Air-sea interaction
Predictability of weather and climate
Target observation
Ensemble forecasting

Ph. D., 2003, Institute of atmospheric physics, Chinese academy of sciences, Beijing
M. S., 2000,Kunming University of Science and Technology, Kunming
B. S., 1995, Shanxi University, Taiyuan

2019.8.4-8.17，senior visiting scholar, Royal Meteorological Institute of Belgium, Belgium

2017.7.24-8.5, senior visiting scholar, University of Northern British Columnbia, Prince Geoger, Canada

2016.1 - present, Specially-appointed Researcher of Chinese Academy of Sciences

2015. 1 - present, Professor, University of Chinese Academy of Sciences

2014.3.29-4.11, senior visiting scholar,CSRIO computation and Information, Austrialia

2011-2015, the 27th committee member, Dynamic meteorology in Chinese Meteorological Society 

2010.1-present, Professor, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 

2006.11-2010.1, Associate Professor, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 

2003.7-2006.11, Research Assistant, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing

Journal Editor

1. 《Scientia Sinica(Terrae)》、《SCIENCE CHINA Earth Sciences》Editor, 2023.1-2027.12
2. 《Nonlinear Processes in Geophysics》Editor, 2017.10-present
3. 《Advance in Atmospheric Sciences》Editor, 2013-present
4. 《Journal of Marine Science and Engineering》Editor, 2021. 2-present
5. 《Chinese Journal of Atmospheric Sciences》Editor, 2010-present
6. 《Journal of Tropical Meteorology》the Outstanding Editor, 2022.7-2025.12
7. 《Arid Meteorology》Editor, 2021.9-present.


Academic Organization Member

1. the member of IAMAS-ICDM, 2013-present
2. the member of IAMAS-CNC, 2020.07-present
3. the committee member of the 7th CNC-WCRP, 2016-present
4. academic secretary, the Atmospheric Sciences Appraisal Group , the Academic Degrees Committee of the State Council, 2009-2020
5. the 27th committee member, Dynamic meteorology in Chinese Meteorological Society;2011-present
6. the editorial committee member of marine science for the "10000 science problems"; 2015.12-2017.01
7. the academic committee member of the nonlinear air-sea disaster system collaborative innovation center in Ning Bo university;2014-2019

(1) Special government allowances of the State Council, 2020

(2) Zhu-Li Yuehua Outstanding Teacher Award of Chinese academy  of sciences, 2019

(3) Outstanding Member of Youth Talents Innovation Council of Chinese Academy of Sciences,2016

(4) Annual Advanced Researcher of CAS-IAP, 2015

(5) National Science Fund for Distinguished Young Scholars, 2015

(6) Member of Youth Talents Innovation Council of Chinese Academy of Sciences, 2011

(7) Lu Jia Xi Young Talent Award of Chinese Academy of Sciences, 2009

(8) Annual Advanced Researcher of CAS-IAP, 2009

(9) National Outstanding Young Meteorological Science and Technology Researchers Award, 2006

(10) The Author of National Excellent Doctoral Dissertation of PR China, 2006

(11) Outstanding Doctoral Dissertation of Chinese academy of sciences, 2005

(1) Coupled Conditional Nonlinear Optimal Perturbations and its applications to ENSO ensemble forecasts. SCIENCE CHINA Earth Sciences, 2023, to be submitted. 耦合条件非线性最优扰动及其在ENSO集合预报研究中的应用。 段晚锁、胡蕾和冯蓉。中国科学：地球科学，2023, 二审中。

(2) The Sensitive Area for Targeting Observations of Paired Mesoscale Eddies associated with Sea Surface Height Anomaly Forecasts. Jiang Lin, Duan Wansuo, Wang Hui, JGR-Ocean, 2023, Submitted。

(3) Westward-Propagating Disturbances Shape Diverse MJO Propagation. Geophysical Research Letters, 2023, doi: 10.1029/2023GL104778.

(4) Spatiotemporal estimation of analysis errors in the operational global data assimilation system at the China Meteorological Administration using a modified SAFE method. Quarterly Journal of Royal Meteorological Society, 2023, https://doi.org/10.1002/qj.4507

(5) Evaluating the joint effect of tropical and extratropical Pacific initial errors on two types of El Niño prediction using particle filter approach. Journal of Marine Science and Engineering, 2023,11(7), 1292. .

(6) An approach to refining the ground meteorological observation stations for improving PM2.5 forecasts in Beijing-Tianjin-Hebei region. Geoscientific Model Development, 2023,16, 3827–3848 .

(7) Recent advances in China on the predictability studies of weather and climate. . Advances in Atmospheric Science, 2023, 40(8), 1521−1547 .

(8)Evaluation of the sensitivity on mesoscale eddy associated with the sea surface height anomaly forecasting in the Kuroshio Extension. Frontiers in Marine Science, 2023, 10:1097209. doi: 10.3389/fmars.2023.1097209.

(9)A multi-model prediction system for ENSO. Science China Earth Sciences, 2023, 66, https://doi.org/10.1007/s11430-022-1094-0..

(10)Role of the thermodynamic structure of the inner core in predicting the intensification of Hurricane Patricia (2015). J. Geophys. Res. Atmos., 2023, accepted.

(11)Impact of the low wavenumber structure in the initial vortex wind analyses on the prediction of the intensification of Hurricane Patricia (2015).  J. Geophys. Res. Atmos., 2022, 128, e2022JD037082.

