島 伸一郎

Abstract Recent aircraft observations of marine stratocumulus clouds consistently showed that cloud microphysical relationships vary with altitude, indicating inhomogeneous mixing characteristics near cloud top and homogeneous mixing characteristics in mid‐levels of clouds. Here, we conduct model intercomparison of an idealized, non‐precipitating stratocumulus cloud to evaluate model consistency and examine whether simulations can reproduce the observed mixing characteristics. The results show that eleven large‐eddy simulations with various dynamics and microphysics schemes show good agreement on the thermodynamical, microphysical, and dynamical properties of the stratocumulus‐topped boundary layer in a steady state. The inter‐model spread in steady‐state liquid water path is significantly reduced compared to previous model intercomparison studies. This improvement might be due to better models and more consistent initial conditions than those used decades ago. In addition, most simulations, including a low‐dimensional simulation, capture inhomogeneous mixing characteristics near the cloud top and homogeneous mixing characteristics inside the cloud. Moreover, simulations using Lagrangian microphysics schemes agree better with the observed mixing characteristics compared with those using the bin microphysics schemes. Since most simulations do not fully resolve the entrainment process, the apparent mixing characteristics arise from the variations in the resolved cloud properties. Our results support the vertical circulation mixing hypothesis, which suggests that homogeneous mixing characteristics in mid‐levels of clouds are due to the vertical circulation of entrainment‐affected and diluted parcels from the cloud top moved to lower levels.

Abstract. Models are universally challenged to accurately predict the coupled microphysical, turbulent and radiative processes within widespread, long-lived marine cold-air outbreak (CAO) cloud fields, which leads to biases and uncertainties in atmospheric predictions over all time scales. Here we assemble a suite of ground-based and satellite measurements to initialize and constrain large-eddy simulations (LES) of cloud field evolution with distance downwind from the marginal ice zone during a strong, highly supercooled and convective CAO observed during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). Detailed LES results are compared with large-scale models run in single-column model (SCM) mode, providing an observation-constrained framework for large-scale model evaluation and future improvements. All models reproduce rapid cloud formation off the ice edge, and a monotonic ascent of downwind cloud-top heights that is well correlated with time-integrated surface heat fluxes. LES generally reproduce domain-mean observational targets using a modest test domain (25 x 25 km2), and a larger domain (125 x 125 km2) enables better reproducing the observed growth of convective cell sizes. In realistic mixed-phase LES compared with liquid-only simulations, ice processes lead to thinner, broken cloud decks and substantially reduced cloud radiative effects on top-of-atmosphere longwave fluxes. By contrast, mixed-phase SCM simulations generally underpredict the impact of ice on radiative fluxes, primarily owing to insufficient reduction of cloud cover. Results indicate that cellular cloud structure is qualitatively captured by LES, and thus LES could provide guidance to improvement of large-scale model physics schemes. Follow-on work will extend these results to larger domains, apply objective analysis of mesoscale structure, and include prognostic aerosol properties for droplet and heterogeneous ice formation.

Abstract. Understanding the complete lifecycle of cloud hydrometeors is fundamental to advancing cloud microphysics, yet a formally documented and computationally efficient framework for tracking individual particles through complex processes like coalescence within parallelized cloud models has been lacking. This study addresses this methodological gap by presenting the detailed design, implementation, and application of two complementary super-droplet tracking algorithms—a backward "lineage" tracking algorithm and a forward "tagging" tracking algorithm—developed within a Large-Eddy Simulation model coupled with the Super-Droplet Method (SDM). The backward algorithm establishes a direct historical link for every super-droplet, enabling efficient Ο(1) lookup for reconstructing a particle's complete microphysical history. The forward algorithm employs a stratified random sampling method to select and assign persistent identifiers to a representative cohort of super-droplets, allowing for detailed prognostic analysis with manageable data storage costs. A key feature of both algorithms is the comprehensive method for recording and outputting detailed information on coalescence events. The utility and power of these algorithms are demonstrated in a case study of marine stratocumulus. The framework enabled a quantitative, process-level validation of the critical 15–20 µm radius range for the onsite of efficient warm rain initiation. Furthermore, the lineage-tracing capability mechanistically confirmed the classical formation pathway of large droplets within cloud-base updrafts, directly linking large-scale turbulent structures to the lifecycle of individual precipitation embryos. In conclusion, the tracking algorithms presented here provide the scientific community with a powerful and versatile toolset to investigate the intricate lifecycle of cloud particles with unprecedented detail and offer a robust methodology for evaluating and improving microphysical parameterizations in larger-scale weather and climate models.

Mixed-phase clouds, composed of supercooled liquid droplets and ice crystals, play a critical role in weather and climate systems. Their complex microphysical interactions and coupling with turbulence at microscales govern the cloud properties at macroscales, yet remain challenging to observe and quantify under atmospheric conditions. This model intercomparison study utilizes ten model configurations to simulate mixed-phase cloud evolution in the Michigan Technological University's Pi Chamber. The models span a range of frameworks, including box models, direct numerical simulation, and large-eddy simulation models, and incorporate both bin and Lagrangian microphysics. Each model was tuned to reproduce the observed liquid-phase steady state prior to ice injection. Ice particles were then introduced into the domain at various rates to examine cloud glaciation behavior. By the intercomparison design, all models successfully reproduced the observed mean droplet radius and number concentration during the liquid-phase stage. Increasing ice particle injection rates led to consistent qualitative trends across models: depletion of liquid water, reduced total water content, and a shift in particle size distributions toward larger radii. However, quantitative differences arose due to variations in model treatment in dynamics and microphysics, including subgrid-scale turbulence parameterizations, wall forcing, and particle removal parameterizations. Most models that simulate the full chamber retained liquid droplets near the lower boundary, where supersaturation forcing is strongest and droplets are replenished before mixing into the core region. These surviving liquids droplets were absent in simulations assuming a well-mixed domain, excluding the near-wall region, or using coarse grid spacing.