Articles | Volume 15, issue 2
Atmos. Meas. Tech., 15, 365–381, 2022
https://doi.org/10.5194/amt-15-365-2022

Special issue: Fusion of radar polarimetry and numerical atmospheric modelling...

Atmos. Meas. Tech., 15, 365–381, 2022
https://doi.org/10.5194/amt-15-365-2022
Research article
24 Jan 2022
Research article | 24 Jan 2022

Using artificial neural networks to predict riming from Doppler cloud radar observations

Teresa Vogl et al.

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Cited articles

Atmospheric Radiation Measurement (ARM) user facility: Ka ARM Zenith Radar (KAZRSPECCMASKMDCOPOL), 2014-02-21 to 2014-02-22, ARM Mobile Facility (TMP) U. of Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), compiled by: Lindenmaier, I., Bharadwaj, N., Johnson, K., Nelson, D., Matthews, A., Wendler, T., and Castro, V., ARM Data Center, https://doi.org/10.5439/1095603, 2014a. a
Atmospheric Radiation Measurement (ARM) user facility: Microwave Radiometer (MWRLOS), 2014-02-21 to 2014-02-22, ARM Mobile Facility (TMP) U. of Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), compiled by: Cadeddu, M., ARM Data Center., https://doi.org/10.5439/1046211, 2014b. a
Atmospheric Radiation Measurement (ARM) user facility: Balloon-Borne Sounding System (SONDEWNPN), 2014-02-01 to 2014-03-20, ARM Mobile Facility (TMP) U. of Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), compiled by: Keeler, E., Coulter, R., and Kyrouac, J., ARM Data Center, https://doi.org/10.5439/1021460, 2014c. a
Barrett, A. I., Westbrook, C. D., Nicol, J. C., and Stein, T. H. M.: Rapid ice aggregation process revealed through triple-wavelength Doppler spectrum radar analysis, Atmos. Chem. Phys., 19, 5753–5769, https://doi.org/10.5194/acp-19-5753-2019, 2019. a
Bühl, J., Seifert, P., Myagkov, A., and Ansmann, A.: Measuring ice- and liquid-water properties in mixed-phase cloud layers at the Leipzig Cloudnet station, Atmos. Chem. Phys., 16, 10609–10620, https://doi.org/10.5194/acp-16-10609-2016, 2016. a
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We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.