An Intercomparison of Large‐Eddy Simulations of a Convection Cloud Chamber Using Haze‐Capable Bin and Lagrangian Cloud Microphysics Schemes

Abstract

Recent in situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large‐eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation was modeled based on Twomey‐type parameterizations, wherein cloud droplets were formed when a critical supersaturation for the available cloud condensation nuclei (CCN) was exceeded and haze particles were not explicitly resolved. Here, we develop and adapt haze‐capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey‐type CCN‐based bin microphysics scheme in which haze particles are not fully resolved. We find that results from the haze‐capable bin microphysics scheme agree well with those from the Lagrangian microphysics scheme. However, both schemes significantly differ from those from a CCN‐based bin microphysics scheme unless CCN recycling is considered. Haze particles from the recycling of deactivated cloud droplets can strongly enhance cloud droplet number concentration due to a positive feedback in haze‐cloud interactions in the cloud chamber. Haze particle size distributions are more realistic when considering solute and curvature effects that enable representing the complete physics of the activation process. Our study suggests that haze particles and their interactions with cloud droplets may have a strong impact on cloud properties when supersaturation fluctuations are comparable to mean supersaturation, as is the case in the cloud chamber and likely is the case in the atmosphere, especially in polluted conditions.

Designing a Convection‐Cloud Chamber for Collision‐Coalescence Using Large‐Eddy Simulation With Bin Microphysics

“…Although Morrison et al (2018) have shown the artificially enhanced broadening of DSDs associated with vertical diffusion in a Eulerian dynamical model, Yang et al (2022) find that the impact of numerical broadening of the DSDs in the cloud-chamber LES is very small due to the relatively fine grid spacing, short time step, and weak vertical velocity compared to convection in an atmospheric boundary layer. Additionally, Yang et al (2023) shows that the cloud-chamber LES results from an Eulerian bin microphysics scheme agree well with those from a Lagrangian microphysics scheme, and the latter does not experience numerical diffusion. To narrow the scope of this study, we will focus on the sensitivity of the results to the chamber configurations rather than numerical methods.…”

“…Additionally, Yang et al. (2023) shows that the cloud‐chamber LES results from an Eulerian bin microphysics scheme agree well with those from a Lagrangian microphysics scheme, and the latter does not experience numerical diffusion. To narrow the scope of this study, we will focus on the sensitivity of the results to the chamber configurations rather than numerical methods.…”

“…The momentum equations are solved on an Arakawa C-grid with an anelastic approximation, a 1.5-order TKE subgrid-scale (SGS) model, and a second-order-central advection scheme. The scalars (temperature, microphysical fields, and SGS TKE) are advected using a multidimensional positive definite advection transport algorithm (Smolarkiewicz & Grabowski, 1990), which is chosen as it has been widely used in the study of cloud-chamber simulations (Thomas et al, 2019;Yang et al, 2022Yang et al, , 2023. Although the sensitivity to the advection scheme is beyond the scope of this study, it is worth noting that a less diffusive advection scheme has been found to produce a higher number concentration and LWC (Yang et al, 2022).…”

Enhancements in Cloud Condensation Nuclei Activity From Turbulent Fluctuations in Supersaturation

“…The LES of the Pi Chamber is a modified version of the System for Atmospheric Modeling (SAM) (Khairoutdinov & Randall, 2003;Thomas et al, 2019;Yang et al, 2022Yang et al, , 2023, with a grid spacing of 3.125 cm in each dimension. This small grid spacing is several orders of magnitude smaller than cloud-scale LES, resolving fluctuations in environmental properties at very small scales.…”

“…Other representations of cloud microphysics, such as Lagrangian super‐droplet method, do not represent non‐activated aerosol particles and cloud droplets as separate classes (Grabowski, 2020a; Hoffmann et al., 2019) which may cause the super‐droplet method to be a better representation of CCN activation than bin microphysics. However, both the super‐droplet method and bin microphysics approach produce slightly different but comparable cloud droplet spectra (Grabowski, 2020a, 2020b; Xue et al., 2022; Yang et al., 2023).…”