WetCH4: A machine learning-based upscaling of methane fluxes of northern 
wetlands during 2016–2022

Ying, Qing; Poulter, Benjamin; Watts, Jennifer D.; Arndt, Kyle A.; Virkkala, Anna-Maria; Bruhwiler, Lori; Oh, Youmi; Rogers, Brendan M.; Natali, Susan M.; Sullivan, Hilary; Schiferl, Luke D.; Elder, Clayton; Peltola, Olli; Bartsch, Annett; Armstrong, Amanda; Desai, Ankur R.; Euskirchen, Eugénie; Göckede, Mathias; Lehner, Bernhard; Nilsson, Mats B.; Peichl, Matthias; Sonnentag, Oliver; Tuittila, Eeva-Stiina; Sachs, Torsten; Kalhori, Aram; Ueyama, Masahito; Zhang, and Zhen

doi:10.5194/essd-2024-84

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WetCH₄: A machine learning-based upscaling of methane fluxes of northern wetlands during 2016–2022

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Göckede, Mathias
Integrating surface-atmosphere Exchange Processes Across Scales - Modeling and Monitoring, Dr. Mathias Göckede, Department Biogeochemical Signals, Prof. Dr. Sönke Zaehle, Max Planck Institute for Biogeochemistry, Max Planck Society;

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https://doi.org/10.5194/essd-2024-84
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Citation

Ying, Q., Poulter, B., Watts, J. D., Arndt, K. A., Virkkala, A.-M., Bruhwiler, L., et al. (2024). WetCH₄: A machine learning-based upscaling of methane fluxes of northern wetlands during 2016–2022. Earth System Science Data Discussions. doi:10.5194/essd-2024-84.

Cite as: https://hdl.handle.net/21.11116/0000-000F-1DE1-3

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