(12)2022 年汛期气候趋势预测与展望。气候与环境研究，2022, 27(4), 547-558。

(13)Distinct effects of initial and model parametric uncertainties on El Niño predictions associated with spring predictability barrier, Climate Dynamics, 2023, submitted.

(14)Impacts of initial zonal current errors on the predictions of two types of El Niño events. JGR-Oceans, 2023, 128, e2023JC019833.

(15)A New Approach to Represent Model Uncertainty in forecasting Tropical Cyclones: The Orthogonal Nonlinear Forcing Singular Vectors. Quarterly Journal of Royal Meteorological Society, 2023, accepted. https://doi.org/10.1002/qj.4502.

(16)  Using the orthogonal conditional nonlinear optimal perturbations approach to address the uncertainties of tropical cyclone track forecasts generated by the WRF model. Weather and Forecasting, 2023, accepted.

(17)Using an ensemble nonlinear forcing singular vector data assimilation approach to address the challenge of ENSO forecasts posed by "spring predictability barrier" and El Nino diversity. Climate Dynamics, 2023, https://doi.org/10.1007/s00382-023-06834-3.

(18) Impact of the low wavenumber structure in the initial vortex wind analyses on the prediction of the intensification of Hurricane Patricia (2015). J. Geophys. Res. Atmos., 2022,  128, e2022JD037082..

(19)Seasonally Alternate Roles of the North Pacific Oscillation and the South Pacific Oscillation in Tropical Pacific Zonal Wind and ENSO.  Journal of Climate, 2023. https://doi.org/10.1175/JCLI-D-22-0461.1

(18)Effects of dropsonde data in field campaigns on forecasts of tropical cyclones over the western North Pacific in 2020 and role of CNOP sensitivity. Advances in Atmospheric Sciences, 2022.

(19)An ensemble forecasting method for dealing with the combined effect of the initial errors and the model errors and a potential deep learning implementation. Mon. Wea. Rev., 2022

(20)Evaluation and Projections of Precipitation Extremes using a Spatial Extremes Framework. International Journal of Climatology. 2022

(21)Toward targeted observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing-Tianjin-Hebei region.  Atmospheric Chemistry and Physics, 2022

(22)A new approach to data assimilation for numerical weather forecasting and climate prediction.  Journal of Applied Analysis and Computation. 2022

(23)非线性最优扰动方法在热带气旋目标观测研究和外场试验中的应用。地球科学进展，2022

(24)Toward an optimal observational array for improving two flavors of El Niño predictions in the whole Pacific.  Climate Dynamics, 2022.

(25)The different relationships between ENSO spring Persistence Barrierand Predictability Barrier.  Journal of Climate, 2022.

(26)台风集合预报研究进展综述。大气科学学报，2022, 45(5), 713-727。

(27)The Deep Learning Galerkin Method for the General Stokes Equations. Li Jian, Jing Yue, Zhang Wen, and Duan Wansuo, Journal of Scientific Computing, 2022, 93, 5, https://doi.org/10.1007/s10915-022-01930-8.

(28)伴随敏感性方法、第一奇异向量方法以及条件非线性最优扰动方法在台风目标观测敏感区识别中的比较研究，周菲凡, 叶一苇, 段晚锁, 等.大气科学, 2022，46(X): 1−14.

(29)Complex network analysis of fine particulate matter (PM2.5): transport and clustering, Na Ying, Duan Wansuo, Zhao Zhidan, Fan Jingfang, Earth System Dynamics. 2022. 13, 1029-1039

(30)The most sensitive initial error of sea surface height anomaly forecasts and its implication for target observations of mesoscale eddies. J. Physical Oceanography. 2022.

(31)台风强度模拟的海温目标观测研究，大气科学，2022. 通讯作者

(32)近海台风立体协同观测科学试验进展, 地球科学进展，2022，37(8)：771-785。

(33)A precursory signal of the Central Pacific El Niño event: Eastern Pacific cooling mode. J. Climate. 2021

(34)Model errors of an intermediate model and their effects on realistic predictions of El Niño diversity.JGR-Atmosphere, 2021. 

(35)Using Conditional Nonlinear Optimal Perturbation to Generate Initial Perturbations in ENSO Ensemble Forecasts.  Weather and Forecasting. 2021. 通讯作者

(36)How does El Nino affect predictability barrier of its accompanied positive Indian Ocean Dipole event? J. Marine Sciences and Engineering. 2021. 通讯作者

(37)The most sensitive initial error modes modulating intensities of CP- and EP- El Niño events. Dynamics of Atmospheres and Oceans, 2021, 通讯作者

(38)Interdecadal change in the relationship between boreal winter North Pacific Oscillation and Eastern Australian rainfall in the following autumn.  Climate Dynamics. 2021. 

(39)The Initial Errors in the Tropical Indian Ocean that Can Induce a Significant “Spring Predictability Barrier” for La Niña Events and Their Implication for Targeted Observations. Advances in Atmospheric Sciences, 2021. 

(40)On the sensitive areas for targeted observations in ENSO forecasting,  AOSL, 2021.  通讯作者

(41)Typhoon intensity forecasting based on LSTM using the rolling forecast method,  Algorithms，2021

(42)Optimally growing initial errors of El Nino events in the CESM, 2021, Climate Dynamics

(43)Which features of the SST forcing error are most likely to disturb the simulation of tropical cyclone intensity?  Adavnces in Atmospheric Sciences, 2021. 通讯作者

(44)Forecast uncertainty of rapid intensification of typhoon Dujuan (201521) induced by uncertainty in the boundary layer.  Atmosphere, 2020. 通讯作者

(45)Model forecast error correction based on the Local Dynamical Analog method: an1example application to the ENSO forecast by an Intermediate Coupled Model. Geophysical Research Letters. 2020.

