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

2012 ◽  
Vol 6 (6) ◽  
pp. 1275-1294 ◽  
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.

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 Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes

2019 ◽  
Vol 13 (1) ◽  
pp. 281-296 ◽  
Author(s):  
Cécile Agosta ◽  
Charles Amory ◽  
Christoph Kittel ◽  
Anais Orsi ◽  
Vincent Favier ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Ice Sheet ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Drifting Snow ◽  
The Antarctic ◽  
Snow Transport

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 SMB 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 MERRA-2, for the period 1979–2015, and we compare MAR 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 or underestimated 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 drifting snow transport fluxes not included in MAR and probably underestimated in RACMO2 by a factor of 3. Our results tend to confirm that drifting snow transport and sublimation fluxes are much larger than previous model-based estimates and need to be better resolved and constrained in climate models. Sublimation of precipitating particles in low-level atmospheric layers is responsible for the significantly lower snowfall rates in MAR than in RACMO2 in katabatic channels at the ice sheet margins. Atmospheric sublimation in MAR represents 363 Gt yr−1 over the grounded ice sheet for the year 2015, which is 16 % of the simulated snowfall loaded at the ground. This estimate is consistent with a recent study based on precipitation radar observations and is more than twice as much as simulated in RACMO2 because of different time residence of precipitating particles in the atmosphere. The remaining spatial differences in snowfall between MAR and RACMO2 are attributed to differences in advection of precipitation with snowfall particles being likely advected too far inland in MAR.

scholarly journals What is the Surface Mass Balance of Antarctica? An Intercomparison of Regional Climate Model Estimates

2020 ◽  
Author(s):  
Ruth Mottram ◽  
Nicolaj Hansen ◽  
Christoph Kittel ◽  
Melchior van Wessem ◽  
Cécile Agosta ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Ice Sheet ◽  
Regional Climate Models ◽  
Coastal Areas ◽  
Surface Mass Balance ◽  
Antarctic Ice Sheet ◽  
Surface Mass ◽  
Ensemble Mean

Abstract. Antarctic ice sheet mass loss is currently equivalent to around 1 mm year−1 of global mean sea level rise. Most mass is lost due to sub-ice shelf melting and calving of icebergs. Ice sheet models of the Antarctic ice sheet have thus largely concentrated on parameterising sub-shelf and calving processes. However, surface mass balance (SMB) is also of crucial importance in controlling the stability and evolution of the vast Antarctic ice sheet. In this paper we compare the performance of five different regional climate models (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM and RACMO2.3p2) in simulating the near surface climate and SMB of Antarctica. Our results show that, when regional climate models (RCMs) are forced by the ERA-Interim reanalysis, the integrated Antarctic ice sheet ensemble mean annual SMB is 2329 ± 94 Gigatonnes (Gt) year−1 over the common 1987 to 2015 period. However, individual model estimates vary from 1961 ± 70 to 2519 ± 118 Gt year−1. The large differences are mostly explained by different SMB estimates in West Antarctica and the peninsula as well as around the Transantarctic mountains. The calculated annual average SMB is very sensitive to the period chosen but over the climatological mean period of 1980 to 2010 the ensemble mean is 2486 Gt year−1. The interannual variability in SMB is consistent between the models and dominated by variability in the driving ERA-Interim reanalysis. The declining trend in Antarctic SMB reported in other studies is also very sensitive to period chosen and models disagree on the sign and magnitude of the trend in Antarctic SMB over the ERA-Interim period. Evaluation of models shows that they simulate Antarctic climate well when compared with daily observed temperature (Pearson correlation of 0.85 and higher) and pressure (bias ranges from −0.39 hPa in HIRHAM5 to −6.01 hPa in MAR with a mean of −3.49 hPa over all models) and nudged models, constrained within the domain as well as at lateral boundaries, perform better than un-nudged models. We compare modelled surface mass balance with a large dataset of observations which, though biased by undersampling in some regions, indicates that many of the biases in modelled SMB are common between models. The inclusion of drifting snow schemes improves modelled SMB on ice sheet slopes between 1000 and 2000 m where strong katabatic winds form but other regions where precipitation rates are high lack observations needed for the evaluation of different SMB estimates. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution is therefore factored into our analysis. The majority of the different values for continental SMB are due to differences in modelled precipitation at relatively few grid points in coastal areas. Our analysis suggests that targeting coastal areas for observational campaigns will be key to improving and refining estimates of the total surface mass balance of Antarctica.

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

2012 ◽  
Vol 6 (3) ◽  
pp. 2059-2113 ◽  
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.

scholarly journals Coupling of climate models and ice sheet models by surface mass balance gradients: application to the Greenland Ice Sheet

2012 ◽  
Vol 6 (2) ◽  
pp. 255-272 ◽  
Author(s):  
M. M. Helsen ◽  
R. S. W. van de Wal ◽  
M. R. van den Broeke ◽  
W. J. van de Berg ◽  
J. Oerlemans
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Lapse Rate ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Temperature Lapse Rate

Abstract. It is notoriously difficult to couple surface mass balance (SMB) results from climate models to the changing geometry of an ice sheet model. This problem is traditionally avoided by using only accumulation from a climate model, and parameterizing the meltwater run-off as a function of temperature, which is often related to surface elevation (Hs). In this study, we propose a new strategy to calculate SMB, to allow a direct adjustment of SMB to a change in ice sheet topography and/or a change in climate forcing. This method is based on elevational gradients in the SMB field as computed by a regional climate model. Separate linear relations are derived for ablation and accumulation, using pairs of Hs and SMB within a minimum search radius. The continuously adjusting SMB forcing is consistent with climate model forcing fields, also for initially non-glaciated areas in the peripheral areas of an ice sheet. When applied to an asynchronous coupled ice sheet – climate model setup, this method circumvents traditional temperature lapse rate assumptions. Here we apply it to the Greenland Ice Sheet (GrIS). Experiments using both steady-state forcing and glacial-interglacial forcing result in realistic ice sheet reconstructions.

