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Estimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested

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  • Soetaert, Karline
  • Gregoire, Marilaure

Abstract

Oxygen (O2), nitrate (NO3), dissolved inorganic carbon (DIC) or pCO2, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying time-scales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O2, NO3, DIC, pCO2, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O2, NO3, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings.

Suggested Citation

  • Soetaert, Karline & Gregoire, Marilaure, 2011. "Estimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested," Ecological Modelling, Elsevier, vol. 222(12), pages 1929-1942.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:12:p:1929-1942
    DOI: 10.1016/j.ecolmodel.2011.03.012
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    1. Mo, Xingguo & Chen, Jing M. & Ju, Weimin & Black, T. Andrew, 2008. "Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 217(1), pages 157-173.
    2. Ciavatta, Stefano & Pastres, Roberto & Badetti, Christian & Ferrari, Giorgio & Beck, M.B., 2008. "Estimation of phytoplanktonic production and system respiration from data collected by a real-time monitoring network in the Lagoon of Venice," Ecological Modelling, Elsevier, vol. 212(1), pages 28-36.
    3. Chen, M. & Liu, S. & Tieszen, L.L. & Hollinger, D.Y., 2008. "An improved state-parameter analysis of ecosystem models using data assimilation," Ecological Modelling, Elsevier, vol. 219(3), pages 317-326.
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