Layering of surface snow and firn at Kohnen Station, Antarctica: Noise or seasonal signal?

• Published in: Journal of Geophysical Research: Earth Surface
• Main Authors: Laepple, Thomas, Hörhold, Maria, Münch, Thomas, Freitag, Johannes, Wegner, Anna, Kipfstuhl, Sepp
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2016
• Subjects: Institut für Physik und Astronomie; Antarctic; Dronning Maud Land; Greenland; Kohnen; Kohnen Station; Antarc*; Antarctica; ice core
• Online Access: https://publishup.uni-potsdam.de/opus4-ubp/frontdoor/index/index/docId/44870; https://doi.org/10.1002/2016JF003919

The density of firn is an important property for monitoring and modeling the ice sheets as well as to model the pore close-off and thus to interpret ice core-based greenhouse gas records. One feature, which is still in debate, is the potential existence of an annual cycle of firn density in low-accumulation regions. Several studies describe or assume seasonally successive density layers, horizontally evenly distributed, as seen in radar data. On the other hand, high-resolution density measurements on firn cores in Antarctica and Greenland show no clear seasonal cycle in the top few meters. A major caveat of most existing snow-pit and firn-core-based studies is that they represent one vertical profile from a laterally heterogeneous density field. To overcome this, we created an extensive data set of horizontal and vertical density data at Kohnen Station, Dronning Maud Land, on the East Antarctic Plateau. We drilled and analyzed three 90m long firn cores as well as 143 one-meter-long vertical profiles from two elongated snow trenches to obtain a two-dimensional view of the density variations. The analysis of the 45m wide and 1m deep density fields reveals a seasonal cycle in density. However, the seasonality is overprinted by strong stratigraphic noise, making it invisible when analyzing single firn cores. Our density data set extends the view from the local ice core perspective to a hundred meter scale and thus supports linking spatially integrating methods such as radar and seismic studies to ice and firn cores.