Articles | Volume 13, issue 12
Atmos. Meas. Tech., 13, 6645–6656, 2020
Atmos. Meas. Tech., 13, 6645–6656, 2020

Research article 09 Dec 2020

Research article | 09 Dec 2020

Detecting the melting layer with a micro rain radar using a neural network approach

Maren Brast and Piet Markmann

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Cited articles

Austin, P. M. and Bemis, A. C.: A quantitative study of the “bright band” in radar precipitation echoes, J. Meteorol., 7, 145–151,<0145:AQSOTB>2.0.CO;2, 1950. a
Battan, L. J.: Radar meteorology, University of Chicago Press, Chicago, Illinois, USA, 161 pp., 1959. a
Byers, H. R. and Coons, R. D.: The “bright line” in radar cloud echoes and its probable explanation, J. Meteorol., 4, 75–81,<0078:TLIRCE>2.0.CO;2, 1947. a
Cha, J.-W., Chang, K.-H., Yum, S. S., and Choi, Y.-J.: Comparison of the bright band characteristics measured by Micro Rain Radar (MRR) at a mountain and a coastal site in South Korea, Adv. Atmos. Sci., 26, 211–221,, 2009. a, b, c
Fabry, F. and Zawadzki, I.: Long-term radar observations of the melting layer of precipitation and their interpretation, J. Atmos. Sci., 52, 838–851,<0838:LTROOT>2.0.CO;2, 1995. a, b, c
Short summary
An artificial neural network was trained to identify melting layers in micro rain radar data. It was successfully tested on simple and complex cases, which are difficult to identify using classical approaches, and also provided information on the melting layer width.