analytical constraints on layered gas trapping and smoothing of atmospheric variability in ice under low-accumulation conditions
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2017
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Abstract
We investigate for the first time the loss and alteration of past
atmospheric information from air trapping mechanisms under low-accumulation
conditions through continuous CH4 (and CO) measurements. Methane
concentration changes were measured over the Dansgaard–Oeschger event 17
(DO-17, ∼ 60 000 yr BP) in the Antarctic Vostok 4G-2 ice
core. Measurements were performed using continuous-flow analysis combined
with laser spectroscopy. The results highlight many anomalous layers at the
centimeter scale that are unevenly distributed along the ice core. The anomalous
methane mixing ratios differ from those in the immediate surrounding layers
by up to 50 ppbv. This phenomenon can be theoretically reproduced
by a simple layered trapping model, creating very localized gas age scale
inversions. We propose a method for cleaning the record of anomalous values
that aims at minimizing the bias in the overall signal. Once the
layered-trapping-induced anomalies are removed from the record, DO-17 appears
to be smoother than its equivalent record from the high-accumulation WAIS
Divide ice core. This is expected due to the slower sinking and densification
speeds of firn layers at lower accumulation. However, the
degree of smoothing appears surprisingly similar between modern and DO-17 conditions at
Vostok. This suggests that glacial records of trace gases from low-accumulation sites in the East Antarctic plateau can provide a better time
resolution of past atmospheric composition changes than previously expected.
We also developed a numerical method to extract the gas age distributions in
ice layers after the removal of the anomalous layers based on comparison
with a weakly smoothed record. It is particularly adapted for the conditions
of the East Antarctic plateau, as it helps to characterize smoothing for a
large range of very low-temperature and low-accumulation conditions.
| Reference Key |
fourteau2017climateanalytical
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|---|---|
| Authors | ;K. Fourteau;X. Faïn;P. Martinerie;A. Landais;A. A. Ekaykin;V. Ya. Lipenkov;J. Chappellaz |
| Journal | proceedings - 16th ieee/acis international conference on computer and information science, icis 2017 |
| Year | 2017 |
| DOI |
10.5194/cp-13-1815-2017
|
| URL | |
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