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 Eemian Greenland Surface Mass Balance strongly sensitive to SMB model choice

2018 ◽  
Author(s):  
Andreas Plach ◽  
Kerim H. Nisancioglu ◽  
Sébastien Le clec’h ◽  
Andreas Born ◽  
Petra M. Langebroek ◽  
...  
Keyword(s):  
Mass Balance ◽  
Regional Climate ◽  
Greenland Ice Sheet ◽  
Model Complexity ◽  
Surface Mass Balance ◽  
Potential Contribution ◽  
Surface Mass ◽  
Degree Day ◽  
Positive Degree ◽  
Uncertainty Estimates

Abstract. Understanding the behavior of the Greenland ice sheet in a warmer climate, and particularly its surface mass balance (SMB), is important for assessing Greenland’s potential contribution to future sea level rise. The Eemian interglacial, the most recent warmer-than-present period in Earth’s history approximately 125 000 years ago, provides an analogue for a warm summer climate over Greenland. The Eemian is characterized by a positive Northern Hemisphere summer insolation anomaly, which introduces uncertainties in Eemian SMB when using positive degree day estimates. In this study, we use Eemian global and regional climate simulations in combination with three types of SMB models – a simple positive degree day, an intermediate complexity, and a full surface energy balance model – to evaluate the importance of regional climate and model complexity for estimates of Greenland SMB. We find that all SMB models perform well under the relatively cool pre-industrial and late Eemian. For the relatively warm early Eemian, the differences between SMB models are large which is associated with the representation of insolation in the respective models. For all simulated time slices there is a systematic difference between globally and regionally forced SMB models, due to the different representation of the regional climate over Greenland. We conclude that both the resolution of the simulated climate as well as the method used to estimate the SMB, are important for an accurate simulation of Greenland’s SMB. Whether model resolution or SMB method is most important depends on the climate state and in particular the prevailing insolation pattern. We suggest that future Eemian climate model inter-comparison studies are combined with different SMB models to quantify Eemian SMB uncertainty estimates.

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 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>

scholarly journals Vital role of daily temperature variability in surface mass balance parameterizations of the Greenland Ice Sheet

2014 ◽  
Vol 8 (2) ◽  
pp. 575-585 ◽  
Author(s):  
I. Rogozhina ◽  
D. Rau
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Temperature Variability ◽  
Daily Temperature ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
Continental Scale ◽  
Degree Day

Abstract. This study aims to demonstrate that the spatial and seasonal effects of daily temperature variability in positive degree-day (PDD) models play a decisive role in shaping the modeled surface mass balance (SMB) of continental-scale ice masses. Here we derive monthly fields of daily temperature standard deviation (SD) across Greenland from the ERA-40 (European Centre for Medium-Range Weather Forecasts 40 yr Reanalysis) reanalysis spanning from 1958 to 2001 and apply these fields to model recent surface responses of the Greenland Ice Sheet (GIS). Neither the climate data set analyzed nor in situ measurements taken in Greenland support the range of commonly used spatially and temporally uniform SD values (~ 5 °C). In this region, the SD distribution is highly inhomogeneous and characterized by low values during summer months (~ 1 to 2.5 °C) in areas where most surface melting occurs. As a result, existing SMB parameterizations using uniform, high SD values fail to capture both the spatial pattern and amplitude of the observed surface responses of the GIS. Using realistic SD values enables significant improvements in the modeled regional and total SMB with respect to existing estimates from recent satellite observations and the results of a high-resolution regional model. In addition, this resolves large uncertainties associated with other major parameters of a PDD model, namely degree-day factors. The model appears to be nearly insensitive to the choice of degree-day factors after adopting the realistic SD distribution.

Sources of Uncertainty in Greenland Surface Mass Balance in the 21st century.

2021 ◽  
Author(s):  
Katharina Meike Holube ◽  
Tobias Zolles ◽  
Andreas Born
Keyword(s):  
Mass Balance ◽  
Greenhouse Gas ◽  
21St Century ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Sources Of Uncertainty ◽  
Ensemble Of Simulations

<p>The surface mass balance (SMB) of the Greenland Ice Sheet is subject to considerable uncertainties that complicate predictions of sea-level rise caused by climate change.<br>We examine the SMB of the Greenland Ice Sheet and its uncertainty in the 21st century using a wide ensemble of simulations with the surface energy and mass balance model "BEr<em>ge</em>n Snow SImulator" (BESSI). We conduct simulations for four greenhouse gas emission scenarios using the output of 26 climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to force BESSI. In addition, the uncertainty of the SMB simulation is estimated by using 16 different parameter sets in our SMB model. The median SMB across climate models, integrated over the ice sheet, decreases for every emission scenario and every parameter set. As expected, the decrease in SMB is stronger for higher greenhouse gas emissions. The uncertainty range in SMB is considerably greater in our ensemble than in other studies that used fewer climate models as forcing. An analysis of the different sources of uncertainty shows that the differences between climate models are the main reason for SMB uncertainty, exceeding even the uncertainty due to the choice of climate scenario. In comparison, the uncertainty caused by the snow model parameters is negligible. The differences between the climate models are most pronounced in the north of Greenland and in the area around the equilibrium line, whereas the ensemble of simulations agrees that the SMB decrease is greatest in the west of Greenland. </p>