(46)Predictable patterns of wintertime surface air temperature in Northern Hemisphere and their predictability sources in SEAS5, Journal of Climate, 2020

(47)Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach.  Climate Dynamics, 2020. 通讯作者

(48)On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems. Climate Dynamics, 2020

(49) Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF. Advances in Atmospheric Sciences, 2020

(50)Errors in current velocity in the low-latitude north Pacific: results from the regional ocean modeling system. Advances in Atmospheric Sciences, 2019.通讯作者

(49)近海台风立体协同观测科学试验。地球科学进展，2019。

(50)Exploring sensitive area in the tropical Indian Ocean for the El Nino predictions: an implication for targeted observation. Journal of Oceanology and Limnology, 2019. 通讯作者

(51)Using a nonlinear forcing singular vector approach to reduce model error effects in ENSO forecasting. Weather and Forecasting, 2019. 通讯作者

(52)始扰动振幅和集合样本数对CNOPs集合预报的影响。大气科学，2019，已接收。通讯作者

(53)Season-dependent predictability barrier for two types of El Niño-Southern Oscillation events revealed by an approach to data analysis for predictability. Climate Dynamics, 2019. 通讯作者

(54)数值天气预报、气候预测的集合预报方法：思考与展望。气候与环境研究，2019。第一作者

(55)Indian Ocean Dipole-related predictability barriers induced by initial errors in the tropical Indian Ocean in a CGCM. Advances in Atmospheric Sciences, 2019. 通讯作者

(56)Season-dependent predictability and error growth dynamics for La Niña predictions. Climate Dynamics, 2019. 通讯作者

(57)The Initial Condition Errors Occurring in the Indian Ocean Temperature That Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean. JGR-Ocean, 2019. 通讯作者

(58)Ensemble forecasts of tropical cyclone track with orthogonal conditional nonlinear optimal perturbations.  Advances in Atmospheric Sciences, 2019. 通讯作者

(59)The role of initial signals in the tropical Pacific Ocean in predictions of negative Indian Ocean Dipole events. SCIENCE CHINA Earth Sciences. 2018. 通讯作者

(60) Progress in ENSO prediction and predictability study. National Science Review. 2018.

(61)Asymmetry of the predictability limit of the warm ENSO phase. Geophysical Research Letters. 2018.

(62)The application of the orthogonal conditional nonlinear optimal perturbations method to typhoon track ensemble forecasts. SCIENCE CHINA Earth Sciences. 2018. 通讯作者

(63)Impact of SST anomaly events over the Kuroshio-Oyashio Extension on the "summer prediction barrier".Advances in Atmospheric Sciences, 2018.

(64)北京地区一次空气重污染过程的目标观测分析[J]. 气候与环境研究. 2018. 通讯作者

(65)"Summer Predictability Barrier" of Indian Ocean Dipole Events and Corresponding Error Growth Dynamics. JGR-Ocean, 2018. 通讯作者 

(66)Possible sources of forecast errors generated by the global/regional assimilation and prediction system for landfalling tropical cyclones. Part II: model uncertainty. Adv. Atmos. Sci., 2018.

(67)Investigating the initial errors that cause predictability barriers for IOD events using CMIP5 model outputs. Advances in Atmospheric Sciences, 2018. 通讯作者 

(68) Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño. Climate Dynamics, 2018.第一作者

(69)季风与ENSO的选择性相互作用：年循环和春季预报障碍的影响。大气科学，2018

(70)粒子滤波同化在厄尔尼诺-南方涛动目标观测中的应用。大气科学，2018. 第一作者

(71)Predictability of El Niño-Southern Oscillation Events.Oxford Research Encyclopedia of Climate Science, 2018. 第一作者

(72)The application of nonlinear local Lyapynov vectors to the Zebiak-Cane model and their performance in ensemble prediction. Clim Dyn. 2017.

(73)耦合模式中北太平洋和北大西洋海表面温度年代际可预报性和预报技巧的季节依赖性，地球科学进展，2017.

(74)The predictability of atmospheric and oceanic motions: Retrospect and prospects.Science China: Earth Sciencess, 2017. 通讯作者

(75)On the "spring predictability barrier" for strong El Nino events as derived from an intermediate coupled model ensemble prediction system. SCIENCE CHINA Earth Sciences, 2017. 通讯作者

(76)Nonlinearity Modulating Intensities and Spatial Structures of Central Pacific- and Eastern Pacific-El Niño Events. Adv. Atmos. Sci., 2017.第一作者 

(77)Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction. Journal of Geophysical Research: Oceans, 2017.

(78)Reducing the prediction uncertainties of high-impact weather and climate events: an overview of studies at LASG. Journal of Meteorological Research. 2017.第一作者

(79)Numerical Analysis of the Mixed 4th-Order Runge-Kutta Scheme of Conditional Nonlinear Optimal Perturbation Approach for the El Nino-Southern Oscillation Model, Adv. Appl. Math. Mech., 2016.

