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Location: Home > People > Scientist Details

Zhu Jiang

Name:
Zhu Jiang
Position:
Director-General of IAP
Title:
Professor
100029
Mailing Address:
P.O. Box 9804, Zip Code: 100029, Beijing, China
E-mail:
jzhu@mail.iap.ac.cn

Education and Professional Experience:

  Education  

  Ph.D (1991)   Lancaster University, United Kingdom 

  M.Sc (1988)   Harbin Institute of Technology 

  B.Sc (1984)   Anhui Normal University 

    

  Professional Experience 

  2014-Now: Director-General of Institute of Atmospheric Physics, Chinese Academy of Sciences. 

  2001-Now: Professor, Institute of Atmospheric Physics, Chinese Academy of Sciences.  

  1998-2001: Researcher, Meteorological Research Institute, Japan Meteorological Agency. 

  1996-1998: Associated Professor, Institute of Atmospheric Physics, Chinese Academy of Sciences. 

  1994-1996: Postdoc, Institute of Atmospheric Physics, Chinese Academy of Sciences. 

  1991-1994: Postdoc, Qingdao Ocean University, Qingdao, China. 

Expertise:
  • Data assimilation with variational and ensemble methods. I have been developing a 3DVAR ocean data assimilation system for sigma- and z-coordinate ocean models with my group. Recently a ensemble-based ocean data assimilation have been developed for hybrid-coordinate ocean model (HYCOM) and for ROMS. These data assimilation systems have been used by other national and international users. 
  • El Nino forecasting using fully coupled and intermediate coupled models. Using fully coupled climate models and an intermediate coupled model, ensemble ENSO forecast systems have been developed with coupled data assimilation schemes. The forecast systems yield high scores from both long-term hindcast experiments and real-time forecasts of recent years. ENSO forecast systems has been transferred to several national operational centers. 
  • Development of operational marine forecasting system. Based on our modeling and data assimilation systems we have been developed pre-operational marine forecast systems for Indian Ocean, South China Sea and coastal seas around China. These systems have been transferred to various operational forecast centers, including National Marine Environmental Forecast Center of China. 
  • Atmospheric Chemistry data assimilation. Due to recent problem of heavy air pollution in China, I have being collaborated with my colleges in air quality modeling and developed an atmospheric chemistry data assimilation system for air quality forecasting and emission inversion.   

Honors:
  • Distinguished Young Scientist Fund by National Science Foundation of China (2002);
  • Top 100 Excellent PhD Supervisor Award by Ministry of Education (2009);
  • Outstanding Science and Technology Achievement Prize (major contributor) of the Chinese Academy of Sciences (2011);
  • National Science and Technology Advancement Prize (Second Class) from State Council of China (2012);
  • Science and Technology Advancement Prize of Heliang-Heli Foundation (2013).

