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.
Speaker
Prof. Dr. Sebastian Reich, University of Potsdam, Department of Mathematics
Managing Director
Dr. Liv Heinecke, University of Potsdam, Department of Mathematics
News
Covid-19 study published!

The study our PIs Ralf Engbert and Sebastian Reich on Sequential Data Assimilation of the Stochastic SEIR Epidemic Model for Regional COVID-19… more ›
Mini Seminar Series on "Non-Gaussian large scale Bayesian inversion"

Our PI Jana de Wiljes organised a Mini Seminiar Series together with the Lappeenranta-Lahti University of Technology (LUT), which will take place on… more ›
Alexandra Carpentier receives von Kaven-Ehrenpreis 2020

Congratulations! We are very proud that our PI Alexandra Carpentier received the von Kaven Ehrenpreis 2020 awarded by the DFG for her work on the… more ›
Upcoming Events
Karsten Tabelow
Karsten Tabelow, WIAS Berlin online10:15 - 11:15
tba
invited by Ulrike Lucke
***Due to the current pandemic this colloquium will be conducted online. We invite you to join and spread the news. We…
more ›Almut Veraart
Almut Veraart, Imperial College London online10:15 - 11:15
tba
invited by Sebastian Reich
***Due to the current pandemic this colloquium will be conducted online. We invite you to join and spread the news.…
more ›Tatsuo Shibata
Tatsuo Shibata, RIKEN Center for Biosystems Dynamics Research, Japan online10:15 - 11:15
tba
invited by Carsten Beta
***Due to the current pandemic this colloquium will be conducted online. We invite you to join and spread the news. We…
more ›Latest Publications
Ba, Y., de Wiljes, J., Oliver, D.S., and Reich, S. (2021). Randomized maximum likelihood based posterior sampling. arXiv:2101.03612
Lange, T. (2020): Derivation of Ensemble Kalman-Bucy Filters with unbounded nonlinear coefficients. arXiv 2012.07572
Schwetlick, L., Rothkegel, L.O.M., Trukenbrod, H.A., Engbert, R. (2020). Modeling the effects of perisaccadic attention on gaze statistics during scene viewing. Communications Biology, 3, 727. doi: 10.1038/s42003-020-01429-8