Process-based modelling of the methane balance in periglacial landscapes (JSBACH-methane)

• Main Authors: S. Kaiser, M. Göckede, K. Castro-Morales, C. Knoblauch, A. Ekici, T. Kleinen, S. Zubrzycki, T. Sachs, C. Wille, C. Beer
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-01-01
• Series: Geoscientific Model Development
• Online Access: http://www.geosci-model-dev.net/10/333/2017/gmd-10-333-2017.pdf

A detailed process-based methane module for a global land surface scheme has been developed which is general enough to be applied in permafrost regions as well as wetlands outside permafrost areas. Methane production, oxidation and transport by ebullition, diffusion and plants are represented. In this model, oxygen has been explicitly incorporated into diffusion, transport by plants and two oxidation processes, of which one uses soil oxygen, while the other uses oxygen that is available via roots. Permafrost and wetland soils show special behaviour, such as variable soil pore space due to freezing and thawing or water table depths due to changing soil water content. This has been integrated directly into the methane-related processes. A detailed application at the Samoylov polygonal tundra site, Lena River Delta, Russia, is used for evaluation purposes. The application at Samoylov also shows differences in the importance of the several transport processes and in the methane dynamics under varying soil moisture, ice and temperature conditions during different seasons and on different microsites. These microsites are the elevated moist polygonal rim and the depressed wet polygonal centre. The evaluation shows sufficiently good agreement with field observations despite the fact that the module has not been specifically calibrated to these data. This methane module is designed such that the advanced land surface scheme is able to model recent and future methane fluxes from periglacial landscapes across scales. In addition, the methane contribution to carbon cycle–climate feedback mechanisms can be quantified when running coupled to an atmospheric model.