Shaoqing Zhang

Designation:
Professor
Department:
Key Laboratory of Physical Oceanography
University:
Ocean University of China
Email:
szhang@ouc.edu.cn
Country:
China
Journal Associated: Annals of Marine Science Biography:

EDUCATION:

2000        Department of Meteorology, Florida State University, Ph.D.

1998        Department of Meteorology, Florida State University, MS

1991        Nanjing Institute of Meteorology, China, MS

1985        Department of Atmospheric Sciences, Nanjing University, China, B.Sc.


APPOINTMENT:

2016.12 -     Senior Professor and Distinguished Scientist Leader of Regional Climate Prediction Initiative,Key Laboratory of Physical Oceanography (POL), Ministry of Education, Ocean University of China, Qingdao National Laboratory of Marine Science and Technology (QNLM), – Regional Coupled model and data assimilation, Regional weather and climate predictions, Super-high-resolution regional coupled model and initialization for seamless numerical weather-climate studies, Ocean Extended   Range Prediction Mechanism and System Development.

2008 – 2016.11 Meteorologist & Oceanographer, GFDL/OAR/NOAA/DOC, – Climate model predictability and data assimilation, Climate reanalysis and prediction initialization, Coupled model parameter estimation, Decadal predictability depending on observing systems, High-Resolution Coupled Model Initialization towards Seamless Numerical Weather-Climate Studies.

2002-2007 Research Scientist I,II, UCAR/GFDL, Princeton University – Coupled model data assimilation with emphasis on ocean reanalysis, Impact of observing systems on climate predictability.

2000-2001 Visiting Scientist, AOS/Princeton University, – Nonlinear filtering for atmosphere and ocean data assimilation.


1996-1999 Research Assistant, Department of Meteorology, Florida State University – Adjoint and model sensitivities, 4-Dimensional variational data assimilation.

1995-1996 Visiting Scientist, EMC/NCEP – Tangent linear and adjoint models.

1985-1995 Branch Chair, Engineer, National Meteorological Center of China  – Atmospheric model and numerical weather prediction.


HONORS

2014        US Department of Commerce GOLD MEDAL Award

2008        NOAA Outstanding Research Paper Award

1998        Members of Royal Meteorology Society (UK) and AMS (US)

1995        Numerical Weather Prediction Fellow (Committee Member) of

Chinese Meteorological Society

1994-1995    Outstanding Research Awards from Chinese Meteorology Society,

Chinese Meteorological Administration, National Meteorological

Center of China,


EDITORIAL EXPERIENCES:

Lead Guest Editor: Special Issue on Advances in Meteorology

Regional Coupled Model and Data Assimilation 2017

https://www.hindawi.com/journals/amete/si/146016/cfp

Data Assimilation in Numerical Weather and Climate Models 2016

Data Assimilation in Numerical Weather and Climate Models 2015

https://www.hindawi.com/journals/amete/si/837235/cfp

Research Interest:


Prof. Zhang specializes in coupled Earth system modeling, Earth system predictability, coupled model data assimilation and parameter estimation, as well as the ultra fine-resolution global-regional coupled model and initialization for seamless weather-climate predictability studies and predictions. Currently one of his major missions is leading a national-wide large group to develop an ultra-high resolution Earth system model on Chinese home-grown heterogeneous high-performance-computing systems toward making seamless weather-climate predictions and coupled Earth system reanalysis. Predicting tropical cyclone (TC) genesis is of great societal importance but scientifically challenging. Prof. Zhang leads the team to build a high-resolution Asia-Pacific regional coupled prediction system with dynamically downscaling coupled data assimilation. This regional coupled prediction system has been used extensively in our research programs, including the studies of predictability of TC genesis, and improvement of TC track and intensity forecasts.

URL: http://pol.ouc.edu.cn/2020/0526/c18669a288339/page.htm

Grants:

1)    An Ultra High Resolution Coupling Extension Prediction System of Multi-Layer in Two Oceans and One Ocean Region, National Key Research and Development Program, Ministry of Science and Technology of China, Grant No. 2017YFC1404100, ¥15740000, PI. 2017.07-2021.06.
2)    A Study of High Efficiency EnKF Approximate Algorithm, Project of National Natural Science Foundation of China (NSFC), Grant No. 41775100, ¥680000, PI, 2018.01-2021.12.
3)    A Study of Coupled Model and Coupled Data Assimilation Based on Key Physical Processes on The Air-Sea Interface, Key Project of National Natural Science Foundation of China (NSFC), Grant No. 41830964, ¥3050000, PI, 2019.01-2023.12.
4)    Causes and predictions of Extremes in the East Asian Water Cycle, Nationality cooperation and exchange program of National Natural Science Foundation of China (NSFC), Grant No. 41981230039, ¥150000, PI, 2019.01-2019.12.