(80)The role of nonlinear forcing singular vector tendency error in causing the "spring predictability barrier" for ENSO. Journal of Meteorological Research, 2016.第一作者

(81)IOD-related optimal initial errors and optimal precursors for IOD predictions from reanalysis data.  SCIENCE CHINA Earth Sciences. 2016，通讯作者

(82)Seasonal predictability of sea surface temperature anomalies over the Kuroshio-Oyashio Extension: low in summer and high in winter, JGR-Ocean, 2016,通讯作者

(83)Time-scale Decomposed Threshold Regression Downscaling Approach to Forecasting South China Early Summer Rainfall, Advances in Atmospheric Sciences, 2016,通讯作者

(84)Relationship between optimal precursory disturbances and optimally growing initial errors associated with ENSO events: Implications to target observations for ENSO prediction. Journal of Geophysical Research - Oceans, 2016.通讯作者

(85)Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictions, Climate Dynamics,2016. 通讯作者

(86)Comparison of constant and time-variant optimal forcing approaches in El Niño simulations by using the Zebiak-Cane model.  Adv. Atmos. Sci., 2016. 通讯作者

(87)An approach to generating mutually independent initial perturbations for ensemble forecasts: orthogonal conditional nonlinear optimal perturbations. J. Atmos. Sci., 2016. 第一作者

(88)Application of Conditional Nonlinear Optimal Perturbation to Targeted Observation Studies of the Atmosphere and Ocean,  J. Meteor. Res,. 2015

(89)关于线性奇异向量和条件非线性最优扰动差别的一个注记。气候与环境研究，2015，通讯作者

(90)The influence of boreal winter extratropical North Pacific Oscillation on Australian spring rainfall, Clim Dyn, 2015, 通讯作者 

(91) Dynamics of nonlinear error growth and the "spring predictability barrier" for El Nino predictions. Duan Wansuo, Mu Mu, Chapter 5 in Climate Change edited by Chin-Pei Chang, Michael Ghil, Mojib Latif, and John M. Wallace. World Scientific Series on Asian-Pacific Weather and Climate, 2015.

(92)Comparison of the initial errors most likely to cause a spring predictability barrier for two types of El Nino event. Clim Dyn, 2015, 通讯作者

(93) Interannual Relationship between the Winter Aleutian Low and Rainfall in the Following Summer in South China, Atmos. Oceanic Sci. Lett, 2015,通讯作者

(94) The initial errors that induce a significant “spring predictability barrier” for El Nino events and their implications for target observations:results from an earth system model,Clim Dyn, 2015,第一作者

(95) Target observations for improving initialization of high-impact ocean-atmospheric environmental events forecasting, National Science Review,2015, 通讯作者

(96) The “winter predictability barrier” for IOD events and its error growth dynamics: results from a fully coupled GCM, Journal of Geophysical Research: Oceans, 2014, 通讯作者

(97) Influence of Positive/Negative Indian Ocean Dipole on Pacific ENSO through Indonesian Throughflow: results from Sensitivity Experiments, Adv. Atmos. Sci., 2014, 通讯作者

(98) Revealing the most disturbing tendency error of Zebiak-Cane model associated with El Nino predictions by nonlinear forcing singular vector approach，Climate Dynamics，2014，第1作者 

(99) Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies，Climate Dynamics，2014，第1作者 

(100) Study on the “winter persistence barrier” of Indian Ocean dipole events using observation data and CMIP5 model outputs，Theoretical and Applied Climatology，2014，通讯作者 

(101) A SVD-based ensemble projection algorithm for calculating conditional nonlinear optimal perturbation, SCIENCE CHINA: Earth Sciences，2014，第2作者

(102)  Using CMIP5 model outputs to investigate the initial errors that cause the “spring predictability barrier” for El Niño events, SCIENCE CHINA: Earth Sciences, 2014，通讯作者 

(103)  ENSO预测的目标观测敏感区在热带太平洋海温的多模式集合预报中的应用，大气科学，2014，通讯作者 

(104) Time-dependent nonlinear forcing singular vector-type tendency error of the Zebiak-Cane model, Atmos. Oceanic Sci. Lett., 2014，通讯作者 

(105)The combined effect of initial error and model error on ENSO prediction uncertainty generated by the Zebiak-Cane model, Atmos. Oceanic Sci. Lett., 2014，通讯作者 

(106) The spatial patterns of initial errors related to the “winter predictability barrier” of the Indian Ocean dipole, Atmos. Oceanic Sci. Lett., 2014，通讯作者 

(107) Conditions under which CNOP Sensitivity Is Valid for Tropical Cyclone Adaptive Observations，Quarterly J. RMS，2013，通讯作者 

(108) 条件非线性最优扰动方法在可预报性研究中的应用，大气科学，2013，第2作者 

(109) 数值天气预报和气候预测可预报性研究的若干动力学方法，气候与环境研究，2013，第1作者 

(110) Climate Variability and Predictability at Various Time Scales，Advances in Meteorology，2013，第3作者 

(111) Seasonal modulations of different impacts of two types of ENSO events on tropical cyclone activity in the western North Pacific，Climate Dynamics，2013，第4作者 

(112) Modulation of PDO on the predictability of the inter-annual variability of early summer rainfall over South China，JGR-Atmosphere，2013，第1作者 

(113) Simulations of two types of El Nino events by an optimal forcing vector approach，Climate Dynamics，2013，第1作者 

(114) The role of nonlinearities associated with air-sea coupling processes in El Nino’s peak-phase locking，Sciences in China (D)，2013，第1作者 

(115) Behaviors of nonlinearities modulating El Nino events induced by optimal precursory disturbance，Climate Dynamics，2013，第1作者 

(116) The role of constant optimal forcing in correcting forecast model，Sciences in China (D)，2013，通讯作者 

(117) Nonlinear forcing singular vector of a two-dimensional quasi-geostrophic model，Tellus-A，2013，第1作者 

(118) Does model parameter error cause a significant spring predictability barrier for El Nino events in the Zebiak-Cane model，J. Climate，2012，通讯作者 

