Yin, C. Z., S.-I. Shima, C. S. Lu, S. N. Gao, and X. Q. Xu, 2025: Resolving entrainment–mixing in marine stratocumulus: The role of LES grid resolution and super-droplet number. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-025-5043-z.
Citation: Yin, C. Z., S.-I. Shima, C. S. Lu, S. N. Gao, and X. Q. Xu, 2025: Resolving entrainment–mixing in marine stratocumulus: The role of LES grid resolution and super-droplet number. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-025-5043-z.

Resolving Entrainment–Mixing in Marine Stratocumulus: The Role of LES Grid Resolution and Super-Droplet Number

  • Marine stratocumulus clouds profoundly affect Earth’s energy budget by reflecting solar radiation over extensive oceanic areas. Yet, after using a large-eddy simulation (LES) and a Lagrangian microphysics scheme (Super-Droplet Method, SDM) for entrainment-mixing studies, uncertainty remains in the grid resolution and super-droplet number concentration (SDNC) required for accurate homogeneity capture. This study analyzes the homogeneous mixing degree (HMD) and the Damkohler number ( Da ) in stratocumulus using an LES with SDM, from microphysical and dynamical perspectives, respectively. Results show that HMD and Da both display a top-to-base gradient, with more intense inhomogeneity near the cloud top and relatively homogeneous conditions toward the base, although the upper region is more complex. Even at a fine horizontal resolution of 12.5 m and vertical resolution of 2.5 m, HMD remains sensitive and does not converge, whereas Da converges at coarser grid spacings (up to horizontal and vertical spacings of 25 m and 10 m, respectively) in the mid-cloud region. Similarly, HMD requires an SDNC well above 128 per cell for near-complete convergence, while Da converges once SDNC exceeds about 16 per cell. This difference arises because HMD depends on microphysical details, thereby demanding a high SDNC to capture local droplet inhomogeneities, whereas Da reflects turbulence–evaporation timescales that converge more readily once extreme droplet gradients are resolved. We further find that HMD and Da exhibit a significant negative correlation, with stronger anti-correlations emerging under finer spatial resolutions, reinforcing their complementary roles in diagnosing mixing regimes. Overall, these findings provide guidelines for selecting numerical configurations in entrainment–mixing simulations, ensuring that both turbulence-driven and microphysical processes are adequately resolved.
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