Review of Spatial and temporal variability of snow accumulation for the South-Western Greenland Ice Sheet

ABSTRACTThe increasingly negative mass balance of the Greenland ice sheet (GrIS) over the last ~25 years has been associated with enhanced surface melt and increased ice loss from marine-terminating outlet glaciers. Accelerated retreat during 2000–2010 was concentrated in the southeast and northwest sectors of the ice sheet; however, there was considerable spatial and temporal variability in the timing and magnitude of retreat both within and between these regions. This behaviour has yet to be quantified and compared for all glaciers in both regions. Furthermore, it is unclear whether retreat has continued after 2010 in the northwest, and whether the documented slowdown in the southeast post-2005 has been sustained. Here, we compare spatial and temporal patterns of frontal change in the northwest and southeast GrIS, for the period 2000–2015. Our results show near-ubiquitous retreat of outlet glaciers across both regions for the study period; however, the timing and magnitude of inter-annual frontal position change is largely asynchronous. We also find that since 2010, there is continued terminus retreat in the northwest, which contrasts with considerable inter-annual variability in the southeast. Analysis of the role of glacier-specific factors demonstrates that fjord and bed geometry are important controls on the timing and magnitude of glacier retreat.

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Measured and Modeled Snow Cover Properties across the Greenland Ice Sheet

10.5194/tc-2017-55 ◽

2017 ◽

Cited By ~ 2

Author(s):

Sascha Bellaire ◽

Martin Proksch ◽

Martin Schneebeli ◽

Masashi Niwano ◽

Konrad Steffen

Keyword(s):

Snow Cover ◽

Ice Sheet ◽

Geographical Location ◽

Indirect Evidence ◽

Greenland Ice Sheet ◽

Reanalysis Data ◽

Snow Accumulation ◽

Water Infiltration ◽

Spatial And Temporal Variability ◽

Spatially Distributed

Abstract. The Greenland ice sheet (GrIS) is known to be contributing to sea level rise in a warming climate. The snow cover on the ice sheet is the direct link between a potentially warmer atmosphere and the ice itself. However, little is known about the microstructure and especially about the spatial and temporal variability of the snow cover, except from indirect evidence from remote sensing. The detailed snowpack stratigraphy is relevant for processes such as the albedo feedback, water infiltration and firn densification. During a field campaign in 2015, spatially distributed snow observations of the GrIS were gathered at stations belonging to the Greenland Climate Network (GC-Net). High-resolution snow profiles of density, specific surface area and hardness were measured. Hardness was measured with the SnowMicroPen, which was also used to assess the spatial variability of the snow density with depth. The snow cover model SNOWPACK was forced with reanalysis data from the model NHM-SMAP. The measured mean density of the upper snow cover was in good agreement with the simulations using constant densities for snow accumulation, i.e. new snow, depending on the geographical location on the GrIS. However, the observed stratigraphy in terms of density and SSA could not be reproduced. We found that for a one-dimensional snowpack model it is difficult to parameterize for snowpacks undergoing multiple erosion and redeposition events, as is typical for the GrIS and other perennial polar snowpacks. This limitation may be a drawback to understanding past and future changes of the snow, and the associated processes.

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Spatial and temporal variability of snow accumulation for the South-Western Greenland Ice Sheet

10.5194/tc-2019-184 ◽

2019 ◽

Author(s):

Achim Heilig ◽

Olaf Eisen ◽

Martin Schneebeli ◽

Michael MacFerrin ◽

C. Max Stevens ◽

...

