Supplementary material to "The surface albedo of the Greenland Ice Sheet between 1982 and 2015, and its relationship to the ice sheet’s surface mass balance and ice discharge"

2019 ◽  
Author(s):  
Aku Riihelä ◽  
Michalea D. King ◽  
Kati Anttila
Keyword(s):  
Mass Balance ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Supplementary Material

Supplementary material to "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 ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sea Level Change ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Sheet Surface ◽  
Level Change ◽  
Supplementary Material

scholarly journals Supplementary material to "GrSMBMIP: Intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice sheet"

2020 ◽  
Author(s):  
Xavier Fettweis ◽  
Stefan Hofer ◽  
Uta Krebs-Kanzow ◽  
Charles Amory ◽  
Teruo Aoki ◽  
...  
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Supplementary Material

scholarly journals The surface albedo of the Greenland Ice Sheet between 1982 and 2015 from the CLARA-A2 dataset and its relationship to the ice sheet's surface mass balance

2019 ◽  
Vol 13 (10) ◽  
pp. 2597-2614 ◽  
Author(s):  
Aku Riihelä ◽  
Michalea D. King ◽  
Kati Anttila
Keyword(s):  
Time Series ◽  
Mass Balance ◽  
Surface Runoff ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Early Summer ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Surface Melt

Abstract. The Greenland Ice Sheet is losing mass at a significant rate, driven in part by increasing surface-melt-induced runoff. Because the ice sheet's surface melt is closely connected to changes in the surface albedo, studying multidecadal changes in the ice sheet's albedo offers insight into surface melt and associated changes in its surface mass balance. Here, we first analyse the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data second edition (CLARA-A2) Surface Albedo (SAL), covering 1982–2015, to obtain decadal albedo trends for each summer month. We also examine the rates of albedo change during the early summer, supported with atmospheric reanalysis data from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2), to discern changes in the intensity of early summer melt, and their likely drivers. We find that rates of albedo decrease during summer melt have accelerated during the 2000s relative to the early 1980s and that the surface albedos now often decrease to values typical of bare ice at elevations 50–100 m higher on the ice sheet. The southern margins exhibit the opposite behaviour, though, and we suggest this is due to increasing snowfall over the area. We then subtract ice discharge from the mass balance estimates observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission to estimate surface mass balance. The CLARA-A2 albedo changes are regressed with these data to obtain a summer-aggregated proxy surface mass balance time series for the summer periods 1982–2015. This proxy time series is compared with latest regional climate model estimates from the MAR model to perform an observation-based test on the dominance of surface runoff in the magnitude and variability of the summer surface mass balance. We show that the proxy time series agrees with MAR through the analysed period within the associated uncertainties of the data and methods, demonstrating and confirming that surface runoff has dominated the rapid surface mass loss period between the 1990s and 2010s. Finally, we extend the analysis to the drainage basin scale to examine discharge–albedo relationships. We find little evidence of surface-melt-induced ice flow acceleration at annual timescales.

scholarly journals The surface albedo of the Greenland Ice Sheet between 1982 and 2015, and its relationship to the ice sheet’s surface mass balance and ice discharge

2019 ◽  
Author(s):  
Aku Riihelä ◽  
Michalea D. King ◽  
Kati Anttila
Keyword(s):  
Mass Balance ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Early Summer ◽  
Surface Mass Balance ◽  
Time Lags ◽  
Surface Mass ◽  
Seasonal Maximum ◽  
Surface Melt

Abstract. The Greenland Ice Sheet is losing mass at a significant rate, primarily driven by increasing surface melt-induced runoff. Because the ice sheet’s surface melt is closely connected to changes in the surface albedo, studying multidecadal changes in the ice sheet’s albedo offers insight into surface melt and associated changes in its surface mass balance. Here, we first analyse the CLARA-A2 SAL satellite-based surface albedo dataset, covering 1982–2015, to obtain decadal albedo trends for each summer month. We also examine the rates of albedo change during the early summer, supported with atmospheric reanalysis data from MERRA-2, to discern changes in the intensity of early summer melt, and their likely drivers. We find that rates of albedo decrease during summer melt have accelerated during the 2000s relative to early 1980s, and that the surface albedos now often decrease to values typical of bare ice at elevations 50–100 m higher on the ice sheet. The southern margins exhibit the opposite behaviour, though, and we suggest this is due to increasing snowfall over the area. We then correct the mass balance estimates observed by the GRACE satellite mission with state-of-the-art ice discharge estimates to obtain observation-based estimates for the surface mass balance. The CLARA albedo changes are regressed with this data to obtain a proxy surface mass balance timeseries for the summer periods 1982–2015. This proxy timeseries is compared with latest regional climate model estimates from the MAR model. We show that the proxy timeseries agrees with MAR through the analyzed period within the associated uncertainties of the data and methods, demonstrating and confirming that surface runoff has dominated the rapid mass loss period between 1990s and 2010s. Finally, we extend the analysis to GrIS basin scale to examine discharge-albedo relationships in order to ascertain if the surface melt contributes to discharge acceleration via basal lubrication. While there is little evidence of surface melt-induced ice flow acceleration at annual timescales, we find time lags between seasonal maximum runoff production and seasonal maximum discharge rate to be in agreement with recent modelling results.