List of Publications:

Ma M. -C., Y. Gao,* A. -J. Ding, H. Su, H. Liao, S.- X. Wang, X. -M. Wang, B. Zhao, S. -Q.  Zhang, P. -Q. Fu, A. -B. Guenther, M.-H. Wang, S. -S Li, B.-W. Chu, X. -H. Yao, and H. -W. Gao, 2022: Development and Assessment of a High-Resolution Biogenic Emission Inventory from Urban Green Spaces in China. Environmental Science & Technology, 56, 175−184
Guo X. -W., Y. Gao*, S. -Q. Zhang*, L. -X. Wu, P. Chang, W. -J. Cai, J. Zscheischler, L. -R. Leung, J. Small, G. Danabasoglu, L. Thompson, and H. -W. Gao, 2022:Threat by marine heatwaves to adaptive large marine ecosystems in an eddy-resolving model. Nature Climate Change,12, 179–186.
Mao, K., F. Gao*; S. -Q. Zhang*; and C. Liu,.2022: An Initial Field Intelligent Correcting Algorithm for Numerical Forecasting Based on Artificial Neural Networks under the Conditions of Limited Observations: Part I—Focusing on Ocean Temperature. J. Mar. Sci. Eng. 10, 311.
ZHAO H. -R., S. -Q. Zhang*, J.-P. Li*, and Y. -W. Ma, 2021: A Study of Predictability of Coupled Ocean–Atmosphere System Using Attractor Radius and Global Attractor Radius. Climate Dynamics, 56: 1317–1334.
ZHENG J.-B., S. -Q. Zhang*, D. Wang, and J. Jiang, 2021: Optimization for the Assessment of Spudcan Peak Resistance in Clay–Sand–Clay Deposits. Journal of Marine Science and Engineering,  9(7), 689.
WANG X., S. -Q. Zhang*, X. -P. Lin*, B. Qiu, and L. -S. Yu, 2021: Characteristics of 3-Dimensional Structure and Heat Budget of Mesoscale Eddies in the South Atlantic Ocean. Journal of Geophysical Research-Oceans,126, e2020JC016922.
MA Y. -W., J.-P. Li*, S. -Q. Zhang*, H. -R. Zhao, 2021: A multi‑model study of atmosphere predictability in coupled  ocean–atmosphere systems. Climate Dynamics, 56: 3489–3509.
SU A., L. Zhang,*, X. -F. Zhang*, S. -Q. Zhang, Z. Liu, C. -L. Liu, and A. Zhang, 2021: A New Scheme of Adaptive Covariance Inflation for Ensemble Filtering Data Assimilation. Journal of Marine Science and Engineering, 9, 1054.
YEAGER S. -G.*, F. Castruccio, P. Chang, G. Danabasoglu, E. Maroon, J. Small1, H. Wang, L. -X. Wu, S. -Q. Zhang*, 2021: An Outsized Role for the Labrador Sea in the Multidecadal Variability of the Atlantic OverturningCirculation. Science advances: in press.
LIU Z., S. -Q. Zhang*, Y. Shen, Y. -P. Guan, and X. Deng, 2021: A Study of Capturing AMOC Regime Transition through Observation-Constrained Model Parameters. Nonlinear Processes in Geophysics, 28, 481–500.
REN S. -M., S. -Q. Zhang*, L. L, Y. -J. Jiang, Y. -W. Ma, 2021: A Study of the Impact of Tropical Atlantic Warming on the Pacific Walker Circulation with Numerical Experiments of CGCM. Advances in Climate Change Research, in press.
Liu C. -L., S. -Q. Zhang⁎, Y. Gao⁎⁎, Y. -H., Wang L. -F. Sheng, H. -W. Gao, J. -C.-H. Fung. Optimal estimation of initial concentrations and emission sources with 4D-Var for air pollution prediction in a 2D transport modelScience of the Total Environment773:145580
Zhang S. -Q.*, Z. Liu, X. Zhang, X. Wu, G. Han, Y. Zhao, X. Yu, C. Liu, Y. Liu, S. Wu, F. Lu, M. Li, and X. Deng, 2020: Coupled data assimilation and parameter estimation in coupled ocean-atmosphere models: a review. Climate dynamics, 54(11-12): 5127-5144.
JIANG Y., S. -Q. Zhang, J. Tian, Z. Zhang, J. Gan, and C. R. Wu, 2020: An Examination of Circulation Characteristics in the Luzon Strait and the South China Sea Using High‐Resolution Regional Atmosphere‐Ocean Coupled Models. Journal of geophysical research. Oceans, 125(6): e2020JC016253.
LI J., and S. -Q. Zhang, 2020: Mitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20. Geoscientific model development, 13(3): 1035-1054.
LEE J. -H., Y. S. Chang, and S. -Q. Zhang, 2020: Assessment of the JMA Serial Observation Lines in the Northwestern Pacific in OSSE Studies with the GFDL Ensemble Coupled Data Assimilation System. Journal of geophysical research. Oceans, 125(3): e2019JC015686.
GAO Y., H. Shan, S. -Q. Zhang, L. Sheng, J. Li, J. Zhang, M. Ma, H. Meng, K. Luo, H. Gao, and X. Yao, 2020: Characteristics and sources of PM2.5 with focus on two severe pollution events in a coastal city of Qingdao, China. Chemosphere, 247: 125861-125861.
