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.
Research article
| 
06 Apr 2017
Research article |
| 06 Apr 2017
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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Cited
52 citations as recorded by crossref.
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- Microphysics of Snowfall Over Coastal East Antarctica Simulated by Polar WRF and Observed by Radar É. Vignon et al. 10.1029/2019JD031028
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- Meteorological Electromagnetics: Optical and Radar Measurements, Modeling, and Characterization of Snowflakes and Snow B. Notaros 10.1109/MAP.2021.3054298
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- The Geometry of Rimed Aggregate Snowflakes: A Modeling Study A. Seifert et al. 10.1029/2018MS001519
- Hydrometeor Identification Using Multiple-Frequency Microwave Links: A Numerical Simulation K. Pu et al. 10.3390/rs12132158
- Melting of fractal snowflakes: Experiments and modeling K. Köbschall et al. 10.1016/j.ijheatmasstransfer.2023.124254
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52 citations as recorded by crossref.
- Objective classification for solid hydrometeor particles using deep learning A. Yoshimura et al. 10.1186/s40645-024-00667-2
- A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations S. Cooper et al. 10.5194/amt-10-2557-2017
- Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach A. Billault-Roux et al. 10.5194/amt-16-911-2023
- RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland D. Wolfensberger et al. 10.5194/amt-14-3169-2021
- Microphysical properties of three types of snow clouds: implication for satellite snowfall retrievals H. Jeoung et al. 10.5194/acp-20-14491-2020
- Arctic observations and numerical simulations of surface wind effects on Multi-Angle Snowflake Camera measurements K. Fitch et al. 10.5194/amt-14-1127-2021
- Relating storm-snow avalanche instabilities to data collected from the Differential Emissivity Imaging Disdrometer (DEID) T. Morrison et al. 10.1016/j.coldregions.2023.103839
- Microphysics of Snowfall Over Coastal East Antarctica Simulated by Polar WRF and Observed by Radar É. Vignon et al. 10.1029/2019JD031028
- Method for Classification of Snowflakes Based on Images by a Multi-Angle Snowflake Camera Using Convolutional Neural Networks A. Hicks & B. Notaroš 10.1175/JTECH-D-19-0055.1
- Comparative measurement of rainfall with a precipitation micro-physical characteristics sensor, a 2D video disdrometer, an OTT PARSIVEL disdrometer, and a rain gauge X. Liu et al. 10.1016/j.atmosres.2019.06.020
- Meteorological Electromagnetics: Optical and Radar Measurements, Modeling, and Characterization of Snowflakes and Snow B. Notaros 10.1109/MAP.2021.3054298
- Precipitation at Dumont d'Urville, Adélie Land, East Antarctica: the APRES3 field campaigns dataset C. Genthon et al. 10.5194/essd-10-1605-2018
- The behavior of high-CAPE (convective available potential energy) summer convection in large-domain large-eddy simulations with ICON H. Rybka et al. 10.5194/acp-21-4285-2021
- Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica J. Grazioli et al. 10.5194/tc-11-1797-2017
- McSnow: A Monte‐Carlo Particle Model for Riming and Aggregation of Ice Particles in a Multidimensional Microphysical Phase Space S. Brdar & A. Seifert 10.1002/2017MS001167
- MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall J. Grazioli et al. 10.1038/s41597-022-01269-7
- Microphysics and dynamics of snowfall associated with a warm conveyor belt over Korea J. Gehring et al. 10.5194/acp-20-7373-2020
- Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS) H. Thompson et al. 10.5194/essd-15-5785-2023
- Variations in Snow Crystal Riming and ZDR: A Case Analysis P. Kennedy et al. 10.1175/JAMC-D-17-0068.1
- Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera M. Schaer et al. 10.5194/tc-14-367-2020
- Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign S. Park et al. 10.5194/gmd-17-7199-2024
