scholarly journals Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet

2021 ◽  
Author(s):  
Devon Dunmire ◽  
Alison F. Banwell ◽  
Jan T. M. Lenaerts ◽  
Rajashree Tri Datta
Keyword(s):  
Mass Loss ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Late Summer ◽  
Shortwave Radiation ◽  
Regional Variability ◽  
Meltwater Runoff ◽  
Lake Formation

Abstract. The Greenland Ice Sheet (GrIS) rapid mass loss is primarily driven by an increase in meltwater runoff, which highlights the importance of understanding the formation, evolution and impact of meltwater features on the ice sheet. Buried lakes are meltwater features that contain liquid water and exist under layers of snow, firn, and/or ice. These lakes are invisible in optical imagery, challenging the analysis of their evolution and implication for larger GrIS dynamics and mass change. Here, we present a method that uses a convolutional neural network, a deep learning method, to automatically detect buried lakes across the GrIS. For the years 2018 and 2019, we compare total areal extent of both buried and surface lakes across six regions, and use a regional climate model to explain the spatial and temporal differences. We find that the total buried lake extent after the 2019 melt season is 56 % larger than after the 2018 melt season across the entire ice sheet. Northern Greenland observes the largest increase in buried lake extent after the 2019 melt season, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that different processes are responsible for buried lake formation in different regions of the ice sheet. For example, in western Greenland, buried lakes often appear on the surface during the previous melt season, indicating that these features form when surface lakes partially freeze and become insulated as snowfall buries them. In contrast, in southeast Greenland, most buried lakes never appear on the surface, signifying that these features may form due to subsurface penetration of shortwave radiation and/or downward percolation of meltwater. This study helps to provide additional perspective on the potential role of meltwater on GrIS dynamics and mass loss.

scholarly journals Contrasting regional variability of buried meltwater extent over 2 years across the Greenland Ice Sheet

2021 ◽  
Vol 15 (6) ◽  
pp. 2983-3005
Author(s):  
Devon Dunmire ◽  
Alison F. Banwell ◽  
Nander Wever ◽  
Jan T. M. Lenaerts ◽  
Rajashree Tri Datta
Keyword(s):  
Mass Loss ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Late Summer ◽  
Shortwave Radiation ◽  
Regional Variability ◽  
Meltwater Runoff ◽  
Lake Formation

Abstract. The Greenland Ice Sheet (GrIS) rapid mass loss is primarily driven by an increase in meltwater runoff, which highlights the importance of understanding the formation, evolution, and impact of meltwater features on the ice sheet. Buried lakes are meltwater features that contain liquid water and exist under layers of snow, firn, and/or ice. These lakes are invisible in optical imagery, challenging the analysis of their evolution and implication for larger GrIS dynamics and mass change. Here, we present a method that uses a convolutional neural network, a deep learning method, to automatically detect buried lakes across the GrIS. For the years 2018 and 2019 (which represent low- and high-melt years, respectively), we compare total areal extent of both buried and surface lakes across six regions, and we use a regional climate model to explain the spatial and temporal differences. We find that the total buried lake extent after the 2019 melt season is 56 % larger than after the 2018 melt season across the entire ice sheet. Northern Greenland has the largest increase in buried lake extent after the 2019 melt season, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that different processes are responsible for buried lake formation in different regions of the ice sheet. For example, in southwest Greenland, buried lakes often appear on the surface during the previous melt season, indicating that these meltwater features form when surface lakes partially freeze and become insulated as snowfall buries them. Conversely, in southeast Greenland, most buried lakes never appear on the surface, indicating that these features may form due to downward percolation of meltwater and/or subsurface penetration of shortwave radiation. We provide support for these processes via the use of a physics-based snow model. This study provides additional perspective on the potential role of meltwater on GrIS dynamics and mass loss.

