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International Symposium on Data Assimilation 2012

Data Assimilation and Inverse Problems

Our 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:

  • numerical weather prediction (NWP),
  • cognitive neuroscience / neural field theory (NFT),
  • inverse scattering problems / remote sensing.

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.

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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

For more news see IP News and IP Events!

My Christian Blog

Thinking 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

Group

My group consists of about 25 researchers on data assimilation and inverse problems in Frankfurt/Offenbach, Reading (UK) and Göttingen, see group.

COST Action 1303 “TOPROF” Website
Journal Mathematical Inverse Problems

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.

start.txt · Last modified: 2014/03/04 07:45 by potthast