Quantifying the dependence of drop  spectrum width on cloud drop number  concentration for cloud remote sensing

Lebsock, Matthew D.; Witte, Mikael

doi:https://doi.org/10.5194/acp-23-14293-2023

Articles | Volume 23, issue 22

https://doi.org/10.5194/acp-23-14293-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-14293-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 22

Research article

|

20 Nov 2023

Research article |

| 20 Nov 2023

Quantifying the dependence of drop spectrum width on cloud drop number concentration for cloud remote sensing

Matthew D. Lebsock and Mikael Witte

Related authors

Retrieval simulations of a spaceborne differential absorption radar near the 380 GHz water vapor line

Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski

EGUsphere, https://doi.org/10.5194/egusphere-2025-322,https://doi.org/10.5194/egusphere-2025-322, 2025

Short summary

Vertical Wind and Drop Size Distribution Retrieval with the CloudCube G-band Doppler Radar

Nitika Yadlapalli Yurk, Matthew Lebsock, Juan Socuellamos, Raquel Rodriguez Monje, Ken Cooper, and Pavlos Kollias

EGUsphere, https://doi.org/10.5194/egusphere-2025-618,https://doi.org/10.5194/egusphere-2025-618, 2025

Short summary

The Diurnal Susceptibility of Subtropical Clouds to Aerosols

Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley

EGUsphere, https://doi.org/10.5194/egusphere-2025-714,https://doi.org/10.5194/egusphere-2025-714, 2025

Short summary

Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds

Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias

Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024,https://doi.org/10.5194/amt-17-6965-2024, 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

More articles (10)

Aircraft evaluation of MODIS cloud drop number concentration retrievals

Scarlet R. Passer, Mikael K. Witte, and Patrick Y. Chuang

Atmos. Meas. Tech., 18, 3819–3831, https://doi.org/10.5194/amt-18-3819-2025,https://doi.org/10.5194/amt-18-3819-2025, 2025

Short summary

Retrieval simulations of a spaceborne differential absorption radar near the 380 GHz water vapor line

Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski

EGUsphere, https://doi.org/10.5194/egusphere-2025-322,https://doi.org/10.5194/egusphere-2025-322, 2025

Short summary

Vertical Wind and Drop Size Distribution Retrieval with the CloudCube G-band Doppler Radar

Nitika Yadlapalli Yurk, Matthew Lebsock, Juan Socuellamos, Raquel Rodriguez Monje, Ken Cooper, and Pavlos Kollias

EGUsphere, https://doi.org/10.5194/egusphere-2025-618,https://doi.org/10.5194/egusphere-2025-618, 2025

Short summary

The Diurnal Susceptibility of Subtropical Clouds to Aerosols

Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley

EGUsphere, https://doi.org/10.5194/egusphere-2025-714,https://doi.org/10.5194/egusphere-2025-714, 2025

Short summary

Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES

Kerry Meyer, Steven Platnick, G. Thomas Arnold, Nandana Amarasinghe, Daniel Miller, Jennifer Small-Griswold, Mikael Witte, Brian Cairns, Siddhant Gupta, Greg McFarquhar, and Joseph O'Brien

Atmos. Meas. Tech., 18, 981–1011, https://doi.org/10.5194/amt-18-981-2025,https://doi.org/10.5194/amt-18-981-2025, 2025

Short summary

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, and Peng Wu

Atmos. Chem. Phys., 21, 3103–3121, https://doi.org/10.5194/acp-21-3103-2021,https://doi.org/10.5194/acp-21-3103-2021, 2021

Short summary

Cited articles

Ackerman, A. S., Toon, O. B., Taylor, J. P., Johnson, D. W., Hobbs, P. V., and Ferek, R. J.: Effects of Aerosols on Cloud Albedo: Evaluation of Twomey's Parameterization of Cloud Susceptibility Using Measurements of Ship Tracks, J. Atmos. Sci., 57, 2684–2695, 2000.

Albrecht, B. A., Ghate, V., Mohrmann, J., Wood, R., Zuidema, P., Bretherton, C., Schwartz, C., Eloranta, E., Glienke, S., Donaher, S., Sarkar, M., McGibbon, J., Nugent, A. D., Shaw, R. A., Fugal, J., Minnis, P., Paliknoda, R., Lussier, L., Jensen, J., Vivekanandan, J., Ellis, S., Tsai, P., Rilling, R., Haggerty, J., Campos, T., Stell, M., Reeves, M., Beaton, S., Allison, J., Stossmeister, G., Hall, S., and Schmidt, S.: Cloud System Evolution in the Trades (CSET): Following the evolution of boundary layer cloud systems with the NSF–NCAR GV, B. Am. Meteorol. Soc., 100, 93–121, https://doi.org/10.1175/BAMS-D-17-0180.1, 2019.

ARM: FCDP for ACE-ENA, https://adc.arm.gov/discovery/#/ (last access: 17 November 2023), 2023.

Bennartz, R.: Global assessment of marine boundary layer cloud droplet number concentration from satellite, J. Geophys. Res., 112, D02201, https://doi.org/10.1029/2006JD007547, 2007.

Bennartz, R. and Rausch, J.: Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations, Atmos. Chem. Phys., 17, 9815–9836, https://doi.org/10.5194/acp-17-9815-2017, 2017.