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

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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
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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.
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