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Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

Journal of advances in modeling earth systems, 2020-08, Vol.12 (8), p.n/a

2020

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MODELING OF CLOUD MICROPHYSICS: Can We Do Better?

Bulletin of the American Meteorological Society, 2019-04, Vol.100 (4), p.655-672

2019

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Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions

Advances in atmospheric sciences, 2023-05, Vol.40 (5), p.747-790

2023

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Numerical Convergence of Shallow Convection Cloud Field Simulations: Comparison Between Double‐Moment Eulerian and Particle‐Based Lagrangian Microphysics Coupled to the Same Dynamical Core

Journal of advances in modeling earth systems, 2018-07, Vol.10 (7), p.1495-1512

2018

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Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence

Journal of the atmospheric sciences, 2013-09, Vol.70 (9), p.2768-2777

2013

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Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method

Geoscientific Model Development, 2023-11, Vol.16 (21), p.6211-6245

2023

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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

Geoscientific Model Development, 2020-09, Vol.13 (9), p.4107-4157

2020

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A grid refinement study of trade wind cumuli simulated by a Lagrangian cloud microphysical model: the super‐droplet method

Atmospheric science letters, 2017-09, Vol.18 (9), p.359-365

2017

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Response of high-altitude clouds to the galactic cosmic ray cycles in tropical regions

Frontiers in earth science (Lausanne), 2023-07, Vol.11

2023

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NHM-Chem, the Japan Meteorological Agency's Regional Meteorology – Chemistry Model: Model Evaluations toward the Consistent Predictions of the Chemical, Physical, and Optical Properties of Aerosols

Journal of the Meteorological Society of Japan. Ser. II, 2019, Vol.97(2), pp.337-374

2019

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Progress and Challenges in Modeling Dynamics–Microphysics Interactions: From the Pi Chamber to Monsoon Convection

Bulletin of the American Meteorological Society, 2022-05, Vol.103 (5), p.E1413-E1420

2022

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Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables

Geoscientific Model Development, 2021-04, Vol.14 (4), p.2235-2264

2021

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Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model

Nonlinear processes in geophysics, 2017-09, Vol.24 (3), p.553-567

2017

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Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0

Geoscientific Model Development, 2024-09, Vol.17 (17), p.6761-6774

2024

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Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1

Geoscientific Model Development, 2024-07, Vol.17 (13), p.5167-5189

2024

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On the CCN (de)activation nonlinearities

Nonlinear processes in geophysics, 2017-09, Vol.24 (3), p.535-542

2017

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Progress and Challenges in Modeling Dynamics–Microphysics Interactions: From the Pi Chamber to Monsoon Convection

Bulletin of the American Meteorological Society, 2022-05, Vol.103 (5), p.1413

2022

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Rotating Spirals without Phase Singularity in Reaction-Diffusion Systems

Progress of theoretical physics. Supplement, 2003-01, Vol.150, p.115-125

2003

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Rotating spiral waves with phase-randomized core in nonlocally coupled oscillators

Physical review. E, Statistical, nonlinear, and soft matter physics, 2004-03, Vol.69 (3 Pt 2), p.036213-036213, Article 036213

2004

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Various oscillation patterns in phase models with locally attractive and globally repulsive couplings

Physical review. E, Statistical, nonlinear, and soft matter physics, 2015-10, Vol.92 (4), p.042922-042922, Article 042922

2015

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Impacts of Stochastic Coalescence Variability on Warm Rain Initiation Using Lagrangian Microphysics in Box and Large-Eddy Simulations

Journal of the atmospheric sciences, 2024-06, Vol.81 (6), p.1067-1093

2024

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Mean-Field Theory Revives in Self-Oscillatory Fields with Non-Local Coupling

Progress of theoretical physics. Supplement, 2006-01, Vol.161 (161), p.127-143

2006

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Corrigendum to: A grid refinement study of trade wind cumuli simulated by a Lagrangian cloud microphysical model: the super‐droplet method

Atmospheric science letters, 2018-06, Vol.19 (6), p.n/a

2018

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MODELING OF CLOUD MICROPHYSICS: Can We Do Better? The Lagrangian particle-based approach is an emerging technique to model cloud microphysics and its coupling with dynamics, offering significant advantages over Eulerian approaches typically used in cloud models

Bulletin of the American Meteorological Society, 2019-04, Vol.100 (4), p.655

2019

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Visualization of the Cloud and Rainfall Simulation with Super-droplet Method

Journal of the Visualization Society of Japan, 2006/09/15, Vol.26(Supplement2), pp.27-28

2006

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Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

MODELING OF CLOUD MICROPHYSICS: Can We Do Better?

Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions

Numerical Convergence of Shallow Convection Cloud Field Simulations: Comparison Between Double‐Moment Eulerian and Particle‐Based Lagrangian Microphysics Coupled to the Same Dynamical Core

Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence

Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method

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

A grid refinement study of trade wind cumuli simulated by a Lagrangian cloud microphysical model: the super‐droplet method

Response of high-altitude clouds to the galactic cosmic ray cycles in tropical regions

NHM-Chem, the Japan Meteorological Agency's Regional Meteorology – Chemistry Model: Model Evaluations toward the Consistent Predictions of the Chemical, Physical, and Optical Properties of Aerosols

Progress and Challenges in Modeling Dynamics–Microphysics Interactions: From the Pi Chamber to Monsoon Convection

Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables

Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model

Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0

Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1

On the CCN (de)activation nonlinearities

Progress and Challenges in Modeling Dynamics–Microphysics Interactions: From the Pi Chamber to Monsoon Convection

Rotating Spirals without Phase Singularity in Reaction-Diffusion Systems

Rotating spiral waves with phase-randomized core in nonlocally coupled oscillators

Various oscillation patterns in phase models with locally attractive and globally repulsive couplings

Impacts of Stochastic Coalescence Variability on Warm Rain Initiation Using Lagrangian Microphysics in Box and Large-Eddy Simulations

Mean-Field Theory Revives in Self-Oscillatory Fields with Non-Local Coupling

Corrigendum to: A grid refinement study of trade wind cumuli simulated by a Lagrangian cloud microphysical model: the super‐droplet method

MODELING OF CLOUD MICROPHYSICS: Can We Do Better? The Lagrangian particle-based approach is an emerging technique to model cloud microphysics and its coupling with dynamics, offering significant advantages over Eulerian approaches typically used in cloud models

Visualization of the Cloud and Rainfall Simulation with Super-droplet Method

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