物理海洋学(气象学)

王云鹤,男,副研究员,主要从事极地海冰变化与预测研究,聚焦南、北极,在海冰变率特征、驱动机制、可预测性评价、预测模型发展方面取得一系列成果。主要科学发现:1)发现了南极冬季云-大气环流-海冰系统的耦合模态,阐明了wave-3在该耦合系统中的作用;2)发展了基于人工智能的南极海冰季节内预测模型,预测能力显著优于ECMWF、NCEP、GFDL-SPEAR等主流数值模式;3)发展了北极海冰厚度季节预测模型,可实现超前12个月的预测;4)发展了基于Markov模型的北极太平洋扇区海冰季节预测模型,预测技巧显著优于美国GFDL-FLOR数值模式。在npj、JC、GRL、TC、ERL、JGR等期刊发表SCI论文22篇,其中第一/通讯作者11篇;授权发明专利4项,软件著作权1项;主持国家自然科学基金等项目5项。担任GRL、ERL、Climate Dynamics、JGR等期刊审稿人。

一、研究领域 

极地海冰变化与预测研究

二、招生专业及方向

物理海洋学,海洋遥感与数值模拟、预测方法方向;气象学,海洋气象方向;环境工程,海洋环境工程方向

三、研究室及联系方式

中国科学院海洋环流与波动重点实验室,联系方式:wangyunhe@qdio.ac.cn、15610040352  

四、承担的主要科研项目

1. 国家自然科学基金青年项目,42106223,南极冬季中层云对海冰的强迫机制研究,2022-01,2024-12, 主持

2. 山东省自然科学基金青年项目,ZR2021QD059,基于马尔科夫模型南极海冰季节预测,2022-01,2024-12,主持

3. 博士后特别资助(站前),2020TQ0322,基于马尔科夫模型北极太平洋扇区海冰季节性预报, 2021-01,2022-12,主持

4. 中国科学院战略性先导科技专项(A类)子课题, XDA19060101, 全球海洋基础数据库构建, 2018-01, 2022-12, 项目骨干                          

五、研究成果及奖励        

1. 发展了基于人工智能的南极海冰季节内预测模型,预测能力显著强于ECMWF、NCEP、GFDL-SPEAR等主流数值模式;

2. 发展了基于Markov模型的北极太平洋扇区海冰季节预测模型,预测能力显著优于美国GFDL-FLOR数值模式;3. 发展了北极海冰厚度季节预测模型,可超前预测12个月。

4. Journal of Oceanology and Limnology 年度优秀论文奖,2023

5. 海洋所“优秀博士后”激励计划, 2022                       

六、代表性论文及著作

1. Yunhe Wang, Xiaojun Yuan*, Yibin Ren, Xiaofeng Li*, and Arnold L. Gordon. ENSO's Impact on Linear and Nonlinear Predictability of Antarctic Sea Ice. npj Climate and Atmospheric Science, 2025, 8(1): 77. https://doi.org/10.1038/s41612-025-00962-9

2. Yunhe Wang, Xiaojun Yuan*, Haibo Bi, Yibin Ren, Yu Liang, Cuihua Li, and Xiaofeng Li*. Understanding Arctic Sea Ice Thickness Predictability by a Markov Model. Journal of Climate, 2023, 36(15): 4879–4897.

3. Yunhe Wang, Xiaojun Yuan*, Yibin Ren, Mitchell Bushuk, Qi Shu, Cuihua Li, Xiaofeng Li*. Subseasonal Prediction of Regional Antarctic Sea Ice by a Deep Learning Model. Geophysical Research Letters, 2023, 50(17),

4. Yunhe Wang, Xiaojun Yuan*, Mark A. Cane. Coupled mode of cloud, atmospheric circulation, and sea ice controlled by wave-3 pattern in Antarctic winter. Environmental Research Letters, 2022, 17(4): 044053.

5. Yunhe Wang, Xiaojun Yuan*, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, Haijun Huang. Reassessing seasonal sea ice predictability of the Pacific-Arctic sector using a Markov model. The Cryosphere, 2022, 16(3): 1141-1156. https://doi.org/10.5194/tc-16-1141-2022

6. Yunhe Wang, Xiaojun Yuan, Haibo Bi*, Yu Liang, Haijun Huang*, Zehua Zhang, and Yanxia Liu. The Contributions of Winter Cloud Anomalies in 2011 to the Summer Sea-Ice Rebound in 2012 in the Antarctic. Journal of Geophysical Research: Atmospheres, 2019, 124: 3435-3447. https://doi.org/10.1029/2018JD029435

7. Yunhe Wang, Haibo Bi*, and Yu Liang. A satellite-observed substantial decrease in multiyear ice area export through the Fram Strait over the last decade. Remote Sensing, 2022, 14:2562. https://doi.org/10.3390/rs14112562

8. Yunhe Wang, Haibo Bi*, Haijun Huang*, Yanxia Liu, Yilin Liu, Xi Liang, Min Fu, Zehua Zhang, Satellite-observed trends in the Arctic sea ice concentration for the period 1979-2016. Journal of Oceanology and Limnology, 2019, 37(1): 18–37. https://doi.org/10.1007/s00343-019-7284-0

9. BI Haibo, WANG Yunhe*, ZHANG Wenfeng, ZHANG Zehua, LIANG Yu, ZHANG Yi, HU Wenmin, FU Min, HUANG Haijun*, Recent satellite-derived sea ice volume flux through the Fram Strait: 2011-2015. Acta Oceanologica Sinica, 2018, 37(9): 107–115. https://doi.org/10.1007/s13131-018-1270-9

10. BI Haibo, Liang Yu, Wang Yunhe*, Liang Xi, Zhang Zehua, Du tingqin, Yu Qinglong, Huang Jue, Kong Mei; HUANG Haijun. Arctic multiyear sea ice variability observed from satellites: A review. Journal of Oceanology and Limnology, 2020, 38: 962–984. https://doi.org/10.1007/s00343-021-0382-9