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Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes

Dutta, Debsunder and Schimel, David S. and Sun, Ying and van der Tol, Christiaan and Frankenberg, Christian (2019) Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes. Biogeosciences, 16 (1). pp. 77-103. ISSN 1726-4189.

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Canopy structural and leaf photosynthesis parameterizations such as maximum carboxylation capacity (V_(cmax)), slope of the Ball–Berry stomatal conductance model (BB_(slope)) and leaf area index (LAI) are crucial for modeling plant physiological processes and canopy radiative transfer. These parameters are large sources of uncertainty in predictions of carbon and water fluxes. In this study, we develop an optimal moving window nonlinear Bayesian inversion framework to use the Soil Canopy Observation Photochemistry and Energy fluxes (SCOPE) model for constraining V_(cmax), BB_(slope) and LAI with observations of coupled carbon and energy fluxes and spectral reflectance from satellites. We adapted SCOPE to follow the biochemical implementation of the Community Land Model and applied the inversion framework for parameter retrievals of plant species that have both the C₃ and C₄ photosynthetic pathways across three ecosystems. We present comparative analysis of parameter retrievals using observations of (i) gross primary productivity (GPP) and latent energy (LE) fluxes and (ii) improvement in results when using flux observations along with reflectance. Our results demonstrate the applicability of the approach in terms of capturing the seasonal variability and posterior error reduction (40 %–90 %) of key ecosystem parameters. The optimized parameters capture the diurnal and seasonal variability in the GPP and LE fluxes well when compared to flux tower observations (0.95>R²>0.79). This study thus demonstrates the feasibility of parameter inversions using SCOPE, which can be easily adapted to incorporate additional data sources such as spectrally resolved reflectance and fluorescence and thermal emissions.

Item Type:Article
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URLURL TypeDescription
Schimel, David S.0000-0003-3473-8065
Sun, Ying0000-0002-9819-1241
Frankenberg, Christian0000-0002-0546-5857
Additional Information:© 2019 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License. Received: 25 June 2018 – Discussion started: 16 July 2018. Revised: 17 November 2018 – Accepted: 16 December 2018 – Published: 11 January 2019. AmeriFlux site Missouri Ozark (US-MOz) is supported by the US Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research Program, through Oak Ridge National Laboratory's Terrestrial Ecosystem Science-Science Focus Area; ORNL is managed by UT-Battelle, LLC, for DOE under contract DE-AC05-00OR22725. The research was carried out, in part, at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Government sponsorship is acknowledged. Author contributions: DD and CF designed the research, developed the inversion framework and conducted the modeling simulations. DD, CF, CvdT, YS and DSS contributed towards interpretation and analysis of the results. DD and CF developed the initial draft of the manuscript, and DD, CF, CvdT, YS and DSS contributed towards improvement of the original draft and finalization of the paper. The authors declare that they have no conflict of interest. Edited by: Dan Yakir. Reviewed by: Peter Rayner and two anonymous referees.
Funding AgencyGrant Number
Department of Energy (DOE)DE-AC05-00OR22725
Issue or Number:1
Record Number:CaltechAUTHORS:20200212-103702422
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Official Citation:Dutta, D., Schimel, D. S., Sun, Y., van der Tol, C., and Frankenberg, C.: Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes, Biogeosciences, 16, 77–103,, 2019
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101239
Deposited By: Tony Diaz
Deposited On:12 Feb 2020 19:47
Last Modified:12 Feb 2020 19:47

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