Low Permafrost Methane Emissions from Arctic Airborne Flux Measurements
One of the most pressing questions with regard to climate feedback processes in a warming Arctic is the regional-scale greenhouse gas release from Arctic permafrost areas. Ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of ene...
| Main Authors: | , , , , |
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| Format: | Conference Object |
| Language: | unknown |
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AGU
2014
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| Subjects: | |
| Online Access: | https://epic.awi.de/id/eprint/39551/ https://agu.confex.com/agu/fm14/meetingapp.cgi/Paper/21775 https://hdl.handle.net/10013/epic.46702 |
| Summary: | One of the most pressing questions with regard to climate feedback processes in a warming Arctic is the regional-scale greenhouse gas release from Arctic permafrost areas. Ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of energy and matter. However, these observations are rare in the Arctic permafrost zone and site selection is bound by logistical constraints among others. Consequently, these observations cover only small areas that are not necessarily representative of the region of interest. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this question. During the AIRMETH-2012 and AIRMETH-2013 campaigns aboard the research aircraft POLAR 5 we measured turbulent exchange of energy, methane, and (in 2013) carbon dioxide along thousands of kilometers covering the North Slope of Alaska and the Mackenzie Delta, Canada. Time-frequency (wavelet) analysis, footprint modeling, and machine learning techniques are used to (i) determine spatially resolved turbulence statistics, fluxes, and contributions of biophysical surface properties, and (ii) extract regionally valid functional relationships between environmental drivers and the observed fluxes. These environmental response functions (ERF) are used to explain spatial flux patterns and – if drivers are available in temporal resolution – allow for spatio-temporal scaling of the observations. This presentation will focus on 2012 methane fluxes on the North Slope of Alaska and the relevant processes on the regional scale and provide an updated 100 m resolution methane flux map of the North Slope of Alaska. |
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