Publication:
  •   Cheng, L. J., J. Zhu, R. Cowley, T. P. Boyer and S. Wijffels, 2014: Time, probe type and temperature variable bias corrections on historical expendable bathythermograph observations. Journal of Atmospheric and Oceanic Technology, in press. 
  •   Cheng, L. J. and J. Zhu, 2014: Uncertainties of the ocean heat content estimation induced by insufficient vertical resolution of historical ocean subsurface observations, Journal of Atmospheric and Oceanic Technology, in press. 
  •   Du J., F. Fang, C.C. Pain, I.M. Navon, J. Zhu, D.A. Ham, 2013:  POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow. Computers and Mathematics with Applications, 65, 362–379. 
  •   Du J., I.M. Navon, Jiang Zhu, Fangxin Fang, A.K. Alekseev,2013: Reduced order modeling based on POD of a parabolized Navier–Stokes equations model II: Trust region POD 4D VAR data assimilation, Computers and Mathematics with Applications,65,380–394. 
  •   Zhang Rong-Hua, Fei Zheng, Jiang Zhu and Zhanggui Wang, 2013: A successful real-time forecast of the 2010–11 La Nin˜a event, Scientific Report. DOI: 10.1038/srep01108 
  •   Tang X., Zhu J., Wang Zifa, 2011: Improvement of Ozone Forecast over Beijing Based on Ensemble Kalman Filter with Simultaneous Adjustment of Initial Conditions and Emissions, Atmospheric Chemistry and Physics, 11, 12901-12916. 
  •   Shu Y. Q., J. Zhu and D. X. Wang, 2011: Assimilating remote sensing and in situ observations into a coastal model of northern South China Sea using ensemble Kalman filter, Continental Shelf Research. 316, Supplement, 2011, S24–S36. 
  •   Nie S., J. Zhu, and Y. Luo, 2011: Simultaneous estimation of land surface scheme states and parameters using the ensemble Kalman filter: identical twin experiments, Hydrol. Earth Syst. Sci., 15, 2437–2457.  
  •   Fu W. and J. Zhu: 2011: Effects of sea level data assimilation by the EnOI and 3DVAR on the Variability in an equatorial tropical Pacific model. Journal of Atmospheric and Oceanic Technology. In press. 
  •   Zhu, J. 2011: Overview of Regional and Coastal Systems, Chapter 17 of  Operational Oceanography in the 21st Century, A. Schiller, G. B. Brassington (eds.), DOI 10.1007/978-94-007-0332-2_17, © Springer Science +Business Media B.V. 2011. 
  •   Chen L., J. Zhu, F. Reseghetti and Q. Liu, 2011: A new method to estimate the Systematical Biases of Expendable Bathythermograph, Journal of Atmospheric and Oceanic Technology. 28(2), 244-265. 
  •   Zhu Jiang, Fei Zheng, and Xichen Li, 2011: A new localization implementation scheme for ensemble data assimilation  of non-local observations. Tellus A. 63(2), 244-255. 
  •   Tianyi Zhang, J. Zhu, Reiner Wassmann, 2010: Responses of rice yields to recent climate change in China Part I: Empirical assessment based on long-term observations at different spatial scales (1981 – 2005),  Agricultural and Forest Meteorology. 150(7-8), 1128-1137, doi:10.1016/j.agrformet.2010.04.013,.  
  •   Zheng F., and J. Zhu, 2010: Coupled assimilation for an intermediated coupled ENSO prediction model, Ocean Dynamics, 60(5), 1061-1073.  
  •   Zheng, F., and J. Zhu, 2010: Spring barrier of ENSO forecast from the perspective of an ENSO ensemble prediction system. Global and Planetary Change. 72(3), 108-117. doi:10.1016/j.gloplacha.2010. 01.021. 
  •   Xie J.P., and J Zhu, 2010: Optimal ensemble interpolation schemes for assimilation of Argo profiles into HYCOM. Ocean Modelling. 33. 283–298 
  •   Li Xichen, J. Zhu, Yiguo Xiao and Ruiwen Wang, 2010: A model-based observation thinning scheme for assimilation of high resolution SST in the shelf and coastal seas around China. Journal of Atmospheric and Oceanic Technology. 276),1044–1058. 
