAM5, NorESM1-M, CCSM4 and EC-EARTH. Finally, climate change over the Southern Ocean in CMIP5 is less sensitive to the global warming signal than it is to the present-day simulated sea-ice extent and to the feedback between sea-ice decrease and air temperature increase around Antarctica.

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