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.

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 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.

Trends and projections in ice sheet mass balance

2020 ◽  
Author(s):  
Andrew Shepherd ◽  
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Sea Levels ◽  
Global Sea Level

<p>In recent decades, the Antarctic and Greenland Ice Sheets have been major contributors to global sea-level rise and are expected to be so in the future. Although increases in glacier flow and surface melting have been driven by oceanic and atmospheric warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite records of changes in polar ice sheet volume, flow and gravitational potential to produce a reconciled estimate of their mass balance. <strong>Since the early 1990’s, ice losses from Antarctica and Greenland have caused global sea-levels to rise by 18.4 millimetres, on average, and there has been a sixfold increase in the volume of ice loss over time. Of this total, 41 % (7.6 millimetres) originates from Antarctica and 59 % (10.8 millimetres) is from Greenland. In this presentation, we compare our reconciled estimates of Antarctic and Greenland ice sheet mass change to IPCC projection of sea level rise to assess the model skill in predicting changes in ice dynamics and surface mass balance.  </strong>Cumulative ice losses from both ice sheets have been close to the IPCC’s predicted rates for their high-end climate warming scenario, which forecast an additional 170 millimetres of global sea-level rise by 2100 when compared to their central estimate.</p>

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

2018 ◽  
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. 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 to global sea level rise between 1.9 and 13.0 cm 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 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 Annual Greenland accumulation rates (2009–2012) from airborne snow radar

2016 ◽  
Vol 10 (4) ◽  
pp. 1739-1752 ◽  
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.

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 The effect of overshooting 1.5 °C global warming on the mass loss of the Greenland ice sheet

2018 ◽  
Vol 9 (4) ◽  
pp. 1169-1189 ◽  
Author(s):  
Martin Rückamp ◽  
Ulrike Falk ◽  
Katja Frieler ◽  
Stefan Lange ◽  
Angelika Humbert
Keyword(s):  
Global Warming ◽  
Mass Loss ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
21St Century ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. Sea-level rise associated with changing climate is expected to pose a major challenge for societies. Based on the efforts of COP21 to limit global warming to 2.0 ∘C or even 1.5 ∘C by the end of the 21st century (Paris Agreement), we simulate the future contribution of the Greenland ice sheet (GrIS) to sea-level change under the low emission Representative Concentration Pathway (RCP) 2.6 scenario. The Ice Sheet System Model (ISSM) with higher-order approximation is used and initialized with a hybrid approach of spin-up and data assimilation. For three general circulation models (GCMs: HadGEM2-ES, IPSL-CM5A-LR, MIROC5) the projections are conducted up to 2300 with forcing fields for surface mass balance (SMB) and ice surface temperature (Ts) computed by the surface energy balance model of intermediate complexity (SEMIC). The projected sea-level rise ranges between 21–38 mm by 2100 and 36–85 mm by 2300. According to the three GCMs used, global warming will exceed 1.5 ∘C early in the 21st century. The RCP2.6 peak and decline scenario is therefore manually adjusted in another set of experiments to suppress the 1.5 ∘C overshooting effect. These scenarios show a sea-level contribution that is on average about 38 % and 31 % less by 2100 and 2300, respectively. For some experiments, the rate of mass loss in the 23rd century does not exclude a stable ice sheet in the future. This is due to a spatially integrated SMB that remains positive and reaches values similar to the present day in the latter half of the simulation period. Although the mean SMB is reduced in the warmer climate, a future steady-state ice sheet with lower surface elevation and hence volume might be possible. Our results indicate that uncertainties in the projections stem from the underlying GCM climate data used to calculate the surface mass balance. However, the RCP2.6 scenario will lead to significant changes in the GrIS, including elevation changes of up to 100 m. The sea-level contribution estimated in this study may serve as a lower bound for the RCP2.6 scenario, as the currently observed sea-level rise is not reached in any of the experiments; this is attributed to processes (e.g. ocean forcing) not yet represented by the model, but proven to play a major role in GrIS mass loss.

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.

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