Articles | Volume 17, issue 12
https://doi.org/10.5194/amt-17-3679-2024
https://doi.org/10.5194/amt-17-3679-2024
Research article
 | 
19 Jun 2024
Research article |  | 19 Jun 2024

Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements

Gerald G. Mace

Viewed

Total article views: 582 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
403 141 38 582 24 25
  • HTML: 403
  • PDF: 141
  • XML: 38
  • Total: 582
  • BibTeX: 24
  • EndNote: 25
Views and downloads (calculated since 21 Dec 2023)
Cumulative views and downloads (calculated since 21 Dec 2023)

Viewed (geographical distribution)

Total article views: 582 (including HTML, PDF, and XML) Thereof 582 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 29 Jun 2024
Download
Short summary
The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers.  We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.