(119)Contribution of the location and spatial pattern of initial error to uncertainties in El Nino predictions，JGR-Ocean，2012，第3作者 

(120) The spring predictability barrier for ENSO predictions and its possible mechanism: results from a fully coupled model，Inter. J. Climatology，2012，第1作者 

(121) The amplitude-duration relation of the observed El Nino events，Atmos. Oceano. Sci. Lett.，2012，通讯作者 

(122) 四个耦合模式ENSO后报试验的“春季预报障碍”，气象学报，2012，第3作者 

(123)Progresses in the studies of nonlinear atmospheric dynamics and predictability for weather and climate in China （2007-2010），Adv. Atmos. Sci.，2012，第5作者 

(124) Can the Uncertainties of Madden–Jullian Oscillation Cause a Significant Spring Predictability Barrier for ENSO Events，Acta Meteorologica Sinica.，2012，第2作者 

(125) Effect of Stochastic MJO Forcing on ENSO Predictability，Adv. Atmos. Sci.，2011，通讯作者 

(126) A new strategy for solving a class of nonlinear optimization problems related to weather and climate predictability，Adv. Atmos. Sci.，2010，第1作者 

(127) An extension of conditional nonlinear optimal perturbation approach and its applications，Nonlin. Processes Geophys，2010，通讯作者 

(128) The “Spring Predictability Barrier” Phenomenon of ENSO Predictions Generated with the FGOALS-g Model，AOSL，2010，通讯作者 

(129) Is model parameter error related to spring predictability barrier for El Nino events，Adv. Atmos. Sci，2010，第1作者 

(130) Conditional nonlinear optimal perturbation: applications to stability, sensitivity, and predictability，Science in China (D)，2009，第1作者 

(131) Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model，Quarterly Journal of Royal Meteorological Society，2009，第2作者 

(132)Decisive role of nonlinear temperature advection in El Nino and La Nina amplitude asymmetry，J. Geophysical Research，2009，第1作者 

(133) Exploring the initial error that causes a significant spring predictability barrier for El Nino events，J. Geophysical Research，2009，第1作者 

(134) 赤道高频纬向风强迫对ENSO强度的影响，气候与环境研究，2009，第2作者 

(135) Zebiak-Cane数值模式的可预报性分析，气候与环境研究，2008，第2作者 

(136) What kind of initial errors cause the severest prediction uncertainties for El Nino in Zebiak-Cane model，Adv. Atmos. Sci.，2008，通讯作者 

(137) Investigating a nonlinear characteristic of ENSO events by conditional nonlinear optimal perturbation，Atmospheric Research，2008，第1作者 

(138) Season-dependent dynamics of nonlinear optimal error growth and ENSO predictability in a theoretical model，Journal of Geophysical Research，2007，第1作者 

(139) A kind of initial errors related to “spring predictability barrier“ for El Nino event in Zebiak-Cane model，Geophysical Research Letters，2007，第3作者 

(140) Progress in predictability studies in China (2003-2006)，Adv. Atmos. Sci.，2007，第1作者 

(141) Investigating decadal variability of El Nino-Southern Oscillation asymmetry by conditional nonlinear optimal perturbation，J. Geophysical. Research，2006，第1作者 

(142) Applications of conditional nonlinear optimal perturbation in predictability study and sensitivity analysis of weather and climate，Adv. Atmos. Sci.，2006，通讯作者 

(143) 用非线性最优化方法研究El Nino可预报性的进展与前瞻，大气科学，2006，第1作者 

(144) The Tangent Linear Model and Adjoint of a Coupled Ocean-Atmosphere Model and Its Application to the Predictability of ENSO，International Geoscience and Remote Sencing Symposium，2006，第2作者 

(145) 数值模式误差对降水四维变分资料同化及预报的影响，气候与环境研究，2006，第2作者 

(146) Applications of nonlinear optimization method to the numerical studies of atmospheric and oceanic sciences，Appl. Math. Mech.，2005，第1作者 

(147) Applications of nonlinear optimization methods to quantifying the numerical model for ENSO，Progress in Natural Sciences，2005，第1作者 

(148) Recent advances in predictability studies in China (1999-2002)，Adv. Atmos. Sci.，2004，第2作者 

(149) Conditional nonlinear optimal perturbation as the optimal precursors for El Nino-Southern Oscillation events，J. Geophy. Res.，2004，第1作者 

(150) Chaotic and resonant streamlines in quasi-symmetric flows，Mathematic Applicata，2004，第1作者

