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

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).

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Elevation change of the Greenland Ice Sheet due to surface mass balance and firn processes, 1960–2014

The Cryosphere ◽

10.5194/tc-9-2009-2015 ◽

2015 ◽

Vol 9 (6) ◽

pp. 2009-2025 ◽

Cited By ~ 36

Author(s):

P. Kuipers Munneke ◽

S. R. M. Ligtenberg ◽

B. P. Y. Noël ◽

I. M. Howat ◽

J. E. Box ◽

...

Keyword(s):

Mass Balance ◽

Volume Change ◽

Climate Model ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Elevation ◽

Surface Mass Balance ◽

Elevation Change ◽

Ice Dynamics ◽

Surface Mass

Abstract. Observed changes in the surface elevation of the Greenland Ice Sheet are caused by ice dynamics, basal elevation change, basal melt, surface mass balance (SMB) variability, and by compaction of the overlying firn. The last two contributions are quantified here using a firn model that includes compaction, meltwater percolation, and refreezing. The model is forced with surface mass fluxes and temperature from a regional climate model for the period 1960–2014. The model results agree with observations of surface density, density profiles from 62 firn cores, and altimetric observations from regions where ice-dynamical surface height changes are likely small. In areas with strong surface melt, the firn model overestimates density. We find that the firn layer in the high interior is generally thickening slowly (1–5 cm yr−1). In the percolation and ablation areas, firn and SMB processes account for a surface elevation lowering of up to 20–50 cm yr−1. Most of this firn-induced marginal thinning is caused by an increase in melt since the mid-1990s and partly compensated by an increase in the accumulation of fresh snow around most of the ice sheet. The total firn and ice volume change between 1980 and 2014 is estimated at −3295 ± 1030 km3 due to firn and SMB changes, corresponding to an ice-sheet average thinning of 1.96 ± 0.61 m. Most of this volume decrease occurred after 1995. The computed changes in surface elevation can be used to partition altimetrically observed volume change into surface mass balance and ice-dynamically related mass changes.

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Elevation change of the Greenland ice sheet due to surface mass balance and firn processes, 1960–2013

The Cryosphere Discussions ◽

10.5194/tcd-9-3541-2015 ◽

2015 ◽

Vol 9 (3) ◽

pp. 3541-3580 ◽

Cited By ~ 5

Author(s):

P. Kuipers Munneke ◽

S. R. M. Ligtenberg ◽

B. P. Y. Noël ◽

I. M. Howat ◽

J. E. Box ◽

...

Keyword(s):

Mass Balance ◽

Volume Change ◽

Climate Model ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Elevation ◽

Surface Mass Balance ◽

Elevation Change ◽

Ice Dynamics ◽

Surface Mass

Abstract. Observed changes in the surface elevation of the Greenland ice sheet are caused by ice dynamics, basal elevation change, surface mass balance (SMB) variability, and by compaction of the overlying firn. The latter two contributions are quantified here using a firn model that includes compaction, meltwater percolation, and refreezing. The model is forced with surface mass fluxes and temperature from a regional climate model for the period 1960–2013. The model results agree with observations of surface density, density profiles from 62 firn cores, and altimetric observations from regions where ice-dynamical surface height changes are likely small. We find that the firn layer in the high interior is generally thickening slowly (1–5 cm yr−1). In the percolation and ablation areas, firn and SMB processes account for a surface elevation lowering of up to 20–50 cm yr−1. Most of this firn-induced marginal thinning is caused by an increase in melt since the mid-1990s, and partly compensated by an increase in the accumulation of fresh snow around most of the ice sheet. The total firn and ice volume change between 1980 and 2013 is estimated at −3900 ± 1030 km3 due to firn and SMB, corresponding to an ice-sheet average thinning of 2.32 ± 0.61 m. Most of this volume decrease occurred after 1995. The computed changes in surface elevation can be used to partition altimetrically observed volume change into surface mass balance and ice-dynamically related mass changes.

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

10.5194/tc-2018-76 ◽

2018 ◽

Cited By ~ 4

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.

