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Aerosol Data Assimilation

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Atmospheric Aerosols

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Abstract

Data assimilation aims to combine information from observations describing the real world, some prior information from a model, and in some cases the physical and chemical laws governing the evolution of the system in consideration. This chapter provides a short description of the mathematical principles of data assimilation from the best linear unbiased estimator to variational techniques and Kalman filters. It introduces the vocabulary (background, control vector, analysis) and highlights the importance of error covariance matrices in data assimilation. Finally, the chapter reviews past applications of data assimilation for atmospheric aerosols.

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Authors and Affiliations

  1. Laboratoire de Météorologie Dynamique, Centre National de la Recherche Scientifique, Tour 45–55, 3e étage, Case courrier 99 Université Pierre et Marie Curie 4 place Jussieu, 75252, Cedex 05, Paris, France

    Olivier Boucher

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  1. Olivier Boucher
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Boucher, O. (2015). Aerosol Data Assimilation. In: Atmospheric Aerosols. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9649-1_7

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