Articles | Volume 25, issue 3
https://doi.org/10.5194/npg-25-713-2018
https://doi.org/10.5194/npg-25-713-2018
Research article
 | 
19 Sep 2018
Research article |  | 19 Sep 2018

Nonlinear effects in 4D-Var

Massimo Bonavita, Peter Lean, and Elias Holm

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (03 Aug 2018)  Author's response
ED: Publish subject to minor revisions (review by editor) (08 Aug 2018) by Michael Ghil
AR by Lorena Grabowski on behalf of the Authors (20 Aug 2018)  Author's response
ED: Publish as is (21 Aug 2018) by Michael Ghil
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Short summary
This paper deals with the effects of nonlinearity in a state-of-the-art atmospheric global data assimilation system. It is shown that these effects have become increasingly important over the years due to increased model resolution and use of nonlinear observations. The ability to deal with nonlinearities has thus become a crucial asset of data assimilation algorithms. At ECMWF this is done in a perturbative fashion. Advantages and limitations of this technique are discussed.