scholarly journals Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections

2020 ◽  
Vol 14 (6) ◽  
pp. 1747-1762 ◽  
Author(s):  
Heiko Goelzer ◽  
Brice P. Y. Noël ◽  
Tamsin L. Edwards ◽  
Xavier Fettweis ◽  
Jonathan M. Gregory ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sea Level Change ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Level Change

Abstract. Future sea-level change projections with process-based stand-alone ice sheet models are typically driven with surface mass balance (SMB) forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the geometry used by the climate model. We present a method for applying SMB forcing from climate models to a wide range of Greenland ice sheet models with varying and temporally evolving geometries. In order to achieve that, we translate a given SMB anomaly field as a function of absolute location to a function of surface elevation for 25 regional drainage basins, which can then be applied to different modelled ice sheet geometries. The key feature of the approach is the non-locality of this remapping process. The method reproduces the original forcing data closely when remapped to the original geometry. When remapped to different modelled geometries it produces a physically meaningful forcing with smooth and continuous SMB anomalies across basin divides. The method considerably reduces non-physical biases that would arise by applying the SMB anomaly derived for the climate model geometry directly to a large range of modelled ice sheet model geometries.

scholarly journals Greenland Surface Mass Balance as Simulated by the Community Earth System Model. Part I: Model Evaluation and 1850–2005 Results

2013 ◽  
Vol 26 (20) ◽  
pp. 7793-7812 ◽  
Author(s):  
Miren Vizcaíno ◽  
William H. Lipscomb ◽  
William J. Sacks ◽  
Jan H. van Angelen ◽  
Bert Wouters ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Earth System Model ◽  
System Model ◽  
Surface Mass Balance ◽  
Earth System ◽  
Surface Mass ◽  
Community Earth System Model

Abstract The modeling of the surface mass balance (SMB) of the Greenland Ice Sheet (GIS) requires high-resolution models in order to capture the observed large gradients in the steep marginal areas. Until now, global climate models have not been considered suitable to model ice sheet SMB owing to model biases and insufficient resolution. This study analyzes the GIS SMB simulated for the period 1850–2005 by the Community Earth System Model (CESM), which includes a new ice sheet component with multiple elevation classes for SMB calculations. The model is evaluated against observational data and output from the regional model Regional Atmospheric Climate Model version 2 (RACMO2). Because of a lack of major climate biases, a sophisticated calculation of snow processes (including surface albedo evolution) and an adequate downscaling technique, CESM is able to realistically simulate GIS surface climate and SMB. CESM SMB agrees reasonably well with in situ data from 475 locations (r = 0.80) and output from RACMO2 (r = 0.79). The simulated mean SMB for 1960–2005 is 359 ± 120 Gt yr−1 in the range of estimates from regional climate models. The simulated seasonal mass variability is comparable with mass observations from the Gravity Recovery and Climate Experiment (GRACE), with synchronous annual maximum (May) and minimum (August–September) and similar amplitudes of the seasonal cycle. CESM is able to simulate the bands of precipitation maxima along the southeast and northwest margins, but absolute precipitation rates are underestimated along the southeastern margin and overestimated in the high interior. The model correctly simulates the major ablation areas. Total refreezing represents 35% of the available liquid water (the sum of rain and melt).

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 Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections

2019 ◽  
Author(s):  
Heiko Goelzer ◽  
Brice P. Y. Noel ◽  
Tamsin L. Edwards ◽  
Xavier Fettweis ◽  
Jonathan M. Gregory ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sea Level Change ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Level Change ◽  
Wide Range

Abstract. Future sea-level change projections with process-based standalone ice sheet models are typically driven with surface mass balance (SMB) forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the one used by the climate model. We present a method to apply SMB forcing from climate models to a wide range of Greenland ice sheet models with varying and temporally evolving geometries. In order to achieve that, we translate a given SMB anomaly field as a function of absolute location, to a function of surface elevation for 25 regional drainage basins, which can then be applied to different modelled ice sheet geometries. The key feature of the approach is the non-locality of this remapping process. The method reproduces the original forcing data closely when remapped to the original geometry. When remapped to different modelled geometries it produces a physically meaningful forcing with smooth and continuous SMB anomalies across basin divides. The method considerably reduces non-physical biases that would arise by applying the SMB anomaly derived for the observed geometry directly to a large range of modelled ice sheet model geometries.

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