Improved modelling of the present-day Greenland firn layer

2021 ◽  
Author(s):  
Max Brils ◽  
Peter Kuipers Munneke ◽  
Willem Jan van de Berg ◽  
Achim Heilig ◽  
Baptiste Vandercrux ◽  
...  
Keyword(s):  
Mass Loss ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Model ◽  
Pore Space ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass ◽  
Meltwater Runoff

<p>Recent studies indicate that a declining surface mass balance will dominate the Greenland Ice Sheet’s (GrIS) contribution to 21<sup>st</sup> century sea level rise. It is therefore crucial to understand the liquid water balance of the ice sheet and its response to increasing temperatures and surface melt if we want to accurately predict future sea level rise. The ice sheet firn layer covers ~90% of the GrIS and provides pore space for storage and refreezing of meltwater. Because of this, the firn layer can retain up to ~45% of the surface meltwater and thus act as an efficient buffer to ice sheet mass loss. However, in a warming climate this buffer capacity of the firn layer is expected to decrease, amplifying meltwater runoff and sea-level rise. Dedicated firn models are used to understand how firn layers evolve and affect runoff. Additionally, firn models are used to estimate the changing thickness of the firn layer, which is necessary in altimetry to convert surface height change into ice sheet mass loss.</p><p>Here, we present the latest version of our firn model IMAU-FDM. With respect to the previous version, changes have been made to the handling of the freshly fallen snow, the densification rate of the firn and the conduction of heat. These changes lead to an improved representation of firn density and temperature. The results have been thoroughly validated using an extensive dataset of density and temperature measurements that we have compiled covering 126 different locations on the GrIS. Meltwater behaviour in the model is validated with upward-looking GPR measurements at Dye-2. Lastly, we present an in-depth look at the evolution firn characteristics at some typical locations in Greenland.</p><p>Dedicated, stand-alone firn models offer various benefits to using a regional climate model with an embedded firn model. Firstly, the vertical resolution for buried snow and ice layers can be larger, improving accuracy. Secondly, a stand-alone firn model allows for spinning up the model to a more accurate equilibrium state. And thirdly, a stand-alone model is more cost- and time-effective to use. Firn models are increasingly capable of simulating the firn layer, but areas with large amounts of melt still pose the greatest challenge.</p>

scholarly journals Time-evolving mass loss of the Greenland ice sheet from satellite altimetry

2014 ◽  
Vol 8 (1) ◽  
pp. 1057-1093
Author(s):  
R. T. W. L. Hurkmans ◽  
J. L. Bamber ◽  
C. H. Davis ◽  
I. R. Joughin ◽  
K. S. Khvorostovsky ◽  
...  
Keyword(s):  
Mass Loss ◽  
Satellite Altimetry ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Laser Altimetry ◽  
Radar Altimetry ◽  
Appropriate Treatment ◽  
Satellite Radar

Abstract. Mass changes of the Greenland ice sheet may be estimated by the Input Output Method (IOM), satellite gravimetry, or via surface elevation change rates (dH / dt). Whereas the first two have been shown to agree well in reconstructing mass changes over the last decade, there are few decadal estimates from satellite altimetry and none that provide a time evolving trend that can be readily compared with the other methods. Here, we interpolate radar and laser altimetry data between 1995 and 2009 in both space and time to reconstruct the evolving volume changes. A firn densification model forced by the output of a regional climate model is used to convert volume to mass. We consider and investigate the potential sources of error in our reconstruction of mass trends, including geophysical biases in the altimetry, and the resulting mass change rates are compared to other published estimates. We find that mass changes are dominated by SMB until about 2001, when mass loss rapidly accelerates. The onset of this acceleration is somewhat later, and less gradual, compared to the IOM. Our time averaged mass changes agree well with recently published estimates based on gravimetry, IOM, laser altimetry, and with radar altimetry when merged with airborne data over outlet glaciers. We demonstrate, that with appropriate treatment, satellite radar altimetry can provide reliable estimates of mass trends for the Greenland ice sheet. With the inclusion of data from CryoSat II, this provides the possibility of producing a continuous time series of regional mass trends from 1992 onward.

scholarly journals Time-evolving mass loss of the Greenland Ice Sheet from satellite altimetry

2014 ◽  
Vol 8 (5) ◽  
pp. 1725-1740 ◽  
Author(s):  
R. T. W. L. Hurkmans ◽  
J. L. Bamber ◽  
C. H. Davis ◽  
I. R. Joughin ◽  
K. S. Khvorostovsky ◽  
...  
Keyword(s):  
Mass Loss ◽  
Satellite Altimetry ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Laser Altimetry ◽  
Radar Altimetry ◽  
Surface Mass ◽  
Satellite Radar

