Articles | Volume 22, issue 21
https://doi.org/10.5194/acp-22-14441-2022
https://doi.org/10.5194/acp-22-14441-2022
Research article
 | 
11 Nov 2022
Research article |  | 11 Nov 2022

Predicting atmospheric background number concentration of ice-nucleating particles in the Arctic

Guangyu Li, Jörg Wieder, Julie T. Pasquier, Jan Henneberger, and Zamin A. Kanji

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Cited articles

Cooper, W. A.: Ice initiation in natural clouds, in: Precipitation enhancement – A scientific challenge, American Meteorological Society, Boston, MA, 29–32, https://doi.org/10.1007/978-1-935704-17-1_4, 1986. a, b, c
Creamean, J. M., Cross, J. N., Pickart, R., McRaven, L., Lin, P., Pacini, A., Hanlon, R., Schmale, D. G., Ceniceros, J., Aydell, T., Colombi, N., Bolger, E., and DeMott, P. J.: Ice nucleating particles carried from below a phytoplankton bloom to the Arctic atmosphere, Geophys. Res. Lett., 46, 8572–8581, https://doi.org/10.1029/2019GL083039, 2019. a
Creamean, J. M., Kirpes, R. M., Pratt, K. A., Spada, N. J., Maahn, M., de Boer, G., Schnell, R. C., and China, S.: Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location, Atmos. Chem. Phys., 18, 18023–18042, https://doi.org/10.5194/acp-18-18023-2018, 2018. a
David, R. O., Cascajo-Castresana, M., Brennan, K. P., Rösch, M., Els, N., Werz, J., Weichlinger, V., Boynton, L. S., Bogler, S., Borduas-Dedekind, N., Marcolli, C., and Kanji, Z. A.: Development of the DRoplet Ice Nuclei Counter Zurich (DRINCZ): validation and application to field-collected snow samples, Atmos. Meas. Tech., 12, 6865–6888, https://doi.org/10.5194/amt-12-6865-2019, 2019. a, b, c, d, e
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci. USA, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010. a, b, c
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The concentration of ice-nucleating particles (INPs) is atmospherically relevant for primary ice formation in clouds. In this work, from 12 weeks of field measurement data in the Arctic, we developed a new parameterization to predict INP concentrations applicable for pristine background conditions based only on temperature. The INP parameterization could improve the cloud microphysical representation in climate models, aiding in Arctic climate predictions.
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