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Annual Greenland accumulation rates (2009–2012) from airborne snow radar

The Cryosphere ◽

10.5194/tc-10-1739-2016 ◽

2016 ◽

Vol 10 (4) ◽

pp. 1739-1752 ◽

Cited By ~ 36

Author(s):

Lora S. Koenig ◽

Alvaro Ivanoff ◽

Patrick M. Alexander ◽

Joseph A. MacGregor ◽

Xavier Fettweis ◽

...

Keyword(s):

Mass Balance ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Ice Cores ◽

Snow Accumulation ◽

Ultra Wideband ◽

The Arctic ◽

Surface Mass Balance ◽

Accumulation Rates ◽

Surface Mass

Abstract. Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2–6.5 GHz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semiautomated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009–2012. The uncertainty in these radar-derived accumulation rates is on average 14 %. A comparison of the radar-derived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and long-term mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models.

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Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model

10.5194/tc-2016-268 ◽

2016 ◽

Cited By ~ 3

Author(s):

Xavier Fettweis ◽

Jason E. Box ◽

Cécile Agosta ◽

Charles Amory ◽

Christoph Kittel ◽

...

Keyword(s):

Mass Balance ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Ice Cores ◽

Surface Mass Balance ◽

Reference Period ◽

Ice Dynamics ◽

Near Surface ◽

Surface Mass

Abstract. With the aim of studying the recent Greenland Ice Sheet (GrIS) Surface Mass Balance (SMB) decrease with respect to the last century, we have forced the regional climate MAR model (version 3.5.2) with the ERA-Interim (1979–2015), ERA-40 (1958–2001), NCEP-NCARv1 (1948–2015), NCEP-NCARv2 (1979–2015), JRA-55 (1958–2014), 20CRv2(c) (1900–2014) and ERA-20C (1900–2010) reanalysis. While all of these forcing products are reanalyses assumed to represent the same climate, they produce significant differences in the MAR simulated SMB over their common period. A temperature adjustment of +1 °C (respectively −1 °C) improved the accuracy of MAR boundary conditions from both ERA-20C and 20CRv2 reanalyses given that ERA-20C (resp. 20CRv2) is 1 °C colder (resp. warmer) over Greenland than ERA-Interim over 1980–2010. Comparisons with daily PROMICE near-surface observations validated these adjustments. Comparisons with SMB measurements from PROMICE, ice cores and satellite derived melt extent reveal the most accurate forcing data sets for simulating the GrIS SMB to be ERA-Interim and NCEP-NCARv1. However, some biases remain in MAR suggesting that some improvements need still to be done in its cloudiness and radiative scheme as well as in the representation of the bare ice albedo. Results from all forcing simulations indicate: (i) the period 1961–1990 commonly chosen as a stable reference period for Greenland SMB and ice dynamics is actually a period when the SMB was anomalously positive (~ +10 %) compared to the last 120 years; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120 year common period; (iii) before 1960, both ERA-20C and 20CRv2 forced MAR simulations suggest a significant precipitation increase over 1900–1950 although this increase could be the result of an artefact in reanalysis not enough constrained by observations during this period. These MAR-based SMB and accumulation reconstructions are however quite similar to those from Box (2013) after 1930, which confirms the Box (2013)'s stationarity assumption of SMB over the last century. Finally, the ERA-20C forced simulation only suggests that SMB during the 1920–1930 warm period over Greenland was comparable to the SMB of the 2000's due to both higher melt and lower precipitation than normal.

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Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model

The Cryosphere ◽

10.5194/tc-11-1015-2017 ◽

2017 ◽

Vol 11 (2) ◽

pp. 1015-1033 ◽

Cited By ~ 156

Author(s):

Xavier Fettweis ◽

Jason E. Box ◽

Cécile Agosta ◽

Charles Amory ◽

Christoph Kittel ◽

...

