An AI-Enhanced 1km-Resolution Seamless Global Weather and Climate Model to Achieve Year-Scale Simulation Speed using 34 Million Cores

Global Storm Resolving Models (GSRMs) is crucial for understanding extreme weather events under the climate change background. In this study, we optimize Global-Regional Integrated Forecast System (GRIST), which is a unified weather-climate modeling system designed for research and operation, for the next-generation Sunway supercomputer, incorporating AI-enhanced physics suite, OpenMP-based parallelization, and mixed-precision optimizations to enhance both efficiency and performance portability, as well as the unified modeling capability. Our experiments successfully capture significant events during the "23.7" extreme rainfall over northern China influenced by super Typhoon Doksuri, at 1km resolution. Notably, our work scales to 34 million cores, enabling simulation speeds at 491 SDPD (3km) and 181 SDPD (1km).

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Publication Details

Published
2025-02-28
DOI
https://doi.org/10.1145/3710848.3710893
Citations
3
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
3.90
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article

An AI-Enhanced 1km-Resolution Seamless Global Weather and Climate Model to Achieve Year-Scale Simulation Speed using 34 Million Cores

Yilun Han, Xiaohui Duan, Yi Zhang, Wenguang Chen et al.
3 citations
Meteorological Phenomena and Simulations
3.90
article

An AI-Enhanced 1km-Resolution Seamless Global Weather and Climate Model to Achieve Year-Scale Simulation Speed using 34 Million Cores

Yilun Han, Xiaohui Duan, Yi Zhang, Wenguang Chen, Jiale Hou, Dongqiang Huang, Zhao Jing, Haohuan Fu, Kai Xu, Yiming Wang, Haopeng Huang, Siyuan Chen, Wei Xue, Zhuang Liu, Hailong Liu, Weiguo Liu, Bin Yang, Zhuangzhuang Zhou, Maoxue Yu, Lixin Wu, Huimin An, Xiting Ju, Bowen Yan, Jian Li, Chenyu Wang
article en
3 citations

Abstract

Global Storm Resolving Models (GSRMs) is crucial for understanding extreme weather events under the climate change background. In this study, we optimize Global-Regional Integrated Forecast System (GRIST), which is a unified weather-climate modeling system designed for research and operation, for the next-generation Sunway supercomputer, incorporating AI-enhanced physics suite, OpenMP-based parallelization, and mixed-precision optimizations to enhance both efficiency and performance portability, as well as the unified modeling capability. Our experiments successfully capture significant events during the "23.7" extreme rainfall over northern China influenced by super Typhoon Doksuri, at 1km resolution. Notably, our work scales to 34 million cores, enabling simulation speeds at 491 SDPD (3km) and 181 SDPD (1km).

Qinghai University (CN), Shandong University (CN), Tianjin University (CN), Nanjing University of Information Science and Technology (CN), National Supercomputing Center in Shenzhen (CN), Chinese University of Hong Kong, Shenzhen (CN), Chinese Academy of Meteorological Sciences (CN), National Supercomputing Center in Wuxi (CN), Laoshan Laboratory, Tsinghua University (CN)
Climate action
Openalex Percentile: Top 8%
Meteorological Phenomena and Simulations
3.90
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