External Doctoral Candidate - Nora Schenk, M. Sc.

Research interests

  • Particle filter methods for high-dimensional spaces (e.g. for application in Numerical Weather Prediction)
  • In particular the application of localized particle filters in data assimilation with respect to the global ICON model as well as the regional ICON-LAM model
  • Ensemble filter data assimilation methods with respect to different dynamical systems, e.g. Lorenz 1963 or Lorenz 1996
  • Stability of Bayesian data assimilation methods


Submitted papers

  • A. Walter, N. Schenk, P.-J. van Leeuwen, R. Potthast, Particle Filtering and Gaussian Mixtures - On a Localized Mixture Coefficients Particle Filter (LMCPF) for global NWP

Publications in peer-reviewed journals



Awards and Fellowships

  • Award for the best master's degree sponsored by Alte Leipziger Lebensversicherung a.G. (2020)
  • DAAD-PROMOS-Scholarship for a semester abroad at the University of Toronto, Canada (2018)
  • Germany Scholarship at Goethe University Frankfurt am Main (October 2015 - September 2017)