戴国锟

副教授

daigk@fudan.edu.cn

021-31248857

研究兴趣

中纬度天气气候可预测性，北极与中纬度天气气候的联系，人工智能在大气科学中的应用

教育背景

2008年9月-2012年7月，南京信息工程大学，理学学士

2012年9月-2017年7月，中国科学院大气物理研究所，理学博士

研究经历

2017年6月—2021年5月，复旦大学，博士后

2021年6月—2023年12月，复旦大学，青年副研究员

2023年10月—2024年10月，欧洲中期天气预报中心，访问学者

2024年1月—至今，复旦大学，副教授

承担课题

 1. 冬季北极平流层初始不确定性对欧亚极端冷事件次季节可预报性的影响，国家自然科学基金面上项目，2025.1-2028.12，主持（在研）

 2. 基于增长型初始扰动分布最优估计的台风智能集合预报研究，上海市教育委员会人工智能促进科研范式改革赋能学科跃升计划项目，2025.1-2025.12，主持（已结题）

 3. 北极海-冰-气系统和热带海-气系统的相互作用及其与全球变换的联系，科技部重点研发项目，2023.1-2027.12，课题骨干（在研）

 4. 冬季北极对流层快速增温事件对中纬度极端低温事件对影响及机理研究，国家自然科学基金青年项目，2021.1-2023.12，主持（已结题）

 5. 北极海-冰-气系统对欧亚大陆冬季极端天气事件可预报性的影响，国家自然科学基金重大项目，2018.1-2022.12，课题骨干（已结题）

教学经历

2025年—至今，天气分析与预报，本科生课程，复旦大学大气与海洋科学系

2023年，Fortran语言程序设计，本科生课程，复旦大学大气与海洋科学系

2025年—至今，现代天气学，研究生课程，复旦大学大气与海洋科学系

2021年—至今，可预报性、资料同化和集合预报，研究生课程，复旦大学大气与海洋科学系

出版专著

穆穆, 徐辉,戴国锟, 张坤. 2025. 条件非线性最优扰动及其在大气-海洋研究中的应用. 北京: 科学出版社, ISBN 978-7-03-081765-5.

发表论文

（本人名称加粗，通讯作者加*号）

Han, Z., Duan, W.^*, Dai, G.^*, Li, S., Chen, B., & Hou, Y. (2026). The “predictability barrier” phenomenon of winter extreme cold events in central and eastern China and mechanisms of error amplification. Geophysical Research Letters, 53(5), e2025GL120069.

Li, Z., Mu, M., & Dai, G.^* (2025). Effect of stratospheric temperature perturbation on the onset of Ural blocking events in winter. Quarterly Journal of the Royal Meteorological Society, e5000.

Li, Z., Dai, G.^* & Mu, M. (2024). Effects of stratospheric warming on Ural blocking events in winter. Journal of Geophysical Research: Atmospheres, 129(2), e2023JD039672.

Mu, M., Qin, B., & Dai, G.^* (2024). A commentary of “Artificial intelligence models bring new breakthroughs in global accurate weather forecasting”: Top 10 Scientific Advances of 2023, China. Fundamental Research, 4(3), 690-692.

Dai, G., Ma, X., Mu, M.^*, Han, Z., Li, C., Jiang, Z., & Zhu, M. (2023). Optimal Arctic sea ice concentration perturbation in triggering Ural blocking formation. Atmospheric Research, 289, 106775.

Han, Z., Dai, G.^*, Mu, M., Li, C., Li, S., Ma, X., & Zhu, M. (2023). Extent of the impact of Arctic atmospheric uncertainty on extended-range forecasting of cold events in East Asia. Journal of Geophysical Research: Atmospheres, 128(9), e2022JD037187.

Li, C., Dai, G.^*, Mu, M., Han, Z., Ma, X., Jiang, Z. Zheng, J. & Zhu, M. (2023). Influence of Arctic sea-ice concentration on extended-range forecasting of cold events in East Asia. Advances in Atmospheric Sciences, 40(12), 2224-2241.

