Articles | Volume 31, issue 3
https://doi.org/10.5194/npg-31-335-2024
https://doi.org/10.5194/npg-31-335-2024
Research article
 | 
12 Jul 2024
Research article |  | 12 Jul 2024

Bridging classical data assimilation and optimal transport: the 3D-Var case

Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, and Yelva Roustan

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Cited articles

Amodei, M. and Stein, J.: Deterministic and fuzzy verification methods for a hierarchy of numerical models, Meteorol. Appl., 16, 191–203, https://doi.org/10.1002/met.101, 2009. a, b
Asch, M., Bocquet, M., and Nodet, M.: Data Assimilation: Methods, Algorithms, and Applications, Fundamentals of Algorithms, SIAM, Philadelphia, ISBN 978-1-611974-53-9, https://doi.org/10.1137/1.9781611974546, 2016. a, b
Bocquet, M.: Towards optimal choices of control space representation for geophysical data assimilation, Mon. Weather Rev., 137, 2331–2348, https://doi.org/10.1175/2009MWR2789.1, 2009. a
Bocquet, M., Wu, L., and Chevallier, F.: Bayesian design of control space for optimal assimilation of observations. I: Consistent multiscale formalism, Q. J. Roy. Meteor. Soc., 137, 1340–1356, https://doi.org/10.1002/qj.837, 2011. a
Boyd, S. P. and Vandenberghe, L.: Convex optimization, Cambridge university press, ISBN 978-0521833783, 2004. a, b
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Short summary
A novel approach, optimal transport data assimilation (OTDA), is introduced to merge DA and OT concepts. By leveraging OT's displacement interpolation in space, it minimises mislocation errors within DA applied to physical fields, such as water vapour, hydrometeors, and chemical species. Its richness and flexibility are showcased through one- and two-dimensional illustrations.
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