scholarly journals Scoring Antarctic surface mass balance in climate models to refine future projections

2019 ◽  
Author(s):  
Tessa Gorte ◽  
Jan T. M. Lenaerts ◽  
Brooke Medley
Keyword(s):  
Mass Balance ◽  
Temporal Variability ◽  
Climate Models ◽  
Ice Sheet ◽  
Snow Accumulation ◽  
Historical Period ◽  
Surface Mass Balance ◽  
Max Planck ◽  
Data Set ◽  
Surface Mass

Abstract. An increase of Antarctic Ice Sheet (AIS) surface mass balance (SMB) has the potential to mitigate future sea level rise that is driven by enhanced solid ice discharge from the ice sheet. For climate models, AIS SMB provides a difficult challenge, as it is highly susceptible to spatial, seasonal and interannual variability. Here we use a reconstructed data set of AIS snow accumulation as "true" observational data, to evaluate the ability of the CMIP5 and CMIP6 suites of models in capturing the mean, trends, temporal variability and spatial variability in SMB over the historical period (1850–2000). This gives insight into which models are most reliable for predicting SMB into the future. We found that the best scoring models included the National Aeronautics and Space Administration's GISS models and the Max Planck Institute far Meteorologie's MPI models. Using a scoring system based on SMB magnitude, trend, and temporal variability across the AIS, as well as spatial SMB variability, we selected a subset of the top 10th percentile of models to refine 21st century (2000–2100) AIS-integrated SMB projections to 2295 ± 1222 Gt per year 2382 ± 1316 Gt per year, and 2648 ± 1530 Gt per year for Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. We also reduced the spread in AIS-integrated mean SMB by 78 %, 75 %, and 78 % in RCPs 2.6, 4.5, and 8.5, respectively.

scholarly journals Scoring Antarctic surface mass balance in climate models to refine future projections

2020 ◽  
Vol 14 (12) ◽  
pp. 4719-4733
Author(s):  
Tessa Gorte ◽  
Jan T. M. Lenaerts ◽  
Brooke Medley
Keyword(s):  
Spatial Variability ◽  
Mass Balance ◽  
Temporal Variability ◽  
Climate Models ◽  
Ice Sheet ◽  
Snow Accumulation ◽  
Historical Period ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass

Abstract. An increase in Antarctic Ice Sheet (AIS) surface mass balance (SMB) has the potential to mitigate future sea level rise that is driven by enhanced solid ice discharge from the ice sheet. For climate models, AIS SMB provides a difficult challenge, as it is highly susceptible to spatial, seasonal, and interannual variability. Here we use a reconstructed data set of AIS snow accumulation as “true” observational data, to evaluate the ability of the CMIP5 and CMIP6 suites of models in capturing the mean, trends, temporal variability, and spatial variability in SMB over the historical period (1850–2000). This gives insight into which models are most reliable for predicting SMB into the future. We found that the best scoring models included the National Aeronautics and Space Administration (NASA) GISS model and the Max Planck Institute (MPI) for Meteorology's model for CMIP5, as well as one of the Community Earth System Model v2 (CESM2) models and one MPI model for CMIP6. Using a scoring system based on SMB mean value, trend, and temporal variability across the AIS, as well as spatial SMB variability, we selected a subset of the top 10th percentile of models to refine 21st century (2000–2100) AIS-integrated SMB projections to 2274 ± 282 Gt yr−1, 2358 ± 286 Gt yr−1, and 2495 ± 291 Gt yr−1 for Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. We also reduced the spread in AIS-integrated mean SMB by 79 %, 79 %, and 74 % in RCPs 2.6, 4.5, and 8.5, respectively. Notably, we find that there is no improvement from CMIP5 to CMIP6 in overall score. In fact, CMIP6 performed slightly worse on average compared to CMIP5 at capturing the aforementioned SMB criteria. Our results also indicate that model performance scoring is affected by internal climate variability (particularly the spatial variability), which is illustrated by the fact that the range in overall score between ensemble members within the CESM1 Large Ensemble is comparable to the range in overall score between CESM1 model simulations within the CMIP5 model suite. We also find that a higher horizontal resolution does not yield to a conclusive improvement in score.

scholarly journals Analysis of the surface mass balance for deglacial climate simulations

2021 ◽  
Vol 15 (2) ◽  
pp. 1131-1156
Author(s):  
Marie-Luise Kapsch ◽  
Uwe Mikolajewicz ◽  
Florian A. Ziemen ◽  
Christian B. Rodehacke ◽  
Clemens Schannwell
Keyword(s):  
Mass Balance ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Ice Sheet ◽  
Meridional Overturning Circulation ◽  
Balance Model ◽  
Surface Mass Balance ◽  
Max Planck ◽  
Equilibrium Line Altitude ◽  
Surface Mass

Abstract. A realistic simulation of the surface mass balance (SMB) is essential for simulating past and future ice-sheet changes. As most state-of-the-art Earth system models (ESMs) are not capable of realistically representing processes determining the SMB, most studies of the SMB are limited to observations and regional climate models and cover the last century and near future only. Using transient simulations with the Max Planck Institute ESM in combination with an energy balance model (EBM), we extend previous research and study changes in the SMB and equilibrium line altitude (ELA) for the Northern Hemisphere ice sheets throughout the last deglaciation. The EBM is used to calculate and downscale the SMB onto a higher spatial resolution than the native ESM grid and allows for the resolution of SMB variations due to topographic gradients not resolved by the ESM. An evaluation for historical climate conditions (1980–2010) shows that derived SMBs compare well with SMBs from regional modeling. Throughout the deglaciation, changes in insolation dominate the Greenland SMB. The increase in insolation and associated warming early in the deglaciation result in an ELA and SMB increase. The SMB increase is caused by compensating effects of melt and accumulation: the warming of the atmosphere leads to an increase in melt at low elevations along the ice-sheet margins, while it results in an increase in accumulation at higher levels as a warmer atmosphere precipitates more. After 13 ka, the increase in melt begins to dominate, and the SMB decreases. The decline in Northern Hemisphere summer insolation after 9 ka leads to an increasing SMB and decreasing ELA. Superimposed on these long-term changes are centennial-scale episodes of abrupt SMB and ELA decreases related to slowdowns of the Atlantic meridional overturning circulation (AMOC) that lead to a cooling over most of the Northern Hemisphere.

