New insights into ice multiplication using remote-sensing observations of slightly supercooled mixed-phase clouds in the Arctic

• Published in: Proceedings of the National Academy of Sciences
• Main Authors: Luke, Edward P., Yang, Fan, Kollias, Pavlos, Vogelmann, Andrew M., Maahn, Maximilian
• Language: unknown
• Published: 2022
• Subjects: 54 ENVIRONMENTAL SCIENCES; Arctic; Rime
• Online Access: http://www.osti.gov/servlets/purl/1782540; https://www.osti.gov/biblio/1782540; https://doi.org/10.1073/pnas.2021387118

Secondary ice production (SIP) can significantly enhance ice particle number concentrations in mixed-phase clouds, resulting in a substantial impact on ice mass flux and evolution of cold cloud systems. SIP is especially important at temperatures warmer than –10 °C, for which primary ice nucleation lacks a significant number of efficient ice nucleating particles. However, determining the climatological significance of SIP has proved difficult using existing observational methods. Here we quantify the long-term occurrence of secondary ice events and their multiplication factors in slightly supercooled clouds using a multisensor, remote-sensing technique applied to 6 y of ground-based radar measurements in the Arctic. Further, we assess the potential contribution of the underlying mechanisms of rime splintering and freezing fragmentation. Our results show that the occurrence frequency of secondary ice events averages to <10% over the entire period. Although infrequent, the events can have a significant impact in a local region when they do occur, with up to a 1,000-fold enhancement in ice number concentration. We show that freezing fragmentation, which appears to be enhanced by updrafts, is more efficient for SIP than the better-known rime-splintering process. Furthermore, our field observations are consistent with laboratory findings while shedding light on the phenomenon and its contributing factors in a natural environment. This study provides critical insights needed to advance parameterization of SIP in numerical simulations and to design future laboratory experiments.