Invited Talks:
(1)Wansuo Duan, HuiXu, A study on ENSO asymmetry by conditional nonlinear optimal perturbation, Asia Oceanic Geosciences Society16－20 June,  Busan,Korea, 2008.
(2)Wansuo Duan, MuMu, Conditional nonlinear optimal perturbation and its applications to thestudies of ENSO predictability. 1st PRIMA conference, Sydney,Australia, July 6-10, 2009.
(3)Wansuo Duan, XinchaoLiu, Mu Mu, Characteristic of initial errors that cause a significant springpredictability barrier for El Nino events. AOGS 2009, Singapore, August 10-15, 2009.
(4)Wansuo Duan, Revealing a new feature of ENSO events, EGU2010, May 2-7,  Vienna, Austria, 2010.
(5)Wansuo  Duan, MuMu, Conditional nonlinear optimal perturbation and its applications. CIMPAUNESCO THEMATIC SCHOOL, DATAASSIMILATION FOR GEOPHYSICAL FLUIDS, WUHAN (China), May 3 – May 14 , 2010.
(6)Wansuo Duan , The nonlinear optimization method and its application in the study of weather and climate predictability, NSNMF,  Beijing. Aug, 2011
(7)Wansuo Duan, Wei Chao, The "spring predictabilitybarrier" for ENSO predictions and its possible mechanism: results from afully coupled model，EGU 2012 General Assembly，Vienna，Austria. April 22-27 2012.
(8)Wansuo Duan, Yu Yanshan, Does model parameter error cause asignificant spring predictability barrier for El Nino events in the Zebiak-Canemodel?，AOGS-AGU 2012 General Assembly，Singapore. August 13-17 2012.
(9)Wansuo Duan, Wu Yujie, Season-dependent predictability of PDO-related SST anomalies and its error growth dynamics . the academic annual conference of the second institute of oceanography, SOA, Hangzhou, Jan 7-9, 2014.
(10)Wansuo Duan, Nonlinear forcing singular vector and related predictability，2015 International Workshop on Control problem with PDE constraints and interface problems. Nanjing Normal University, Xianlin Campus from June 10 to June 12, 2015.
(11)Wansuo Duan, Tian Ben, Constrasting initial errors that cause a significant "spring predictability barrier" for ENSO. IGU2015, Moscow, Aug. 17-21, 2015.
(12)Wansuo Duan, Application of sensitive area for target observation associated with El Nino Southern Oscillation predictions to multimodel ensemble forecast of the tropical Pacific sea surface temperature. Chengdu, Sep, 14-15,2015.
(13)Wansuo Duan, The nonlinear forcing singular vector method and its application in the study of ENSO predictability.  The academic annual conference of IAP, Beijing, Sep, 24,2015.
(14)Wansuo Duan, Feng Rong, Mu Mu, Target observation of high-impact ocean-atmospheric environmental events. National conference on the climate system research, Nanjing, Nov, 25-27,2015
(15)Wansuo Duan, Tian Ben, Chen Lei, Li Xuquan, Comparison of initial errors most likely to cause a significant spring predictability barrier for two types of El Nino events. workshop on the western Pacific Ocean circulation and ENSO and long-term climate dynamics, Qingdao, 12.7-8, 2015.
(16) Wansuo Duan, A new method to generate initial disturbance  for ensemble forecast and its application in the typhoon forecast research. Academic annual conference of Chinese Academy of Meteorological Sciences. Beijing, 1. 7-8, 2016.

(17) Wansuo Duan, Ben Tian, Xuquan Li, Lei Chen, Sensitive areas for targeting observations associated with predictions of two types of El Nino events. COAA. Beijing, China. 07.27-30,  2016.

(18) Wansuo Duan, Peng Zhao, The most disturbing tendency error of the Zebiak-Cane model associated with ENSO predictions. AOGS2016,  Beijing, China. 08.01-05, 2016.

(19) Wansuo Duan, Target observations for two types of El Nino events and their role in reducing prediction uncertainties. The 2016 academic annual conference of Chinese Meteorological Society, Xi'an, China. 11.02-04,2016.

(20) Wansuo Duan, Ben Tian, Xuquan Li, Target observation for improving initialization of two types of El Nino predictions. PAMS 2017, Jeju Island, South Korea, 4.11-13. 2017.

(21) Wansuo Duan, An approach to generating mutually independent initial perturbations for ensemble forecasts: orthogonal conditional nonlinear optimal perturbations. International Conference on Random Dynamical Systems, Wuhan, China. 6. 24-27, 2017.

(22) Wansuo Duan, Ben Tian,Target observations for improving initializations for two types of El Nino events predictions. AOGS2017, Singapore, 8.6-11, 2017.

(23) Wansuo Duan, A new targeted observation method based on particle filter and its application in two types of El Nino predictions.The 2017 academic annual conference of Chinese Meteorological Society, Zhengzhou, China. 9.26-30, 2017.

(24) Wansuo Duan, Target observations for improving initializations for two types of El Nino events predictions. BIRS workshop: Nonlinear and Stochastic Problems in Atmospheric and Oceanic Prediction. Banff, Canada, 11.19-24, 2017.

(25) Wansuo Duan，Tao Lingjiang, An ENSO forecast system based on an intermediate model and optimal forcing vector assimilation. AOGS2018. Hawaii, 6.2-8, 2018.
(26) Wansuo Duan, Hou Meiyi, An approach to data analysis for predictability: application to two flavors of El Niño. AOGS2019, July 27-August 3, 2019, Singapore.
(27) Wansuo Duan, Zhou Qian, Mu Mu, The Initial Errors Occurring in the Indian Ocean Temperature that Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean.AOGS2019, July 27-August 3, 2019, Singapore.

(28) Wansuo Duan, A data assimilation approach for dealing with combined effect of kinds of model errors and its application.  13th National Symposium on Assimilation and Numerical Simulation of Marine Data, Hunan, China.12. 3-4, 2020. 

(29) Wansuo Duan, Nonlinear Optimization Method and Its Application in Numerical Weather and Climate forecast，4th CSSC2020，Qingdao, China， 9. 19-20, 2020, On-line.

(30) Wansuo Duan, Junjie Ma, Stephan Vannitsem, A novel ensemble forecasting method for dealing with combined effect of the initial error and the model error and its potential deep learning implementation. AOGS2022, August 01-05, 2022, Singapore.

(31) Wansuo Duan, Zheng Yinchong, Tao Lingjiang Using a novel data approach to address the challenge posed by the spring predictability barrier and El Nino diversity for ENSO forecasting. The 4th World Science and Technology development forum: Climate changes and Environmental Sustainable Development. November 26, 2022, Chengdu, China.

