[A-CG35] Global Carbon Cycle Observation and Analysis

[ACG35-06] Data-driven estimation of soil CH₄ absorption in Japan

*Hina Yamanuki¹, Kazuhito Ichii¹, Yuhei Yamamoto¹, Munemasa Teramoto², Sun Lifei³, Jun Koarashi⁴, Mariko Atarashi-Andoh⁴, Hirohiko Nagano⁵, Takashi Hirano⁶, Kentaro Takagi⁶, Sachinobu Ishida⁷, Masahiro Takagi⁸, Toshiaki Kondo⁹, Yoshiyuki Takahashi³, Naishen Liang³ (1.Center for Environmental Remote Sensing, Chiba University, 2.Arid Land Research Center, Tottori University, 3.National Institute for Environmental Studies, 4.Japan Atomic Energy Agency, 5.Niigata University, 6.Hokkaido University, 7.Hirosaki University, 8.University of Miyazaki, 9.Japan International Research Center for Agricultural Sciences)

Keywords:methane absorption, machine learning, remote sensing, upscaling

Accurate prediction of atmospheric greenhouse gases (GHGs) concentrations is important for understanding climate change such as global warming. Forest soils are considered a sink for CH₄, which has 28 times the greenhouse effect of CO₂. Still, a lack of observational data makes it unclear whether the absorption capability will be maintained with long-term warming. Therefore, accurately estimating the CH₄ sink of forest soils is crucial in predicting future climate change. So far, a field observation network for continuous automatic measurement of soil CH₄ absorption is being developed in Asia, and it has become clear that soil CH₄ absorption capability and global warming response vary greatly from region to region. Spatiotemporal variations in soil CH₄ absorption are considered to be influenced not only by climate but also by the physical and chemical properties of soils. In this study, we estimated soil CH₄ absorption in Japan by applying a machine learning method to data from the largest soil CH₄ absorption observation network in Asia, which has been developed and conducted by National Institute for Environmental Studies (NIES) using the same observation methods, soil properties, organic carbon properties, and microbial properties obtained by Japan Atomic Energy Agency (JAEA) and other organizations, and satellite observation data.