Articles | Volume 14, issue 6
Atmos. Meas. Tech., 14, 4543–4564, 2021
https://doi.org/10.5194/amt-14-4543-2021
Atmos. Meas. Tech., 14, 4543–4564, 2021
https://doi.org/10.5194/amt-14-4543-2021
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

Reanalysis representation of low-level winds in the Antarctic near-coastal region
Thomas Caton Harrison, Stavroula Biri, Thomas J. Bracegirdle, John C. King, Elizabeth C. Kent, Étienne Vignon, and John Turner
Weather Clim. Dynam., 3, 1415–1437, https://doi.org/10.5194/wcd-3-1415-2022,https://doi.org/10.5194/wcd-3-1415-2022, 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., 22, 13551–13568, https://doi.org/10.5194/acp-22-13551-2022,https://doi.org/10.5194/acp-22-13551-2022, 2022
Short summary
Ice fog observed at cirrus temperatures at Dome C, Antarctic Plateau
Étienne Vignon, Lea Raillard, Christophe Genthon, Massimo Del Guasta, Andrew J. Heymsfield, Jean-Baptiste Madeleine, and Alexis Berne
Atmos. Chem. Phys., 22, 12857–12872, https://doi.org/10.5194/acp-22-12857-2022,https://doi.org/10.5194/acp-22-12857-2022, 2022
Short summary
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-295,https://doi.org/10.5194/essd-2022-295, 2022
Preprint under review for ESSD
Short summary
Dual-frequency spectral radar retrieval of snowfall microphysics: a physically constrained deep learning approach
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-199,https://doi.org/10.5194/amt-2022-199, 2022
Revised manuscript accepted for AMT
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023,https://doi.org/10.5194/amt-16-603-2023, 2023
Short summary
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023,https://doi.org/10.5194/amt-16-331-2023, 2023
Short summary
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022,https://doi.org/10.5194/amt-15-7119-2022, 2022
Short summary
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022,https://doi.org/10.5194/amt-15-6653-2022, 2022
Short summary
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022,https://doi.org/10.5194/amt-15-6489-2022, 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], https://doi.org/10.1594/PANGAEA.883562, 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, https://doi.org/10.5194/amt-9-4425-2016, 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, https://doi.org/10.5194/amt-11-4847-2018, 2018. a, b, c
Download
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.