Contemporary (1960–2012) Evolution of the Climate and Surface Mass Balance of the Greenland Ice Sheet

2013 ◽  
Vol 35 (5) ◽  
pp. 1155-1174 ◽  
Author(s):  
J. H. van Angelen ◽  
M. R. van den Broeke ◽  
B. Wouters ◽  
J. T. M. Lenaerts
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass

scholarly journals Simulation of the future sea level contribution of Greenland with a new glacial system model

2018 ◽  
Vol 12 (10) ◽  
pp. 3097-3121 ◽  
Author(s):  
Reinhard Calov ◽  
Sebastian Beyer ◽  
Ralf Greve ◽  
Johanna Beckmann ◽  
Matteo Willeit ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
System Model ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. We introduce the coupled model of the Greenland glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dynamics, the model of basal hydrology HYDRO and a parameterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, imposing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961–1990 standard climatology derived from simulations of the regional atmosphere model MAR with ERA reanalysis boundary conditions. For the palaeo-part of the spin-up, we add the temperature anomaly derived from the GRIP ice core to the years 1961–1990 average surface temperature field. For our projections, we apply surface temperature and surface mass balance anomalies derived from RCP 4.5 and RCP 8.5 scenarios created by MAR with boundary conditions from simulations with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Further on, the impact of elevation–surface mass balance feedback, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation–surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we investigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temperature and subglacial discharge are about equally important for the melting of the examined outlet glaciers.

scholarly journals Estimation of the Sea Level Rise by 2100 Resulting from Changes in the Surface Mass Balance of the Greenland Ice Sheet

10.5772/23913 ◽  
2011 ◽  
Author(s):  
Xavier Fettweis ◽  
Alexandre Belleflamme ◽  
Michel Erpicum ◽  
Bruno Franco ◽  
Samuel Nicolay
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass

scholarly journals Seasonal mass variations show timing and magnitude of meltwater storage in the Greenland Ice Sheet

2018 ◽  
Vol 12 (9) ◽  
pp. 2981-2999 ◽  
Author(s):  
Jiangjun Ran ◽  
Miren Vizcaino ◽  
Pavel Ditmar ◽  
Michiel R. van den Broeke ◽  
Twila Moon ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Spatial Scales ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
High Accumulation ◽  
Outlet Glacier ◽  
Surface Mass ◽  
Meltwater Runoff

Abstract. The Greenland Ice Sheet (GrIS) is currently losing ice mass. In order to accurately predict future sea level rise, the mechanisms driving the observed mass loss must be better understood. Here, we combine data from the satellite gravimetry mission Gravity Recovery and Climate Experiment (GRACE), surface mass balance (SMB) output of the Regional Atmospheric Climate Model v. 2 (RACMO2), and ice discharge estimates to analyze the mass budget of Greenland at various temporal and spatial scales. We find that the mean rate of mass variations in Greenland observed by GRACE was between −277 and −269 Gt yr−1 in 2003–2012. This estimate is consistent with the sum (i.e., -304±126 Gt yr−1) of individual contributions – surface mass balance (SMB, 216±122 Gt yr−1) and ice discharge (520±31 Gt yr−1) – and with previous studies. We further identify a seasonal mass anomaly throughout the GRACE record that peaks in July at 80–120 Gt and which we interpret to be due to a combination of englacial and subglacial water storage generated by summer surface melting. The robustness of this estimate is demonstrated by using both different GRACE-based solutions and different meltwater runoff estimates (namely, RACMO2.3, SNOWPACK, and MAR3.9). Meltwater storage in the ice sheet occurs primarily due to storage in the high-accumulation regions of the southeast and northwest parts of Greenland. Analysis of seasonal variations in outlet glacier discharge shows that the contribution of ice discharge to the observed signal is minor (at the level of only a few gigatonnes) and does not explain the seasonal differences between the total mass and SMB signals. With the improved quantification of meltwater storage at the seasonal scale, we highlight its importance for understanding glacio-hydrological processes and their contributions to the ice sheet mass variability.

scholarly journals Estimation of the Greenland ice sheet surface mass balance for the 20th and 21st centuries

2008 ◽  
Vol 2 (2) ◽  
pp. 117-129 ◽  
Author(s):  
X. Fettweis ◽  
E. Hanna ◽  
H. Gallée ◽  
P. Huybrechts ◽  
M. Erpicum
Keyword(s):  
Mass Balance ◽  
Multiple Regression ◽  
21St Century ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
General Circulation Models ◽  
Climate Simulation ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. Results from a regional climate simulation (1970–2006) over the Greenland ice sheet (GrIS) reveals that more than 97% of the interannual variability of the modelled Surface Mass Balance (SMB) can be explained by the GrIS summer temperature anomaly and the GrIS annual precipitation anomaly. This multiple regression is then used to empirically estimate the GrIS SMB since 1900 from climatological time series. The projected SMB changes in the 21st century are investigated with the set of simulations performed with atmosphere-ocean general circulation models (AOGCMs) of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). These estimates show that the high surface mass loss rates of recent years are not unprecedented in the GrIS history of the last hundred years. The minimum SMB rate seems to have occurred earlier in the 1930s and corresponds to a zero SMB rate. The AOGCMs project that the SMB rate of the 1930s would be common at the end of 2100. The temperature would be higher than in the 1930s but the increase of accumulation in the 21st century would partly offset the acceleration of surface melt due to the temperature increase. However, these assumptions are based on an empirical multiple regression only validated for recent/current climatic conditions, and the accuracy and time homogeneity of the data sets and AOGCM results used in these estimations constitute a large uncertainty.

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