Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon
Abstract
Here, the vast forests and natural areas of the Pacific Northwest comprise one of the most productive ecosystems in the northern hemisphere. The heterogeneous landscape of Oregon poses a particular challenge to ecosystem models. We present a framework using a scaling factor Bayesian inversion to improve the modeled atmosphere-biosphere exchange of carbon dioxide. Observations from 5 CO/CO2 towers, eddy covariance towers, and airborne campaigns were used to constrain the Community Land Model CLM4.5 simulated terrestrial CO2 exchange at a high spatial and temporal resolution (1/24°, 3-hourly). To balance aggregation errors and the degrees of freedom in the inverse modeling system, we applied an unsupervised clustering approach for the spatial structuring of our model domain. Data from flight campaigns were used to quantify the uncertainty introduced by the Lagrangian particle dispersion model that was applied for the inversions. The average annual statewide net ecosystem productivity (NEP) was increased by 32% to 29.7 TgC per year by assimilating the tropospheric mixing ratio data. The associated uncertainty was decreased by 28.4% to 29%, on average over the entire Oregon model domain with the lowest uncertainties of 11% in western Oregon. The largest differences between posterior and prior CO2 fluxes were found for themore »
- Authors:
-
- Oregon State Univ., Corvallis, OR (United States)
- Max Planck Institute for Biogeochemistry, Jena (Germany)
- Univ. of California, Davis, CA (United States)
- Publication Date:
- Research Org.:
- Oregon State Univ., Corvallis, OR (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1326808
- Grant/Contract Number:
- SC0012194; NOAA17 OAR-CPO-2012-2003041; 2014-67003-22065; 2014-35100-22066
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Earth Interactions
- Additional Journal Information:
- Journal Name: Earth Interactions; Journal ID: ISSN 1087-3562
- Publisher:
- American Meteorological Association
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; 97 MATHEMATICS AND COMPUTING; land surface-atmosphere exchange of carbon dioxide; community land model; Bayesian inversion; data assimilation
Citation Formats
Schmidt, Andres, Law, Beverly E., Göckede, Mathias, Hanson, Chad, Yang, Zhenlin, and Conley, Stephen. Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon. United States: N. p., 2016.
Web. doi:10.1175/EI-D-16-0011.1.
Schmidt, Andres, Law, Beverly E., Göckede, Mathias, Hanson, Chad, Yang, Zhenlin, & Conley, Stephen. Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon. United States. https://doi.org/10.1175/EI-D-16-0011.1
Schmidt, Andres, Law, Beverly E., Göckede, Mathias, Hanson, Chad, Yang, Zhenlin, and Conley, Stephen. Thu .
"Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon". United States. https://doi.org/10.1175/EI-D-16-0011.1. https://www.osti.gov/servlets/purl/1326808.
@article{osti_1326808,
title = {Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon},
author = {Schmidt, Andres and Law, Beverly E. and Göckede, Mathias and Hanson, Chad and Yang, Zhenlin and Conley, Stephen},
abstractNote = {Here, the vast forests and natural areas of the Pacific Northwest comprise one of the most productive ecosystems in the northern hemisphere. The heterogeneous landscape of Oregon poses a particular challenge to ecosystem models. We present a framework using a scaling factor Bayesian inversion to improve the modeled atmosphere-biosphere exchange of carbon dioxide. Observations from 5 CO/CO2 towers, eddy covariance towers, and airborne campaigns were used to constrain the Community Land Model CLM4.5 simulated terrestrial CO2 exchange at a high spatial and temporal resolution (1/24°, 3-hourly). To balance aggregation errors and the degrees of freedom in the inverse modeling system, we applied an unsupervised clustering approach for the spatial structuring of our model domain. Data from flight campaigns were used to quantify the uncertainty introduced by the Lagrangian particle dispersion model that was applied for the inversions. The average annual statewide net ecosystem productivity (NEP) was increased by 32% to 29.7 TgC per year by assimilating the tropospheric mixing ratio data. The associated uncertainty was decreased by 28.4% to 29%, on average over the entire Oregon model domain with the lowest uncertainties of 11% in western Oregon. The largest differences between posterior and prior CO2 fluxes were found for the Coast Range ecoregion of Oregon that also exhibits the highest availability of atmospheric observations and associated footprints. In this area, covered by highly productive Douglas-fir forest, the differences between the prior and posterior estimate of NEP averaged 3.84 TgC per year during the study period from 2012 through 2014.},
doi = {10.1175/EI-D-16-0011.1},
journal = {Earth Interactions},
number = ,
volume = ,
place = {United States},
year = {Thu Sep 15 00:00:00 EDT 2016},
month = {Thu Sep 15 00:00:00 EDT 2016}
}
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