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

Dr. Liv Heinecke, University of Potsdam, Department of Mathematics

Funded by


Coordinated by


Upcoming Events

Spring School 2022

The annual SFB Spring School 2022 will take place from the 21st (arrival on the 20th) to the 25nd of March 2022 at the Hotel Döllnsee-Schorfheide.


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Latest Publications

  • Pathiraja, S., van Leeuwen, P. (2021): Multiplicative non-Gaussian model error estimation in data assimilation. arXiv 1807.09621

  • Ruchi, S., Dubinkina, S. and de Wiljes, J. (2021). Fast hybrid tempered ensemble transform filter for Bayesian elliptical problems via Sinkhorn approximation. Nonlinear Processes in Geophysics, 28(1): 23-41 [1]

  • Geßner, H. (2021). Transparently Safeguarding Good Research Data Management with the Lean Process Assessment Model. In: E-Science-Tage 2021: Share Your Research Data. Heidelberg. DOI: 10.11588/heidok.00029719

Participating Institutions

imageHU BerlinGFZ PotsdamTU BerlinWeierstraß-Institut Berlin