News Release

Developing different hydrometeor spectra parameterizations for simulating convective clouds

Peer-Reviewed Publication

Institute of Atmospheric Physics, Chinese Academy of Sciences

Spectral distribution and relative dispersion

image: Spectral distribution and relative dispersion view more 

Credit: ZOU Qinyao

Clouds play significant roles in atmospheric radiation transfer and the water cycle. Therefore, it is necessary to accurately describe their microphysical properties in models, including the spectral relative dispersion of different hydrometeors, which desecribes the width of size distributions. However, in-depth observational analyses on the relationship between the relative dispersion of ice-phase particle spectra and their microphysical properties are lacking.


In a paper recently published in Atmospheric and Oceanic Science Letters, Prof. Chunsong Lu from Nanjing University of Information Science & Technology, and his team, try to address this concern based on their recently completed work on the relationship between relative dispersion and volume-mean diameter in convective clouds.


“Regardless of clean or polluted conditions, the relative dispersion of ice crystal spectra and its volume-mean diameter are negatively correlated, while the relative dispersion of other hydrometeor spectra is positively related to their respective volume-mean diameter. The correlations for cloud droplets and raindrops are affected by the process of collision–coalescence; and the correlations for ice crystals, graupel particles and snow particles could be affected by the deposition, riming, and aggregation processes, respectively,” says the corresponding author, Chunsong Lu.


Based on a comprehensive consideration of the relationships between the relative dispersion and volume-mean diameter, this study develops relative dispersion parameterizations under both polluted and clean conditions.


In the study, the relative dispersion parameterizations are applied to terminal velocity parameterizations, and the results show that, for cloud droplets, ice crystals, graupel particles and snow particles, assuming that the shape parameter in the Gamma distribution is equal to 0 underestimates the shape parameter and overestimates the relative dispersion; and for raindrops, assuming the shape parameter is equal to 0 gives a result that is close to the relative dispersion parameterizations.


The relative dispersion parameterizations developed here shed new light for further optimizing the terminal velocity parameterizations in models.

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