Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

• Published in: Geoscientific Model Development Vol. 13; no. 9; pp. 4107 - 4157
• Main Authors: Shima, Shin-ichiro, Sato, Yousuke, Hashimoto, Akihiro, Misumi, Ryohei
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 08.09.2020; Copernicus Publications
• Subjects: Advection; Aggregation; Algorithms; Analysis; Atmospheric physics; Cloud condensation nuclei; Cloud microphysics; Clouds; Clouds (Meteorology); Coalescence; Coalescing; Computer applications; Computer simulation; Computing time; Condensation; Condensation nuclei; Convection; Deactivation; Dimensions; Droplets; Evaporation; Finite volume method; Fluid dynamics; Freezing; Ice; Ice particles; Laboratories; Large eddy simulation; Large eddy simulations; Life cycle; Life cycles; Mathematical models; Methods; Microphysics; Morphology; Numerical models; Numerical schemes; Oceanic eddies; Performance evaluation; Precipitation; Sedimentation; Simulation; Spheroids; Sublimation; Submerging; Two dimensional models
• ISSN: 1991-9603; 1991-959X; 1991-962X; 1991-9603; 1991-962X
• DOI: 10.5194/gmd-13-4107-2020

The super-droplet method (SDM) is a particle-based numerical scheme that enables accurate cloud microphysics simulation with lower computational demand than multi-dimensional bin schemes. Using SDM, a detailed numerical model of mixed-phase clouds is developed in which ice morphologies are explicitly predicted without assuming ice categories or mass–dimension relationships. Ice particles are approximated using porous spheroids. The elementary cloud microphysics processes considered are advection and sedimentation; immersion/condensation and homogeneous freezing; melting; condensation and evaporation including cloud condensation nuclei activation and deactivation; deposition and sublimation; and coalescence, riming, and aggregation. To evaluate the model's performance, a 2-D large-eddy simulation of a cumulonimbus was conducted, and the life cycle of a cumulonimbus typically observed in nature was successfully reproduced. The mass–dimension and velocity–dimension relationships the model predicted show a reasonable agreement with existing formulas. Numerical convergence is achieved at a super-particle number concentration as low as 128 per cell, which consumes 30 times more computational time than a two-moment bulk model. Although the model still has room for improvement, these results strongly support the efficacy of the particle-based modeling methodology to simulate mixed-phase clouds.