Articles | Volume 14, issue 6
Atmos. Meas. Tech., 14, 4543–4564, 2021
Atmos. Meas. Tech., 14, 4543–4564, 2021
Research article
18 Jun 2021
Research article | 18 Jun 2021

Identification of snowfall microphysical processes from Eulerian vertical gradients of polarimetric radar variables

Noémie Planat et al.

Related authors

Water vapor in cold and clean atmosphere: a 3-year data set in the boundary layer of Dome C, East Antarctic Plateau
Christophe Genthon, Dana E. Veron, Etienne Vignon, Jean-Baptiste Madeleine, and Luc Piard
Earth Syst. Sci. Data, 14, 1571–1580,,, 2022
Short summary
Snowfall in Northern Finland derives mostly from ice clouds
Claudia Mignani, Lukas Zimmermann, Rigel Kivi, Alexis Berne, and Franz Conen
Atmos. Chem. Phys. Discuss.,,, 2022
Preprint under review for ACP
Short summary
Secondary ice production processes in wintertime alpine mixed-phase clouds
Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 22, 1965–1988,,, 2022
Short summary
GABLS4 intercomparison of snow models at Dome C in Antarctica
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere Discuss.,,, 2022
Revised manuscript accepted for TC
Short summary
Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in the WRF (v4.1.3) model during the ICE-POP 2018 field campaign
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev. Discuss.,,, 2022
Revised manuscript under review for GMD
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improving discrimination between clouds and optically thick aerosol plumes in geostationary satellite data
Daniel Robbins, Caroline Poulsen, Steven Siems, and Simon Proud
Atmos. Meas. Tech., 15, 3031–3051,,, 2022
Short summary
Towards the use of conservative thermodynamic variables in data assimilation: a case study using ground-based microwave radiometer measurements
Pascal Marquet, Pauline Martinet, Jean-François Mahfouf, Alina Lavinia Barbu, and Benjamin Ménétrier
Atmos. Meas. Tech., 15, 2021–2035,,, 2022
Short summary
Empirical model of multiple-scattering effect on single-wavelength lidar data of aerosols and clouds
Valery Shcherbakov, Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 15, 1729–1754,,, 2022
Short summary
Analytic characterization of random errors in spectral dual-polarized cloud radar observations
Alexander Myagkov and Davide Ori
Atmos. Meas. Tech., 15, 1333–1354,,, 2022
Short summary
Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms
Yuli Liu and Gerald G. Mace
Atmos. Meas. Tech., 15, 927–944,,, 2022
Short summary

Cited articles

Andrić, J., Kumjian, M. R., Zrnić, D. S., Straka, J. M., and Melnikov, V. M.: Polarimetric signatures above the melting layer in winter storms: An observational and modeling study, J. Appl. Meteorol. Clim., 52, 682–700, 2013. a, b, c
Bader, M., Clough, S., and Cox, G.: Aircraft and dual polarization radar observations of hydrometeors in light stratiform precipitation, Q. J. Roy. Meteor. Soc., 113, 491–515, 1987. a
Berne, A., Grazioli, J., and Genthon, C. Precipitation observations at the Dumont d'Urville station, Adelie Land, East Antarctica, PANGAEA [data set],, 2017. a
Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425–4445,, 2016. a
Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmos. Meas. Tech., 11, 4847–4866,, 2018. a, b, c
Short summary
We implement a new method to identify microphysical processes during cold precipitation events based on the sign of the vertical gradient of polarimetric radar variables. We analytically asses the meteorological conditions for this vertical analysis to hold, apply it on two study cases and successfully compare it with other methods informing about the microphysics. Finally, we are able to obtain the main vertical structure and characteristics of the different processes during these study cases.