Atmospheric and Hydrospheric Sciences (A) | ||
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Session Sub-category | Atmospheric Sciences, Meteorology & Atmospheric Environment(AS) | |
Session ID | A-AS05 | |
Title | Weather, Climate, and Environmental Science Studies using High-Performance Computing | |
Short Title | Weather/Climate Studies using HPC | |
Main Convener | Name | Hisashi Yashiro |
Affiliation | National Institute for Environmental Studies | |
Co-Convener 1 | Name | Masuo Nakano |
Affiliation | Japan Agency for Marine-Earth Science and Technology | |
Co-Convener 2 | Name | Miyakawa Tomoki |
Affiliation | Atmosphere and Ocean Research Institute, The University of Tokyo | |
Co-Convener 3 | Name | Takuya Kawabata |
Affiliation | Meteorological Research Institute | |
Session Language |
E |
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Scope |
High-performance computing (HPC) is one of the important research infrastructures supporting Today's weather, climate, and environmental science studies. The computational performance of supercomputers such as the Earth Simulator, the K computer, and Fugaku makes it possible to achieve higher resolution, a wider computational domain, more ensemble calculations, and the use of more sophisticated physical processes. On the other hand, due to changes in computer trends, large-scale computations of weather and climate require closer collaboration with the computational science field. From FY2025, the design and development of Japan's next flagship machine following Fugaku have begun, and it is becoming increasingly essential to utilize computational accelerators such as GPUs. HPC is also showing its power in data science, and research on data assimilation methods using high-frequency/high-density observational big data and the combined use of AI technology has made remarkable progress in recent years. Furthermore, the 'digital twin' concept supported by these computational results is attracting attention as a large-scale system that includes data infrastructure development and social implementation. Co-hosted with the Meteorological Society of Japan, this session calls for research topics in weather, climate, and environmental science that focus on "computation," including numerical modeling, big data analysis, data assimilation, and AI technology. The participants can share future perspectives on atmospheric science research using HPC and the challenges to be addressed. |
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Presentation Format | Oral and Poster presentation | |
Invited Authors |
Marta Alerany Sole (Barcelona Supercomputing Center) Shao-Yu Tseng (National Taiwan University) Chihiro Kodama (Japan Agency for Marine-Earth Science and Technology) Bertrand Rouet-Leduc (Kyoto University) Ya Ling Li (National Defense University) Jiah Jang |
Time | Presentation No | Title | Presenter |
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Oral Presentation May 28 PM1 | |||
13:45 - 14:00 | AAS05-01 | Earth system model replicability - Statistical validation of a model's climate under a change of computing environment | Kai Keller |
14:00 - 14:15 | AAS05-02 | Scalar metrics for evaluating the scientific skill of Earth System Models | Marta Alerany Sole |
14:15 - 14:30 | AAS05-03 | Projecting future snow changes at kilometer scale for adaptation using machine learning and a CMIP6 multi-model ensemble | Alessandro Damiani |
14:30 - 14:45 | AAS05-04 | The Dependence of Tropical Cyclone Seed Genesis on Convection Aggregation Stages | Shao-Yu Tseng |
14:45 - 15:00 | AAS05-05 | Thermodynamics-Convection Coupling and Precipitation Characteristics In Global Km-scale Simulations | Daisuke Takasuka |
15:00 - 15:15 | AAS05-06 | Local Clustering of Inertial Cloud Droplets in Non-Equilibrium Turbulence | Taketo Tominaga |
Oral Presentation May 28 PM2 | |||
15:30 - 15:45 | AAS05-07 | Efforts in the Field of Weather and Climate towards Next-Generation Supercomputing Infrastructures around 2030 | Chihiro Kodama |
15:45 - 16:00 | AAS05-08 | Evaluating FourCastNet with High-Resolution Data, Varied Internal Resolutions, and Data Conversion | Aihisa KAMIJO |
16:00 - 16:15 | AAS05-09 | Tropical cyclone seasonal hindcast by a Neural-Physics hybrid AGCM | Masuo Nakano |
16:15 - 16:30 | AAS05-10 | Detection of methane emissions in satellite data at large scale using deep learning | Bertrand Rouet-Leduc |
16:30 - 16:45 | AAS05-11 | Modelling and Analysis of heat stress over an Urban city in India | Abhinav Utpal |
Presentation No | Title | Presenter |
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Poster Presentation May 28 PM3 | ||
AAS05-P01 | Dynamically computed characteristic adjustment time scale for Zhang-McFarlane convective parameterization scheme | Minghao Wang |
AAS05-P02 | The Effects of Increasing the Coupling Frequency and Considering the Sublayer Temperature on the Simulation by CAS-ESM2 | Xiao Dong |
AAS05-P03 | Asymmetrical Responses of the ITCZ to Symmetrical Thermal Forcings at Different Latitudes | Shuyun Zhao |
AAS05-P04 | Downstream and upstream effects of urban chains on precipitation in Beijing | Jingjing Dou |
AAS05-P05 | Case Study on the Characteristics of the Atmospheric Boundary Layer in Taipei and Yilan of Northern Taiwan during Winter | PEI-DI JENG |
AAS05-P06 | Wind and Wave Forecasting in the Taiwan Strait: Assessing UFS and GFS Models Through the 2022 Kinmen Shipwreck Case | Ya Ling Li |
AAS05-P07 | Case Simulation Study and Adaptation Methods for the Spread of Dengue Fever in Taiwan | JOU PING HOU |
AAS05-P08 | Preliminary Study on Constructing Grid-Based Meteorological Data for Taiwan Using Machine Learning Models | Yu-Chi Wang |
AAS05-P09 | Enhancement of Precipitation Mapping Accuracy in the Korean Peninsula using AI and Multi-source Dataset | Hyoju Park |
AAS05-P10 | Spatial Analysis and Modeling of Methane Emissions from Rice Paddies Using Machine Learning Based on Satellite Data and Ground Observation | Jiah Jang |
AAS05-P11 | Toward investigation of the potential impact of the single Phased Array Weather Radar observation on a forecast for the July 2020 rainfall event | Yasumitsu Maejima |
AAS05-P12 | The spatial distribution of the influence of the vertical structure of aerosol climatology in ICON model in cloudless conditions. | Aleksei Poliukhov |
AAS05-P13 | Estimates of Dynamical Processes Contributions to Interhemispheric CO2 Transport | Guangyu LIU |
AAS05-P14 | Analyzing Trends in Carbon Monoxide and Tropospheric Formaldehyde Over the Ib River Catchment Using Sentinel-5P | LEELAMBAR SINGH |