Surface snow density along an overland traverse between Kohnen Station and former Plateau Station (East Antarctica)

• Main Authors: Weinhart, Alexander Helmut, Freitag, Johannes, Hörhold, Maria, Kipfstuhl, Sepp, Eisen, Olaf
• Format: Dataset
• Language: English
• Published: PANGAEA 2021
• Subjects: Antarctica; ANT-Land_2016_COFI; ANT-Land_2016_COFI_12; ANT-Land_2016_COFI_16; ANT-Land_2016_COFI_19; ANT-Land_2016_COFI_21; ANT-Land_2016_COFI_22; ANT-Land_2016_COFI_23; ANT-Land_2016_COFI_24; ANT-Land_2016_COFI_25; ANT-Land_2016_COFI_26; ANT-Land_2016_COFI_27; ANT-Land_2016_COFI_4; ANT-Land_2016_COFI_44; ANT-Land_2016_COFI_56; ANT-Land_2016_COFI_60; ANT-Land_2016_COFI_64; ANT-Land_2016_COFI_69; ANT-Land_2016_COFI_71; ANT-Land_2016_COFI_73; ANT-Land_2016_COFI_75; ANT-Land_2016_COFI_77; ANT-Land_2016_COFI_79; ANT-Land_2016_COFI_8; DATE/TIME; density; snow; mean; standard deviation; DML; East Antarctica; ELEVATION; Event label; Kohnen; Kohnen Station; LATITUDE; Location; LONGITUDE; Number of profiles; Snow/ice sample; Volumetric measurement; Antarctic; Austral; Dome Fuji; Dronning Maud Land; Antarc*; The Cryosphere
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.928079; https://doi.org/10.1594/PANGAEA.928079

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°S, 30°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-3, 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-3 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.