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This research aims to improve the representation of cloud droplet spectra using parametric functions in microphysical schemes.

Parametric representation of the cloud droplet spectra for LES warm bulk microphysical schemes

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This research aims to improve the representation of cloud droplet spectra using parametric functions in microphysical schemes.
Evaluated parametric functions (Lognormal, Generalized Gamma) with droplet spectra from stratocumulus and shallow cumulus clouds.
Tuning parameters were optimized by minimizing errors in the first, second, fifth, and sixth moments of the droplet size distribution.
Proposed a new parameterization where tuning parameter is linked to liquid water content.
Optimized tuning parameters significantly improved the fit of cloud droplet spectra.
Achieved minimized errors for droplet size distribution moments compared to current methods.
Developed an approach highlighting the dependency of tuning parameters on liquid water content, enhancing accuracy.

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Parametric functions enhance droplet spectrum modeling in clouds, suggesting improved microphysical parameterization strategies.

Geoffroy et al. (2010) studied this question.

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