[1]
Z. Shen, Y. Yao, and Y. Zhang, “Ocean State Estimation in CESM via a Localized Particle Filter: Joint Assimilation of Satellite SST and In-situ TS Profiles,” Atmosphere, vol. accepted, 2025.
[2]
Z. Shen, “Conditional Denoising Score Matching for Sequential Data Assimilation,” OLAR, vol. 4, no. 0103, 2025, doi: .
[3]
Z. He, J. Brajard, Y. Wang, X. Wang, and Z. Shen, “Improving dynamical climate predictions with machine learning: insights from a twin experiment framework,” Nonlinear Processes in Geophysics, vol. Accepted, 2025.
[4]
Y. Chen, Y. Tang, Z. Shen, and Y. Li, “Enhancing satelite sea level anomaly data assimilation in a coupled general circulation model with a hybrid mean dynamical topography,” CD, vol. 63, no. 8, 2025, doi: .
[5]
Y. Chen, Z. Shen, and X. Song, “Assessment of an ENSO prediction system based on the Community Earth System Model and Ensemble Adjustment Kalman Filter,” Acta Oceanologica Sinica, vol. accepted, 2025.
[6]
R. Wang and Z. Shen, “A Deep Neural Network Ensemble Adjustment Kalman Filter and Its Application on Strongly Coupled Data Assimilation,” JMSE, vol. 12, no. 108, 2024, doi: .
[7]
Q. Wang, Z. Shen, Y. Chen, X. Chen, and Y. Zhang, “Improving ocean analyses in the ensemble-based data assimilation system using the Community Earth System Model by assimilating satellite sea surface salinity,” Journal of Operational Oceanography, vol. 17, no. 3, pp. 217–230, 2024, doi: .
[8]
Z. Shen, Y. Chen, X. Li, and X. Song, “Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts,” Geosci. Model Dev., vol. 17, no. 4, pp. 1651–1665, Feb. 2024, doi: .
[9]
Y. Chen, X. Yan, Y. Tang, Q. Song, Z. Shen, and Y. Wu, “Decline in Atlantic Niño prediction skill in the North American multi-model ensemble,” CEE, vol. 5, no. 524, 2024, doi: .
[10]
W. Rao et al., “A new ensemble-based targeted observational method and its application in TPOS 2020,” National Science Review, vol. 10, no. 11, Sept. 2023, doi: .
[11]
X. Li, Y. Tang, Z. Shen, and Y. Li, “Spatial Variations in Seamless Predictability of Subseasonal Precipitation Over Asian Summer Monsoon Region in S2S Models,” Journal of Geophysical Research: Atmospheres, 2023, doi: .
[12]
X. Li et al., “A Region-Optional Targeted Observation Method and its Application in the Sea Surface Temperature Prediction Associated with the Indian Ocean Dipole,” Journal of Geophysical Research: Oceans, vol. 128, no. 8, 2023.
[13]
Y. Chen, Z. Shen, Y. Tang, and X. Song, “Ocean data assimilation for the initialization of seasonal prediction with the Community Earth System Model,” Ocean Modelling, vol. 183, no. 102194, 2023, doi: .
[14]
Z. Shen, Q. Zhong, and Z. Chen, “Parameter estimation using adaptive observations towards maximum total variance reduction with ensemble adjustment Kalman filter,” Frontiers in Climate, vol. 4, 2022, doi: .
[15]
T. Liu, X. Song, Y. Tang, Z. Shen, and X. Tan, “ENSO predictability over the past 137 years based on a CESM ensemble prediction system,” Journal of Climate, vol. 35, no. 2, pp. 763–777, 2022, doi: .
[16]
Z. Shen and Y. Tang, “A two-stage inflation method in parameter estimation to compensate for constant parameter evolution in Community Earth System Model,” Acta Oceanologica Sinica, vol. 41, no. 2, p. 12, 2022, doi: .
[17]
M. Hou, Y. Tang, W. Duan, and Z. Shen, “Toward an Optimal Observational Array for Improving Two Flavors of El Niño Predictions in the Whole Pacific,” Climate Dynamics, 2022, doi: .