ZHANG L., Y. Gao, S. Wu, S. -Q. Zhang, K. R. Smith, X. Yao, and H. Gao, 2020: Global impact of atmospheric arsenic on health risk: 2005 to 2015. Proceedings of the National Academy of Sciences – PNAS, 117(25): 13975-13982.
LU L., S. -Q. Zhang*, S. G. Yeager, G. Danabasoglu, P. Chang, L. Wu, X. Lin, A. Rosati, and F. Lu, 2020: Impact of Coherent Ocean Stratification on AMOC Reconstruction by Coupled Data Assimilation with a Biased Model. Journal of climate, 33(17): 7319-7334.
FENG X., N. Klingaman, S. -Q. Zhang, and L. Guo, 2020: Building sustainable science partnerships between early-career researchers to better understand and predict East Asia water cycle extremes. Bulletin Of The American Meteorological Society, 101 (6): E785–E789.
LI M., S. -Q. Zhang* L. Wu, X. Lin, P. Chang, G. Danabasoglu, Z. Wei, X. Yu, H. Hu, X. Ma, W. Ma, H. Zhao, D. Jia, X. Liu, K. Mao, Y. Ma, Y. Jiang, X. Wang, G. Liu, and Y. Chen, 2020: An Examination of the Predictability of Tropical Cyclone Genesis in High-Resolution Coupled Models with Dynamically Downscaled Coupled Data Assimilation Initialization. Advances in atmospheric sciences, 37(9): 939-950.
GAO Y., L. Zhang, G. Zhang, F. Yan, S. -Q. Zhang, L. Sheng, J. Li, M. Wang, S. Wu, J. S. Fu, X. Yao, and H. Gao, 2020: The climate impact on atmospheric stagnation and capability of stagnation indices in elucidating the haze events over North China Plain and Northeast China. Chemosphere, 258: 127335-127335.
LI M., S. -Q. Zhang*, L. Wu, X. Lin, P. Chang, G. Danabasoglu, Z. Wei, X. Yu, H. Hu, X. Ma, W. Ma, D. Jia, X. Liu, H. Zhao, K. Mao, Y. Ma, Y. Jiang, X. Wang, G. Liu, and Y. Chen, 2020: A high-resolution Asia-Pacific regional coupled prediction system with dynamically downscaling coupled data assimilation. Science bulletin, 65(21): 1849-1858.
ROBERTS M. -J., L. C. Jackson, C. D. Roberts, V. Meccia, D. Docquier, T. Koenigk, P. Ortega, E. Moreno‐Chamarro, A. Bellucci, A. Coward, S. Drijfhout, E. Exarchou, O. Gutjahr, H. Hewitt, D. Iovino, K. Lohmann, D. Putrasahan, R. Schiemann, J. Seddon, L. Terray, X. Xu, Q. Zhang, P. Chang, S. G. Yeager, F. S. Castruccio, S. -Q. Zhang, and L. Wu, 2020: Sensitivity of the Atlantic Meridional Overturning Circulation to Model Resolution in CMIP6 HighResMIP Simulations and Implications for Future Changes. Journal of advances in modeling earth systems, 12(8): e2019MS002014.
SUN J., Z. Liu, F. Lu, W. Zhang, and S. -Q. Zhang, 2020: Strongly Coupled Data Assimilation Using Leading Averaged Coupled Covariance (LACC). Part III: Assimilation of Real World Reanalysis. Monthly weather review, 148(6): 2351-2364.
Zhang S. -Q.*, H. Fu, L. Wu, Y. Li, H. Wang, Y. Zeng, X. Duan, W. Wan, L. Wang, Y. Zhuang, H. Meng, K. Xu, P. Xu, L. Gan, Z. Liu, S. Wu, Y. Chen, H. Yu, S. Shi, L. Wang, S. Xu, W. Xue, W. Liu, Q. Guo, J. Zhang, G. Zhu, Y. Tu, J. Edwards, A. Baker, J. Yong, M. Yuan, Y. Yu, Q. Zhang, Z. Liu, M. Li, D. Jia, G. Yang, Z. Wei, J. Pan, P. Chang, G. Danabasoglu, S. Yeager, N. Rosenbloom, and Y. Guo, 2020: Optimizing high-resolution Community Earth System Model on a heterogeneous many-core supercomputing platform. Geosci. Model Dev., 13(10): 4809-4829.
HOU Z., B. Zuo, S. -Q. Zhang, F. Huang, R. Ding, W. Duan, and J. Li, 2020: Model forecast error correction based on the Local Dynamical Analog method: an example application to the ENSO forecast by an Intermediate Coupled Model. Geophysical Research Letters,  47(19): 1-10.
CHANG P., S. -Q. Zhang*, G. Danabasoglu, S. G. Yeager, H. Fu, H. Wang, F. S. Castruccio, Y. Chen, J. Edwards, D. Fu, Y. Jia, L. C. Laurindo, X. Liu, N. Rosenbloom, R. J. Small, G. Xu, Y. Zeng, Q. Zhang, J. Bacmeister, D. A. Bailey, X. Duan, A. K. DuVivier, D. Li, Y. Li, R. Neale, A. Stössel, L. Wang, Y. Zhuang, A. Baker, S. Bates, J. Dennis, X. Diao, B. Gan, A. Gopal, D. Jia, Z. Jing, X. Ma, R. Saravanan, W. G. Strand, J. Tao, H. Yang, X. Wang, Z. Wei, and L. Wu, 2020: An Unprecedented Set of High-Resolution Earth System Simulations for Understanding Multiscale Interactions in Climate Variability and Change. Journal of Advances in Modeling Earth Systems, 12(12): e2020MS002298.
