Articles | Volume 14, issue 15
https://doi.org/10.5194/acp-14-8185-2014
https://doi.org/10.5194/acp-14-8185-2014
Research article
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14 Aug 2014
Research article | Highlight paper |  | 14 Aug 2014

Quantification of ice nuclei active at near 0 °C temperatures in low-altitude clouds at the Puy de Dôme atmospheric station

M. Joly, P. Amato, L. Deguillaume, M. Monier, C. Hoose, and A.-M. Delort

Abstract. The distribution, abundance and nature of ice nucleation active particles in the atmosphere are major sources of uncertainty in the prediction of cloud coverage, precipitation patterns and climate. Some biological ice nuclei (IN) induce freezing at temperatures at which most other atmospheric particles exhibit no detectable activity (> −10 °C). Their actual contribution to the pool of IN in clouds remains poorly known, but numerical studies have suggested a probable significance of biological IN in atmospheric processes. In this study, cloud water was collected aseptically from the summit of Puy de Dôme (1465 m a.s.l., France) within contrasted meteorological and physico-chemical situations. Total and biological (i.e. heat-sensitive) IN were quantified by droplet-freezing assay between −5 °C and −14 °C. We observed that freezing was systematically induced by biological material, between −6 °C and −8 °C in 92% of the samples. Its removal by heat treatment consistently led to a decrease of the onset freezing temperature, by 3 °C or more in most samples. At −10 °C, 0 to ~ 220 biological IN mL−1 of cloud water were measured (i.e. 0 to ~ 22 m−3 of cloud air based on cloud liquid water content estimates), and these represented 65% to 100% of the total IN. Based on back-trajectories and on physico-chemical analyses, the high variability observed resulted probably from a source effect, with IN originating mostly from continental sources. Assuming that biological IN were all bacteria, at maximum 0.6% of the bacterial cells present in cloud water samples could have acted as IN at −8 °C, 1.5% at −10 °C, and 3.1% at −12 °C. The data set generated here will help elucidate the role of biological and bacterial IN on cloud microphysics by numeric modelling, and their impact on precipitation at local scale.

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