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Data · dataset · 2026

Observed and simulated variability of droplet spectral dispersion in convective clouds over the Amazon

Listed in National Center for Atmospheric Research

In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated.

Description

Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice-free cumulus. In cleaner clouds, the relative dispersion epsilon, defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content (q(c)) to the adiabatic liquid water content (q(a)), while no strong correlation between epsilon and q(c)/q(a) is seen in polluted clouds.

Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision-coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision-coalescence simultaneously broadens the DSDs and decreases q(c), explaining the inverse relationship between epsilon and q(c)/q(a) in cleaner clouds.

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Secondary droplet activation broadens the DSDs but has little direct impact on q(c). The combination of a rather modest DSD broadening due to weak collision-coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform epsilon within polluted clouds. These findings can be useful for parameterizing the shape parameter (mu) of gamma DSDs in bulk microphysics cloud-resolving models.

It is shown that emulating the observed mu-q(c)/q(a) relationship improves the estimation of the collision-coalescence rate in bulk microphysics simulations compared to the bin simulations.

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Cloud physics 76%
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