SUN J., Z*. Liu, F. Lu, W. Zhang, Y. Zhao and S. -Q. Zhang, 2020:Quantitatively Isolating Extratropical Atmospheric Impact on the Tropical Pacific Interannual Variability in Coupled Climate Model. IEEE Access, 8: 163857-163867.
MA M., Y. Gao*, Y. Wang*, S. -Q. Zhang, L. R. Leung, C. Liu, S. Wang, B. Zhao, X. Chang, H. Su, T. Zhang, L. Sheng, X. Yao, H. Gao, and R. W. A. Pacific Northwest National Lab, 2019: Substantial ozone enhancement over the North China Plain from increased biogenic emissions due to heat waves and land cover in summer 2017. Atmospheric chemistry and physics, 19(19): 12195-12207.
CHIKAMOTO Y. *, A. Timmermann, M. J. Widlansky, S. -Q. Zhang, and M. A. Balmaseda, 2019: A Drift-Free Decadal Climate Prediction System for the Community Earth System Model. Journal of climate, 32(18): 5967-5995.
ZHAO Y., X. Deng, S. -Q. Zhang*, Z. Liu, and C. Liu, 2019: Sensitivity determined simultaneous estimation of multiple parameters in coupled models: part I—based on single model component sensitivities. Climate dynamics, 53(9): 5349-5373.
HU H., F. Huang*, S. -Q. Zhang, C. Ruan, S. Gao, and P. Li, 2019: Case Study of Fog Predictability for an Event with Cold-Front Synoptic Pattern. Journal of Ocean University of China, 18(2): 271-281.
YU X., S. -Q. Zhang*, J. Li, L. Lu, Z. Liu, M. Li, H. Yu, G. Han, X. Lin, L. Wu, and P. Chang, 2019: A Multi‐Timescale EnOI‐like High‐Efficiency Approximate Filter for Coupled Model Data Assimilation. Journal of advances in modeling earth systems, 11(1): 45-63.
ZHANG S. -Q., L. Yang*, X. Ma, H. Wang, X. Zhang, X. Yu, and L. Lu, 2018: The 'Two oceans and one sea' extended range numerical prediction system with an ultra-high resolution atmosphere-ocean-land regional coupled model. Atmospheric and oceanic science letters = Daqi-he-haiyang-kexue-kuaibao, 11(4): 364-371.
ZHANG S. -Q.*, Y. Xie, F. Counillon, X. Ma, P. Yu, and Z. Jing, 2018: Regional Coupled Model and Data Assimilation. Advances in meteorology, 2018: 1-2.
PARK J.-Y.*, C. A. Stock, X. Yang, J. P. Dunne, A. Rosati, J. John, and S. -Q. Zhang, 2018: Modeling Global Ocean Biogeochemistry With Physical Data Assimilation: A Pragmatic Solution to the Equatorial Instability. Journal of advances in modeling earth systems, 10(3): 891-906.
YU H.*, J. Li, K. Wu, Z. Wang, H. Yu, S. -Q. Zhang, Y. Hou, and R. M. Kelly, 2018: A global high-resolution ocean wave model improved by assimilating the satellite altimeter significant wave height. ITC journal, 70: 43-50.
LI S.*, S. -Q. Zhang*, Z. Liu, L. Lu, J. Zhu, X. Zhang, X. Wu, M. Zhao, G. A. Vecchi, R. H. Zhang, and X. Lin, 2018: Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation. Journal of advances in modeling earth systems, 10(4): 989-1010.
CHANG Y.-S.*, S. -Q. Zhang, A. Rosati, G. A. Vecchi, and X. Yang, 2018: An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System. Ocean science journal, 53(2): 179-189.
LIU C., S. -Q. Zhang, S. Li, and Z. Liu, 2017: Impact of the Time Scale of Model Sensitivity Response on Coupled Model Parameter Estimation. Advances in atmospheric sciences, 34(11): 1346-1357.
HU H., Q. Zhang, J. Sun, C. Ruan, F. Huang, and S. -Q. Zhang, 2017: Impact of high-frequency observations on fog forecasting: a case study of OSSE. Tellus. Series A, Dynamic meteorology and oceanography, 69(1): 1396182.
FU H., J. Yang, W. Li, X. Wu, G. Han, Y. Xie, S. -Q. Zhang, X. Zhang, Y. Cao, and X. Zhang, 2017: A Potential Density Gradient Dependent Analysis Scheme for Ocean Multiscale Data Assimilation. Advances in meteorology, 2017: 1-13.
ZHAO Y., X. Deng, S. -Q. Zhang, Z. Liu, C. Liu, G. Vecchi, G. Han, and X. Wu, 2017: Impact of an observational time window on coupled data assimilation: simulation with a simple climate model. Nonlinear processes in geophysics, 24(4): 681-694.
YU X., S. -Q. Zhang, X. Lin, and M. Li, 2017: Insights on the role of accurate state estimation in coupled model parameter estimation by a conceptual climate model study. Nonlinear Processes in Geophysics, 24: 125-139.
