Low permafrost methane emissions from regional airborne flux measurements

• Main Authors: Sachs, Torsten, Serafimovic, Andrei, Metzger, Stefan, Kohnert, Katrin, Hartmann, Jörg
• Format: Conference Object
• Language: unknown
• Published: http://www.icop2016.org/index.html 2016
• Subjects: north slope; permafrost; Alaska
• Online Access: https://epic.awi.de/id/eprint/43164/; http://www.icop2016.org/index.html; https://hdl.handle.net/10013/epic.49663

Large uncertainties still exist in the global methane budget with clear disagreements between bottom-up and top-down estimates, limiting confidence in climate projections. This is particularly true in the Arctic, which is warming rapidly while storing vast amounts of organic carbon that could potentially be released as carbon dioxide and methane, adding a new greenhouse gas source of unknown magnitude. Regional scale methane emission estimates and functional relationships between potential drivers and methane fluxes are currently unavailable. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this question. While ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of energy and matter, they 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. During the AIRMETH-2012 campaign aboard the research aircraft POLAR 5 we measured turbulent exchange fluxes of energy and methane along thousands of kilometers covering the North Slope of Alaska. Time-frequency (wavelet) analysis, footprint modeling, and machine learning techniques are used to extract spatially resolved turbulence statistics and fluxes, spatially resolved contributions of land cover and biophysical surface properties to each flux observation, as well as regionally valid functional relationships between environmental drivers and observed fluxes that can explain spatial flux patterns and – if available in temporal resolution – allow for spatio-temporal scaling of the observations. Here we present a 100 m resolution gridded methane flux map for the North Slope of Alaska, covering about 90.000 km2. We show that ...