Ryo Onishi

Influence of gravity on collisions of monodispersed droplets in homogeneous isotropic turbulence

This paper studies the gravity influence on collisions of monodispersed droplets in homogeneous isotropic turbulence by means of direct numerical simulations (DNSs). The DNS results show that, in certain Stokes and Reynolds regimes, collision frequencies are significantly reduced in the presence of gravity. Those decreases are mainly attributable to the decrease in the droplet relative velocity, since the change in radial distribution function—often referred to preferential concentration—is small. Further analysis of the results reveals that droplet sedimentation due to gravity shortens the droplet-fluid interaction time, consequently weakening the relative motions between droplets. These observations lead to an analytical model that can be used to estimate the velocity fluctuations of sedimenting particles under gravity. Utilizing this model, we constructed a further analytical model for estimating the gravitational influence on collisions. Given flow and particle parameters, the model calculates the rat...

A Warm-Bin-Cold-Bulk Hybrid Cloud Microphysical Model*

This study describes a newly developed bin‐bulk hybrid cloud microphysical model named MSSG-Bin, which has been implemented in the Multi-Scale Simulator for the Geoenvironment (MSSG). In the hybrid approach, a spectral bin scheme is used for liquid droplets, while a bulk scheme is used for solid particles. That is, the expensive but more reliable spectral bin scheme treats the relatively well-understood physics of the liquid phase, and the computationally efficient but less robust bulk scheme is used to treat the poorly understood physics of the ice phase. In the bulk part, the prognostic variables are the mixing ratios of cloud ice, snow, and graupel and the number density of cloud ice particles. The bulk component is consistent with MSSG-Bulk, which is a conventional bulk model implemented in MSSG. One-dimensional kinetic simulations and three-dimensional cloud simulations have confirmed the reliability of MSSG-Bin for warm clouds, free from the approximations made in bulk parameterizations, and its applicability to cold clouds, without the significant additional costs required for a bin treatment of the ice phase. Compared with MSSG-Bulk, MSSGBin with 33 bins requires 8.3 times more floating-point operations for a one-dimensional shallow convection case, and 4.9 times more for a three-dimensional shallow convection case. Present results have shown the feasibility of using this model for a 25-m-resolution simulation of shallow cumulus on a 512 3 512 3 200 grid.

Large-scale forcing with less communication in finite-difference simulations of stationary isotropic turbulence

This study proposes a new forcing scheme suitable for massively-parallel finite-difference simulations of stationary isotropic turbulence. The proposed forcing scheme, named reduced-communication forcing (RCF), is based on the same idea as the conventional large-scale forcing scheme, but requires much less data communication, leading to a high parallel efficiency. It has been confirmed that the RCF scheme works intrinsically in the same manner as the conventional large-scale forcing scheme. Comparisons have revealed that a fourth-order finite-difference model run in combination with the RCF scheme (FDM-RCF) is as good as a spectral model, while requiring less computational costs. For the range 80

Lagrangian Tracking Simulation of Droplet Growth in Turbulence-Turbulence Enhancement of Autoconversion Rate*

AbstractThe authors describe the Lagrangian cloud simulator (LCS), which simulates droplet growth in air turbulence. The LCS adopts the Euler–Lagrangian framework and can provide reference data for cloud microphysical models by tracking the growth of particles individually. The collisional growth in a stagnant flow is calculated by the LCS and also by solving the stochastic collision–coalescence equation (SCE). Good agreement is obtained between the LCS and SCE simulations. Comparisons between the results for stagnant and turbulent flows confirm that in-cloud turbulence enhances collisional growth. The enhancement is well predicted by the SCE method if a proper collision model is employed. To quantify the enhancement, the paper defines the time scale of the autoconversion process, in which cloud droplets grow into raindrops through collisions, as the time taken for 10% of the cloud to become rain (t10%). The authors then define the turbulence enhancement factor Eturb as , where the overbar denotes the mea...

Influence of Microscale Turbulent Droplet Clustering on Radar Cloud Observations

This study investigates the influence of microscale turbulent clustering of cloud droplets on the radar reflectivity factor and proposes a new parameterization to account for it. A three-dimensional direct numerical simulationofparticle-ladenisotropicturbulenceisperformedtoobtainturbulentclusteringdata.Theclusteringdata arethenusedtocalculatethepowerspectraofdropletnumberdensityfluctuations,whichshowadependenceon the Taylor microscale-based Reynolds number (Rel) and the Stokes number (St). First, the Reynolds number dependency of the turbulent clustering influence is investigated for 127 , Rel , 531. The spectra for this wide range of Rel values reveal that Rel 5 204 is sufficiently large to be representative of the whole wavenumber range relevant for radar observations of atmospheric clouds. The authors then investigate the Stokes number dependencyforRel5204andproposeanempiricalmodelfortheturbulentclusteringinfluenceassumingpower laws for the number density spectrum. For Stokes numbers less than 2, the proposed model can estimate the influence of turbulenceonthe spectrumwith an RMS errorless than 1dB when calculated over thewavenumber range relevant for radar observations. For larger Stokes number droplets, the model estimate has larger errors, but the influence of turbulence is likely negligible in typical clouds. Applications of the proposed model to two idealized cloud observing scenarios reveal that microscale turbulent clustering can cause a significant error in estimating cloud droplet amounts from radar observations with microwave frequencies less than 13.8 GHz.

Seamless Simulations in Climate Variability and HPC

Multi-Scale Simulator for the Geoenvironment (MSSG), which is a coupled non-hydrostatic atmosphere-ocean-land model, has been developed in the Earth simulator Center. Outline of MSSG is introduced and characteristics are presented. After optimizing computational performance of MSSG, performance analysis has been performed on the Earth Simulator. As the results of optimization, ultra high performance with MSSG has been achieved. Computational performance of the coupled non-hydrostatic atmosphere-ocean-land model has attained 52–55% of theoretical peak performance. Furthermore, results from preliminary validations including forecasting experiments are presented.

Impact of Coupled Nonhydrostatic Atmosphere-Ocean-Land Model with High Resolution

This chapter presents basic formulation of Multi-Scale Simulator for the Geoenvironment (MSSG) which is a coupled non-hydrostatic AGCM-OGCM developed in Earth Simulator Center. MSSG is characterized by Yin-Yang grid system for both of the components, computational schemes with high accuracy in the dynamical core and high computational performance on the Earth Simulator. In particular some preliminary results from 120-h forecast experiments with MSSG are presented.

Global 7-km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): Experimental design and preliminary results

Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ∼ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIPG7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.

MJO simulation in a cloud‐system‐resolving global ocean‐atmosphere coupled model

An observed Madden–Julian Oscillation (MJO) propagating from the central Indian Ocean to the western Pacific from 15 December 2006 to 10 January 2007 was successfully simulated by a cloud-system-resolving global ocean–atmosphere coupled model without parameterization of cumulus convection. We found that the ocean coupling has significant impacts on the MJO simulation; e.g. strength of the moisture convergence, and the timing and strength of the westerly wind burst over the Maritime Continent. The model also generally well simulated the decay of the MJO in the western Pacific, as well as the changes in sea surface temperature. These results demonstrate that the cloud-system-resolving global ocean-atmosphere coupled model can be used for realistic MJO simulation.

Laboratory Measurements of Heat Transfer and Drag Coefficients at Extremely High Wind Speeds

AbstractHeat and momentum transfer across the wind-driven breaking air–water interface at extremely high wind speeds was experimentally investigated using a high-speed wind-wave tank. An original m...