  •   Wan L. Y., L. Bertino and J. Zhu, 2010Assimilating altimetry data into a HYCOM model of the PacificEnsemble Optimal Interpolation versus Ensemble Kalman Filter, Journal of Atmospheric and Oceanic Technology, 27(4), 753-765 
  •   Fu Weiwei, J. Zhu, Changxiang Yan and Hailong Liu, 2009: Towards a global ocean data assimilation system based on Ensemble Optimum Interpolation: Altimetry data assimilation experiment, Ocean Dynamics,59(4), 587-602 
  •   Liu Ye, J. Zhu, She Jun, Zhuang Shiyu, and Jidong Gao, 2009: Impacts of assimilating ocean profile observations using a bottom-topography-following recursive filter on ocean forecasting in North Sea/Baltic Sea. Ocean Modelling. 26(2-3), 75-87 
  •   Shu Yeqiang, J. Zhu, Xiao Xianjun, Yan Changxiang, Wang Dongxiao, 2009: Performance of four sea surface temperature assimilation schemes in the South China Sea. Continental Shelf Research. Vol. 29, 11-12, 1489-1501. 
  •   Fu W.W., J. Zhu and C. X.. Yan, 2009, A comparison between 3DVAR and EnOI techniques for Satellite altimetry data assimilation, Ocean Modelling. 269(3-4), 206-216 
  •   Zhang T., J. Zhu, X.. Yang , 2008: Non-stationary thermal time accumulation reduces the predictability of climate change effects on agricuture, Agr. Forest. Meteorol. Doi:10.1016/j.agrformet.2008.04.007. 
  •   Zheng F., J. Zhu, 2008: Balanced Multivariate Model Error in the Ensemble Kalman Filter Data Assimilation for an Intermediate Coupled Model, JGR-Oceans. 113, C07002, doi:10.1029/2007JC004621. 
  •   Xie J.P., J. Zhu and L. Yan, 2008: Assessment and inter-comparison of five high resolution sea surface temperature products in the shelf and coastal seas around China, Continental Shelf Research, 28,1286–1293. 
  •   Lin C., J. Zhu and Z. Wang, 2008: Model biases correction using ensemble Kalman filter assimilation for dust storm prediction, JGR-Atmosphere, VOL. 113, D14306, doi:10.1029/2007JD009498. 
  •   Zhang Tianyi, J. Zhu, Yang Xiaoguang, Zhang Xiaoyu 2008: Correlations changes between rice yield in the North and Northwest China and ENSO during the period of 1960–2004, Agr. Forest. Meteorol., doi:10.1016/j.agrformet.2008.01.018 
  •   Wan L., J. Zhu, L. Bertino, and H. Wang, 2008: Initial Ensemble Generation and Validation for Ocean Data Assimilation using HYCOM in the Pacific. Ocean Dynamics, 58:8199. DOI 10.1007/s10236-008-0133-x.. 
  •   Xie J., and J. Zhu, 2008: Estimation of the Surface and Mid-Depth Currents from ARGO Floats and Error Analysis in Pacific. J. Marine System. 73, 61-75. 
  •   Lin C., Z. Wang, and J. Zhu, 2008: A data assimilation method of the Ensemble Kalman Filter for use in severe dust storm forecasts over China. Atmos. Chem. Phys. 8, 2975–2983. 
  •   Wan L.Y., J. Zhu, C. X. Yan, H. Wang and L. Bertino, 2007: Dressing Ensemble Kalman Filter using Hybrid Coordinate Ocean Model in Pacific, Advances in Atmospheric Science. in press. 
  •   Zheng, F., J. Zhu, H. Wang, and R.-H. Zhang, 2009: Ensemble hindcasts of ENSO events over past 120 years using large number of ensembles. Adv. Atmos. Sci., in press. 
  •   Zheng, F., H. Wang, and J. Zhu, 2009: ENSO ensemble prediction: initial condition perturbations vs. model perturbations. Chin. Sci. Bull., in press. 
  •   Fu W.W., J. Zhu and C. X.. Yan, 2008, A comparison between 3DVAR and EnOI techniques for Satellite altimetry data assimilation, Ocean Modelling. doi:10.1016/j.ocemod.2008.10.002  