LU F. -Z. Liu, S. -Q. Zhang, and R. Jacob, 2017: Assessing extratropical impact on the tropical bias in coupled climate model with regional coupled data assimilation. Geophysical research letters, 44(7): 3384-3392.
LU F. -Z. Liu, Y. Liu, S. -Q. Zhang, and R. Jacob, 2017: Understanding the control of extratropical atmospheric variability on ENSO using a coupled data assimilation approach. Climate dynamics, 48(9-10): 3139-3160.
KARSPECK A. -R., D. Stammer, A. Köhl, G. Danabasoglu, M. Balmaseda, D. M. Smith, Y. Fujii, S. -Q. Zhang, B. Giese, H. Tsujino. and A. Rosati, 2017: Comparison of the Atlantic meridional overturning circulation between 1960 and 2007 in six ocean reanalysis products. Climate dynamics, 49(3): 957-982.
CHANG Y.-S., and S. -Q. Zhang, 2016: XBT Effects on the Global Ocean State Estimates Using a Coupled Data Assimilation System. TAO : Terrestrial, atmospheric, and oceanic sciences, 27(6): 1019-1031.
CHENG J., Z. Liu, S. -Q. Zhang, W. Lina, and D. Peng, 2016: Reply to Parker: Robust response of AMOC interdecadal variability to future intense warming. Proceedings of the National Academy of Sciences of the United States of America, 113: E2762–E2763.
CHENG J., Z. Liu, S. -Q. Zhang, W. Liu, L. Dong, P. Liu, and H. Li, 2016: Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming. Proceedings of the National Academy of Sciences - PNAS, 113(12): 3175-3178.
FU H., X. Wu, W. Li, Y. Xie, G. Han, and S. -Q. Zhang, 2016: Reconstruction of Typhoon Structure Using 3-Dimensional Doppler Radar Radial Velocity Data with the Multigrid Analysis: A Case Study in an Idealized Simulation Context. Advances in meteorology, 2016: 1-10.
LI S., S. -Q. Zhang, Z. Liu, X. Yang, A. Rosati, J.-C. Golaz, and M. Zhao, 2016: The Role of Large-Scale Feedbacks in Cumulus Convection Parameter Estimation. Journal of climate, 29(11): 4099-4119.
LIU H., F. Lu, Z. Liu, Y. Liu, and S. -Q. Zhang, 2016: Assimilating atmosphere reanalysis in coupled data assimilation. Journal of meteorological research, 30(4): 572-583.
WU X., G. Han, S. -Q. Zhang, and Z. Liu, 2016: A study of the impact of parameter optimization on ENSO predictability with an intermediate coupled model. Climate dynamics, 46(3): 711-727.
WU X. -R., S. -Q. Zhang, and Z. L., 2016: Implementation of a One-Dimensional Enthalpy Sea-Ice Model in a Simple Pycnocline Prediction Model for Sea-Ice Data Assimilation Studies. Advances in atmospheric sciences, 33(2): 193-207.
ZHANG X., S. -Q. Zhang, Z. Liu, X. Wu, and G. Han, 2016: Correction of biased climate simulated by biased physics through parameter estimation in an intermediate coupled model. Climate dynamics, 47(5): 1899-1912.
GODDARD P. B., J. Yin, S. M. Griffies, and S. Zhang, 2015: An extreme event of sea-level rise along the Northeast coast of North America in 2009–2010. Nature communications, 6(1): 6346-6346.
HAN G., X. Wu, S. Zhang, Z. Liu, I. M. Navon, and W. Li, 2015: A Study of Coupling Parameter Estimation Implemented by 4D-Var and EnKF with a Simple Coupled System. Advances in meteorology, 2015: 1-16.
HUANG B., J. Zhu, L. Marx, X. Wu, A. Kumar, Z.-Z. Hu, M. A. Balmaseda, S. Zhang, J. Lu, E. K. Schneider, and J. L. Kinter Iii, 2015: Climate drift of AMOC, North Atlantic salinity and arctic sea ice in CFSv2 decadal predictions. Climate dynamics, 44(1): 559-583.
JIA L., X. Yang, G. A. Vecchi, R. G. Gudgel, T. L. Delworth, A. Rosati, W. F. Stern, A. T. Wittenberg, L. Krishnamurthy, S. Zhang, R. Msadek, S. Kapnick, S. Underwood, F. Zeng, W. G. Anderson, V. Balaji, and K. Dixon, 2015: Improved Seasonal Prediction of Temperature and Precipitation over Land in a High-Resolution GFDL Climate Model. Journal of climate, 28(5): 2044-2062.
LU F. -Z. Liu, S. Zhang, and Y. Liu, 2015: Strongly Coupled Data Assimilation Using Leading Averaged Coupled Covariance (LACC). Part I: Simple Model Study. Monthly weather review, 143(9): 3823-3837.
LU F., -Z. Liu, S. Zhang, Y. Liu, R. Jacob, and A. I. L. Argonne National Lab, 2015: Strongly Coupled Data Assimilation Using Leading Averaged Coupled Covariance (LACC). Part II: CGCM Experiments. Monthly weather review, 143(11): 4645-4659.
