文献类型：期刊文献

英文题名：Data Analyses and Parallel Optimization of the Tropical-Cyclone Coupled Numerical Model

作者：Wang, Yanqiang[1,2]; Zhang, Tianyu[3]; Yin, Zhaohui[4]; Hao, Sai[1]; Wang, Chenqi[1]; Lin, Bo[1]

机构：[1] National Marine Environmental Forecasting Center, Beijing, 100081, China; [2] College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China; [3] Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department of Education of Guangdong Province, Guangdong Ocean University, Zhanjiang, 54008, China; [4] Baidu Inc., Beijing, 10105, China

年份：2022

卷号：1628 CCIS

起止页码：17

外文期刊名：Communications in Computer and Information Science

收录：EI(收录号：20223512666686)

基金：Acknowledgments. We thank Dr. Yunfei Zhang and Dr. Xiang Li from the National Marine Environmental Forecasting Center for setting up the coupling modeling system and their valuable suggestions on this work. This research is supported by the National Natural Science Foundation of China (41976200) and the project of Guangdong Ocean University (060302032106). We acknowledge the comments of three anonymous reviewers.

语种：英文

外文关键词：Air - Hurricanes - Numerical models - Tropics

外文摘要：Tropical cyclones (TCs) are one of the most feared and deadly weather systems in the world. An air-sea coupled numerical model offers a more accurate description of physical processes between atmospheric-ocean fluids. An operational ocean-atmosphere-wave coupled modeling system is employed to improve the prediction accuracy of tropical cyclones in the National Marine Environmental Forecasting Center (NMEFC). Due to the urgent need for operational timeliness, the parallel performance of the operational forecasting system has been analyzed. The parallel algorithm, parallel partitioning grids, and other optimizations were tested after system deployment on the Lenovo cluster of the NMEFC. After optimization, a well-balanced performance of the system is obtained, and computing resources are reasonably utilized, thus laying the foundation for real-time tropical cyclone forecasting. ? 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.