Abstract
Representation and analysis of uncertainties (errors) is at the core of any data assimilation system. The main aim of data assimilation is to reduce uncertainties of model predictions using observations. Under Gaussian error statistics for both parts of the assimilation system (data and forecast), and by making the assumption of zero bias, optimal estimation schemes can be derived.
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Acknowledgments
A large portion of this work has been funded by NASA’s UARS grant UARS “Towards Interactive Three-dimensional chemical data assimilation”.
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Khattatov, B., Yudin, V. (2010). Representation and Modelling of Uncertainties in Chemistry and Transport Models. In: Lahoz, W., Khattatov, B., Menard, R. (eds) Data Assimilation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74703-1_17
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DOI: https://doi.org/10.1007/978-3-540-74703-1_17
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