Representative surface snow density on the East Antarctic Plateau
<p>Surface mass balances of polar ice sheets are essential to estimate the contribution of ice sheets to sea level rise. Uncertain snow and firn densities lead to significant uncertainties in surface mass balances, especially in the interior regions of the ice sheets, such as the East Antarcti...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-11-01
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| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/14/3663/2020/tc-14-3663-2020.pdf |
| Summary: | <p>Surface mass balances of polar ice sheets are essential to estimate the
contribution of ice sheets to sea level rise. Uncertain snow and firn
densities lead to significant uncertainties in surface mass balances,
especially in the interior regions of the ice sheets, such as the East
Antarctic Plateau (EAP). Robust field measurements of surface snow density
are sparse and challenging due to local noise. Here, we present a snow
density dataset from an overland traverse in austral summer 2016/17 on the
Dronning Maud Land plateau. The sampling strategy using 1 m carbon fiber
tubes covered various spatial scales, as well as a high-resolution study in
a trench at 79<span class="inline-formula"><sup>∘</sup></span> S, 30<span class="inline-formula"><sup>∘</sup></span> E. The 1 m snow density has been
derived volumetrically, and vertical snow profiles have been measured using a
core-scale microfocus X-ray computer tomograph. With an error of less than
2 %, our method provides higher precision than other sampling devices of
smaller volume. With four spatially independent snow profiles per location,
we reduce the local noise and derive a representative 1 m snow density with an error of the mean of less than 1.5 %. Assessing sampling methods used in previous studies, we find the highest horizontal variability in density
in the upper 0.3 m and therefore recommend the 1 m snow density as a robust
measure of surface snow density in future studies. The average 1 m snow
density across the EAP is 355 kg m<span class="inline-formula"><sup>−3</sup></span>, which we identify as
representative surface snow density between Kohnen Station and Dome Fuji. We cannot detect a temporal trend caused by the temperature increase over the
last 2 decades. A difference of more than 10 % to the density of
320 kg m<span class="inline-formula"><sup>−3</sup></span> suggested by a semiempirical firn model for the same
region indicates the necessity for further calibration of surface snow
density parameterizations. Our data provide a solid baseline for tuning the
surface snow density parameterizations for regions with low accumulation and low temperatures like the EAP.</p> |
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| ISSN: | 1994-0416 1994-0424 |