  •   Wan L., J. Zhu, L. Bertino, and H. Wang, 2008: Initial Ensemble Generation and Validation for Ocean Data Assimilation using HYCOM in the Pacific. Ocean Dynamics. 58:8199. DOI 10.1007/s10236-008-0133-x.. 
  •   Xie J.P., J. Zhu and L. Yan, 2008: Assessment and inter-comparison of five high resolution sea surface temperature products in the shelf and coastal seas around China, Continental Shelf Research, 28,1286–1293. 
  •   Xie J.P. and J. Zhu, 2008: Estimation of the Surface and Mid-Depth Currents from ARGO Floats and Error Analysis in Pacific. J. Marine System73, 61-75.. 
  •   Lin C., J. Zhu and Z. Wang, 2008: Model biases correction using ensemble Kalman filter assimilation for dust storm prediction, JGR-Atmosphere, VOL. 113, D14306, doi:10.1029/2007JD009498. 
  •   Lin C., Z. Wang, and J. Zhu, 2008: A data assimilation method of the Ensemble Kalman Filter for use in severe dust storm forecasts over China. Atmos. Chem. Phys., 8, 2975–2983. 
  •   Zhang T., J. Zhu, X.. Yang, 2008: Non-stationary thermal time accumulation reduces the predictability of climate change effects on agricuture, Agr. Forest. Meteorol. Doi:10.1016/j.agrformet.2008.04.007. 
  •   Zhang T., J. Zhu, X. Yang, X. Zhang, 2008: Correlations changes between rice yield in the North and Northwest China and ENSO during the period of 1960–2004, Agr. Forest. Meteorol., doi:10.1016/j.agrformet.2008.01.018. 
  •   Zheng F., J. Zhu, 2008: Balanced Multivariate Model Error in the Ensemble Kalman Filter Data Assimilation for an Intermediate Coupled Model, JGR-Ocean. 113, C07002, doi:10.1029/2007JC004621. 
  •   Wang R. W., J. Zhu, Z.D. Luo, M, I. Navon, 2008: An equation-free, reduced-order modeling approach to tropic Pacific simulation, Advances in Geosciences book series, World Scientific Publishing. In press.  
  •   Zheng F., J. Zhu, R. Zhang, 2007: The Impact of Altimetry Data on ENSO Ensemble Initializations and Predictions, Geophysical Research Letters. 34, L13611, doi:10.1029/2007GL030451. 
  •   Luo, Z. D., J. Zhu, R.W. Wang, and I. M. Navon, 2007Proper orthogonal decomposition approach and error estimation of mixed finite element methods for the tropical Pacific Ocean reduced gravity model. Computer Methods in Applied Mechanics and Engineering. 196, 4184-4195. 
  •   Luo Z, J. Chen, J. Zhu, R. Wang and I. M. Navon, 2007: An optimizing reduced order FDS for the tropical Pacific Ocean reduced gravity model, International Journal for Numerical Methods in Fluids, DOI: 10.1002/fld.1452. 
  •   Cao Y., J. Zhu, I. M. Navon, and Z. D Luo, 2007: A reduced order approach to four-dimensional variational data assimilation using proper orthogonal decomposition. International Journal for Numerical Methods in Fluids. DOI10.1002/fld.1365. 2007; 53:1571–1583. 
  •   Liu F., J. Zhu, F. Hu and E. Y. Wang, 2007: An optimal, weather condition dependent approach to decision-support of emission control of urban air pollution. Environmental Modeling and Software. 22(4), 548-557. 
  •   Xinan Yue, Weixing Wan, Libo Liu, Fei Zheng, Jiuhou Lei, Biqiang Zhao, Guirong Xu, Shun-Rong Zhang, and Jiang Zhu, 2007: Data assimilation of incoherent scatter radar observation into a one-dimensional midlatitude ionospheric model by applying ensemble Kalman filter, Radio Science, Vol. 42, RS6006, doi:10.1029/2007RS003631. 
  •   Cao, Y., J. Zhu, Z. D. Luo and I. M. Navon, 2006. Reduced Order Modeling of the Upper Tropical Pacific Ocean Model Using Proper Orthogonal Decomposion, Computer Mathematics with Applications. 521373-1386. 
  •   Zheng F., J. Zhu, Zhang R. H., and G. Q. Zhou, 2006: Ensemble forecast of ENSO using an intermediate coupled model. Geophysical Research Letters, 33, L19604, doi:10.1029/2006GL026994. 