- Identification of snowfall microphysical processes from Eulerian vertical gradients of polarimetric radar variables N. Planat et al. 10.5194/amt-14-4543-2021
- Unsupervised classification of snowflake images using a generative adversarial network and <i>K</i>-medoids classification J. Leinonen & A. Berne 10.5194/amt-13-2949-2020
- Snowfall in Northern Finland derives mostly from ice clouds C. Mignani et al. 10.5194/acp-22-13551-2022
- Quantifying riming from airborne data during the HALO-(AC)3campaign N. Maherndl et al. 10.5194/amt-17-1475-2024
- New type of evidence for secondary ice formation at around −15 °C in mixed-phase clouds C. Mignani et al. 10.5194/acp-19-877-2019
- Observation of Ice Pellets and its Association with Meteorological Conditions in the Yeongdong Region of Korea Y. Chae et al. 10.1007/s13143-024-00361-9
- Time-resolved measurements of the densities of individual frozen hydrometeors and fresh snowfall D. Singh et al. 10.5194/amt-17-4581-2024
- A Versatile Method for Ice Particle Habit Classification Using Airborne Imaging Probe Data C. Praz et al. 10.1029/2018JD029163
- Deep Learning-Based Water Crystal Classification H. Thi et al. 10.3390/app12020825
- Ice crystal images from optical array probes: classification with convolutional neural networks L. Jaffeux et al. 10.5194/amt-15-5141-2022
- The Retrieval of Drop Size Distribution Parameters Using a Dual-Polarimetric Radar G. Lee et al. 10.3390/rs15041063
- Radar and ground-level measurements of precipitation collected by the École Polytechnique Fédérale de Lausanne during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games J. Gehring et al. 10.5194/essd-13-417-2021
- Ultra-dense ground observation of snow crystals by citizen science “#KantoSnowCrystal project” K. ARAKI 10.5331/seppyo.80.2_115
- Unraveling hydrometeor mixtures in polarimetric radar measurements N. Besic et al. 10.5194/amt-11-4847-2018
- Microphysical investigation of the seeder and feeder region of an Alpine mixed-phase cloud F. Ramelli et al. 10.5194/acp-21-6681-2021
- Measurement and Analysis of the Microphysical Properties of Arctic Precipitation Showing Frequent Occurrence of Riming K. Fitch & T. Garrett 10.1029/2021JD035980
- The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning R. Atlas et al. 10.5194/amt-14-7079-2021
- ICE-CAMERA: a flatbed scanner to study inland Antarctic polar precipitation M. Del Guasta 10.5194/amt-15-6521-2022
- Experimental investigation and semi-empirical modeling of snowflake melting B. Aguilar et al. 10.1016/j.ijheatmasstransfer.2023.124117
- Reconstruction of the mass and geometry of snowfall particles from multi-angle snowflake camera (MASC) images J. Leinonen et al. 10.5194/amt-14-6851-2021
- Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica A. Ferrone & A. Berne 10.5194/essd-15-1115-2023
- From model to radar variables: a new forward polarimetric radar operator for COSMO D. Wolfensberger & A. Berne 10.5194/amt-11-3883-2018
- Precipitation characteristics and associated weather conditions on the eastern slopes of the Canadian Rockies during March–April 2015 J. Thériault et al. 10.5194/hess-22-4491-2018
- Microphysical Characteristics of Winter Precipitation in Eastern China from 2014 to 2019 K. Pu et al. 10.3390/w12030920
- Auto-Encoder Classification Model for Water Crystals with Fine-Tuning H. Hosni Mahmoud & N. Ali Hakami 10.3390/cryst12111667
- Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm H. Kalesse et al. 10.5194/amt-12-4591-2019
- The Geometry of Rimed Aggregate Snowflakes: A Modeling Study A. Seifert et al. 10.1029/2018MS001519
- Hydrometeor Identification Using Multiple-Frequency Microwave Links: A Numerical Simulation K. Pu et al. 10.3390/rs12132158
- Melting of fractal snowflakes: Experiments and modeling K. Köbschall et al. 10.1016/j.ijheatmasstransfer.2023.124254
- Introducing the Video In Situ Snowfall Sensor (VISSS) M. Maahn et al. 10.5194/amt-17-899-2024
- Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks V. Przybylo et al. 10.1175/JTECH-D-21-0094.1
Latest update: 14 Dec 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...
