Spatial and temporal variability of snow accumulation using ground-penetrating radar and ice cores on a Svalbard glacier

Pälli, Anja; Kohler, Jack; Isaksson, Elisabeth; Moore, John C.; Pinglot, J. F.; Pohjola, Veijo; Samuelsson, Håkan

doi:10.3189/172756502781831205

Cited by 79 publications

(79 citation statements)

References 24 publications

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“…Additionally, temporal variability in γ p will also have a considerable impact on the simulated mass balance. Accumulation rates along a horizontal profile in the accumulation zone of Nordenskiöldbreen, presented by Pälli et al (2002), confirm that the accumulation rate varies significantly in space. Errors in the cloud cover estimates, derived from observations at Svalbard Airport, have a significant impact on the modelled shortwave and longwave budget.…”

Section: Conclusion and Discussionmentioning

confidence: 51%

“…Discrepancies in the simulated temperatures in the upper 12 m of the snow pack could be related to an overestimation of modelled accumulation. Pälli et al (2002) found a relatively small accumulation rate at the top of the ice cap in comparison with the higher parts of the glacier and ascribed this difference to the effect of wind-driven snow transport. Note that the temperature at great depth is much higher than the RACMO derived yearly mean air temperature at this altitude of −12 • C, which is an indication of the significance of refreezing.…”

Section: Initialisationmentioning

confidence: 99%

“…With this gradient, the average maximum precipitation of 540 mm w.e. per year (Pälli et al, 2002) is reached at 971 m a.s.l.…”

Section: Calibrationmentioning

confidence: 99%

“…The altitude of 971 m a.s.l. is chosen such that the parameterised mean maximum precipitation rate is equal to the observed mean maximum precipitation of 540 mm per year found by Pälli et al (2002) on Nordenskiöldbreen for the period 1963-1999. Gridded 3-hourly air temperature, pressure and specific humidity input is constructed from output at a 11 km resolution of the Regional Atmospheric Climate Model (RACMO), as presented by Ettema et al (2010). RACMO is forced at the boundaries with ERA-Interim reanalysis data, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) for the period 1989-2010.…”

Section: Meteorological Inputmentioning

confidence: 99%

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Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model

et al. 2012

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Abstract.A distributed energy balance model is coupled to a multi-layer snow model in order to study the mass balance evolution and the impact of refreezing on the mass budget of Nordenskiöldbreen, Svalbard. The model is forced with output from the regional climate model RACMO and meteorological data from Svalbard Airport. Extensive calibration and initialisation are performed to increase the model accuracy. For the period 1989-2010, we find a mean net mass balance of −0.39 m w.e. a −1 . Refreezing contributes on average 0.27 m w.e. a −1 to the mass budget and is most pronounced in the accumulation zone. The simulated mass balance, radiative fluxes and subsurface profiles are validated against observations and are generally in good agreement. Climate sensitivity experiments reveal a non-linear, seasonally dependent response of the mass balance, refreezing and runoff to changes in temperature and precipitation. It is shown that including seasonality in climate change, with less pronounced summer warming, reduces the sensitivity of the mass balance and equilibrium line altitude (ELA) estimates in a future climate. The amount of refreezing is shown to be rather insensitive to changes in climate.

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Section: Conclusion and Discussionmentioning

confidence: 51%

Section: Initialisationmentioning

confidence: 99%

“…With this gradient, the average maximum precipitation of 540 mm w.e. per year (Pälli et al, 2002) is reached at 971 m a.s.l.…”

Section: Calibrationmentioning

confidence: 99%

Section: Meteorological Inputmentioning

confidence: 99%

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Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model

et al. 2012

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“…However, the physical processes leading to these IRHs still remain poorly known. For instance, as pointed out by Eisen et al (2008), annual layers are still visible with radar wavelengths much larger than the annual thickness (a typical 100 MHz wave in the cold dry snow of the plateau has a wavelength of 2 m: much larger than the 10 cm annual snow thickness at Dome Concordia (DC) for instance), which contradicts the theory unless constructive interferences are considered as suggested by Palli et al (2002) DC S1 S2 S1 S0 S0 S0 DC S1 S2 S1 S0 S0 Fig. 1.…”