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 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 A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015)

2016 ◽  
Vol 10 (5) ◽  
pp. 2361-2377 ◽  
Author(s):  
Brice Noël ◽  
Willem Jan van de Berg ◽  
Horst Machguth ◽  
Stef Lhermitte ◽  
Ian Howat ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
Ice Caps ◽  
Elevation Model

Abstract. This study presents a data set of daily, 1 km resolution Greenland ice sheet (GrIS) surface mass balance (SMB) covering the period 1958–2015. Applying corrections for elevation, bare ice albedo and accumulation bias, the high-resolution product is statistically downscaled from the native daily output of the polar regional climate model RACMO2.3 at 11 km. The data set includes all individual SMB components projected to a down-sampled version of the Greenland Ice Mapping Project (GIMP) digital elevation model and ice mask. The 1 km mask better resolves narrow ablation zones, valley glaciers, fjords and disconnected ice caps. Relative to the 11 km product, the more detailed representation of isolated glaciated areas leads to increased precipitation over the southeastern GrIS. In addition, the downscaled product shows a significant increase in runoff owing to better resolved low-lying marginal glaciated regions. The combined corrections for elevation and bare ice albedo markedly improve model agreement with a newly compiled data set of ablation measurements.

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 Surface mass balance of the Greenland ice sheet from climate-analysis data and accumulation/runoff models

2002 ◽  
Vol 35 ◽  
pp. 67-72 ◽  
Author(s):  
Edward Hanna ◽  
Philippe Huybrechts ◽  
Thomas L. Mote
Keyword(s):  
Mass Balance ◽  
Satellite Data ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Surface Elevation ◽  
Great Promise ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass

AbstractWe used surface climate fields from high-resolution (~0.5660.56˚) European Centre for Medium-RangeWeather Forecasts (ECMWF) operational analyses (1992–98), together with meteorological and glaciological models of snow accumulation and surface meltwater runoff/retention, to produce novel maps of Greenland ice sheet (GIS) net accumulation, net runoff and surface mass balance (SMB). We compared our runoff maps with similar-scaled runoff (melt minus refreezing) maps based on passive-microwave satellite data. Our gross spatial/temporal patterns of runoff compared well with those from the satellite data, although amounts of modelled runoff are likely too low. Mean accumulation was 0.287 (0.307)ma–1, and mean runoff was 0.128 (0.151)ma–1, averaged across the W. Abdalati (T. L. Mote) GIS mask. Corresponding mean SMB was 0.159 (0.156)ma–1, with considerable interannual variability (standard deviation ~0.11ma–1) primarily due to variations in runoff. Considering best estimates of current iceberg calving, overall the GIS is probably currently losing mass. Our study shows great promise for meaningfully modelling SMB based on forthcoming ``second-generation’’ ECMWF re-analysis (ERA-40) data, and comparing the results with ongoing laser/radarmeasurements of surface elevation. This should help elucidate to what extent surface elevation changes are caused by short-term SMB variations or other factors (e.g. ice dynamics).

scholarly journals High resolution (1 km) positive degree-day modelling of Greenland ice sheet surface mass balance, 1870–2012 using reanalysis data

2016 ◽  
Vol 63 (237) ◽  
pp. 176-193 ◽  
Author(s):  
DAVID J. WILTON ◽  
AMY JOWETT ◽  
EDWARD HANNA ◽  
GRANT R. BIGG ◽  
MICHIEL R. VAN DEN BROEKE ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Local Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Reanalysis Data ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Degree Day ◽  
Positive Degree

ABSTRACTWe show results from a positive degree-day (PDD) model of Greenland ice sheet (GrIS) surface mass balance (SMB), 1870–2012, forced with reanalysis data. The model includes an improved daily temperature parameterization as compared with a previous version and is run at 1 km rather than 5 km resolution. The improvements lead overall to higher SMB with the same forcing data. We also compare our model with results from two regional climate models (RCMs). While there is good qualitative agreement between our PDD model and the RCMs, it usually results in lower precipitation and lower runoff but approximately equivalent SMB: mean 1979–2012 SMB (± standard deviation), in Gt a−1, is 382 ± 78 in the PDD model, compared with 379 ± 101 and 425 ± 90 for the RCMs. Comparison with in situ SMB observations suggests that the RCMs may be more accurate than PDD at local level, in some areas, although the latter generally compares well. Dividing the GrIS into seven drainage basins we show that SMB has decreased sharply in all regions since 2000. Finally we show correlation between runoff close to two calving glaciers and either calving front retreat or calving flux, this being most noticeable from the mid-1990s.

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 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

<p>The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 +/- 10 Gt/yr<sup>2</sup> 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<sup>2</sup> (with a significance of 96%), mainly driven by an increase of 8.0 Gt/yr<sup>2</sup> (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). </p>

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