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南京气象加拿大28 （南京信息工程大学），学士、硕士，大气科学
加拿大不列颠哥伦比亚大学（UBC），博士，物理海洋
曾先后在成都信息工程大学，英国爱丁堡大学，美国纽约大学，加拿大北哥伦比亚大学工作。目前在加拿大28-加拿大28开奖网 领导“人工智能预测和海洋资料同化”团队。研究兴趣主要是使用数值模式，机器学习，和集合滤波器等方法开展高影响海气相互作用环境事件的机理，可预报行和预测研究，包括ENSO，IOD,台风和热带海洋动力环境等。在人工智能气候预测，海洋资料同化和热带海气相互作用等领域，做了一些开创性工作。比如发展了世界上第一个ENSO动力-神经网杂交耦合模型；也带领团队开发了几个海洋资料同化和集合预报系统，并已应用于加拿大和中国业务化预报系统中。已发表180余篇专业论文，其中150多篇SCI论文，包括在Nature Geoscience，Nature Communication，GRL，JGR-Ocean 等一流专业刊物。领导和完成了数十个国家级研究项目。已培养了15名博士后科学家和60多名硕、博研究生，培养的学生由于在数值模式和资料同化方面较强的实际应用能力，在工作市场颇受青睐。其中不少已成为相关领域的优秀人才。
Rao, W., Tang, Y., Wu, Y., Shen, Z., Song, X., Li, X., Lian, T., Chen, D., and Zhou, F., 2023: A new ensemble-based targeted observational method and its application in the TPOS 2020,National Science Review, 10:nwad231, //doi.org/10.1093/nsr/nwad231
Song, Q., Tang, Y., Aiki, H., 2023: Dual Wave Energy Sources for the Atlantic Nino Events Identified by Wave Energy Flux in Case Studies,JGR-ocean, //doi.org/10.1029/2023JC019972
You, Li., Tang, X. and Tang, Y., 2023: Construction of deep learning based WWBs parameterization for ENSO prediction, Atmospheric Research, 289, 106770,
Li, Y, Tang, Y. and Shuai Wang and Li, X, 2023: Rapid Growth of Tropical Cyclone Outer Size over the Western North Pacific, Remote Sensing 15(2):486DOI:10.3390/rs15020486
Li, Y, Tang, Y. and Toumi, R. and Shuai Wang, 2023: Recent Increase of Tropical Cyclone Rapid Intensification in Global Coastal Regions, Nature Communication, 14(1), DOI:10.1038/s41467-023-40605-2
Gao, Y, Tang, Y. and Liu, T, 2023: Reducing Model Error Effects in El Niño–Southern Oscillation Prediction Using Ensemble Coupled Data Assimilation, Remote Sensing 15(3):762 DOI:10.3390/rs15030762
Li, X., Tang, Y., Z. Shen and Y. Li, 2023: A Region-Optional Targeted Observation Method and Its Application in the Sea Surface Temperature Prediction Associated With the Indian Ocean Dipole, JGR-Ocean, 128(8), DOI:10.1029/2023JC019781
Li, X., Tang, Y., Z. Shen and Y. Li, 2023: Spatial Variations in Seamless Predictability of Subseasonal Precipitation over Asian Summer Monsoon Region in S2S Models, JGR-Atmosphere, Journal of Geophysical Research Atmospheres 128(7), DOI:10.1029/2023JD038480
Song, Q. , Aiki, H., and Tang, Y.,2023: The role of the equatorially forced wave in triggering Benguela Nino/Nina through an energy flux based, JGR-Ocean, //doi.org/10.1029 /2022JC019272
Liu, T, Y. Gao, X. Song, C. Gao, L. Tao, Tang, Y., and D. Chen, 2023:, A Multi-model prediction system for ENSO, Science China Earth Sciences 66(6), DOI:10.1007/s11430-022-1094-0
Li, Y and Tang, Y., Li., X., Song., X and Q. Wang, 2023: Recent increase in the potential threat of severe tropical cyclones over the western North Pacific, npj Climate and Atmospheric Sciences, 6, 53 (2023). //doi.org/10.1038/s41612-023-00379-2
Yan, X., Tang, Y. and Yang, D., 2023: Study of decadal predictability of Mediterranean Sea surface temperature based on observation, J Climate, March 2023, 1487-1501, //doi.org/10.1175/JCLI-D-21-0999.1
Alam, M, and Tang, Y., 2023: Impact of Westerly Wind Bursts (WWBs) on ENSO: Part II --- ENSO prediction, Atmosphere-Ocean, DOI: 10.1080/07055900.2023.2173555
Wu, Y and Tang, Y., 2023: Diagnosing seasonal forecast skill of the Indian Ocean Dipole mode using model-analogs, Journal of Atmospheric and Oceanic Technology, 40(9),DOI:10.1175/JTECH-D-22-0106.1
Chen, Y., Shen, Z, Tang, Y. and Song, X, 2023: Seasonal prediction with an Ensemble Adjustment Kalman Filter for the oceanic initialization, Ocean Modeling, Vol 183, //doi.org/10.1016/j.ocemod.2023.102194
Yao, W, Yan, X, Tang, Y., Yang, D., Tan, X., Song, X, and Liu, T, 2022: Multidecadal Variation of the Seasonal Predictability of Winter PNA and Its Sources, GRL, DOI: 10.1029/2022GL099393.
