Antarctic snow accumulation mapped using polarization of 4.3‐cm wavelength microwave emission

Abstract

[1] Different parts of Antarctica receive different amounts of snowfall each year. In this paper we map the variations of the mean annual snow accumulation across the ice sheet. We also quantify the uncertainty in our estimates more objectively than has been possible for earlier maps. The new map is produced using observations from satellites and ground-based measurements. After a logarithmic transformation, these are combined using the geostatistical method of continuous-part universal kriging to give an estimate of the snow accumulation within each cell of a rectangular grid covering Antarctica. We also derive spatial averages over the major drainage systems of the ice sheet, along with their confidence intervals. We obtain a value of 143 ± 4 kg m À2 a À1 for the average rate of snow accumulation upon the grounded ice sheet of Antarctica.

An improved Antarctic dataset for high resolution numerical ice sheet models (ALBMAP v1)

“…The accumulation is generally higher than that of Arthern et al (2006), especially in data-sparse areas. The integrated accumulation exceeds previous estimates by up to 15%.…”

“…7c). The dataset was masked using the −2000 m bathymetry contour in the same way as the Arthern et al (2006) accumulation, again, areas beyond the present day ice sheet are a result of the extrapolation process and the interpolation method used.…”

“…The accumulation dataset of Arthern et al (2006) was derived from interpolation of in situ point measurements, i.e. snow pits, ice cores and stake measurements.…”

Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica

“…The spatial variations of brightness temperature are generally continuous, except in coastal and mountainous regions. Snow properties retrieved from microwave data, like the accumulation (Vaughan et al, 1999;Arthern et al, 2006) or the grain size profile (Brucker et al, 2011), are also spatially continuous. This suggests that the snowpack from one pixel to a neighbor is generally similar.…”

“…They have several advantages over other remote sensing techniques: high sensitivity to snow properties (temperature, grain size, density), subdaily coverage in the polar regions, and independence of cloud conditions and solar illumination. Typical applications for ice sheets aim to retrieve snow temperature (Shuman et al, 1995;Schneider and Steig, 2002;Schneider et al, 2004), snowmelt (e.g., Zwally, 1977;Abdalati and Steffen, 1995;Torinesi et al, 2003), snow accumulation (Vaughan et al, 1999;Arthern et al, 2006), grain size (Brucker et al, 2010;Picard et al, 2012), thermal properties (Koenig et al, 2007;Picard et al, 2009) or surface state (Shuman et al, 1993;Champollion et al, 2013). Passive microwave data are also widely used in assimilation schemes to constrain atmospheric analyses for which the surface emissivity is an issue, particularly over Antarctica (Guedj et al, 2010).…”