Dai, G., Mu, M.^*, Han, Z., Li, C., Jiang, Z. Zhu, M. & Ma, X. (2023). The Influence of Arctic Sea Ice Concentration on Subseasonal Prediction of the North Atlantic Oscillation Event. Advances in Atmospheric Sciences, 40(12), 2242-2261.

Gao, Y., Mu, M., & Dai, G.^* (2023). Targeted observations on Arctic sea ice concentration for improving extended-range prediction of Ural Blocking. Journal of Geophysical Research: Atmospheres, 128(22), e2023JD039630.

Dai, G., Li, C., Han Z.^*, Luo, D., & Yao, Y. (2022). The nature and predictability of the East Asian extreme cold events of 2020/21. Advances in Atmospheric Sciences, 39, 566-575.

Dai, G., Mu, M.^*, Li, C., Han, Z., & Wang, L. (2021). Evaluation of the Forecast Performance for Extreme Cold Events in East Asia with Subseasonal-to-Seasonal Datasets from ECMWF. Journal of Geophysical Research: Atmospheres, 126(1), e2020JD033860.

Dai, G., Mu, M.^*, & Wang, L. (2021). The Influence of Sudden Arctic Sea-Ice Thinning on North Atlantic Oscillation Events. Atmosphere-Ocean, 59(1), 39-52.

Dai, G., & Mu, M.^* (2020). Influence of the Arctic on the predictability of Eurasian winter extreme weather events. Advances in Atmospheric Sciences, 37(4), 307-317.

Dai, G., & Mu, M.^* (2020). Arctic Influence on the Eastern Asian Cold Surge Forecast: A Case Study of January 2016. Journal of Geophysical Research: Atmospheres, 125(23), e2020JD033298.

Dai, G., Mu, M., & Jiang, Z. (2019). Evaluation of the forecast performance for North Atlantic Oscillation onset. Advances in Atmospheric Sciences, 36(7), 753-765.

Dai, G., Mu, M., & Jiang, Z. (2019). Targeted Observations for Improving Prediction of the NAO Onset. Journal of Meteorological Research, 33(6), 1044-1059.

Dai, G., Mu, M., & Jiang, Z.^* (2016). Relationships between optimal precursors triggering NAO onset and optimally growing initial errors during NAO prediction. Journal of the Atmospheric Sciences, 73(1), 293-317.

Hu, X., Jiang, Z., Li, Y., Dai, G., & Ma, L. (2026). Abrupt Arctic sea ice decline on synoptic timescales during summer: Physical processes and background climate impacts. Journal of Meteorological Research, 40(1), 138–155

Ji, C., Mu, M., Qin, B.^*, Lian, T., Yuan, S., Feng, J., Song, X., Wei, Y., Dai, G., Wang, J., & Fang, X.^* (2025). Toward skillful forecasting of super El Niño events using a diffusion-based westerly wind burst parameterization. npj Climate and Atmospheric Science, 8(1), 273.

Hu, X., Jiang, Z., Yao, Y., & Dai, G. (2025). Arctic Sea ice decline whiplash modes in winter investigated from a Pan-Arctic viewpoint: atmospheric drivers and feedbacks. Environmental Research Communications, 7(8), 085014.

Mu, M., Qin, B.^*, & Dai, G. (2025). Predictability Study of Weather and Climate Events Related to Artificial Intelligence Models. Advances in Atmospheric Sciences, 42(1), 1-8.

Zhang, Q., Sun, G., Dai, G., & Mu, M.^* (2024). Impact of uncertainties in land surface processes on subseasonal predictability of heat waves onset over the Yangtze River Valley. Journal of Geophysical Research: Atmospheres, 129(1), e2023JD038674.

Mu, B., Zhao, Z., Yuan, S.^*, Qin, B., Dai, G., & Zhou, G. (2024). Developing intelligent Earth System Models: An AI framework for replacing sub-modules based on incremental learning and its application. Atmospheric Research, 107306.

