一、研究领域
人工智能海洋学、地球系统模式的评估及优化
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
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,邮箱:yuchaozhu@qdio.ac.cn。
四、承担的主要科研项目
1. 山东省TS学者青年专家,基于人工智能技术的气候数值模式评估及优化,2025.01-2027.12,主持
2. 国家自然科学基金面上项目,气候模拟中海洋次表层温盐误差的成因和影响,2023.01-2026.12,主持
3. 国家自然科学基金青年科学基金项目,海洋垂向混合参数化方案对模式系统性误差的影响机制研究,2020.01-2022.12,主持
4. 中国博士后科学基金面上资助,基于 Argo 资料的海洋垂向混合参数化优化方案,2018.10-2020.7,主持
5. 青岛市博士后应用研究项目,2020-2022,主持
五、研究成果及奖励
山东省TS学者青年专家、中国海洋学会人工智能海洋学专业委员会首届委员、海洋所汇泉学者人才称号,研究成果曾入选“2022年度中国海洋与湖沼十大科技进展”、中国科学院海洋研究所重大成果。
六、代表性论文及著作
[1] Zhu, Y., Zhang, R.-H., Moum, J. N., Wang, F., Li, X., Li, D., 2022. Physics-informed deep learning parameterization of ocean vertical mixing improves climate simulations. Natl. Sci. Rev. 9 (8).
[2] Zhu, Y., Zhang, R.-H., Li, D., 2022. An ocean modeling study to quantify wind forcing and oceanic mixing effects on the tropical North Pacific subsurface warm bias in CMIP and OMIP simulations. Clim. Dyn. 58 (3), 999-1014.
[3] Zhu, Y., Zhang, R.-H., Li, D., Chen, D., 2021. The Thermocline Biases in the Tropical North Pacific and Their Attributions. J. Climate 34 (5), 1635-1648.
[4] Zhu, Y., Zhang, R.-H., Sun, J., 2020. North Pacific Upper-Ocean Cold Temperature Biases in CMIP6 Simulations and the Role of Regional Vertical Mixing. J. Climate 33 (17), 7523-7538.
[5] Zhu, Y., Zhang, R.-H., 2019. A Modified Vertical Mixing Parameterization for Its Improved Ocean and Coupled Simulations in the Tropical Pacific. J. Phys. Oceanogr. 49 (1), 21-37.
[6] Zhu, Y., Zhang, R.-H., 2018. An Argo-Derived Background Diffusivity Parameterization for Improved Ocean Simulations in the Tropical Pacific. Geophys. Res. Lett. 45 (3), 1509-1517.
[7] Zhu, Y., Zhang, R.-H., 2018. Scaling wind stirring effects in an oceanic bulk mixed layer model with application to an OGCM of the tropical Pacific. Clim. Dyn. 51 (5), 1927-1946.
[8] Zhu, Y., Zhang, R.-H., 2023. A deep learning–based U-Net model for ENSO-related precipitation responses to sea surface temperature anomalies over the tropical Pacific. Atmospheric and Oceanic Science Letters, 100351.