scholarly journals Regional Greenland Accumulation Variability from Operation IceBridge Airborne Accumulation Radar

2016 ◽  
Author(s):  
Gabriel Lewis ◽  
Erich Osterberg ◽  
Robert Hawley ◽  
Brian Whitmore ◽  
Hans Peter Marshall
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Function Analysis ◽  
Greenland Ice Sheet ◽  
Northern Region ◽  
Snow Accumulation ◽  
Accumulation Rates

Abstract. The mass balance of the Greenland Ice Sheet (GIS) in a warming climate is of critical interest to scientists and the general public in the context of future sea-level rise. An improved understanding of temporal and spatial variability of snow accumulation will reduce uncertainties in GIS mass balance models and improve projections of Greenland's contribution to sea-level rise, currently estimated at 0.089 ± 0.03 m by 2100. Here we analyze 25 NASA Operation IceBridge Accumulation Radar flights totaling > 17 700 km from 2013–2014 to determine snow accumulation in the GIS dry snow and percolation zones over the past 100–300 years. IceBridge accumulation rates are calculated and used to validate accumulation rates from three regional climate models. Averaged over all 25 flights, the RMS difference between the models and IceBridge accumulation is between 0.037 ± 0.022 and 0.064 ± 0.033 m w.e. a−1, although each model shows significantly larger differences from IceBridge accumulation on a regional basis. In the central northern region, for example, the Regional Atmospheric Climate MOdel (RACMO2) underestimates by 26.9 ± 4.5 %, while in the southeast region the Modèle Atmosphérique Régional (MAR) overestimates by as much as 35.5 ± 6.8 %. Our results indicate that these regional differences between model and IceBridge accumulation are large enough to significantly alter GIS surface mass balance estimates. Empirical orthogonality function analysis suggests that the first two principal components account for 33 % and 18 % of the variance and correlate with the Atlantic Multidecadal Oscillation (AMO) and wintertime North Atlantic Oscillation (NAO), respectively. From 1976–2014 accumulation increased over most of the ice sheet's interior, consistent with the response to a positive AMO trend over this period. Regions that disagree strongest with climate models are those in which we have the fewest IceBridge data points, requiring additional in situ measurements to verify model uncertainties.

scholarly journals Regional Greenland accumulation variability from Operation IceBridge airborne accumulation radar

2017 ◽  
Vol 11 (2) ◽  
pp. 773-788 ◽  
Author(s):  
Gabriel Lewis ◽  
Erich Osterberg ◽  
Robert Hawley ◽  
Brian Whitmore ◽  
Hans Peter Marshall ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Drainage Basin ◽  
Function Analysis ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Accumulation Rates ◽  
Surface Mass

Abstract. The mass balance of the Greenland Ice Sheet (GrIS) in a warming climate is of critical interest to scientists and the general public in the context of future sea-level rise. An improved understanding of temporal and spatial variability of snow accumulation will reduce uncertainties in GrIS mass balance models and improve projections of Greenland's contribution to sea-level rise, currently estimated at 0.089 ± 0.03 m by 2100. Here we analyze 25 NASA Operation IceBridge accumulation radar flights totaling  >  17 700 km from 2013 to 2014 to determine snow accumulation in the GrIS dry snow and percolation zones over the past 100–300 years. IceBridge accumulation rates are calculated and used to validate accumulation rates from three regional climate models. Averaged over all 25 flights, the RMS difference between the models and IceBridge accumulation is between 0.023 ± 0.019 and 0.043 ± 0.029 m w.e. a−1, although each model shows significantly larger differences from IceBridge accumulation on a regional basis. In the southeast region, for example, the Modèle Atmosphérique Régional (MARv3.5.2) overestimates by an average of 20.89 ± 6.75 % across the drainage basin. Our results indicate that these regional differences between model and IceBridge accumulation are large enough to significantly alter GrIS surface mass balance estimates. Empirical orthogonal function analysis suggests that the first two principal components account for 33 and 19 % of the variance, and correlate with the Atlantic Multidecadal Oscillation (AMO) and wintertime North Atlantic Oscillation (NAO), respectively. Regions that disagree strongest with climate models are those in which we have the fewest IceBridge data points, requiring additional in situ measurements to verify model uncertainties.