Mu, B., Zhao, Z., Yuan, S.^*, Chen, X., Qin, B., & Dai, G. (2024). An extension to ensemble forecast of conditional nonlinear optimal perturbation considering nonlinear interaction between initial and model parametric uncertainties. Atmospheric Research, 311, 107682.

Qin, B., Yang, Z., Mu, M.^*, Wei, Y., Cui, Y., Fang, X., Dai, G., & Yuan, S. (2024). The first kind of predictability problem of El Niño predictions in a multivariate coupled data-driven model. Quarterly Journal of the Royal Meteorological Society, 150(765), 5452-5471.

Wang, H., Zuo, Z.^*, Zhang, R., Peng, L., Zhang, K., Chen, D., Xiao, D., You, Q., Dai, G., Zhang, R., Yang, H., Chen, X., Lin, Z., Xu, P., & Qiao, L. (2024). Thermodynamic effect dictates influence of the Atlantic Multidecadal Oscillation on Eurasia winter temperature. npj Climate and Atmospheric Science, 7(1), 151.

Hu, X., Jiang, Z.^*, & Dai, G. (2024). Atmospheric warming during rapid sea ice loss over the Barents–Kara seas in winter. Quarterly Journal of the Royal Meteorological Society, 150(765), 5535-5547.

Li, Y., Jiang, Z.^*, Dai, G., & Ding, M. (2024). The enhanced synoptic variation in sea ice over Pacific sector of Arctic Ocean during summer half year. Advances in Polar Science, 35(4), 438-448.

Cai, Z., You, Q.^*, Chen, H. W., Zhang, R.^*, Zuo, Z., Dai, G., Chen, D., Cohen, J., Zolina, O. & Gulev, S. K. (2023). Interdecadal variability of the warm Arctic-cold Eurasia pattern linked to the Barents oscillation. Atmospheric Research, 287, 106712.

Feng, J., Wang, J.^*, Dai, G., Zhou, F. & Duan, W. (2023). Spatiotemporal estimation of analysis errors in the operational global data assimilation system at the China Meteorological Administration using a modified SAFE method. Quarterly Journal of the Royal Meteorological Society, 1–19.

Mu, B., Li, J., Yuan, S.^*, Luo, X., & Dai, G. (2022). Optimal Precursors Identification for North Atlantic Oscillation Using the Parallel Intelligence Algorithm. Scientific Programming, 2022.

Ma, X., Mu, M.^*, Dai, G., Han, Z., Li, C., & Jiang, Z. (2022). Influence of Arctic sea ice concentration on extended-range prediction of strong and long-lasting Ural blocking events in winter. Journal of Geophysical Research: Atmospheres, 127, e2021JD036282.

Xu, Z., Chen, J.^*, Mu, M., Dai, G. & Ma, Y. (2022). A nonlinear representation of model uncertainty in a convective-scale ensemble prediction system. Advances in Atmospheric Sciences, 39(9), 1432-1450.

Xu, Z., Chen, J.^*, Mu, M., Tao, L., Dai, G., Wang, J., & Ma, Y. (2022). A stochastic and non-linear representation of model uncertainty in a convective-scale ensemble prediction system. Quarterly Journal of the Royal Meteorological Society, 148(746), 2507-2531.

Zhang, R.^*, Zhang, R., & Dai, G. (2021). Intraseasonal contributions of Arctic sea-ice loss and Pacific decadal oscillation to a century cold event during early 2020/21 winter. Climate Dynamics, 1-18.

Chen, R., Dai, G., Liu, R., & Wang, L.^* (2021). Seasonal Influence of the Atmosphere and Ocean on the Fall Sea Ice Extent in the Barents-Kara Seas. Journal of Geophysical Research: Atmospheres, 126, e2021JD035114.

Mu, B., Li, J., Yuan, S.^*, Luo, X., & Dai, G. (2020). CNOP-P-Based Parameter Sensitivity Analysis for North Atlantic Oscillation in Community Earth System Model Using Intelligence Algorithms. Advances in Meteorology, 2020.

  #以上信息由本人提供，更新时间：2026/03/12