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International |
Roland Potthast, Director and Professor, Division on Data Assimilation and Inverse Problems
German Meteorological Service DWD (Federal Ministery of Transport, Building and Urban Development, Germany)
and University of Reading (United Kingdom)
Data Assimilation and Inverse ProblemsOur Division for Data Assimilation (FE12) of the German Weather Service (DWD) is working on data assimilation for numerical weather prediction (NWP). The research of our group at the University of Reading, UK, is concerned with inverse problems and data assimilation in three areas:
These are extremely exciting areas scientifically and very important for society, for example for air traffic, severe weather warnings and national energy supply, in medicine by medical imaging and for many industrial and environmental questions. Institutions Prof. Dr. Roland Potthast Deutscher Wetterdienst (DWD) Frankfurter Strasse 135 63067 Offenbach, Germany Roland.Potthast@dwd.de Professor for Applied Mathematics Department of Mathematics and Statistics, Whiteknights, PO Box 220, Reading RG6 6AX, UK r.w.e.potthast@reading.ac.uk |
News
My Christian BlogThinking about faith and life has always been a passion for me. I have become a Christian and have started to explore the world as someone who follows Jesus - that has turned out to be quite an adventure and highly exciting. In my daily blog I explore thoughts and arguments about faith, and monitor how faith works on a daily basis: Jesus Network GroupMy group consists of about 25 researchers on data assimilation and inverse problems in Frankfurt/Offenbach, Reading (UK) and Göttingen, see group. |
Publications
Recent publications can be found on publications. Working in an operational center, our focus is to develop state-of-the-art inversion methods which can be run in a reliable way on a supercomputer in near real-time. It includes codes on scattering of waves, propagation of light and radiation, tomography, large-scale optimization and uncertainty quanitfication, ensemble and particle methods.
However, the development of insight into the scientific problems we need to solve is an indispensible ingredient of our daily work. Part of this insight is based on mathematical analysis and the testing of computational methods for purpuse-built small-scale demonstration systems.