A regional atmospheric warming threshold for irreversible Greenland ice sheet mass loss

2020 ◽  
Author(s):  
Michiel van den Broeke ◽  
Brice Noël ◽  
Leo van Kampenhout ◽  
Willem-Jan van de Berg
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Global Climate Models ◽  
The Future

<p>The mass balance of the Greenland ice sheet (GrIS, units Gt per year) equals the surface mass balance (SMB) minus solid ice discharge across the grounding line. As the latter is definite positive, an important threshold for irreversible GrIS mass loss occurs when long-term average SMB becomes negative. For this to happen, runoff (mainly meltwater, some rain) must exceed mass accumulation (mainly snowfall minus sublimation). Even for a single year, this threshold has not been passed since at least 1958, the first year with reliable estimates of SMB components, although recent years with warm summers (e.g. 2012 and 2019) came close. Simply extrapolating the recent (1991-present) negative SMB trend into the future suggests that the SMB = 0 threshold could be reached before ~2040, but such predictions are extremely uncertain given the very large interannual SMB variability, the relative brevity of the time series and the uncertainty in future warming. In this study we use a cascade of models, extensively evaluated with in-situ and remotely sensed (GRACE) SMB observations, to better constrain the future regional warming threshold for the 5-year average GrIS SMB to become negative. To this end, a 1950-2100 climate change run with the global model CESM2 (app. 100 km resolution) was dynamically downscaled using the regional climate model RACMO2 (app. 11 km), which in turn was statistically downscaled to 1 km resolution. The result is a threshold regional Greenland warming of close to 4 degrees. We then use a range of CMIP5 and CMIP6 global climate models to translate the regional value into a global warming threshold for various warming scenarios, including its timing this century. We find substantial differences, ranging from stabilization before the threshold is reached in the RCP/SSP2.6 scenarios with a limited but still significant sea-level rise contribution (< 5 cm by 2100) to an imminent crossing of the warming threshold for the RCP/SSP8.5 scenarios with substantial and ever-growing contributions to sea level rise (> 10 cm by 2100). These results stress the need for strong mitigation to avoid irreversible GrIS mass loss. We finish by discussing the caveats and uncertainties of our approach.</p>

scholarly journals Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

2013 ◽  
Vol 7 (2) ◽  
pp. 469-489 ◽  
Author(s):  
X. Fettweis ◽  
B. Franco ◽  
M. Tedesco ◽  
J. H. van Angelen ◽  
J. T. M. Lenaerts ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Near Surface ◽  
Surface Mass

Abstract. To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Modèle Atmosphérique Régional), forced by output of three CMIP5 (Coupled Model Intercomparison Project Phase 5) general circulation models (GCMs). Our results indicate that in a warmer climate, mass gain from increased winter snowfall over the GrIS does not compensate mass loss through increased meltwater run-off in summer. Despite the large spread in the projected near-surface warming, all the MAR projections show similar non-linear increase of GrIS surface melt volume because no change is projected in the general atmospheric circulation over Greenland. By coarsely estimating the GrIS SMB changes from GCM output, we show that the uncertainty from the GCM-based forcing represents about half of the projected SMB changes. In 2100, the CMIP5 ensemble mean projects a GrIS SMB decrease equivalent to a mean SLR of +4 ± 2 cm and +9 ± 4 cm for the RCP (Representative Concentration Pathways) 4.5 and RCP 8.5 scenarios respectively. These estimates do not consider the positive melt–elevation feedback, although sensitivity experiments using perturbed ice sheet topographies consistent with the projected SMB changes demonstrate that this is a significant feedback, and highlight the importance of coupling regional climate models to an ice sheet model. Such a coupling will allow the assessment of future response of both surface processes and ice-dynamic changes to rising temperatures, as well as their mutual feedbacks.

