New Data-Driven Estimation of Terrestrial CO2 Fluxes in Asia Using a Standardized Database of Eddy Covariance Measurements, Remote Sensing Data, and Support Vector Regression

Abstract

Verbatim from NASA NTRS. Not paraphrased, not summarized.

The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.

Authors

• Ichii, Kazuhito Japan Agency for Marine-Earth Science and Technology
• Ueyama, Masahito Osaka Prefecture Univ.
• Kondo, Masayuki Japan Agency for Marine-Earth Science and Technology
• Saigusa, Nobuko National Inst. for Environmental Studies
• Kim, Joon Seoul National University
• Alberto, Ma. Carmelita International Rice Research Inst.
• Ardö, Jonas Lund Univ.
• Euskirchen, Eugénie S. Alaska Univ.
• Kang, Minseok National Institute of Meteorological Research
• Hirano, Takashi Hokkaido Univ.
• Joiner, Joanna NASA Goddard Space Flight Center
• Kobayashi, Hideki Japan Agency for Marine-Earth Science and Technology
• Marchesini, Luca Belelli VU Univ.
• Merbold, Lutz International Livestock Research Inst.
• Miyata, Akira National Agriculture and Food Research Organization
• Saitoh, Taku M. Gifu Univ.
• Takagi, Kentaro Hokkaido Univ.
• Varlagin, Andrej Russian Academy of Natural Sciences
• Bret-Harte, M. Syndonia Alaska Univ.
• Kitamura, Kenzo Forestry and Forest Products Research Inst.
• Kosugi, Yoshiko Kyoto Univ.
• Kotani, Ayumi Nagoya Univ.
• Kumar, Kireet Ministry of Environment and Forests
• Li, Sheng-Gong Chinese Academy of Sciences
• Machimura, Takashi Osaka Univ.
• Matsuura, Yojiro Forestry and Forest Products Research Inst.
• Mizoguchi, Yasuko Forestry and Forest Products Research Inst.
• Ohta, Takeshi Nagoya Univ.
• Mukherjee, Sandipan Ministry of Environment and Forests
• Yanagi, Yuji Japan Agency for Marine-Earth Science and Technology
• Yasuda, Yukio Forestry and Forest Products Research Inst.
• Zhang, Yiping Chinese Academy of Sciences
• Zhao, Fenghua Chinese Academy of Sciences

Keywords

• chlorophyll fluorescence
• flux tower