Articles | Volume 13, issue 9
Development and technical paper
16 Sep 2020
Development and technical paper |  | 16 Sep 2020

Efficient ensemble data assimilation for coupled models with the Parallel Data Assimilation Framework: example of AWI-CM (AWI-CM-PDAF 1.0)

Lars Nerger, Qi Tang, and Longjiang Mu

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Cited articles

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. a
Androsov, A., Nerger, L., Schnur, R., Schröter, J., Albertella, A., Rummel, R., Savcenko, R., Bosch, W., Skachko, S., and Danilov, S.: On the assimilation of absolute geodetic dynamics topography in a global ocean model: Impact on the deep ocean state, J. Geodesy, 93, 141–157, 2019. a, b
Browne, P. A. and Wilson, S.: A simple method for integrating a complex model into an ensemble data assimilation system using MPI, Environ. Modell. Softw., 68, 122–128, 2015. a, b
Browne, P. A., de Rosnay, P., Zuo, H., Bennett, A., and Dawson, A.: Weakly coupled ocean–atmosphere data assimilation in the ECMWF NWP system, Remote Sensing, 11, 234,, 2019. a
Burgers, G., van Leeuwen, P. J., and Evensen, G.: On the Analysis Scheme in the Ensemble Kalman Filter, Mon. Weather Rev., 126, 1719–1724, 1998. a
Short summary
Data assimilation combines observations with numerical models to get an improved estimate of the model state. This work discusses the technical aspects of how a coupled model that simulates the ocean and the atmosphere can be augmented by data assimilation functionality provided in generic form by the open-source software PDAF (Parallel Data Assimilation Framework). A very efficient program is obtained that can be executed on high-performance computers.