Articles | Volume 17, issue 17
https://doi.org/10.5194/acp-17-10855-2017
https://doi.org/10.5194/acp-17-10855-2017
Research article
 | 
14 Sep 2017
Research article |  | 14 Sep 2017

Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

Sarvesh Garimella, Daniel A. Rothenberg, Martin J. Wolf, Robert O. David, Zamin A. Kanji, Chien Wang, Michael Rösch, and Daniel J. Cziczo

Viewed

Total article views: 4,950 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,872 1,637 441 4,950 489 442
  • HTML: 2,872
  • PDF: 1,637
  • XML: 441
  • Total: 4,950
  • BibTeX: 489
  • EndNote: 442
Views and downloads (calculated since 31 Jan 2017)
Cumulative views and downloads (calculated since 31 Jan 2017)

Viewed (geographical distribution)

Total article views: 4,950 (including HTML, PDF, and XML) Thereof 4,893 with geography defined and 57 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 13 Nov 2026
Download
Short summary
This study investigates systematic and variable low bias in the measurement of ice nucleating particle concentration using continuous flow diffusion chambers. We find that non-ideal instrument behavior exposes particles to different humidities and/or temperatures than predicted from theory. We use a machine learning approach to quantify and minimize the uncertainty associated with this measurement bias.
Share
Altmetrics
Final-revised paper
Preprint