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Discussion papers | Copyright
https://doi.org/10.5194/acp-2018-277
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Jun 2018

Research article | 12 Jun 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Characterisation of short-term extreme methane fluxes related to non-turbulent mixing above an Arctic permafrost ecosystem

Carsten Schaller1,2,a, Fanny Kittler2, Thomas Foken1,3, and Mathias Göckede2 Carsten Schaller et al.
  • 1University of Bayreuth, Department of Micrometeorology, 95440 Bayreuth, Germany
  • 2Max-Planck-Institute for Biogeochemistry, 07745 Jena, Germany
  • 3University of Bayreuth, Bayreuth Center of Ecology and Environmental Research (BayCEER), 95440 Bayreuth, Germany
  • anow at: University of Münster, Institute of Landscape Ecology, Climatology Group, Heisenbergstr. 2, 48149 Münster, Germany

Abstract. Methane (CH4) emissions from biogenic sources, such as Arctic permafrost wetlands, are associated with large uncertainties because of the high variability of fluxes in both space and time. This variability poses a challenge to monitoring CH4 fluxes with the eddy covariance (EC) technique, because this approach requires stationary signals from spatially homogeneous sources. Episodic outbursts of CH4 emissions, i.e. outgassing in the form of bubbles from oversaturated groundwater or surfacewater, are particularly challenging to quantify. Such events typically last for only a few minutes, which is much shorter than the common averaging interval for EC (30 minutes). The steady state assumption is jeopardized, which potentially leads to a non-negligible bias in the CH4 flux. We tested and evaluated a flux calculation method based on wavelet analysis, which, in contrast to regular EC data processing, does not require steady-state conditions and is allowed to obtain fluxes over averaging periods as short as 1 minute. We demonstrate that the occurrence of extreme CH4 flux events over the summer season followed a seasonal course with a maximum in early August, which is strongly correlated with the maximum soil temperature. Statistics on meteorological conditions before, during, and after the detected events revealed that it is atmospheric mixing that triggered such events rather than CH4 emission from the soil. By investigating individual events in more detail, we identified various mesoscale processes like gravity waves, low-level jets, weather fronts passing the site, and cold-air advection from a nearby mountain ridge as the dominating processes. Overall, our findings demonstrate that wavelet analysis is a powerful method for resolving highly variable flux events on the order of minutes. It is a reliable reference to evaluate the quality of EC fluxes under non-steady-state conditions.

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Short summary
Methane emissions from biogenic sources, e.g. Arctic permafrost ecosystems, are associated with uncertainties due to the high variability of fluxes in both space and time. Besides the traditional eddy covariance method, we evaluated a method based on wavelet analysis, which does not require a stationary time series, to calculate fluxes. The occurrence of found extreme methane flux events was strongly correlated with the soil temperature. They were triggered by atmospheric non-turbulent mixing.
Methane emissions from biogenic sources, e.g. Arctic permafrost ecosystems, are associated with...
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