[18]
S. Deng, Z. Shen, S. Chen, and R. Wang, “Comparison of perturbation strategies for the initial ensemble in ocean data assimilation with a fully coupled earth system model,” Journal of Marine Science and Engineering, vol. 10, no. 3, p. 412, 2022, doi: .
[19]
Y. Chen, Z. Shen, and Y. Tang, “On Oceanic Initial State Errors in the Ensemble Data Assimilation for a Coupled General Circulation Model,” J Adv Model Earth Syst, vol. 14, no. 12, Dec. 2022, doi: .
[20]
张钰婷, 沈浙奇, and 伍艳玲, “基于 CESM 模式的局地化粒子滤波器与集合卡尔曼滤波器同化实验,” 海洋学报, vol. 43, no. 10, pp. 137–148, 2021.
[21]
Z. Shen, Y. Tang, X. Li, and Y. Gao, “On the localization in strongly coupled ensemble data assimilation using a two‐scale Lorenz model,” Earth and Space Science, vol. 8, pp. 1–24, 2021, doi: .
[22]
Y. Hu, X. Tan, Y. Tang, Z. Shen, and Y. Bao, “The Influence of Wind-Induced Waves on ENSO Simulations,” Journal of Marine Science and Engineering, vol. 9, no. 5, p. 14, 2021.
[23]
Y. Gao, Y. Tang, X. Song, and Z. Shen, “Parameter Estimation Based on a Local Ensemble Transform Kalman Filter Applied to El Niño–Southern Oscillation Ensemble Prediction,” Remote Sensing, vol. 13, no. 3923, 2021.
[24]
X. Zhang et al., “A variational successive corrections approach for the sea ice concentration analysis,” Acta Oceanol. Sin., vol. 39, no. 9, pp. 140–154, Sept. 2020, doi: .
[25]
J. Zhang et al., “Targeted observation analysis of the tides and currents in a Coastal Marine Proving Ground,” Ocean Dynamics, Aug. 2020, doi: .
[26]
Y. Wu, Z. Shen, and Y. Tang, “A Flow-dependent Targeted Observation Method for Ensemble Kalman Filter Assimilation Systems,” Earth and Space Science, vol. 7, no. 7, May 2020, doi: .
[27]
X. Li et al., “Optimal error analysis of MJO prediction associated with uncertainties in sea surface temperature over Indian Ocean,” Clim Dyn, Apr. 2020, doi: .
[28]
Y. Gao, T. Liu, X. Song, Z. Shen, Y. Tang, and D. Chen, “An extension of LDEO5 model for ENSO ensemble predictions,” Clim Dyn, Aug. 2020, doi: .
[29]
Z. He, Y. Wang, J. Brajard, X. Wang, and Z. Shen, “Improving Seasonal Arctic Sea Ice Predictions with the Combination of Machine Learning and Earth System Model,” The Cryosphere, vol. 19, no. 3279–3293, 2025, doi: .
1
Z. Shen, Y. Chen, X. Li, and X. Song, “Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts,” Geosci. Model Dev., vol. 17, no. 4, pp. 1651–1665, Feb. 2024, doi: . （参数估计）
2
Z. Shen, Y. Tang, X. Li, and Y. Gao, “On the localization in strongly coupled ensemble data assimilation using a two‐scale Lorenz model,” Earth and Space Science, vol. 8, pp. 1–24, 2021, doi: . （强耦合同化）
3
Z. Shen, Y. Tang, and X. Li, “A new formulation of vector weights in localized particle filter,” Quarterly Journal of the Royal Meteorological Society, vol. 143, no. 709, pp. 3268–3278, 2017, doi: . （局地化粒子滤波）
4
Z. Shen and Y. Tang, “A modified ensemble Kalman particle filter for non-Gaussian systems with nonlinear measurement functions,” Journal of Advances in Modeling Earth Systems, vol. 7, no. 1, pp. 50–66, 2015, doi: . （混合粒子滤波）
5
Z. Shen, “Conditional Denoising Score Matching for Sequential Data Assimilation,” OLAR, vol. 4, no. 0103, 2025, doi: . （扩散模型同化）
