Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4565-2021
https://doi.org/10.5194/amt-14-4565-2021
Research article
 | 
21 Jun 2021
Research article |  | 21 Jun 2021

Evaluation of micro rain radar-based precipitation classification algorithms to discriminate between stratiform and convective precipitation

Andreas Foth, Janek Zimmer, Felix Lauermann, and Heike Kalesse-Los

Data sets

JOYCE-CF Cloud and Precipitation Exploration Laboratory (CPEX-LAB) http://cpex-lab.de/cpex-lab/EN/Home/JOYCE-CF/JOYCE-CF_node.html

Model code and software

TensorFlow (Version v2.5.0) TensorFlow Developers https://doi.org/10.5281/zenodo.4758419

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Short summary
In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.