We previously demonstrated (Kogan, 2022, JAS) using LES data, that a nearly perfect correlation (R = 0.99) exists between the phase transition rate (i.e., condensation/evaporation rate) and the upward mass flux. It was shown that functional dependency of transition rates on the upward mass flux can be very accurately approximated by a simple linear fit.
The talk will present results of the most recent study which generalizes results obtained previously for cloud integral variables to the vertically dependent, horizontally averaged variables. The latter serve as prognostic variables in meso- and large-scale models.
The LES derived relationship was confirmed theoretically based on condensational growth equation and the concept of “quasi-steady” supersaturation. The theory provided an analytical expression for the coefficient of proportionality 𝛼(z) in the linear relationship Tr (z) = 𝛼(z) ℳ (z) which defines the phase transition rate, Tr(z), as a function of the upward mass flux, ℳ(z).
The deviation of the LES derived coefficient 𝛼 from its theoretical expression can serve as a measure of non-equilibrium in various cloud regions. LES based estimates showed that the condensation contribution of these regions to the total amount of condensation is, for most clouds, less than a few percents. As a result, we suggest that condensation rates in shallow Cu clouds can be estimated using a single variable - the upward mass flux. Moreover, because the theory behind the condensation-mass flux relationship is valid for any local point, we can expect that the relationship Tr (z) = 𝛼(z) ℳ (z) will hold for a wide range of warm convective clouds.
Kogan, Y. L., 2022: Estimating Phase Transition Rates in Shallow Cumulus Clouds from Mass Flux. Part I: Theory and Numerical Simulations. Journal of the Atmospheric Science. https://doi.org/10.1175/JAS-D-22-0060.1
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