  •   Zhu J., Yan C X., 2006: Nonlinear balance constraint in 3DVAR. Science in China (D), 49. 331-336. 
  •   Zhu J., G.. Q. Zhou, C. X. Yan and X. B. You, 2006, A three-dimensional variational ocean data assimilation system: Scheme and preliminary resultsScience in China (D), 49(12),12121222. 
  •   Hua J. H. Wang, J. Zhu and B. K. Tan, 2006: Relationship between real meridional volume transport and Sverdrup transport in the North Subtropical Pacific, Chinese Science Bulletin,51(14), 1757-1760. 
  •   Zheng F., J. Zhu, R. H. Zhang, and G. Q. Zhou, 2006: Improved ENSO forecasts by assimilating sea surface temperature observations into an intermediate coupled model, Advances in Atmospheric Sciences, 23, 615-624. 
  •   Liu F, Hu F and Zhu J. 2005: Adjoint method for optimum planning of industrial pollutant sources. Science in China (D), 48 (8): 1270~1279. 
  •   Fu, W. W., J. Zhu, G. Q. Zhou and H. J. Wang, 2005: A comparison study of tropic Pacific ocean state estimation: low-resolution assimilation vs. high resolution simulation. Advances in Atmospheric Sciences.,vol.22 No.2, 212-219. 
  •   Han, G., J. Zhu and G. Zhou, 2004: Salinity estimation using T-S relation in the context of variational data assimilation. JGR-Ocean, 109. doi:10.1029/2003JC001781. 
  •   Yan C. X., J. Zhu and G. Q. Zhou, 2004: The roles of vertical correlation of the background covariance and T-S relation in estimation temperature and salinity profiles from surface dynamic height. JGR-Ocean, 109. doi:10.1029/2003JC002224. 
  •   Zhou, G.., W. Fu, and J. Zhu, 2004: The impact of location dependent correlation length scales of background covariance on an ocean data assimilation system. Geophy. Res. Letters. 31, L21306, doi: 10.1029/2004GL020579. 
  •   You X, G. Zhou, J. Zhu, R. Li and Q. Zeng, 2003: Sea Temperature Data Assimilation System for the China Sea and Adjacent Areas, Chinese Science Bulletin , 48 Supp.II.70-76. 
  •   Zhu J., M. Kamachi, and D. Wang, 2002: Estimation of air-sea heat flux from ocean measurements: an ill-posed problem. JGR-Ocean, 107, C10, doi: 10.1029/2001JC000995. 
  •   Zhu J., W. Hui, and Zhou G., 2002: SST data assimilation experiments using an adaptive variational method. Chinese Science Bulletin, 47(23), 2010-2013. 
  •   Zhu, J., M. Kamachi, and W. Hui, 2002: The improvement made by a modified TLM in 4DVAR with a geophysical boundary layer model. Advances in Atmospheric Science, 19(4), 563-582.  
  •   Zhu, J., M. Kamachi, and G. Zhou, 2002: Nonsmooth Optimization Approaches to VDA of Models with on/off Parameterizations: Theoretical Issues. Advances in Atmospheric Science, Vol. 19(3),405-424.  
  •   Zhao S., X. Xiong, F. Hu., and J. Zhu., 2001: Rotating annulus experiment: Large-scale helical soliton in the atmosphere? Physical Review (E), Vol. 64, 056621. 
  •   Zhu, J. And M. Kamachi, 2000: The role of time-step size on numerical instablity of tangent linear models. Monthly Weather Review, 128, 1562-1572.  
  •   Zhu, J. And M. Kamachi, 2000: An adaptive variational method for data assimilation with imperfect models. Tellus, 52A, 265-279.  
  •   Wang, B., Zou X., and Zhu J., 2000: Data assimilation and its applications, Proceedings of National Academy of Sciences, USA, 97, 11143-11144. 
  •   Zhu, J., Q. Zeng, D. Guo and Z. Liu, 1999: Optimal control of sedimentation in navigation channels. Journal of Hydraulic Engineering, 125, 750-759. 

Community service:
Editor in Chief of Advances in Atmospheric Sciences

Projects: