Articles | Volume 19, issue 22
Atmos. Chem. Phys., 19, 13911–13932, 2019
https://doi.org/10.5194/acp-19-13911-2019

Special issue: Data assimilation in carbon/biogeochemical cycles: consistent...

Atmos. Chem. Phys., 19, 13911–13932, 2019
https://doi.org/10.5194/acp-19-13911-2019
Review article
19 Nov 2019
Review article | 19 Nov 2019

Fundamentals of data assimilation applied to biogeochemistry

Peter J. Rayner et al.

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Cited articles

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Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P., Denning, A. S., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fung, I. Y., Heimann, M., John, J., Maki, T., Maksyutov, S., Masarie, K., Prather, M., Pak, B., Taguchi, S., and Zhu, Z.: TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003, Global Biogeochem. Cy., 20, GB1002, https://doi.org/10.1029/2004GB002439, 2006. a
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Short summary
This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems. The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system. The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism.
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