(32) Wansuo Duan, Zheng Yinchong, Tao Lingjiang，Using a novel NFSV-DA approach to deal with the challenge posed by the El Nino diversity and spring predictability barrier for ENSO forecasting. IYBSSD--International Forum for Climate and Environmental Changes and Sustainable Development, November 22-26, 2022, Beijing, China.

(33) Wansuo Duan, Ma Junjie, Zhang Han and Zhang Yichi. An ensemble forecasting method for dealing with combined effects of the initial and model errors and a potential deep learning implementation: applications to realistic typhoon forecast. The third conference on complex network and Earth Science. November 26-27, 2022, Zhuhai, China.
(34) Wansuo Duan, A novel ensemble forecasting method for dealing with combined effect of initial and model errors and its potential implementation using machine learning. NSNMF20, March 31-April 2, 2023, Nanjing, China.

Domestic conference 

The first seminar on predictability of atmosphere and ocean

The second seminar on predictability of atmosphere and ocean

The third seminar on predictability of atmosphere and ocean

The first summer workshop on applications of nonlinear optimal approach to the atmosphere and ocean

The second summer workshop on applications of nonlinear optimal approach to the atmosphere and ocean

The third summer workshop on applications of nonlinear optimal approach to the atmosphere and ocean

The seminar on targeted observation and field campaigns of typhoon forecasts

International conference

(1) Youmin Tang, Wansuo Duan, Shouhong Wang,  Mu Mu, Olivier Talagrand, Nonlinear and Stochastic Problems in Atmospheric and Oceanic Prediction. BIRS workshop, Banff, Canada, 11.19-24, 2017.

(2) Local co-chair: Wansuo Duan, Ruiqiang Ding, International Commission on Dynamical Meteorology (ICDM) 2012 workshop: Dynamics and predictability of high-impact weather and climate events, Kunming, China.6–9 July 2012.

Branch of International conference

(1) Wansuo Duan， Chun-Chieh Wu, Hyun Mee Kim, AS05：Predictability of weatherand climate: theory and applications. AOGS2009, Aug 2009.

(2) Wansuo Duan，F.X. Le Dmiet, Youmin Tang, Kyun mee Kim, AS12：Predictability of weatherand climate: theory， methodology, and applications. AOGS2010, India, 2010.

(3) Mu Mu, Wansuo Duan, NP5.3 Nonlinear optimal mode andits applications in predictability, sensitivity, and stability. EGU2010, Vienna, May 2010.

(4) Zoltan Toth, Wansuo Duan, S. Vannesti et al. NP5.3：Nonlinear instability and predictability,EGU2011, Vienna, Apr 2011.

(5) Mu Mu, Wansuo Duan, S. Vannesti NP5.3：Nonlinear optimal mode andrelated predictability, sensitivity, and stability. EGU 2012, Vienna, April 2012.

(6) Wansuo Duan, F. Sellevec, Peter J. Vanllevon, AS39: Predictability ofweather and climate: theory, methodology, and applications.AOGS-AGU2012, Singapore, August 13-17, 2012.
(7) Mu Mu, Wansuo Duan, S. Vannesti, NP5.3: Error growth dynaimics and related predictability for weather and climate. EGU2013, Vienna, Apr 2013.

(8) Mu Mu, S. Vannesti, Wansuo Duan, NP5.3: Initial error dynamics and model error physics in weather and climate predictability studies. EGU2014, Vienna, Apr 28- May 2, 2014.

(9) Shaocheng Xie, Wansuo Duan, Kuan-Man Xu, Masahiro Watanabe et al., AS08-13: Predictability Problems and Systematic Errors in Numerical Weather and Climate Prediction: Theory, Modeling and Evaluation. AOGS 2014 General Assembly, Sapporo, Japan, 28 Jul to 01 Aug, 2014.

(10) Mu Mu, S. Vannesti, Wansuo Duan, NP5.3: Initial error dynamics and model error physics in weather and climate predictability studies. EGU 2014 General Assembly, Vienna,April 12-17, 2015.

(11) Wansuo Duan, Stephane Vannitsem, Tieh-Yong Koh, AS28：Predictability of Weather and Climate: Theory, Methodology and Applications. AOGS 2015 General Assembly, Singapore. Aug 2-7, 2015.

(12) Olivier Talagrand, S. Vannesti, Wansuo Duan, etc，NP5.2: Inverse problem of data assimilation, Initial error and model error. EGU 2016 General Assembly, Vienna, April17 – 22, 2016.

(13) Zheng Fei, Noel Keenlyside, Wansuo Duan, Stephane Vanisstem, et al., OS08-AS16: Advances In Data Assimilation And Ensemble Forecast: Applications To Studies And Predictability Of Atmosphere-ocean Variability. AOGS 2016 General Assembly, Beijing, August 1-5, 2016.

(14) Zhang Ronghua, Wang Dongxiao,  Wansuo Duan, Session Title： Ocean process and modelling. COAA 2016, Beijing, July 27-30, 2016.

(15) Olivier Talagrand, Stéphane Vannitsem, Wansuo Duan, Amos Lawless, Matthew Martin, Alberto Carrassi, Javier Amezcua. NP5.1: Inverse Problems, Data Assimilation and Error Dynamics. EGU2017, Vienna, Austria, 4.24-29, 2017.

(16) Mu Mu,Wansuo Duan, Stéphane Vannitsem. NP5.2: Initial error dynamics and model error physics in predictability studies of weather and climate. EGU2017, Vienna, Austria. 4.24-29, 2017.

