Development of an Atmospheric Simulation Model
for Estimating the Probability of Local Atmospheric Phenomena

Scroll

Outline

For accurate estimation of the probability of weather phenomena that caused wind and flood damage.

Member

Seiya NISHIZAWA

PM & PI

Seiya NISHIZAWA

RIKEN

PI

Junshi ITO

Tohoku University

PI

Yuta KAWAI

RIKEN

Research Theme

Achievement

Presentation(Invited)

2025. 3. 7

Shin-ichiro Shima : 20th anniversary of the super-droplet method , ISEE Symposium Frontier of Space-Earth Environmental Research as Predictive Science
Presentation(Invited)

2025. 2. 21

Manhal Alhilali, Shin-ichiro Shima, Soumya Samanta, Thara Prabhakaran : Advancing the Super-Droplet Method for Deep Convective Cloud Microphysics : Recent Developments and Applications , Workshop on Science and Technology in High Reynolds Number Turbulence
Publication (peer-reviewed)

2025. 2. 7

Yuta Kawai, Hirofumi Tomita : Development of a high-order global dynamical core using the discontinuous Galerkin method for an atmospheric large-eddy simulation (LES) and proposal of test cases: SCALE-DG v0.8.0, Geoscientific Model Development , 18(3) 725-762, 2025, DOI : https://doi.org/10.5194/gmd-18-725-2025
Presentation(Invited)

2024. 12. 9

Shin-ichiro Shima, Wojciech Grabowski, Sylwester Arabas, Kamal Kant Chandrakar, Piotr Dziekan, Fabian Hoffmann, Emily de Jong, Hugh Morrison, Axel Seifert , Simon Unterstrasser : Progress and Prospects of Lagrangian Particle-Based Cloud Modeling , AGU24 Annual Meeting
Publication (peer-reviewed)

2024. 9. 12

Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, Huawei Yang : 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 , 17(17) 6761–6774, 2024, DOI : https://doi.org/10.5194/gmd-17-6761-2024
Presentation(Invited)

2024. 7. 15

Thara Prabhakaran : Microphysics of Convective Clouds : Progress on the Understanding and Challenges, International Conference on Clouds and Precipitation 2024
Publication (peer-reviewed)

2024. 7. 5

Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, Chunsong Lu : 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 , 17(13) 5167–5189, 2024, DOI : https://doi.org/10.5194/gmd-17-5167-2024
Publication (peer-reviewed)

2024. 6. 28

Hugh Morrison, Kamal Kant Chandrakar, Shin-Ichiro Shima, Piotr Dziekan, Wojciech W. Grabowski : Impacts of Stochastic Coalescence Variability on Warm Rain Initiation Using Lagrangian Microphysics in Box and Large-Eddy Simulations, Journal of the Atmospheric Sciences , 81(6) 1067-1093, DOI : https://doi.org/10.1175/JAS-D-23-0132.1
Publication (peer-reviewed)

2024. 5. 10

Seiya Nishizawa : Extracting Latent Variables From Forecast Ensembles and Advancements in Similarity Metric Utilizing Optimal Transport, Journal of Geophysical Research: Machine Learning and Computation, 1(2) 2024, DOI : https://doi.org/10.1029/2023JH000112
Presentation(Invited)

2024. 3. 15

Shin-ichiro Shima, Kotaro Enokido : Simulation of Pi chamber warm/mixed-phase experiments using the super-droplet method, 5th International Workshop on Cloud Turbulence, NiTech 2024, Japan
Presentation(Invited)

2024. 3. 15

Yu Kim, Shin-ichiro Shima : Wake-induced CCN-activation behind precipitation particles and its implementation to the super-droplet method, 5th International Workshop on Cloud Turbulence, NiTech 2024, Japan
Publication (peer-reviewed)

2023. 11. 2

Toshiki Matsushima, Seiya Nishizawa, Shin-ichiro Shima : Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method, Geoscientific Model Development, 16(21), 6211-6245, DOI : https://doi.org/10.5194/gmd-16-6211-2023
Publication (peer-reviewed)

2023. 10. 6

Takumi Tomioka, Yousuke Sato, Syugo Hayashi, Satoru Yoshida, Takeshi Iwashita : Advantage of bulk lightning models for predicting lightning frequency over Japan, Progress in Earth and Planetary Science, 10, Article number : 60 (2023), DOI : https://doi.org/10.1186/s40645-023-00592-w
Publication (peer-reviewed)

2023. 5. 4

Yousuke Sato, Mizuo Kajino, Syugo Hayashi, Ryuichi Wada : A numerical study of lightning-induced NOx and formation of NOy observed at the summit of Mt. Fuji using an explicit bulk lightning and photochemistry model, Atmospheric Environment:X, vol.18, 100218, DOI : https://doi.org/10.1016/j.aeaoa.2023.100218
Publication (peer-reviewed)

2023. 3. 13

Yuta Kawai, Hirofumi Tomita : Numerical Accuracy Necessary for Large-Eddy Simulation of Planetary Boundary Layer Turbulence using Discontinuous Galerkin Method, Monthly Weather Review, 151(6), 1479-1508, DOI : https://doi.org/10.1175/MWR-D-22-0245.1
Presentation(Invited)

2023. 3. 1

Shin-ichiro Shima : Super-Droplet Method and its Application to Mixed-Phase Clouds, Batsheva de Rothschild Seminar on Cloud-Climate Interactions Across Scales
Presentation(Invited)

2022. 11. 24

Sachiho A. Adachi : Dynamical Downscaling Methods for Regional Climate Studies, No.7 Asian Conference on meteorology 2022