Regional scale assessment of methane emission from Arctic permafrost for improving process-based models

• Main Authors: Kohnert, Katrin, Serafimovich, Andrei, Metzger, Stefan, Hartmann, Jörg, Sachs, Torsten
• Format: Conference Object
• Language: unknown
• Published: EUCOP4 2014
• Subjects: Arctic; Mackenzie Delta; north slope; permafrost; Alaska
• Online Access: https://epic.awi.de/id/eprint/39544/; https://epic.awi.de/id/eprint/39544/1/2014_EUCOP4_Book_of_Abstracts.pdf; http://www.eucop4.org/; https://hdl.handle.net/10013/epic.46696; https://hdl.handle.net/10013/epic.46696.d001

Wetlands are the dominant natural source of methane release on a global scale. Estimates about the contribution of Arctic permafrost wetlands to the emission are still uncertain and need further assessment. A reason for that variability is the heterogeneity of the Arctic permafrost landscapes. They extend over large areas and are characterized by varying environmental properties like land cover, surface temperature or soil water content. With chamber and tower measurements, exchange processes of matter fluxes have been measured for decades and have contributed to our understanding of the underlying processes. These results give an idea about possible changes in the future related to changing climatic conditions. For conclusions on a regional scale, however, these measurements cannot represent the true spatial variability of these fluxes, due to their local quality. Regional information about the fluxes, especially carbon fluxes, is indispensable for assessing and predicting the climatic importance of the Arctic permafrost regions. Therefore, regional flux information can help to develop large-scale prediction models for the Arctic. To overcome this spatial limitation we use airborne measurements. During the Airborne Measurements of Methane Fluxes (AIRMETH) campaigns we conducted low level flights across the North Slope of Alaska and the Mackenzie Delta in Canada in the summers of 2012 and 2013. A combination of mechanistic and data-driven analysis tools allows us to relate the measured methane fluxes to spatio-temporally resolved surface properties and basic meteorological information. The aim is to develop a predictive model that produces maps of methane emissions, based on the spatial variation of the land surface and meteorological states. Here we will show first results from the campaigns conducted in the Mackenzie Delta in 2012 and 2013.