Articles | Volume 14, issue 5
Geosci. Model Dev., 14, 2635–2657, 2021

Special issue: Model infrastructure integration and interoperability (MI3)

Geosci. Model Dev., 14, 2635–2657, 2021

Development and technical paper 12 May 2021

Development and technical paper | 12 May 2021

Developing a common, flexible and efficient framework for weakly coupled ensemble data assimilation based on C-Coupler2.0

Chao Sun et al.

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Cited articles

Andersson, E., Haseler, J., Unden, P., Courtier, P., Kelly, G., Vasiljevic, D., and Thepaut, J.: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). III: Experimental results, Q. J. Roy. Meteor. Soc., 124, 1831–1860, 1998. 
Anderson, J. and Collins, N.: Scalable implementations of ensemble filter algorithms for data assimilation, J. Atmos. Ocean Technol., 24, 1452–1463, 2007. 
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and Arellano, A.: The Data Assimilation Research Testbed: A Community Facility, B. Am. Meteorol. Soc., 90, 1283–1296, 2009. 
Bishop, C. and Hodyss, D.: Adaptive ensemble covariance localization in ensemble 4D-VAR state estimation, Mon. Weather Rev., 139, 1241–1255, 2011. 
Blumberg, A. and Mellor, G.: A description of a three-dimensional coastal ocean circulation model, in: Three-Dimensional Coastal Ocean Models, edited by: Heaps, N. S., pp. 1–16, AGU, Washington, DC, 1987. 
Short summary
Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.