导师信息
博士生导师
硕士生导师
 
 
 
地址:青岛市市南区南海路7号
 
电话:0532-82898650

传真:0532-82898654

邮政编码:266071 

电子邮件:yjsb@ms.qdio.ac.cn
  

 

张荣华,男,19621111日生,中国科学院海洋研究所研究员, 博士生导师,国家“千人划”特聘1989年获中国科学院大气物理研究所物理海洋学博士学位;毕业后先后在中科院大气所、日本气象厅气象研究所美国国家海洋大气管理局海洋资料中心美国罗德岛大学美国哥伦比亚大学国际气候研究所和美国马里兰大学工作;曾任美国马里兰大学地球系统交叉科学研究中心资深科学家和大气与海洋系教授;曾为美国多个国家级科研项目的首席科学家。

 

l  研究领域                                                                              

热带海气耦合模式、热带海洋-大气相互作用、厄尔尼诺-南方涛动(ENSO 数值模拟和预测、年代际海洋气候变率、海洋反馈过程参数化及其对气候模拟影响等研究领域。长期以来,其研究工作以海洋数值模式发展和模拟为重点,致力于海洋与地球其它分系统(特别是大气、海洋生物和化学)等耦合模式的发展和改进;建立了各种类型的海洋大气耦合模式;并用所发展的模式进行 年际/年代际气候异常(如厄尔尼诺南方涛动)数值模拟和相关物理过程诊断分析等跨学科研究;近年来,创造性地将海洋卫星遥感资料用于气候反馈过程参数化研究,有效地改进了海气耦合模式和地球系统模式,取得了国际领先的科研成果。详细请查询个人中文主页:  http://www.escience.cn/people/rzhang/index.html  

英文主页 http://essic.umd.edu/~rzhang                                                                  

l  招生专业及方向

物理海洋学,包括热带海洋-大气相互作用,海洋系统模拟和预测,气候模拟等。                                                        

l  联系方式                                                                                                                                      

rzhang@qdio.ac.cn

l  承担的主要科研项目

    中国科学院战略性先导科技专项(A类)“热带西太平洋海洋系统物质能量交换及其影响 (Western Pacific Ocean System: Structure, Dynamics and Consequences, WPOS);国家自然基金委重大项目课题2项(黑潮及延伸体海域气候变化的可预测性及未来气候预估、ENSO多变性及其与太平洋年代际变率等的关系)和面上项目(海洋次表层上卷温度场优化方法及其在提高实时ENSO预测中的应用),国家自然科学基金委—山东省联合研究项目等;入选中组部第十一批“千人计划”创新长期项目、山东省“泰山学者”特聘专家、青岛海洋科学与技术国家实验室“鳌山人才”卓越科学家、山东省透明海洋计划和青岛市领军项目等。                                                                                                                                                         

l  研究成果及奖励                                                                            

发展了一个中间型ENSO实时预报模式,自2003年以来一直为国际社会定期提供ENSO预报结果,这是首次以我国国内单位命名的海气耦合模式为国际学术界提供ENSO实时预报结果;另外, 系统揭示了太平洋中海表淡水通量强迫和海洋生物加热等对ENSO调制作用及其机制。已发表期刊论文120余篇 (其中SCI论文近百余篇,包括Nature及其子刊杂志5)。详细请查询http://www.escience.cn/people/rzhang/index.html.                                                                       

l  代表性论文及著作

(1)     Zhang, R.-H. and Chuan Gao, 2017: Processes involved in the second-year warming of the 2014-15 El Niño event as derived from an intermediate ocean model, Science China Earth Sciences, in press. doi: 10.1007/s11430-016-0201-9

(2)     Gao, C., R.-H. Zhang, Xinrong Wu and Jichang Sun, 2017: Idealized experiments for optimizing model parameters using a 4D-Variational method in an intermediate coupled model of ENSO, Adv. Atmos. Sci., in press,  doi: 10.1007/s00376-017-7109-z.

(3)     Kang , Xianbiao, R.-H. Zhang, Guansuo Wang, 2017: Effects of different freshwater flux representations in an ocean general circulation model of the tropical Pacific, Sci. Bull. 62 (5) :345-351.

(4)     Tao, L., R.-H., Zhang, and C. Gao, 2017: Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model, Adv. Atmos. Sci., 34 (6) :791-803.

(5)     Wang, J., Youyu Lu, Fan Wang, and Rong-Hua Zhang, 2017: Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction, Sci. Rep., 7 (1) :166. 

(6)     Hu, Zeng-Zhen, Arun Kumar, Bohua Huang, Jieshun Zhu, and Rong-Hua Zhang, Asymmetric evolution of El Niño and La Niña: The recharge/discharge processes and meridional gradient, Climate Dynamics , in press.

(7)     Gao Chuan and R.-H.  Zhang, 2017: Roles of atmospheric wind and entrained water temperature (Te) in the second-year cooling of the 2010-12 La Niña event, Climate Dynamics, 48: 597–617, DOI 10.1007/s00382-016-3097-4.

(8)     Zhang, R. H., 2016: A modulating effect of Tropical Instability Wave (TIW)- induced surface wind feedback in a hybrid coupled model of the tropical Pacific. J. Geophys. Res. Oceans,121(10): 7326-7353.

(9)     Zhang, R.-H. and Chuan Gao, 2016: The IOCAS intermediate coupled model (IOCAS ICM) and  its real-time predictions of the 2015-16 El Niño event, Sci. Bull.66 (13): 1061-1070. DOI 10.1007/s11434-016-1064-4.

(10)  Gao, C., X. Wu, R.-H. Zhang, 2016: Testing four dimensional variational data assimilation method using an improved intermediate coupled model for ENSO analysis and prediction, Adv. Atmos. Sci., 33 (7) :875-888. doi:10.1007/s00376-016-5249-1.

(11)  Zhang, R.-H.  and Chuan Gao, 2016: Role of subsurface entrainment temperature (Te) in the onset of El Nino events, as revealed in an intermediate coupled model, Climate Dynamics,465-6),1417-1435. doi: 10.1007/s00382-015-2655-5

(12)  Zhang, R.-H., 2015: A hybrid coupled for the Pacific ocean-atmosphere system: Part I:   Its Formalism and Basic Performance. Adv. Atmos. Sci., 323: 301-318, doi: 10.1007/s00376-014-3266-5.

(13)  Zhang, R.-H., 2015: Structure and Effect of Ocean Biology-induced Heating (OBH) in the Tropical Pacific, Diagnosed from a Hybrid Coupled Model Simulation, Climate Dynamics, 44: 695-715, DOI: 10.1007/s00382-014-2231-4

(14)  Zhang, R.-H., 2015: An ocean biology-induced negative climate feedback onto ENSO in a hybrid coupled model of the Tropical Pacific, J. Geo. Res., 120,   doi:10.1002/2015JC011305

(15)  Zhang, R.-H., Chuan Gao, Xianbiao Kang, Hai Zhi Zhanggui Wang & Licheng Feng, 2015: ENSO modulations due to interannual variability of freshwater forcing  and ocean biology-induced heating in the tropical Pacific, Sci. Rep., DOI: 10.1038/srep18506.