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Measuring the shape of cloud particle size distributions in high-latitude marine cold air outbreaks
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  • Larry Ger B Aragon,
  • Jonathan Crosier,
  • Paul James Connolly,
  • Yi HUANG,
  • Peter T May,
  • Steven Abel
Larry Ger B Aragon
The University of Melbourne

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Jonathan Crosier
University of Manchester
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Paul James Connolly
University of Manchester
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Yi HUANG
The University of Melbourne
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Peter T May
Monash University
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Steven Abel
UK Met Office
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Abstract

Marine cold air outbreaks (MCAOs) drive significant evolutions in marine boundary layer clouds and play a crucial role in high-latitude climate systems. This study examines the variability of cloud particle size distributions (PSDs) and the representation of the Gamma shape parameter μ for high-latitude MCAO clouds in the Northern Hemisphere, focusing on the initial stratocumulus stages and cumulus regime transitions. Aircraft in-situ measurements from 20 flights with identified MCAO conditions were collected during two recent field campaigns: M-Phase conducted over the Labrador Sea in March 2022, and Arctic Cold-Air Outbreak (ACAO) conducted over the Nordic Seas in October to November 2022. Results show that high-latitude MCAO clouds in the Northern Hemisphere exhibit narrow PSDs, characterized by higher μ values (mean μ=20) that imply more reflective clouds compared to the fixed μ=2.5 assumption in some bulk microphysics schemes. Cloud PSDs narrow and μ values increase with height in near-adiabatic stratocumulus clouds, while their patterns are more variable in broken cumulus clouds. Liquid water content correlates more strongly with μ variability than cloud number concentrations, suggesting its better predictability as a prognostic variable for PSD variability in these cloud systems. Both the μ=20 and its derived relation with cloud liquid water content can be applied in bulk microphysics schemes to better represent the microphysical and radiative properties of high-latitude MCAO clouds. The proposed high μ values for MCAO clouds are applicable mainly to typical horizontal resolutions of numerical weather prediction and regional climate models.
26 Nov 2024Submitted to ESS Open Archive
27 Nov 2024Published in ESS Open Archive