YANG X., G. A. Vecchi, R. G. Gudgel, T. L. Delworth, S. Zhang, A. Rosati, L. Jia, W. F. Stern, A. T. Wittenberg, S. Kapnick, R. Msadek, S. D. Underwood, and F. Zeng, W. Anderson and V. Balaji, 2015: Seasonal Predictability of Extratropical Storm Tracks in GFDL’s High-Resolution Climate Prediction Model. Journal of climate, 28(9): 3592-3611.
ZHANG S., G. Han, Y. Xie, and J. J. Ruiz, 2015: Data Assimilation in Numerical Weather and Climate Models. Advances in meteorology, 2015: 1-2.
ZHANG S., M. Zhao, S. J. Lin, X. Yang, W. Anderson, W. Zhang, A. Rosati, S. Underwood, and F. Zeng, 2015: Impact of having realistic tropical cyclone frequency on ocean heat content and transport forecasts in a high‐resolution coupled model. Geophysical research letters, 42(14): 5966-5973.
ZHANG X., S. Zhang, Z. Liu, X. Wu, and G. Han, 2015: Parameter Optimization in an Intermediate Coupled Climate Model with Biased Physics. Journal of climate, 28(3): 1227-1247.
CHANG Y.-S., G. A. Vecchi, A. Rosati, S. Zhang, and X. Yang, 2014: Comparison of global objective analyzed T-S fields of the upper ocean for 2008–2011. Journal of marine systems, 137: 13-20.
HAN G., X. Zhang, S. Zhang, X. Wu, and Z. Liu, 2014: Mitigation of coupled model biases induced by dynamical core misfitting through parameter optimization: simulation with a simple pycnocline prediction model. Nonlinear processes in geophysics, 21(2): 357-366.
LIU Y. -Z. Liu, S. Zhang, R. Jacob, F. Lu, X. Rong, S. Wu, and A. I. L. Argonne National Lab, 2014: Ensemble-Based Parameter Estimation in a Coupled General Circulation Model. Journal of climate, 27(18): 7151-7162.
LIU Y. -Z. Liu, S. Zhang, X. Rong, R. Jacob, S. Wu, F. Lu, and A. I. L. Argonne National Lab, 2014: Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method. Journal of climate, 27(11): 4002-4014.
MSADEK R., T. L. Delworth, A. Rosati, W. Anderson, G. Vecchi, Y. S. Chang, K. Dixon, R. G. Gudgel, W. Stern, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang, 2014: Predicting a Decadal Shift in North Atlantic Climate Variability Using the GFDL Forecast System. Journal of climate, 27(17): 6472-6496.
VECCHI G. -A., T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng, W. Anderson, V. Balaji, K. Dixon, L. Jia, H. S. Kim, L. Krishnamurthy, R. Msadek, W. F. Stern, S. D. Underwood, G. Villarini, X. Yang, and S. Zhang, 2014: On the Seasonal Forecasting of Regional Tropical Cyclone Activity. Journal of climate, 27(21): 7994-8016.
VECCHI G. -A., R. Msadek, W. Anderson, Y. S. Chang, T. Delworth, K. Dixon, R. Gudgel, A. Rosati, B. Stern, G. Villarini, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang, 2014: Reply to Comments on "Multiyear Predictions of North Atlantic Hurricane Frequency: Promise and Limitations". Journal of Climate, 27(1): 490-492.
WU X., W. Li, G. Han, S. Zhang, and X. Wang, 2014: A Compensatory Approach of the Fixed Localization in EnKF. Monthly weather review, 142(10): 3713-3733.
ZHANG S., Y. S. Chang, X. Yang, and A. Rosati, 2014: Balanced and Coherent Climate Estimation by Combining Data with a Biased Coupled Model. Journal of climate, 27(3): 1302-1314.
ZHANG S., M. Zhao, S. J. Lin, X. Yang, and W. Anderson, 2014: Retrieval of tropical cyclone statistics with a high‐resolution coupled model and data. Geophysical research letters, 41(2): 652-660.
HAN G., X. Wu, S. Zhang, Z. Liu, and W. Li, 2013: Error Covariance Estimation for Coupled Data Assimilation Using a Lorenz Atmosphere and a Simple Pycnocline Ocean Model. Journal of climate, 26(24): 10218-10231.
LIU Z., S. Wu, S. Zhang, Y. Liu, and X. Rong, 2013: Ensemble Data Assimilation in a Simple Coupled Climate Model:The Role of Ocean-Atmosphere Interaction. Advances in atmospheric sciences, 30(5): 1235-1248.
VECCHI G. A., R. Msadek, W. Anderson, Y.-S. Chang, T. Delworth, K. Dixon, R. Gudgel, A. Rosati, B. Stern, G. Villarini, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang, 2013: Multiyear Predictions of North Atlantic Hurricane Frequency: Promise and Limitations. Journal of climate, 26(15): 5337-5357.