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.

scholarly journals Blowing snow in Antarctica and its contribution to the surface mass balance

2020 ◽  
Author(s):  
Franziska Gerber ◽  
Varun Sharma ◽  
Michael Lehning
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Special Focus ◽  
Surface Mass Balance ◽  
Blowing Snow ◽  
Surface Mass ◽  
Warming World ◽  
The Antarctic

<p>On the windiest, coldest and driest continent of the world, blowing snow is frequently active, especially during the winter months. Coastal regions with strong katabatic winds are especially prone to blowing snow and its sublimation. However, the contribution of blowing snow to the surface mass balance from snow blown off the continent and blowing snow sublimation is not well constraint by direct measurements. Furthermore, model and satellite assessments disagree on the magnitude of the effect.</p><p>Current studies of the Antarctic surface mass balance are mainly based on regional climate models. However, most models rely on rather simple representations of the snow cover as well as blowing snow. With the aim of improving the surface mass balance representation and specifically snow transport and sublimation due to blowing snow, we coupled the well-established snow model SNOWPACK to the Weather Research and Forecasting Model (WRF). The new coupled model, called ‘CRYOWRF’, is aimed at an improved representation of snow and snow-atmosphere interaction in all cryospheric environments.</p><p>CRYOWRF simulations show good agreement with measurements at meteorological stations on the Antarctic continent. Moreover, the timing of modeled blowing snow events agrees well with few local blowing snow measurements. Monthly frequencies of simulated and satellite-derived spatial blowing snow distributions result in similar patterns. We will present estimates of the amount and importance of blowing snow on the surface mass balance in Antarctica based on 8 years of simulations (2010-2018), with a special focus on blowing snow sublimation. The introduced model will be useful for future predictions of surface mass balance estimates, which are important to assess the contribution of the Antarctic ice sheet to sea level rise in a warming world.</p>

scholarly journals Application of GRACE to the assessment of model-based estimates of monthly Greenland Ice Sheet mass balance (2003–2012)

2016 ◽  
Vol 10 (5) ◽  
pp. 1965-1989 ◽  
Author(s):  
Nicole-Jeanne Schlegel ◽  
David N. Wiese ◽  
Eric Y. Larour ◽  
Michael M. Watkins ◽  
Jason E. Box ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Spatial Scales ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Regional Climate Models ◽  
Surface Mass ◽  
Model Based ◽  
Ice Sheet Mass Balance

Abstract. Quantifying the Greenland Ice Sheet's future contribution to sea level rise is a challenging task that requires accurate estimates of ice sheet sensitivity to climate change. Forward ice sheet models are promising tools for estimating future ice sheet behavior, yet confidence is low because evaluation of historical simulations is challenging due to the scarcity of continental-wide data for model evaluation. Recent advancements in processing of Gravity Recovery and Climate Experiment (GRACE) data using Bayesian-constrained mass concentration ("mascon") functions have led to improvements in spatial resolution and noise reduction of monthly global gravity fields. Specifically, the Jet Propulsion Laboratory's JPL RL05M GRACE mascon solution (GRACE_JPL) offers an opportunity for the assessment of model-based estimates of ice sheet mass balance (MB) at ∼ 300 km spatial scales. Here, we quantify the differences between Greenland monthly observed MB (GRACE_JPL) and that estimated by state-of-the-art, high-resolution models, with respect to GRACE_JPL and model uncertainties. To simulate the years 2003–2012, we force the Ice Sheet System Model (ISSM) with anomalies from three different surface mass balance (SMB) products derived from regional climate models. Resulting MB is compared against GRACE_JPL within individual mascons. Overall, we find agreement in the northeast and southwest where MB is assumed to be primarily controlled by SMB. In the interior, we find a discrepancy in trend, which we presume to be related to millennial-scale dynamic thickening not considered by our model. In the northwest, seasonal amplitudes agree, but modeled mass trends are muted relative to GRACE_JPL. Here, discrepancies are likely controlled by temporal variability in ice discharge and other related processes not represented by our model simulations, i.e., hydrological processes and ice–ocean interaction. In the southeast, GRACE_JPL exhibits larger seasonal amplitude than predicted by the models while simultaneously having more pronounced trends; thus, discrepancies are likely controlled by a combination of missing processes and errors in both the SMB products and ISSM. At the margins, we find evidence of consistent intra-annual variations in regional MB that deviate distinctively from the SMB annual cycle. Ultimately, these monthly-scale variations, likely associated with hydrology or ice–ocean interaction, contribute to steeper negative mass trends observed by GRACE_JPL. Thus, models should consider such processes at relatively high (monthly-to-seasonal) temporal resolutions to achieve accurate estimates of Greenland MB.

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