Keyword(s):

Remote Sensing ◽

Snow Depth ◽

Regional Scale ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Temporal Changes ◽

Snow Accumulation ◽

Small Scale ◽

Spatial And Temporal Variability ◽

Accumulation Pattern

Abstract. The Greenland ice sheet (GrIS) has experienced significant changes in recent decades. Data confirming those changes are derived from remote sensing, regional climate models (RCMs), firn cores and automatic weather stations (AWSs) on the ice sheet. Data sources comprise different extents in area coverage. While remote sensing and RCMs cover at least regional scales with an extent ranging from 1–10 km, AWS data and firn cores are point observations. To link such regional scales with point measurements, we investigate the spatial variability of snow accumulation within areas of approximately 1–4 km2 and its temporal changes. At three different sites of the southwestern GrIS (Swiss Camp, KAN-U, Dye-2), we performed extensive ground-penetrating radar (GPR) transects and numerous snow pits. In dry snow conditions, radar-measured two-way travel time can be converted to snow depth and snow accumulation if the density is known. Density variations per site for snow pits within distances of up to 1 km are found to be consistently within ±5 %. GPR transects were further filtered to remove small scale surface-related noise. The combined uncertainty of density variations and spatial filtering of radar transects is at 7–8 % per regional scale. To link point observations with regional scales, we analyze for spatial representativeness of snow pits. It occurs that with a probability of p = 0.8 (KAN-U) to p > 0.95 (Swiss Camp and Dye-2), randomly selected snow pits are representative in snow accumulation for entire regions with an offset of ±10 % from arithmetic means. However, to achieve such high representativeness of snow pits, it is required to average snow depth for an area of at least 20 m x 20 m. Interannual accumulation pattern at Dye-2 are very persistent for two subsequent accumulation seasons with similarity probabilities of p > 0.95, if again an error of ±10 % is included. Using target reflectors placed at respective end-of-summer-melt horizons, we additionally analyzed for occurrences of lateral redistribution within one melt season. In this study, we show that at Dye-2 lateral flow of meltwater cannot be evidenced in the current climate. Such studies of spatial representativeness and temporal changes in accumulation are inevitable to assess reliability of the linkage between point measurements and regional scale data and predictions, which are used for validation and calibration of remote sensing data and RCM outputs.

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Spatial and temporal variability of snow accumulation in Dronning Maud Land, East Antarctica, including two deep ice coring sites at Dome Fuji and EPICA DML

The Cryosphere Discussions ◽

10.5194/tcd-5-2061-2011 ◽

2011 ◽

Vol 5 (4) ◽

pp. 2061-2114 ◽

Cited By ~ 2

Author(s):

S. Fujita ◽

P. Holmlund ◽

I. Andersson ◽

I. Brown ◽

H. Enomoto ◽

...

Keyword(s):

Temporal Variability ◽

Large Scale ◽

Accumulation Rate ◽

Ice Sheet ◽

Snow Accumulation ◽

East Antarctica ◽

Spatial And Temporal Variability ◽

Surface Mass ◽

Dronning Maud Land ◽

Spatio Temporal

Abstract. To better understand the spatio-temporal variability of the glaciological environment in Dronning Maud Land (DML), East Antarctica, investigations were carried out along the 2800-km-long Japanese-Swedish IPY 2007/2008 traverse. The route covers ice sheet ridges and two deep ice coring sites at Dome Fuji and EPICA DML. The surface mass balance (SMB) distribution was derived based on analysis of isochrones within snow pits, firn cores and subsurface radar signals. The SMB averaged over various time scales in the Holocene was determined. This was then compared with various glaciological data. We find that the large-scale distribution of the SMB depends on the surface elevation, continentality and interactions between ice sheet ridges and the prevailing counterclockwise windfield in DML. A different SMB is found for the windward and leeward sides of the ridges. Local-scale variability in the SMB is essentially governed by bedrock topography which determines the local surface topography. In the eastern part of DML, the accumulation rate in the second half of the 20th century is found to be higher by 15 % compared to averages over longer periods of 722 a or 7.9 ka before AD 2008. A similar trend has been reported for many inland plateau sites in East Antarctica.

