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International Symposium on Data Assimilation 2016 in Reading, UK - New Book “Inverse Modeling” … now available!

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.


  • Academic Visitor at the Chinese University of Hong Kong, Oct 10-20, 2016 and Oct 22-29, 2016, visitors list
  • Oberwolfach meeting Mathematical and Algorithmic Aspects of Data Assimilation in the Geosciences, Oct 2-7, 2016, Talk on Hybrid Ensemble and Particle Filters with Variational Methods for Data Assimilation
  • Keynote Lecture at the EUMETSAT Conference “30 years Eumetsat” on Future Perspectives of Numerical Weather Prediction, Darmstadt Sept 2016
  • Keynote Talk at the Workshop on Data Assimilation in Terrestrial Systems, Sept 2016 in Bonn
  • Lecturer on the EMS Workshop on Basic Data Assimilation Concepts, Annual Meeting of the European Meteorological Society, Triste Sept 11, 2016
  • Invited Talk at “Mathematics in Imaging” Workshop at the Conference of the Optical Society of America, Heidelberg July 25-30, 2016. Programm PDF
  • New book: Inverse Modeling by Nakamura and Potthast now available Inverse Modeling at IOP
  • Invited talk at CREST International Symposium on Big Data Application, Tokyo, Japan, March 4-5: Web
  • workshop High-Dimensional Statistical Models & Big Data: Methodology & Applications held at the British Library, London on 10 to 12 February 2016 WebpageProgramme
  • SINATRA Annual Science Meeting ECMWF Reading Jan 13-15, 2016 Weblink
  • Seminar Talk at University of Grenoble: Laboratoire Jean Kuntzmann, see Seminar Announcement
  • Seminar Talk at FU Berlin: Announcement
  • Workshop: Stochastic Modelling in GFD, data assimilation, and non-equilibrium phenomena, see Workshop on Web
  • For 2015 Roland Potthast received the Pichorides Distinguished Lectureship Award by the Department of Mathematics and Applied Mathematics of the University of Crete, Greece. Pichorides Award see also Award List Uni Crete Departmental News
  • Book “Neural Fields” including simulation and inversion in cognitive neuroscience now available Book at Springer. Since its online publication on May 12, 2014, there has been a total of 4,409 chapter downloads (June 10, 2015) for the eBook on SpringerLink.

For more news see IP News and IP Events!


Prof. Dr. Roland Potthast
Deutscher Wetterdienst (DWD)
Frankfurter Strasse 135
63067 Offenbach, Germany

Professor for Applied Mathematics
Department of Mathematics and Statistics,
Whiteknights, PO Box 220,
Reading RG6 6AX, UK


My group consists of about 30 researchers on data assimilation and inverse problems in Frankfurt/Offenbach and Reading (UK), see group.


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


Recent publications can be found on publications. A book Inverse Modeling by Nakamura and Potthast with an introduction into data assimilation and inverse problems has recently appeared at IOP.

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.

COST Action 1303 “TOPROF” Website; Journal Mathematical Inverse Problems

start.txt · Last modified: 2016/10/12 08:56 by potthast