Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1211-2023
https://doi.org/10.5194/amt-16-1211-2023
Research article
 | 
09 Mar 2023
Research article |  | 09 Mar 2023

Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy

Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont

Related authors

The first microwave and submillimetre closure study using particle models of oriented ice hydrometeors to simulate polarimetric measurements of ice clouds
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech., 17, 3533–3552, https://doi.org/10.5194/amt-17-3533-2024,https://doi.org/10.5194/amt-17-3533-2024, 2024
Short summary
Pico-Light H2O: intercomparison of in situ water vapour measurements during the AsA 2022 campaign
Mélanie Ghysels, Georges Durry, Nadir Amarouche, Dale Hurst, Emrys Hall, Kensy Xiong, Jean-Charles Dupont, Jean-Christophe Samake, Fabien Frérot, Raghed Bejjani, and Emmanuel D. Riviere
Atmos. Meas. Tech., 17, 3495–3513, https://doi.org/10.5194/amt-17-3495-2024,https://doi.org/10.5194/amt-17-3495-2024, 2024
Short summary
Molecular composition of clouds: a comparison between samples collected at tropical (Réunion Island, France) and mid-north (Puy de Dôme, France) latitudes
Lucas Pailler, Laurent Deguillaume, Hélène Lavanant, Isabelle Schmitz, Marie Hubert, Edith Nicol, Mickaël Ribeiro, Jean-Marc Pichon, Mickaël Vaïtilingom, Pamela Dominutti, Frédéric Burnet, Pierre Tulet, Maud Leriche, and Angelica Bianco
Atmos. Chem. Phys., 24, 5567–5584, https://doi.org/10.5194/acp-24-5567-2024,https://doi.org/10.5194/acp-24-5567-2024, 2024
Short summary
Vertical Profiles of Liquid Water Content in fog layers during the SOFOG3D experiment
Théophane Costabloz, Frédéric Burnet, Christine Lac, Pauline Martinet, Julien Delanoë, Susana Jorquera, and Maroua Fathalli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1344,https://doi.org/10.5194/egusphere-2024-1344, 2024
Short summary
Measurement report: Bio-physicochemistry of tropical clouds at Maïdo (Réunion, Indian Ocean): overview of results from the BIO-MAÏDO campaign
Maud Leriche, Pierre Tulet, Laurent Deguillaume, Frédéric Burnet, Aurélie Colomb, Agnès Borbon, Corinne Jambert, Valentin Duflot, Stéphan Houdier, Jean-Luc Jaffrezo, Mickaël Vaïtilingom, Pamela Dominutti, Manon Rocco, Camille Mouchel-Vallon, Samira El Gdachi, Maxence Brissy, Maroua Fathalli, Nicolas Maury, Bert Verreyken, Crist Amelynck, Niels Schoon, Valérie Gros, Jean-Marc Pichon, Mickael Ribeiro, Eric Pique, Emmanuel Leclerc, Thierry Bourrianne, Axel Roy, Eric Moulin, Joël Barrie, Jean-Marc Metzger, Guillaume Péris, Christian Guadagno, Chatrapatty Bhugwant, Jean-Mathieu Tibere, Arnaud Tournigand, Evelyn Freney, Karine Sellegri, Anne-Marie Delort, Pierre Amato, Muriel Joly, Jean-Luc Baray, Pascal Renard, Angelica Bianco, Anne Réchou, and Guillaume Payen
Atmos. Chem. Phys., 24, 4129–4155, https://doi.org/10.5194/acp-24-4129-2024,https://doi.org/10.5194/acp-24-4129-2024, 2024
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024,https://doi.org/10.5194/amt-17-3679-2024, 2024
Short summary
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024,https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024,https://doi.org/10.5194/amt-17-3323-2024, 2024
Short summary
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024,https://doi.org/10.5194/amt-17-3171-2024, 2024
Short summary
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024,https://doi.org/10.5194/amt-17-3011-2024, 2024
Short summary

Cited articles

Atlas, D.: The Estimation Of Cloud Parameters By Radar, J. Atmos. Sci., 11, 309–317, https://doi.org/10.1175/1520-0469(1954)011<0309:TEOCPB>2.0.CO;2, 1954. a, b, c, d, e, f, g, h, i, j, k, l
Baedi, R. J. P., de Wit, J. J. M., Russchenberg, H. W. J., Erkelens, J. S., and Poiares Baptista, J. P. V.: Estimating effective radius and liquid water content from radar and lidar based on the CLARE98 data-set, Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 25, 1057–1062, https://doi.org/10.1016/S1464-1909(00)00152-0, 2000. a, b
Bell, A., Martinet, P., Caumont, O., Vié, B., Delanoë, J., Dupont, J.-C., and Borderies, M.: W-band radar observations for fog forecast improvement: an analysis of model and forward operator errors, Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, 2021. a
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005. a, b
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the forecast of convective activity from the AROME-France system, Q. J. Roy. Meteor. Soc., 142, 2231–2243, https://doi.org/10.1002/qj.2822, 2016. a
Download
Short summary
Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.