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Changes in Greenland ice sheet elevation attributed primarily to snow accumulation variability

Nature ◽

10.1038/35022555 ◽

2000 ◽

Vol 406 (6798) ◽

pp. 877-879 ◽

Cited By ~ 65

Author(s):

J. R. McConnell ◽

R. J. Arthern ◽

E. Mosley-Thompson ◽

C. H. Davis ◽

R. C. Bales ◽

...

Keyword(s):

Ice Sheet ◽

Greenland Ice Sheet ◽

Snow Accumulation

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Oceanic heat delivery via Kangerdlugssuaq Fjord to the south-east Greenland ice sheet

Journal of Geophysical Research Oceans ◽

10.1002/2013jc009295 ◽

2014 ◽

Vol 119 (2) ◽

pp. 631-645 ◽

Cited By ~ 53

Author(s):

Mark E. Inall ◽

Tavi Murray ◽

Finlo R. Cottier ◽

Kilian Scharrer ◽

Timothy J. Boyd ◽

...

Keyword(s):

Ice Sheet ◽

Greenland Ice Sheet ◽

The South ◽

East Greenland

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Spatial and temporal variability of convective instability in the south of Western Siberia, determined on the basis of the total totals index (ERA5 reanalysis)

10.1117/12.2603446 ◽

2021 ◽

Author(s):

Konstantin N. Pustovalov ◽

Valentina P. Gorbatenko ◽

Olga E. Nechepurenko ◽

Petr M. Nagorskiy ◽

Maria V. Oglezneva

Keyword(s):

Temporal Variability ◽

Convective Instability ◽

Western Siberia ◽

Spatial And Temporal Variability ◽

The South

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Snow Accumulation Studies on the Thule Peninsula, Greenland

Journal of Glaciology ◽

10.3189/s0022143000020402 ◽

1968 ◽

Vol 7 (49) ◽

pp. 59-76 ◽

Cited By ~ 2

Author(s):

Steven J. Mock

Keyword(s):

Regional Scale ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Snow Accumulation ◽

Accumulation Rates ◽

Surface Slope ◽

Ice Flow ◽

Accumulation Pattern ◽

Flow Phenomena ◽

Independent Parameters

AbstractData from stake measurements, marker boards and pits along a 136 km trail crossing the Thule peninsula sector of the Greenland ice sheet have been used to determine both the regional and local distribution of snow accumulation, On a regional scale trend surfaces of mean annual accumulation can be adequately predicted from a model using distance from moisture source and elevation as independent parameters. A series of step- or wave-like features break the smooth profile of the ice. sheet and cause profound changes in accumulation rates on a local scale. The accumulation pattern over these features can be predicted from surface slope and departure from regional elevation. Profiles of’ surface and subsurface topography indicate a direct relationship between subsurface hills and step-like features, but cannot be quantitatively accounted for by existing ice-flow theory. Detailed accumulation studies in conjunction with a program of spirit leveling in the vicinity of Camp Century has revealed the development a shallow valley-like feature. Within this feature accumulation rates have increased indicating that it is the result of flow phenomena.

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Spatial and temporal variability of snowfall over Greenland from CloudSat observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-8101-2019 ◽

2019 ◽

Vol 19 (12) ◽

pp. 8101-8121 ◽

Cited By ~ 9

Author(s):

Ralf Bennartz ◽

Frank Fell ◽

Claire Pettersen ◽

Matthew D. Shupe ◽

Dirk Schuettemeyer

Keyword(s):

Annual Cycle ◽

Greenland Ice Sheet ◽

Snow Accumulation ◽

Spatial And Temporal Variability ◽

Mean Values ◽

Annual Cycles ◽

Ground Clutter ◽

Empirical Correction ◽

Precipitation Events

Abstract. We use the CloudSat 2006–2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z–S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z–S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34±7.5 cm yr−1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z–S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30 cm yr−1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24 cm yr−1, depending on the assumed snowpack density and from CloudSat 23±4.5 cm yr−1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months.

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