Revisiting adiabatic fraction estimations in cumulus clouds: high-resolution simulations with a passive tracer

Eshkol Eytan, Ilan Koren*, Orit Altaratz, Mark Pinsky, Alexander Khain*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The process of mixing in warm convective clouds and its effects on microphysics are crucial for an accurate description of cloud fields, weather, and climate. Still, they remain open questions in the field of cloud physics. Adiabatic regions in the cloud could be considered non-mixed areas and therefore serve as an important reference to mixing. For this reason, the adiabatic fraction (AF) is an important parameter that estimates the mixing level in the cloud in a simple way. Here, we test different methods of AF calculations using high-resolution (10m) simulations of isolated warm cumulus clouds. The calculated AFs are compared with a normalized concentration of a passive tracer, which is a measure of dilution by mixing. This comparison enables the examination of how well the AF parameter can determine mixing effects and the estimation of the accuracy of different approaches used to calculate it. Comparison of three different methods to derive AF, with the passive tracer, shows that one method is much more robust than the others. Moreover, this method's equation structure also allows for the isolation of different assumptions that are often practiced when calculating AF such as vertical profiles, cloud-base height, and the linearity of AF with height. The use of a detailed spectral bin microphysics scheme allows an accurate description of the supersaturation field and demonstrates that the accuracy of the saturation adjustment assumption depends on aerosol concentration, leading to an underestimation of AF in pristine environments.

Original languageAmerican English
Pages (from-to)16203-16217
Number of pages15
JournalAtmospheric Chemistry and Physics
Volume21
Issue number21
DOIs
StatePublished - 4 Nov 2021

Bibliographical note

Publisher Copyright:
© 2021 Eshkol Eytan et al.

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