Articles | Volume 23, issue 10
https://doi.org/10.5194/acp-23-5735-2023
https://doi.org/10.5194/acp-23-5735-2023
Research article
 | 
23 May 2023
Research article |  | 23 May 2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Aishwarya Raman, Thomas Hill, Paul J. DeMott, Balwinder Singh, Kai Zhang, Po-Lun Ma, Mingxuan Wu, Hailong Wang, Simon P. Alexander, and Susannah M. Burrows

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Cited articles

Adebiyi, A. A. and Kok, J. F.: Climate models miss most of the coarse dust in the atmosphere, Sci. Adv., 6, eaaz9507 https://doi.org/10.1126/sciadv.aaz9507, 2020. a, b
Alpert, P. A. and Knopf, D. A.: Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model, Atmos. Chem. Phys., 16, 2083–2107, https://doi.org/10.5194/acp-16-2083-2016, 2016. a, b
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., Dobbie, S., O’Sullivan, D., and Malkin, T. L.: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds, Nature, 498, 355–358, 2013. a, b
Beall, C. M., Stokes, M. D., Hill, T. C., DeMott, P. J., DeWald, J. T., and Prather, K. A.: Automation and heat transfer characterization of immersion mode spectroscopy for analysis of ice nucleating particles, Atmos. Meas. Tech., 10, 2613–2626, https://doi.org/10.5194/amt-10-2613-2017, 2017. a
Bergametti, G., Marticorena, B., Rajot, J.-L., Foret, G., Alfaro, S., and Laurent, B.: Size-Resolved Dry Deposition Velocities of Dust Particles: In Situ Measurements and Parameterizations Testing, J. Geophys. Res.-Atmos., 123, 11080–11099, 2018. a
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Ice-nucleating particles (INPs) play an important role in cloud processes and associated precipitation. Yet, INPs are not accurately represented in climate models. This study attempts to uncover these gaps by comparing model-simulated INP concentrations against field campaign measurements in the SO for an entire year, 2017–2018. Differences in INP concentrations and variability between the model and observations have major implications for modeling cloud properties in high latitudes.
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