Welcome to the collaborative Research Center TRR 181 ”Energy transfers in Atmosphere and Ocean“

The seamless integration of large data sets into sophisticated computational models provides one of the central research challenges for the mathematical sciences in the 21st century. When the computational model is based on evolutionary equations and the data set is time-ordered, the process of combining models and data is called data assimilation. The assimilation of data into computational models serves a wide spectrum of purposes ranging from model calibration and model comparison all the way to the validation of novel model design principles.

The field of data assimilation has been largely driven by practitioners from meteorology, hydrology and oil reservoir exploration; but a theoretical foundation of the field is largely missing. Furthermore, many new applications are emerging from, for example, biology, medicine, and the neurosciences, which require novel data assimilation techniques. The goal of the proposed CRC is therefore twofold: First, to develop principled methodologies for data assimilation and, second, to demonstrate computational effectiveness and robustness through their implementation for established and novel data assimilation application areas.

While most current data assimilation algorithms are derived and analyzed from a Bayesian perspective, the CRC will view data assimilation from a general statistical inference perspective. Major challenges arise from the high-dimensionality of the inference problems, nonlinearity of the models and/or non-Gaussian statistics. Targeted application areas include the geoscience as well as emerging fields for data assimilation such as biophysics and cognitive neuroscience.


Prof. Dr. Sebastian Reich, University of Potsdam, Department of Mathematics

Managing Director

Lydia Stolpmann, University of Potsdam, Department of Mathematics

Funded by


Coordinated by


Upcoming Events

Women Networking Lunch

Campus Golm, building 29, 2.5812:00 - 13:00

Our SFB Women Networking Lunch with Claire Vernade (DeepMind) provides a chance to talk about career, chances and how to overcome hurdles as female in…

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Latest Publications

  • Kemeth, F., Alonso, S., Echebarria, B., Moldenhawer, T., Beta, C. and Kevrekidis I. (2022). Black and Gray Box Learning of Amplitude Equations: Application to Phase Field Systems. arXiv: 2207.03954

  • König, J. and Freitag, M. (2022). Time-limited Balanced Truncation for Data Assimilation Problems. arXiv 2212.07719.

  • Riedel, C., Geßner, H., Seegebrecht, A., Ayon, S. I., Chowdhury, S. H., Engbert, R. & Lucke, U., (2022). Including Data Management in Research Culture Increases the Reproducibility of Scientific Results. In: Demmler, D., Krupka, D. & Federrath, H. (Hrsg.), INFORMATIK 2022. Gesellschaft für Informatik, Bonn. (S. 1341-1352). DOI: 10.18420/inf2022_114

Participating Institutions

imageHU BerlinGFZ PotsdamTU BerlinWeierstraß-Institut Berlin