Keyword(s):

Mass Balance ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Ice Cores ◽

Surface Mass Balance ◽

Reference Period ◽

Ice Dynamics ◽

Near Surface ◽

Surface Mass

Abstract. With the aim of studying the recent Greenland ice sheet (GrIS) surface mass balance (SMB) decrease relative to the last century, we have forced the regional climate MAR (Modèle Atmosphérique Régional; version 3.5.2) model with the ERA-Interim (ECMWF Interim Re-Analysis; 1979–2015), ERA-40 (1958–2001), NCEP–NCARv1 (National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis version 1; 1948–2015), NCEP–NCARv2 (1979–2015), JRA-55 (Japanese 55-year Reanalysis; 1958–2014), 20CRv2(c) (Twentieth Century Reanalysis version 2; 1900–2014) and ERA-20C (1900–2010) reanalyses. While all these forcing products are reanalyses that are assumed to represent the same climate, they produce significant differences in the MAR-simulated SMB over their common period. A temperature adjustment of +1 °C (respectively −1 °C) was, for example, needed at the MAR boundaries with ERA-20C (20CRv2) reanalysis, given that ERA-20C (20CRv2) is ∼ 1 °C colder (warmer) than ERA-Interim over Greenland during the period 1980–2010. Comparisons with daily PROMICE (Programme for Monitoring of the Greenland Ice Sheet) near-surface observations support these adjustments. Comparisons with SMB measurements, ice cores and satellite-derived melt extent reveal the most accurate forcing datasets for the simulation of the GrIS SMB to be ERA-Interim and NCEP–NCARv1. However, some biases remain in MAR, suggesting that some improvements are still needed in its cloudiness and radiative schemes as well as in the representation of the bare ice albedo. Results from all MAR simulations indicate that (i) the period 1961–1990, commonly chosen as a stable reference period for Greenland SMB and ice dynamics, is actually a period of anomalously positive SMB (∼ +40 Gt yr−1) compared to 1900–2010; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120-year common period; (iii) before 1960, both ERA-20C and 20CRv2-forced MAR simulations suggest a significant precipitation increase over 1900–1950, but this increase could be the result of an artefact in the reanalyses that are not well-enough constrained by observations during this period and (iv) since the 1980s, snowfall is quite stable after having reached a maximum in the 1970s. These MAR-based SMB and accumulation reconstructions are, however, quite similar to those from Box (2013) after 1930 and confirm that SMB was quite stable from the 1940s to the 1990s. Finally, only the ERA-20C-forced simulation suggests that SMB during the 1920–1930 warm period over Greenland was comparable to the SMB of the 2000s, due to both higher melt and lower precipitation than normal.

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Ice dynamics will remain a primary driver of Greenland ice sheet mass loss over the next century

Communications Earth & Environment ◽

10.1038/s43247-021-00092-z ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Youngmin Choi ◽

Mathieu Morlighem ◽

Eric Rignot ◽

Michael Wood

Keyword(s):

Mass Loss ◽

Mass Balance ◽

Numerical Models ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Mass Balance ◽

Ice Dynamics ◽

Surface Mass ◽

Flow Acceleration ◽

Total Mass Loss

AbstractThe mass loss of the Greenland Ice Sheet is nearly equally partitioned between a decrease in surface mass balance from enhanced surface melt and an increase in ice dynamics from the acceleration and retreat of its marine-terminating glaciers. Much uncertainty remains in the future mass loss of the Greenland Ice Sheet due to the challenges of capturing the ice dynamic response to climate change in numerical models. Here, we estimate the sea level contribution of the Greenland Ice Sheet over the 21st century using an ice-sheet wide, high-resolution, ice-ocean numerical model that includes surface mass balance forcing, thermal forcing from the ocean, and iceberg calving dynamics. The model is calibrated with ice front observations from the past eleven years to capture the recent evolution of marine-terminating glaciers. Under a business as usual scenario, we find that northwest and central west Greenland glaciers will contribute more mass loss than other regions due to ice front retreat and ice flow acceleration. By the end of century, ice discharge from marine-terminating glaciers will contribute 50 ± 20% of the total mass loss, or twice as much as previously estimated although the contribution from the surface mass balance increases towards the end of the century.

