Stochastic reconstruction of precipitation fields using commercial microwave link information

26 Jun 2019, 13:50
large seminar room (KIT Campus Alpin)

large seminar room

KIT Campus Alpin

Kreuzeckbahnstraße 19 82467 Garmisch-Partenkirchen
Oral Specific HyMet CML research topics (presentations on Day2, posters on Day1) Specific research topics


Dr. Barbara Haese (University of Augsburg, Institute of Geography, Augsburg, Germany )


The difficulty when using path-averaged rain rates derived from commercial microwave links (CMLs) is, that they give non-linear constrains for the precipitation field. To address this challenge, we apply Random Mixing to stochastically simulate precipitation fields. We generate precipitation fields as linear combinations of unconditional spatial random fields, where the spatial dependence structure is described by copulas. The weights of the linear combination are optimized in such a way, that the observations and their spatial structure are reproduced. Random Mixing allows to simulate precipitation field ensembles of any size, where each ensemble member is in concordance with the underlying observations.

Primary author

Dr. Barbara Haese (University of Augsburg, Institute of Geography, Augsburg, Germany )


Dr. Sebastian Hörning (School of Earth and Environmental Sciences, University of Queensland, Brisbane, Australia) Dr. Christian Chwala (KIT (IMK-IFU) / Uni Augsburg) Maximilian Graf Prof. András Bárdossy (Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Stuttgart, Germany ) Prof. Harald Kunstmann (University of Augsburg, Institute of Geography, Augsburg, Germany and Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany )

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