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 An Integrated View of Greenland Ice Sheet Mass Changes Based on Models and Satellite Observations

2019 ◽  
Vol 11 (12) ◽  
pp. 1407 ◽  
Author(s):  
Ruth Mottram ◽  
Sebastian B. Simonsen ◽  
Synne Høyer Svendsen ◽  
Valentina R. Barletta ◽  
Louise Sandberg Sørensen ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass ◽  
Ice Shelves ◽  
Ice Velocity

The Greenland ice sheet is a major contributor to sea level rise, adding on average 0.47 ± 0.23 mm year − 1 to global mean sea level between 1991 and 2015. The cryosphere as a whole has contributed around 45% of observed global sea level rise since 1993. Understanding the present-day state of the Greenland ice sheet is therefore vital for understanding the processes controlling the modern-day rates of sea level change and for making projections of sea level rise into the future. Here, we provide an overview of the current state of the mass budget of Greenland based on a diverse range of remote sensing observations to produce the essential climate variables (ECVs) of ice velocity, surface elevation change, grounding line location, calving front location, and gravimetric mass balance as well as numerical modelling that together build a consistent picture of a shrinking ice sheet. We also combine these observations with output from a regional climate model and from an ice sheet model to gain insight into existing biases in ice sheet dynamics and surface mass balance processes. Observations show surface lowering across virtually all regions of the ice sheet and at some locations up to −2.65 m year − 1 between 1995 and 2017 based on radar altimetry analysis. In addition, calving fronts at 28 study sites, representing a sample of typical glaciers, have retreated all around Greenland since the 1990s and in only two out of 28 study locations have they remained stable. During the same period, two of five floating ice shelves have collapsed while the locations of grounding lines at the remaining three floating ice shelves have remained stable over the observation period. In a detailed case study with a fracture model at Petermann glacier, we demonstrate the potential sensitivity of these floating ice shelves to future warming. GRACE gravimetrically-derived mass balance (GMB) data shows that overall Greenland has lost 255 ± 15 Gt year − 1 of ice over the period 2003 to 2016, consistent with that shown by IMBIE and a marked increase compared to a rate of loss of 83 ± 63 Gt year − 1 in the 1993–2003 period. Regional climate model and ice sheet model simulations show that surface mass processes dominate the Greenland ice sheet mass budget over most of the interior. However, in areas of high ice velocity there is a significant contribution to mass loss by ice dynamical processes. Marked differences between models and observations indicate that not all processes are captured accurately within models, indicating areas for future research.

scholarly journals Greenland ice sheet mass balance from 1840 through next week

2021 ◽  
Vol 13 (10) ◽  
pp. 5001-5025
Author(s):  
Kenneth D. Mankoff ◽  
Xavier Fettweis ◽  
Peter L. Langen ◽  
Martin Stendel ◽  
Kristian K. Kjeldsen ◽  
...  
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Balance Model ◽  
Coefficient Of Determination ◽  
Ice Sheet Mass Balance

Abstract. The mass of the Greenland ice sheet is declining as mass gain from snow accumulation is exceeded by mass loss from surface meltwater runoff, marine-terminating glacier calving and submarine melting, and basal melting. Here we use the input–output (IO) method to estimate mass change from 1840 through next week. Surface mass balance (SMB) gains and losses come from a semi-empirical SMB model from 1840 through 1985 and three regional climate models (RCMs; HIRHAM/HARMONIE, Modèle Atmosphérique Régional – MAR, and RACMO – Regional Atmospheric Climate MOdel) from 1986 through next week. Additional non-SMB losses come from a marine-terminating glacier ice discharge product and a basal mass balance model. From these products we provide an annual estimate of Greenland ice sheet mass balance from 1840 through 1985 and a daily estimate at sector and region scale from 1986 through next week. This product updates daily and is the first IO product to include the basal mass balance which is a source of an additional ∼24 Gt yr−1 of mass loss. Our results demonstrate an accelerating ice-sheet-scale mass loss and general agreement (coefficient of determination, r2, ranges from 0.62 to 0.94) among six other products, including gravitational, volume, and other IO mass balance estimates. Results from this study are available at https://doi.org/10.22008/FK2/OHI23Z (Mankoff et al., 2021).

