Articles | Volume 10, issue 4
https://doi.org/10.5194/amt-10-1335-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-10-1335-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera
Christophe Praz
Environmental Remote Sensing Laboratory (LTE), École polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Yves-Alain Roulet
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Environmental Remote Sensing Laboratory (LTE), École polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Latest update: 20 Nov 2024
Short summary
The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling snowflakes and ice crystals. A method is proposed to automatically classify these pictures into six classes of snowflakes as well to estimate the degree of riming and to detect whether or not the particles are melting. Multinomial logistic regression is used with a manually classified
reference set. The evaluation demonstrates the good and reliable performance of the proposed technique.
The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling...