2:30 PM - 2:45 PM
[ACG22-14] Current status of data-driven estimation of terrestrial carbon and energy fluxes using eddy-covariance network and remote sensing data
Keywords:Terrestrial biosphere, Upscaling, Material Cycle
In this presentation, we introduce an overview and applications of data-driven modelling to terrestrial biogeochemical studies. We used regional and global networks of eddy-covariance observations (e.g. AsiaFlux and FLUXNET) and remote sensing as the forcing of data-driven model, and conducted various applications using them. First, we will show the methodology and algorithms of data-driven model. Second, we will show the applications of the resulting data: i.e., spatio-temporal variability in terrestrial CO2 flux (Saigusa et al. 2010; Ueyama et al. 2013) and energy balance (Ueyama et al. 2014). Third, we will present evaluation of data-driven models with an assimilation of atmospheric CO2 from GOSAT Level 4A product (top-down approach) (e.g. Kondo et al. 2015). Fourth, we will demonstrate that regional/global CO2 and H2O fluxes upscaled by data-driven models can be used to refine terrestrial ecosystem models (e.g. Ichii et al. 2009).
Ichii et al. (2009) Agr. For. Met., 149, 1907-1918.
Kondo et al. (2015) JGR Biogeosciences.120, 1226–1245, doi:10.1002/2014JG002866.
Saigusa et al. (2010) Biogeosciences, 7, 641-655.
Ueyama et al. (2013) JGR Biogeosciences, 118, 1266–1281, doi:10.1002/jgrg.20095.
Ueyama et al. (2014) JGR Biogeosciences, 119, 1947–1969, doi:10.1002/2014JG002717.
This study was supported by the Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan, the JAXA Global Change Observation Mission (GCOM) project (grant No. 115), and the JSPS KAKENHI (grant No. 25281003).