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    The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO2 surface fluxes over Australia using a variational assimilation scheme

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    Author
    Villalobos, Y; Rayner, P; Thomas, S; Silver, J
    Date
    2020-07-21
    Source Title
    Atmospheric Chemistry and Physics
    Publisher
    COPERNICUS GESELLSCHAFT MBH
    University of Melbourne Author/s
    Silver, Jeremy; Rayner, Peter
    Affiliation
    School of Earth Sciences
    School of Mathematics and Statistics
    Metadata
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    Document Type
    Journal Article
    Citations
    Villalobos, Y., Rayner, P., Thomas, S. & Silver, J. (2020). The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO2 surface fluxes over Australia using a variational assimilation scheme. ATMOSPHERIC CHEMISTRY AND PHYSICS, 20 (14), pp.8473-8500. https://doi.org/10.5194/acp-20-8473-2020.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/252131
    DOI
    10.5194/acp-20-8473-2020
    Abstract
    <jats:p>Abstract. This paper addresses the question of how much uncertainties in CO2 fluxes over Australia can be reduced by assimilation of total-column carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite instrument. We apply a four-dimensional variational data assimilation system, based around the Community Multiscale Air Quality (CMAQ) transport-dispersion model. We ran a series of observing system simulation experiments to estimate posterior error statistics of optimized monthly-mean CO2 fluxes in Australia. Our assimilations were run with a horizontal grid resolution of 81 km using OCO-2 data for 2015. Based on four representative months, we find that the integrated flux uncertainty for Australia is reduced from 0.52 to 0.13 Pg C yr−1. Uncertainty reductions of up to 90 % were found at grid-point resolution over productive ecosystems. Our sensitivity experiments show that the choice of the correlation structure in the prior error covariance plays a large role in distributing information from the observations. We also found that biases in the observations would significantly impact the inverted fluxes and could contaminate the final results of the inversion. Biases in prior fluxes are generally removed by the inversion system. Biases in the boundary conditions have a significant impact on retrieved fluxes, but this can be mitigated by including boundary conditions in our retrieved parameters. In general, results from our idealized experiments suggest that flux inversions at this unusually fine scale will yield useful information on the carbon cycle at continental and finer scales. </jats:p>

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