Section: Technical Background and Functional Principle Of Gprmentioning

confidence: 80%

Spatial and temporal distributions of surface mass balance between Concordia and Vostok stations, Antarctica, from combined radar and ice core data: first results and detailed error analysis

et al. 2018

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Abstract. Results from ground-penetrating radar (GPR) measurements and shallow ice cores carried out during a scientific traverse between Dome Concordia (DC) and Vostok stations are presented in order to infer both spatial and temporal characteristics of snow accumulation over the East Antarctic Plateau. Spatially continuous accumulation rates along the traverse are computed from the identification of three equally spaced radar reflections spanning about the last 600 years. Accurate dating of these internal reflection horizons (IRHs) is obtained from a depth–age relationship derived from volcanic horizons and bomb testing fallouts on a DC ice core and shows a very good consistency when tested against extra ice cores drilled along the radar profile. Accumulation rates are then inferred by accounting for density profiles down to each IRH. For the latter purpose, a careful error analysis showed that using a single and more accurate density profile along a DC core provided more reliable results than trying to include the potential spatial variability in density from extra (but less accurate) ice cores distributed along the profile. The most striking feature is an accumulation pattern that remains constant through time with persistent gradients such as a marked decrease from 26 mm w.e. yr−1 at DC to 20 mm w.e. yr−1 at the south-west end of the profile over the last 234 years on average (with a similar decrease from 25 to 19 mm w.e. yr−1 over the last 592 years). As for the time dependency, despite an overall consistency with similar measurements carried out along the main East Antarctic divides, interpreting possible trends remains difficult. Indeed, error bars in our measurements are still too large to unambiguously infer an apparent time increase in accumulation rate. For the proposed absolute values, maximum margins of error are in the range 4 mm w.e. yr−1 (last 234 years) to 2 mm w.e. yr−1 (last 592 years), a decrease with depth mainly resulting from the time-averaging when computing accumulation rates.

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Mass and Energy Balances of Glaciers and Ice Sheets

Cogley

2005

Encyclopedia of Hydrological Sciences

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Glaciers exchange energy and mass with the rest of the hydrosphere by snowfall, melting, vapor transfer, and the calving of icebergs. Melting and vapor transfer are significant in both the energy balance and the mass balance, which in consequence are intimately coupled. Glacier energy balances differ from those of other natural surfaces in having small or even negative net radiation. Emission of terrestrial radiation is limited, the surface temperature being no greater than the freezing point, but the surface albedo is always high. The limit on surface temperature, and the year-round tendency for net radiative cooling, means that sensible heat transfer is generally downward, while vapor transfer may be either upward or downward. Once conduction has raised a surface layer to the freezing point, further energy surpluses are used to melt snow or ice. In winter, the energy balance is dominated by radiative cooling. Apart from its close connection with the energy balance, the mass balance is also influenced strongly by glacier dynamics. Glaciers and the flowlines of which they are composed exhibit vertical zonation, with net accumulation at higher and net ablation (mass loss) at lower elevations. This imbalance drives, and is corrected by, the ice flow. The leading methods for the measurement of mass balance are the direct, geodetic, and kinematic methods. Direct measurement involves determining the accumulation and ablation in situ or by equivalent remote sensing, with separate treatment of calving where it occurs. Geodetic measurements require the determination of glacier thickness at two epochs; the change of thickness, approximately equal to the change in surface elevation, gives a volume balance that may be converted to a mass balance if the density of the mass gained or lost can be supplied accurately. In the direct and geodetic approaches, the ice flow is assumed to integrate to zero over any one flowline (correctly, if the entire flowline is measured). Kinematic methods are free of this restriction. They involve measurement of all of the terms in the balance and are therefore more difficult. The need for better understanding of mass balance, at socioeconomic scales from local to global, has stimulated intense study of ways to improve the measurements. Recent and impending methodological advances are coming from radar altimetry, laser altimetry, gravimetry, passive-microwave remote sensing, and interferometry using synthetic aperture radar. A subject requiring increased attention, as the measurements improve in precision and coverage, is improved quantification of the measurement errors. The best current estimates of global average mass balance are equivalent to 0.14-0.44 mm a −1 of sea-level rise, to be compared with the inferred total rate of about 1.9 mm a −1 . This figure is a composite of estimates for "small" glaciers (those other than the ice sheets), whose balance has been growing more negative since the 1960s; the Greenland Ice Sheet, which seems to have a negative balance; and the Antarctic Ice Sheet,...

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Spatial and temporal variability of snow accumulation using ground-penetrating radar and ice cores on a Svalbard glacier

Cited by 79 publications

References 24 publications

Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model

Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model

Spatial and temporal distributions of surface mass balance between Concordia and Vostok stations, Antarctica, from combined radar and ice core data: first results and detailed error analysis

Mass and Energy Balances of Glaciers and Ice Sheets

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