(17) WanSuo Duan, Youmin Tang, Mu Mu, Zhijin Li. 1704061: Data Assimilation, Ensemble Prediction, and Intrinsic Predictability. CMOS 2017 Congress, Toronto , Canada. 6. 4-8, 2017.

(18) Craig H. Bishop, Weijia Kuang, Wansuo Duan, Andrew Moore et al., JA3 - Frontier Challenges In Data Assimilation And Ensemble Forecasting ForThe Atmosphere, Ocean And Solid Earth (IAGA, IAMAS, IAPSO). IAMAS-2017, Cape Town, South Africa, 8.27-9.1, 2017.

(19) Stéphane Vannitsem，Wansuo Duan，Noel Keenlyside，Fei Zheng，AS36 - Ocean-atmosphere Coupling: Dynamics, Assimilation, and Predictability. AOGS2018 General Assembly, Hawaii,  6. 2-8, 2018.

(20) Olivier Talagrand, Javier Amezcua, Alberto Carrassi, Amos Lawless, Mu Mu, Wansuo Duan, Stéphane Vannitsem. NP5.1: Data assimilation, Predictability, Error Identification and Uncertainty Quantification in Geosciences. EGU2019, Vienna, Austria, 4.7-12, 2019.

(21) Mu Mu, Alexander Feigin, Wansuo Duan, Jürgen Kurths, Stéphane Vannitsem, NP5.2 New approaches to predictions and predictability estimation for geophysical fluid. EGU2020, Vienna, Austria, 5.4-8, 2020. On-line.

(22) Vena Pearl Bongolan, Wansuo Duan, and Ramsundram Narayanan. AOGS2021: IG02 Natural Hazards and Disaster Risk. Virtual meeting from Singapore.1-6 August 2021

(23) Vena Pearl Bongolan, Wansuo Duan, Ramsundram Narayanan, James Terry.  AOGS2022: IG31-Natural Hazards and Disaster Risk. 1-5 August 2022, Virtual meeting from Singapore.

Working staff: 

Guodong Sun, researcher; research field: uncertainty of simulation about land progress

Feifan Zhou, associate researcher; research field: the predictability study of tropical cyclones

Xiaohao Qin, associate researcher; research field: the predictability study of tropical cyclones

Rong Feng, associate researcher; research field: the predictability study of Indian Ocean dipole

Hui Xu, assistant researcher; research field: the predictability study of ENSO

Lichao Yang, postdoctor; research field: Atmospheric environmental meteorology and its predictability

 

Graduates: 

2022:

Wenyao Li, master,  meteorological observatory of Lan Zhou center; Lin Jiang, Ph.D, Institute of Marine Science and Technology, Shandong University

2021:

Jiawei Yao, Ph. D, National Marine Environmental Forecasting Center

2020:

Lingjiang Tao, Ph. D, Fudan University; Meiyi Hou, Ph. D, Hohai University

2019:

Xixi Wen, Ph. D, South China Sea Institute of Oceanology Chinese Academy of Sciences

2018:

Na Liu, master,  Insights Value, Beijing; Xuquan Li, Ph. D, Harvest Fund; Qianqian Qi, Ph. D, China Meteorological Administration; Da Liu, Ph. D,  China Meteorological Administration; Ye Wang, Ph. D, Henan University

2017:

Chaoming Huang, Ph. D, Jiangxi Agricultural University

2016:

Junya Hu, Ph. D, Institute of Oceanology, CAS; Fan Feng, Ph. D, Chengdu University of Information Technology; Zhenhua Huo, Ph. D, China Meteorological Administration

2015:

Yujie Wu, Ph. D, National Climate Center; Linye Song, Ph. D, Institude of Urban Metrorology, CMA; Lei Chen, Ph. D, Shanghai Meteorological Service; Jing Zhang, Ph. D, NOAA, America

2014:

Peng Zhao, Ph. D, WMO Regional Training Centre; Ben Tian, Ph. D, National Climate Center

2012:

Rui Zhang, master, Further study in America

2011:

Yuehua Peng, master, DaLian; Yale Zhang, Ph. D, WMO Regional Training Centre

2010:

Chao Wei, master, National Climate Center

2007:

Xinchao Liu, master, Weather bureau of Sichuan province

Students:

2022:
Yijie Zhu, postgraduate student; Can You, Ph. D student; Guangshan Hou, Ph. D studen
2021
Yonghui Li, postgraduate student, target observation and satellite data assimilation; Yuxuan Hou, postgraduate student, ensemble forecasts of typhoon; Yi Zhuang, Ph. D student, the predictability of Mars; Jingjing Zhang, Ph. D student, the predictability study of ENSO

2020:
Yi Ru, postgraduate student, the predictability of IOD; Xiaoyun Wang, Ph. D student, the predictability of MJO;

2019:

Lei Hu, Ph. D student, ensemble forecasts of ENSO
2018:
Han Zhang, postgraduate student, ensemble forecasts of tropical cyclone; Yichi Zhang, postgraduate student, the predictability study of tropical cyclones; Yingcong Zheng, postgraduate student, the predictability study of ENSO, Jingjing Zhang, postgraduate student, the predictability study of tropical cyclones; Junjie Ma, Ph. D student, machine learning and ensemble forecast
2017:
Lin Jiang, Ph. D student, the predictability study of mesoscale eddies in the ocean
2016:
Wenyao Li, Ph. D student, the predictability study of ENSO
2015:
Jiawei Yao, Ph. D student, the predictability study of tropical cyclones