On the composition of firn air and its dependence on seasonally varying atmospheric boundary conditions and the firn structure

• Main Author: Weiler, Karin
• Other Authors: Stocker, T.F.
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: 2008
• Subjects: 530 Physics; Antarc*; Antarctic
• Online Access: https://boris.unibe.ch/192535/1/weiler08phd.pdf; https://boris.unibe.ch/192535/

The dependence of the firn air composition on seasonally varying atmospheric boundary conditions and the firn structure has been studied based on firn air samples from two Antarctic sites, Halley and Kohnen. The Halley data set consists of six profiles sampled in a two month resolution in the year 2003. Settling of the firn and snow accumulation led to a shift of the depth levels of both, the firn air sampling setup and the thermistors. Prediction of this sample level shift with a 1–dimensional box model developed in the frame of this study coincides with the decrease of the analyzed diurnal temperature cycle. By forcing the temperature–diffusion model with the surface temperature history of Halley, temperature oscillations in the firn column originating from seasonal atmospheric temperature variations are reasonably well reproduced. Thus, the dependence of the thermal conductivity on firn density as derived by Schwander et al. [1997] is sufficient also on the seasonal scale. In order to simulate thermal fractionation of the different gas species, thermal diffusion factors αT are determined based on two different model approaches and the firn air data set: αT = 3.727 · 10−3 for the fractionation of 15N14N in N2, αT = 12.480·10−3 for 18O16O in air, αT = 7.321·10−3 for 16O2 in air, αT = 32.241·10−3 for 36Ar in air, αT = 45.516 · 10−3 for 40Ar in air, and 57.371 · 10−3 ≤ αT ≤ 67.811 · 10−3 for CO2 in air. Seasonal oscillations observed in the firn air profiles of CO2 and the isotopic species δ15N, δ18O, and δ36Ar act as expected from theory during the entire year. The imprint of both, seasonal atmospheric temperature variations and atmospheric concentration oscillations is well reproduced by the diffusion–temperature model. Neither a seasonal variability of ±0.5 ppmv in the atmospheric CO2 concentration nor thermal diffusion forced by seasonal atmospheric temperature oscillations will lead to considerable changes of the CO2 concentration in air bubbles finally occluded in the ice. An overestimation of the measured ...