scholarly journals Greenland Ice Sheet runoff reduced by meltwater refreezing in bare ice

2021 ◽  
Author(s):  
Matthew Cooper ◽  
Laurence Smith ◽  
Åsa Rennermalm ◽  
Kang Yang ◽  
Glen Liston ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Glacial Ice ◽  
Meltwater Runoff ◽  
Global Sea Level

Abstract The Greenland Ice Sheet’s contribution to global sea-level rise is accelerating1 due to increased melting of its bare-ice ablation zone2–6, but there is growing evidence that climate models overestimate runoff from this critical area of the ice sheet7–12. Current climate models assume all bare ice runoff escapes to the ocean, unlike snow covered areas where some fraction of runoff is retained and/or refrozen in porous firn13–15. Here we use in situ measurements and numerical modeling to reveal extensive retention and refreezing of liquid meltwater in bare glacial ice, explaining chronic runoff overestimation by climate models. From 2009–2018, refreezing of liquid meltwater in bare, porous glacial ice reduced meltwater runoff by 11–23 Gt a-1 in southwest Greenland alone, equivalent to 10–20% of annual meltwater production. This mass retention is commensurate with current estimates of climate model ice sheet meltwater runoff uncertainty, and may represent an overlooked buffer on projected runoff increases for the coming century16. Inclusion of bare-ice retention and refreezing processes in climate models therefore has immediate potential to improve forecasts of ice sheet runoff and its contribution to global sea-level rise.

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 Using results from the PlioMIP ensemble to investigate the Greenland Ice Sheet during the mid-Pliocene Warm Period

2015 ◽  
Vol 11 (3) ◽  
pp. 403-424 ◽  
Author(s):  
A. M. Dolan ◽  
S. J. Hunter ◽  
D. J. Hill ◽  
A. M. Haywood ◽  
S. J. Koenig ◽  
...  
Keyword(s):  
Sea Level ◽  
Atmospheric Carbon Dioxide ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Warm Period ◽  
Global Mean Temperature ◽  
Model Dependency

Abstract. During an interval of the Late Pliocene, referred to here as the mid-Pliocene Warm Period (mPWP; 3.264 to 3.025 million years ago), global mean temperature was similar to that predicted for the end of this century, and atmospheric carbon dioxide concentrations were higher than pre-industrial levels. Sea level was also higher than today, implying a significant reduction in the extent of the ice sheets. Thus, the mPWP provides a natural laboratory in which to investigate the long-term response of the Earth's ice sheets and sea level in a warmer-than-present-day world. At present, our understanding of the Greenland ice sheet during the mPWP is generally based upon predictions using single climate and ice sheet models. Therefore, it is essential that the model dependency of these results is assessed. The Pliocene Model Intercomparison Project (PlioMIP) has brought together nine international modelling groups to simulate the warm climate of the Pliocene. Here we use the climatological fields derived from the results of the 15 PlioMIP climate models to force an offline ice sheet model. We show that mPWP ice sheet reconstructions are highly dependent upon the forcing climatology used, with Greenland reconstructions ranging from an ice-free state to a near-modern ice sheet. An analysis of the surface albedo variability between the climate models over Greenland offers insights into the drivers of inter-model differences. As we demonstrate that the climate model dependency of our results is high, we highlight the necessity of data-based constraints of ice extent in developing our understanding of the mPWP Greenland ice sheet.

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