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Effect of uncertainty in surface mass balance–elevation feedback on projections of the future sea level contribution of the Greenland ice sheet – Part 1: Parameterisation

The Cryosphere Discussions ◽

10.5194/tcd-7-635-2013 ◽

2013 ◽

Vol 7 (1) ◽

pp. 635-674 ◽

Cited By ~ 2

Author(s):

T. L. Edwards ◽

X. Fettweis ◽

O. Gagliardini ◽

F. Gillet-Chaulet ◽

H. Goelzer ◽

...

Keyword(s):

Mass Balance ◽

Sea Level ◽

Global Climate ◽

Probability Distributions ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Elevation ◽

Surface Mass Balance ◽

Surface Mass ◽

The North

Abstract. We present a new parameterisation that relates surface mass balance (SMB: the sum of surface accumulation and surface ablation) to changes in surface elevation of the Greenland ice sheet (GrIS) for the MAR regional climate model. The motivation is to dynamically adjust SMB as the GrIS evolves, allowing us to force ice sheet models with SMB simulated by MAR while incorporating the SMB–elevation feedback, without the substantial technical challenges of coupling the two models. This also allows us to assess the effect of elevation feedback uncertainty on the GrIS contribution to sea level, using multiple global climate and ice sheet models, without the need for additional, expensive MAR simulations. We estimate this relationship separately below and above the equilibrium line altitude (ELA, separating negative and positive SMB) and for regions north and south of 77° N, from a set of MAR simulations in which we alter the ice sheet surface elevation. These give four "SMB lapse rates", gradients that relate SMB changes to elevation changes. We assess uncertainties within a Bayesian framework, estimating probability distributions for each gradient from which we present best estimates and credibility intervals (CIs) that bound 95% of the probability. Below the ELA our gradient estimates are mostly positive, because SMB usually increases with elevation: 0.54 (95% CI: −0.22 to 1.34) kg m−3 a−1 for the north, and 1.89 (1.03 to 2.61) kg m−3 a−1 for the south. Above the ELA the gradients are much smaller: 0.09 (−0.03 to 0.22) kg m−3 a−1 in the north, and 0.06 (−0.07 to 0.56) kg m−3 a−1 in the south, because SMB can either increase or decrease in response to increased elevation. Our statistically based approach allows us to make probabilistic assessments for the effect of elevation feedback uncertainty on sea level projections. In a companion paper we use the best estimates and upper and lower CI bounds in five ice sheet models, and the full probability distributions in another, to adjust simulated SMB from MAR forced by two global climate models for the SRES A1B scenario (Edwards et al., 2013).

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Reconstruction of historical surface mass balance, 1984–2017 from GreenTrACS multi-offset ground-penetrating radar

Journal of Glaciology ◽

10.1017/jog.2020.91 ◽

2020 ◽

pp. 1-10

Author(s):

Tate G. Meehan ◽

H. P. Marshall ◽

John H. Bradford ◽

Robert L. Hawley ◽

Thomas B. Overly ◽

...

Keyword(s):

Mass Balance ◽

Ground Penetrating Radar ◽

Greenland Ice Sheet ◽

Snow Accumulation ◽

Surface Mass Balance ◽

Snow Density ◽

Surface Mass ◽

Age Model ◽

Ground Penetrating ◽

Good Agreement

Abstract We present continuous estimates of snow and firn density, layer depth and accumulation from a multi-channel, multi-offset, ground-penetrating radar traverse. Our method uses the electromagnetic velocity, estimated from waveform travel-times measured at common-midpoints between sources and receivers. Previously, common-midpoint radar experiments on ice sheets have been limited to point observations. We completed radar velocity analysis in the upper ~2 m to estimate the surface and average snow density of the Greenland Ice Sheet. We parameterized the Herron and Langway (1980) firn density and age model using the radar-derived snow density, radar-derived surface mass balance (2015–2017) and reanalysis-derived temperature data. We applied structure-oriented filtering to the radar image along constant age horizons and increased the depth at which horizons could be reliably interpreted. We reconstructed the historical instantaneous surface mass balance, which we averaged into annual and multidecadal products along a 78 km traverse for the period 1984–2017. We found good agreement between our physically constrained parameterization and a firn core collected from the dry snow accumulation zone, and gained insights into the spatial correlation of surface snow density.

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