WU X., S. Zhang, Z. Liu, A. Rosati, and T. L. Delworth, 2013: A study of impact of the geographic dependence of observing system on parameter estimation with an intermediate coupled model. Climate dynamics, 40(7): 1789-1798.
YANG X., A. Rosati, S. Zhang, T. L. Delworth, R. G. Gudgel, R. Zhang, G. Vecchi, W. Anderson, Y.-S. Chang, T. DelSole, K. Dixon, R. Msadek, W. F. Stern, A. Wittenberg, and F. Zeng, 2013: A Predictable AMO-Like Pattern in the GFDL Fully Coupled Ensemble Initialization and Decadal Forecasting System. Journal of climate, 26(2): 650-661.
ZHANG S., M. Winton, A. Rosati, T. Delworth, and B. Huang, 2013: Impact of Enthalpy-Based Ensemble Filtering Sea Ice Data Assimilation on Decadal Predictions: Simulation with a Conceptual Pycnocline Prediction Model. Journal of climate, 26(7): 2368-2378.
CHANG Y.-S., S. Zhang, A. Rosati, T. L. Delworth, and W. F. Stern, 2013: An assessment of oceanic variability for 1960–2010 from the GFDL ensemble coupled data assimilation. Climate dynamics, 40(3-4): 775-803.
WU X., S. Zhang, Z. Liu, A. Rosati, T. L. Delworth, and Y. Liu, 2012: Impact of Geographic-Dependent Parameter Optimization on Climate Estimation and Prediction: Simulation with an Intermediate Coupled Model. Monthly weather review, 140(12): 3956-3971.
ZHANG S., Z. Liu, A. Rosati, and T. Delworth, 2012: A study of enhancive parameter correction with coupled data assimilation for climate estimation and prediction using a simple coupled model. Tellus. Series A, Dynamic meteorology and oceanography, 64(1): 10963-10920.
CHANG Y.-S., A. Rosati, and S. Zhang, 2011: A construction of pseudo salinity profiles for the global ocean: Method and evaluation. Journal of Geophysical Research, 116(C2): C02002.
CHANG Y.-S., S. Zhang, and A. Rosati, 2011: Improvement of salinity representation in an ensemble coupled data assimilation system using pseudo salinity profiles: improvement of salinity representation. Geophysical research letters, 38(13): L13609.
MAHAJAN S., R. Zhang, T. L. Delworth, S. Zhang, A. J. Rosati, and Y.-S. Chang, 2011: Predicting Atlantic meridional overturning circulation (AMOC) variations using subsurface and surface fingerprints. Deep-sea research. Part II, Topical studies in oceanography, 58(17-18): 1895-1903.
ZHANG S., 2011: Impact of observation-optimized model parameters on decadal predictions: Simulation with a simple pycnocline prediction model: Impact of observation-optimized parameters on decadal predictions. Geophysical research letters, 38(2): L02702.
ZHANG S., 2011: A Study of Impacts of Coupled Model Initial Shocks and State–Parameter Optimization on Climate Predictions Using a Simple Pycnocline Prediction Model. Journal of climate, 24(23): 6210-6226.
ZHANG S., and A. Rosati, 2010: An Inflated Ensemble Filter for Ocean Data Assimilation with a Biased Coupled GCM. Monthly weather review, 138(10): 3905-3931.
ZHANG S., A. Rosati, and T. Delworth, 2010: The Adequacy of Observing Systems in Monitoring the Atlantic Meridional Overturning Circulation and North Atlantic Climate. Journal of climate, 23(19): 5311-5324.
ZHANG S., X. Zou, and J.Ahlquist, 2010: Examination of numerical results from tangent linear and adjoint of discontinuous nonlinear models. Monthly Weather Review, 129(11): 2791-2804.
ZOU X. -K., Sriskandarajah, W. Yu, and S. Zhang, 2010: Eliminating finite-amplitude non-physical oscillation in the time evolution of adjoint model solutions introduced by the leapfrog time-integration scheme. Tellus A: Dynamic Meteorology and Oceanography, 53(5):  578-584.
CHANG Y.-S., A. J. Rosati, S. Zhang, and M. J. Harrison, 2009: Objective analysis of monthly temperature and salinity for the world ocean in the 21st century: Comparison with World Ocean Atlas and application to assimilation validation. Journal of Geophysical Research - Oceans, 114(C2): C02014.
ZHANG S., A. Rosati, and M. J. Harrison, 2009: Detection of multidecadal oceanic variability by ocean data assimilation in the context of a “perfect” coupled model. Journal of Geophysical Research, 114(C12): C12018.
