Detecting rainfall events in CML attenuation time series using convolutional neural networks

26 Jun 2019, 10:50
20m
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

Speaker

julius polz (KIT/IMK-IFU)

Description

CML data might exhibit high signal fluctuations, even during dry periods. At the same time the number of newly available CMLs is rising fast. It is necessary to develop a technique to recognise the pattern of rainfall in CML signal levels, that is (1) generalizing to previously unknown sensors, (2) stable in time and (3) showing better performance than established methods. We therefore introduce convolutional neural networks to the task of wet/dry classification and test them on data from a German-wide CML network.

Primary author

julius polz (KIT/IMK-IFU)

Co-authors

Christian Chwala (KIT (IMK-IFU) / Uni Augsburg) Maximilian Graf Harald Kunstmann

Presentation Materials

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