Abstract. Mass changes of the Greenland Ice Sheet may be estimated by the input–output method (IOM), satellite gravimetry, or via surface elevation change rates (dH/dt). Whereas the first two have been shown to agree well in reconstructing ice-sheet wide mass changes over the last decade, there are few decadal estimates from satellite altimetry and none that provide a time-evolving trend that can be readily compared with the other methods. Here, we interpolate radar and laser altimetry data between 1995 and 2009 in both space and time to reconstruct the evolving volume changes. A firn densification model forced by the output of a regional climate model is used to convert volume to mass. We consider and investigate the potential sources of error in our reconstruction of mass trends, including geophysical biases in the altimetry, and the resulting mass change rates are compared to other published estimates. We find that mass changes are dominated by surface mass balance (SMB) until about 2001, when mass loss rapidly accelerates. The onset of this acceleration is somewhat later, and less gradual, compared to the IOM. Our time-averaged mass changes agree well with recently published estimates based on gravimetry, IOM, laser altimetry, and with radar altimetry when merged with airborne data over outlet glaciers. We demonstrate that, with appropriate treatment, satellite radar altimetry can provide reliable estimates of mass trends for the Greenland Ice Sheet. With the inclusion of data from CryoSat-2, this provides the possibility of producing a continuous time series of regional mass trends from 1992 onward.

scholarly journals Evaluation of Greenland Ice Sheet Surface Climate in the HIRHAM Regional Climate Model Using Automatic Weather Station Data

2003 ◽  
Vol 16 (9) ◽  
pp. 1302-1319 ◽  
Author(s):  
Jason E. Box ◽  
Annette Rinke
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Sheet Surface ◽  
Surface Climate ◽  
Observational Uncertainty

Abstract The 1998 annual cycle and 1991–98 summer simulations of Greenland ice sheet surface climate are made with the 0.5°-horizontal resolution HIRHAM regional climate model of the Arctic. The model output is compared with meteorological and energy balance observations from 15 Greenland Climate Network automatic weather stations. The model reproduces the monthly average surface climate parameters, to a large extent within model and observational uncertainty. However, certain systematic model biases were identified, caused in particular by inaccurate GTOPO30 elevation data over Greenland, 180 m lower on average, with errors as large as −840 m over 50-km grid cells. The resulting warm biases enhance a negative albedo bias, which in turn leads to positive net shortwave radiation biases. Surface sensible and latent heat fluxes are overestimated, apparently due to model warm bias and 100% greater than observed wind speeds. Interannual variability in temperature and albedo are smaller in the model than in the observations, while the opposite is evident for incoming shortwave radiation and wind speed. Annual maps and total mass fluxes of precipitation and evaporation are compared with results from other studies. Based on the results of a multiparameter comparison, solid recommendations for improved regional models of ice sheet climate are made.

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

2021 ◽  
Author(s):  
Kenneth D. Mankoff ◽  
Xavier Fettweis ◽  
Peter L. Langen ◽  
Martin Stendel ◽  
Kristian K. Kjledsen ◽  
...  
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Regional Climate Models ◽  
Mass Gain ◽  
Surface Mass ◽  
Meltwater Runoff

Abstract. The mass of the Greenland ice sheet is declining as mass gain from snowfall 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. Mass gains come from three regional climate models (RCMs; HIRHAM/HARMONIE, MAR, and RACMO) and a semi-empirical surface mass balance (SMB) model. Mass losses come from the RCMs, a statistical SMB model, ice discharge at marine terminating glaciers, and ice melted at the base of the ice sheet. From these products we provide an annual estimate of GIS mass balance from 1840 through 1985 and a daily estimate at sector and region scale from 1986 through next week. Compared to other mass balance estimates, this product updates daily, has higher temporal resolution, and is the first IO product to include the basal mass balance which is a source of an additional ~8 % mass loss. Our results demonstrate an accelerating GIS-scale mass loss and general agreement among six other products. Results from this study are available at https://dataverse01.geus.dk/privateurl.xhtml?token=d09976c4-4f89-43ef-8f91-173d269806a4 (Mankoff et al., 2021).

