New estimations of precipitation and surface sublimation in East Antarctica from snow accumulation measurements

Frezzotti, Màssimo; Pourchet, M.; Flora, O.; Gandolfi, Stefano; Gay, Michel; Urbini, Stefano; Vincent, Christian; Becagli, Silvia; Gragnani, R.; Proposito, Marco; Severi, Mirko; Traversi, Rita; Udisti, Roberto; Fily, Michel

doi:10.1007/s00382-004-0462-5

Cited by 142 publications

(202 citation statements)

References 60 publications

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“…-Our radar accumulation results agree fairly well with measurements made within 25 km of DC by Frezzotti et al (2004) and Urbini et al (2008) for the period 1965-"recent", and with estimates made by Urbini et al (2008) for the period 1739-2008. Differences remained within less than 1 cm w.e.…”

Section: Spatial Variations In Accumulationsupporting

confidence: 87%

“…Other studies focused on the DC sector (Petit et al, 1982;Urbini et al, 2008). Frezzotti et al (2004Frezzotti et al ( , 2005 used snow radar as well as stake farms, ice cores, surface morphology and remote sensing to estimate spatial and temporal variability of the SMB along a transect from Terra Nova Bay to DC, and from D66 to Talos Dome (Magand et al, 2004). However, SMB measurements between DC and the coast are sparse and no SMB radar measurements had ever been made along the DC-DdU traverse.…”

Section: Introductionmentioning

confidence: 99%

“…Results were compared with historical data in the region (Pettré et al, 1986;Mulvaney and Wolff, 1994;Pourchet et al, 2003;Frezzotti et al, 2004;Urbini et al, 2008) and to four SMB climatologies (Arthern et al, 2006;van de Berg et al, 2006, ERAInterim and LMDZ4). We focused on the pre-industrial to the industrial period, which spans the last 300 yr (approximately the top 70 m of snow, or the first 750 ns of the radargrams).…”

Section: Introductionmentioning

confidence: 99%

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Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

et al. 2012

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Abstract. The mass balance of ice sheets is an intensively studied topic in the context of global change and sealevel rise. However -particularly in Antarctica -obtaining mass balance estimates remains difficult due to various logistical problems. In the framework of the TASTE-IDEA (Trans-Antarctic Scientific Traverses Expeditions -Ice Divide of East Antarctica) program, an International Polar Year project, continuous ground penetrating radar (GPR) measurements were carried out during a traverse in Adelie Land (East Antarctica) during the 2008-2009 austral summer between the Italian-French Dome C (DC) polar plateau site and French Dumont D'Urville (DdU) coastal station. The aim of this study was to process and interpret GPR data in terms of snow accumulation, to analyse its spatial and temporal variability and compare it with historical data and modelling. The focus was on the last 300 yr, from the preindustrial period to recent times. Beta-radioactivity counting and gamma spectrometry were applied to cores at the LGGE laboratory, providing a depth-age calibration for radar measurements. Over the 600 km of usable GPR data, depth and snow accumulation were determined with the help of three distinct layers visible on the radargrams (≈ 1730(≈ , 1799(≈ and 1941. Preliminary results reveal a gradual increase in accumulation towards the coast (from ≈ 3 cm w.e. a −1 at Dome C to ≈ 17 cm w.e. a −1 at the end of the transect) and previously undocumented undulating structures between 300 and 600 km from DC. Results agree fairly well with data from previous studies and modelling. Drawing final conclusions on temporal variations is difficult because of the margin of error introduced by density estimation. This study should have various applications, including model validation.

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Section: Spatial Variations In Accumulationsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

et al. 2012

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“…Frezzotti et al (2007) and Eisen et al (2008) argue that in general the snow accumulation variability in East Antarctica on scales 0.1 to 100 m is controlled by wind-induced surface features, i.e. sastrugi and On the x-axis are the ordinal numbers corresponding to the snow pit sites, located 5 km apart from each other (see Fig.…”

Section: Spatial Variability In Snow Densitymentioning

confidence: 99%

“…This is particularly important for the interpretation of accumulation measurements (Wingham, 2000;Frezzotti et al, 2004;Rotschky et al, 2007) and other ice core results . Data on the spatial and temporal variability in the snow pack are essential for validating glaciological models (Dadic et al, 2008) and for use as lower boundary conditions for climate and numerical weather prediction models (Tastula and Vihma, 2011).…”

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confidence: 99%

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

et al. 2011

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Abstract.To quantify the spatial and temporal variability in the snow pack, field measurements were carried out during four summers in Dronning Maud Land, Antarctica. Data from a 310-km-long transect revealed the largest horizontal gradients in snow density, temperature, and hardness in the escarpment region. On the local scale, day-to-day temporal variability dominated the standard deviation of snow temperature, while the diurnal cycle was of second significance, and horizontal variability on the scale of 0.4 to 10 m was least important. In the uppermost 0.2 m, the snow temperature was correlated with the air temperature over the previous 6-12 h, whereas at the depths of 0.3 to 0.5 m the most important time scale was 3 days. Cloud cover and radiative fluxes affected the snow temperature in the uppermost 0.30 m and the snow density in the uppermost 0.10 m. Both on the intra-pit and transect scales, the ratio of horizontal to temporal variability increased with depth. The horizontal standard deviation of snow density increased rapidly between the scales of 0.4 and 2 m, and more gradually from 10 to 100 m. Inter-annual variations in snow temperature and density were due to interannual differences in air temperature and the timing of the precipitation events.

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Modeling the impact of snow drift on the decameter-scale variability of snow properties on the Antarctic Plateau

Libois

Picard

Arnaud

et al. 2014

J. Geophys. Res. Atmos.

133

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The annual accumulation and the physical properties of snow close to the surface on the Antarctic Plateau are characterized by a large decameter‐scale variability resulting from snow drift that is not simulated by one‐dimensional snow evolution models. Here, the detailed snowpack model Crocus was adapted to Antarctic conditions and then modified to account for this drift‐induced variability using a stochastic snow redistribution scheme. For this, 50 simulations were run in parallel and were allowed to exchange snow mass according to rules driven by wind speed. These simple rules were developed and calibrated based on in situ pictures of the snow surface recorded for two years. The simulation performed with this new model shows three substantial improvements with respect to standard Crocus simulations. First, significant and rapid variations of snow height observed in hourly measurements are well reproduced, highlighting the crucial role of snow drift in snow accumulation. Second, the statistics of annual accumulation is also simulated successfully, including the years with net ablation which are as frequent as 15% in the observations and 11% in the simulation. Last, the simulated vertical profiles of snow density and specific surface area down to 50 cm depth were compared to 98 profiles measured at Dome C during the summer 2012–2013. The observed spatial variability is partly reproduced by the new model, especially close to the surface. The erosion/deposition processes explain why layers with density lower than 250 kg m−3 or specific surface area larger than 30 m2 kg−1 can be found deeper than 10 cm.

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New estimations of precipitation and surface sublimation in East Antarctica from snow accumulation measurements

Cited by 142 publications

References 60 publications

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

Modeling the impact of snow drift on the decameter-scale variability of snow properties on the Antarctic Plateau

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