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

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Subject: Clouds and Precipitation | Research Activity: Laboratory Studies | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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Cited articles

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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.
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