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 Sensitivity of Greenland Ice Sheet Projections to Model Formulations

2013 ◽  
Vol 59 (216) ◽  
pp. 733-749 ◽  
Author(s):  
H. Goelzer ◽  
P. Huybrechts ◽  
J.J. Fürst ◽  
F.M. Nick ◽  
M.L. Andersen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Sea Level ◽  
Flow Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Flow ◽  
Outlet Glacier ◽  
Glacier Dynamics

AbstractPhysically based projections of the Greenland ice sheet contribution to future sea-level change are subject to uncertainties of the atmospheric and oceanic climatic forcing and to the formulations within the ice flow model itself. Here a higher-order, three-dimensional thermomechanical ice flow model is used, initialized to the present-day geometry. The forcing comes from a high-resolution regional climate model and from a flowline model applied to four individual marine-terminated glaciers, and results are subsequently extended to the entire ice sheet. The experiments span the next 200 years and consider climate scenario SRES A1B. The surface mass-balance (SMB) scheme is taken either from a regional climate model or from a positive-degree-day (PDD) model using temperature and precipitation anomalies from the underlying climate models. Our model results show that outlet glacier dynamics only account for 6–18% of the sea-level contribution after 200 years, confirming earlier findings that stress the dominant effect of SMB changes. Furthermore, interaction between SMB and ice discharge limits the importance of outlet glacier dynamics with increasing atmospheric forcing. Forcing from the regional climate model produces a 14–31 % higher sea-level contribution compared to a PDD model run with the same parameters as for IPCC AR4.

scholarly journals Impact of updated radiative transfer scheme in RACMO2.3p3 on the surface mass and energy budget of the Greenland ice sheet

2020 ◽  
Author(s):  
Christiaan T. van Dalum ◽  
Willem Jan van de Berg ◽  
Michiel R. van den Broeke
Keyword(s):  
Radiative Transfer ◽  
Energy Budget ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Melt ◽  
Transfer Scheme ◽  
Surface Mass ◽  
The Impact

Abstract. This study evaluates the impact of a new snow and ice albedo and radiative transfer scheme on the surface mass and energy budget for the Greenland ice sheet in the latest version of the regional climate model RACMO2, version 2.3p3. We also evaluate the modeled (sub)surface temperature and snow melt, as subsurface heating by radiation penetration now occurs. The results are compared to the previous model version and are evaluated against stake measurements and automatic weather station data of the K-transect and PROMICE projects. In addition, subsurface snow temperature profiles are compared at the K-transect, Summit and southeast Greenland. The surface mass balance is in good agreement with observations, and only changes considerably with respect to the previous RACMO2 version around the ice margins and in the percolation zone. Snow melt and refreezing, on the other hand, are changed more substantially in various regions due to the changed albedo representation, subsurface energy absorption and melt water percolation. Internal heating leads to considerably higher snow temperatures in summer, in agreement with observations, and introduces a shallow layer of subsurface melt.

scholarly journals A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015)

2016 ◽  
Vol 10 (5) ◽  
pp. 2361-2377 ◽  
Author(s):  
Brice Noël ◽  
Willem Jan van de Berg ◽  
Horst Machguth ◽  
Stef Lhermitte ◽  
Ian Howat ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
Ice Caps ◽  
Elevation Model

Abstract. This study presents a data set of daily, 1 km resolution Greenland ice sheet (GrIS) surface mass balance (SMB) covering the period 1958–2015. Applying corrections for elevation, bare ice albedo and accumulation bias, the high-resolution product is statistically downscaled from the native daily output of the polar regional climate model RACMO2.3 at 11 km. The data set includes all individual SMB components projected to a down-sampled version of the Greenland Ice Mapping Project (GIMP) digital elevation model and ice mask. The 1 km mask better resolves narrow ablation zones, valley glaciers, fjords and disconnected ice caps. Relative to the 11 km product, the more detailed representation of isolated glaciated areas leads to increased precipitation over the southeastern GrIS. In addition, the downscaled product shows a significant increase in runoff owing to better resolved low-lying marginal glaciated regions. The combined corrections for elevation and bare ice albedo markedly improve model agreement with a newly compiled data set of ablation measurements.

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