ZHANG S., M. J. Harrison, A. Rosati, and A. Wittenberg, 2007: System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies. Monthly weather review, 135(10): 3541-3564.
ANDERSON J. -L., B. Wyman, S. Zhang, and T. Hoar, 2005: Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system. Journal of the atmospheric sciences, 62(8): 2925-2938.
QIAO F., S. Zhang, and X. Yin, 2005: Study of Initial Vorticity Forcing for Block Onset by a 4-Dimensional Variational Approach. Advances in atmospheric sciences, 22(2): 246-259.
ZHANG S., M. J. Harrison, A. T. Wittenberg, A. Rosati, J. L. Anderson, and V. Balaji, 2005: Initialization of an ENSO Forecast System Using a Parallelized Ensemble Filter. Monthly weather review, 133(11): 3176-3201.
QIAO F., S. Zhang, and Y. Yuan, 2004: Unification and applications of modern oceanic/atmospheric data assimilation algorithms. Journal of Hydrodynamics. Ser. B, 5: 501-517.
ZHANG S., J. L. Anderson, A. Rosati, M. Harrison, S. P. Khare, and A. Wittenberg, 2004: Multiple time level adjustment for data assimilation. Tellus. Series A, Dynamic meteorology and oceanography, 56(1): 2-15.
ZHANG S., and F. Qiao, 2004: Impact of diabatic processes in AGCM on 4-dimensional variational data assimilation. Acta meteorologica Sinica, 18(3): 259-282.
ZHANG S., and J. L. Anderson, 2003: Impact of spatially and temporally varying estimates of error covariance on assimilation in a simple atmospheric model. Tellus. Series A, Dynamic meteorology and oceanography, 55(2): 126-147.
ZHANG S., Zou, and J. E. Ahlquist, 2001: Examination of numerical results from tangent linear and adjoint of discontinuous nonlinear models. Monthly weather review, 129(11): 2791-2804.
ZOU X. -K. Sriskandarajah, W. Yu, and S. Q. Zhang, 2001: Eliminating finite-amplitude non-physical oscillations in the time evolution of adjoint model solutions introduced by the leapfrog time-integration scheme. Tellus. Series A, Dynamic meteorology and oceanography, 53(5): 578-584.
ZHANG S., Zou, J. Ahlquist, I. M. Navon, and J. G. Sela, 2000: Use of differentiable and nondifferentiable optimization algorithms for variational data assimilation with discontinuous cost functions. Monthly weather review, 128(12): 4031-4044.
ZHANG S., and H. Liu, 1996:Characteristics of mean meridional circulations induced by various forcing factors and their contributions to systematic errors of NWP Model. SCIENTIA ATMOSPHERICA SINICA,1(20),112-122.
LIU H., and S. Zhang, 1996:Moist Potential Vorticity and the Three Dimensional Structure of a Cold Front with Heavy Rainfall. Quarterly Journal of Applied Meteorology (Chinese), 7(3),275-284.
ZHANG S., X.Yang, and Z.Huang, 1995: Evaluation of the statistical performance of the interim numerical prediction (T63L16) system. Meteorology(Chinese), 21(10),14-19.
ZHANG S., H. Liu, and G. Wu, 1995: Diagnosis of NWP systematic errors in zonal mean Circulations. ACTA METEOROLOGICA SINICA, 9(3),.288-301.
LIU H., and S. Zhang, 1994: Dynamic diagnostic analysis of thermal system error in NWP model. Quarterly Journal of Applied Meteorology (Chinese), 5(4), 428-435.
WU X., J.Liu, S.Wen, and S.Zhang, 1994: The IPV analysis of the heavy rain process in 1992.07.25. The Meteorology of Neimenggu(Chinese), (4), 1-6.
ZHANG S., J.Chen, and Z.Lei, 1993: Evolution of blocking process on isentropic surface vortex diagram. Journal of Nanjing Tnstitute of Meteorology(Chinese), 16(2), 221-225.
ZHANG S., and H. Liu, 1993:The design principle of a vertical profile of any section direction in spherical 3-d space. Meteorology(Chinese), 19(11),36-40
LIU H., and Zhang, S, 1992: Lecture 4. Statistical test analysis of medium-term numerical forecasting. Meteorology(Chinese),18(9),50-54.
ZHANG S., J.Chen, and Z.Lei, 1992: The blocking is studied by the integral method of material line trajectory. Journal of Nanjing Tnstitute of Meteorology(Chinese),15(3),315-322.
ZHANG S., J.Chen, and Z.Lei, 1991: IPV - a research tool for the effective implementation of the Lagrangian approach. The Meteorology of Neimenggu(Chinese), (4), 1-6.

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