Sensitivity of mixed-phase moderately deep convective clouds to parameterizations of ice formation – an ensemble perspective

Abstract

Abstract. The formation of ice in clouds is an important processes in mixed-phase and ice-phase clouds. Yet, the representation of ice formation in numerical models is highly uncertain. In the last decade, several new parameterizations for heterogeneous freezing have been proposed. However, it is currently unclear what the effect of choosing one parameterization over another is in the context of numerical weather prediction. We conducted high-resolution simulations (Δx=250 m) of moderately deep convective clouds (cloud top ∼-18 ∘C) over the southwestern United Kingdom using several formulations of ice formation and compared the resulting changes in cloud field properties to the spread of an initial condition ensemble for the same case. The strongest impact of altering the ice formation representation is found in the hydrometeor number concentration and mass mixing ratio profiles. While changes in accumulated precipitation are around 10 %, high precipitation rates (95th percentile) vary by 20 %. Using different ice formation representations changes the outgoing short-wave radiation by about 2.9 W m−2 averaged over daylight hours. The choice of a particular representation for ice formation always has a smaller impact then omitting heterogeneous ice formation completely. Excluding the representation of the Hallett–Mossop process or altering the heterogeneous freezing parameterization has an impact of similar magnitude on most cloud macro- and microphysical variables with the exception of the frozen hydrometeor mass mixing ratios and number concentrations. A comparison to the spread of cloud properties in a 10-member high-resolution initial condition ensemble shows that the sensitivity of hydrometeor profiles to the formulation of ice formation processes is larger than sensitivity to initial conditions. In particular, excluding the Hallett–Mossop representation results in profiles clearly different from any in the ensemble. In contrast, the ensemble spread clearly exceeds the changes introduced by using different ice formation representations in accumulated precipitation, precipitation rates, condensed water path, cloud fraction, and outgoing radiation fluxes.

Sensitivity of cloud phase distribution to cloud microphysics and thermodynamics in simulated deep convective clouds and SEVIRI retrievals

“…with polluted continental aerosols in their simulated moderate convection cases, and they attributed it to enhanced heterogeneous freezing and prolonged ice crystal growth at higher INP loading.This competition between homogeneous and heterogeneous freezing has been discussed in previous studies(Heymsfield et al, 2005;Deng et al, 2018;Takeishi and Storelvmo, 2018). In contrast, simulations of mixed-phase moderately deep convective clouds byMiltenberger and Field (2021) indicate that cloud ice mass concentration increases with increasing INP concentration, which is in opposition to the findings in this work. The main reason is that the CTT is about -18°C in Miltenberger and Field (2021)'s study, and heterogeneous freezing does not compete with homogeneous freezing.…”