Unsupervised classification of vertical profiles of dual polarization radar variables

Tiira, Jussi; Moisseev, Dmitri

doi:https://doi.org/10.5194/amt-13-1227-2020

Articles | Volume 13, issue 3

https://doi.org/10.5194/amt-13-1227-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-13-1227-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 3

Research article

|

13 Mar 2020

Research article |

| 13 Mar 2020

Unsupervised classification of vertical profiles of dual polarization radar variables

Jussi Tiira and Dmitri Moisseev

Supplement

https://doi.org/10.5194/amt-13-1227-2020-supplement

Data sets

The Finnish Meteorological Institute’s open data Finnish Meteorological Institute https://en.ilmatieteenlaitos.fi/open-data

Short summary

Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.