Aiken C. M.,A. Santoso, S. McGregor, and M. H. England, 2015: Optimal forcing of ENSO either side of the 1970's climate shift and its implications for predictability. Climate Dyn.,45, 47-65. https://doi.org/10.1007/s00382-014-2300-8
Bishop C. H.,B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Mon. Wea. Rev.,129, 420-436. https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2
Bishop C. H.,Z. Toth, 1999: Ensemble Transformation and Adaptive Observations.J. Atmos. Sci.,56, 1748-1765. https://doi.org/10.1175/1520-0469(1999)056<1748:ETAAO>2.0.CO;2
Boschat G., P. Terray, S. Masson, 2013: Extratropical forcing of ENSO. Geophys. Res. Lett.,40, 1605-1611. https://doi.org/10.1002/grl.50229
Chen D. K.,M. A. Cane, 2008: El Niño prediction and predictability. J. Comput. Phys.,227, 3625-3640. https://doi.org/10.1016/j.jcp.2007.05.014
Chen D. K.,S. E. Zebiak, A. J. Busalacchi, and M. A. Cane, 1995: An improved procedure for EI Nino forecasting: Implications for predictability. Science,269, 1699-1702. https://doi.org/10.1126/science.269.5231.1699
Chen Y.-Q.,D. S. Battisti, T. N. Palmer, J. Barsugli, and E. S. Sarachik, 1997: A study of the predictability of tropical Pacific SST in a coupled atmosphere-ocean model using singular vector analysis: The role of the annual cycle and the ENSO cycle. Mon. Wea. Rev., 125, 831- 845.
Cravatte S.,A. Ganachaud, B. Dewitte, and F. Hernandez, 2015: TPOS2020: Tropical Pacific observing system for 2020. Mercator Ocean-Coriolis Quarterly Newsletter, 27- 33.
Duan W. S.,C. Wei, 2013: The `spring predictability barrier' for ENSO predictions and its possible mechanism: Results from a fully coupled model. Int. J. Climatol.,33(5),1280-1292 https://doi.org/10.1002/joc.3513
Duan W. S.,J. Y. Hu, 2016: The initial errors that induce a significant "spring predictability barrier" for El Niño events and their implications for target observation: results from an earth system model. Climate Dyn.,46, 3599-3615. https://doi.org/10.1007/s00382-015-2789-5
Duan W. S.,X. C. Liu, K. Y. Zhu, and M. Mu, 2009: Exploring the initial errors that cause a significant "spring predictability barrier" for El Niño events. J. Geophys. Res.,114. https://doi.org/10.1029/2008JC004925
Fan Y.,M. R. Allen, D. L. T. Anderson, and M. A. Balmaseda, 2000: How predictability depends on the nature of uncertainty in initial conditions in a coupled model of ENSO.J. Climate,13, 3298-3313. https://doi.org/10.1175/1520-0442(2000)013<3298:HPDOTN>2.0.CO;2
Feder T.,2000: Argo begins systematic global probing of the upper oceans. Physics Today,53, 50-51. https://doi.org/10.1063/1.1292477
Flügel, M., P. Chang, 1998: Does the predictability of ENSO depend on the seasonal cycle? J.Atmos. Sci.,55, 3230-3243. https://doi.org/10.1175/1520-0469(1998)055<3230:DTPOED>2.0.CO;2
Frauen C.,D. Dommenget, 2012: Influences of the tropical Indian and Atlantic Oceans on the predictability of ENSO. Geophys. Res. Lett.,39, L02706. https://doi.org/10.1029/2011GL050520
Gao C.,R. H. Zhang, 2017: The roles of atmospheric wind and entrained water temperature (T e) in the second-year cooling of the 2010-12 La Niña event. Climate Dyn.,48, 597-617. https://doi.org/10.1007/s00382-016-3097-4
Gao C.,X. R. Wu, and R. H. Zhang, 2016: Testing a four-dimensional variational data assimilation method using an improved intermediate coupled model for ENSO analysis and prediction. Adv. Atmos. Sci.,33, 875-888. https://doi.org/10.1007/s00376-016-5249-1
Gao C.,R.-H. Zhang, X. R. Wu, and J. C. Sun, 2017: Idealized experiments for optimizing model parameters using a 4D-Variational method in an intermediate coupled model of ENSO. Adv. Atmos. Sci.. https://doi.org/10.1007/s00376-017-7109-z(in Press)
Hu J. Y.,W. S. Duan, 2016: Relationship between optimal precursory disturbances and optimally growing initial errors associated with ENSO events: Implications to target observations for ENSO prediction. J. Geophys. Res.,121, 2901-2917. https://doi.org/10.1002/2015JC011386
Keenlyside N.,R. Kleeman, 2002: Annual cycle of equatorial zonal currents in the Pacific. J. Geophys. Res.,107, 8-1-8-13. https://doi.org/10.1029/2000JC000711
Keenlyside N. S.,H. Ding, and M. Latif, 2013: Potential of equatorial Atlantic variability to enhance El Niño prediction. Geophys. Res. Lett.,40, 2278-2283, 0.1002/grl. 50362.
King J. C.,1997: Currents of change: El Niño's impact on climate and society. Weather,52, 159-160. https://doi.org/10.1002/j.1477-8696.1997.tb06299.x
Kumar A.,H. Wang, Y. Xue, and W. Q. Wang, 2014: How much of monthly subsurface temperature variability in the equatorial Pacific can be recovered by the specification of sea surface temperatures? J. Climate,27, 1559-1577. https://doi.org/10.1175/JCLI-D-13-00258.1
Latif M.,A. Sterl, E. Maier-Reimer, and M. M. Junge, 1993a: Climate variability in a coupled GCM.Part I: The tropical Pacific. J. Climate,6, 5-21. https://doi.org/10.1175/1520-0442(1993)006<0005:CVIACG>2.0.CO;2
Latif M.,A. Sterl, E. Maier-Reimer, and M. M. Junge, 1993b: Structure and predictability of the El-Niño/southern oscillation phenomenon in a coupled ocean-atmosphere general circulation model.J. Climate,6, 700-708. https://doi.org/10.1175/1520-0442(1993)006<0700:SAPOTE>2.0.CO;2
Lee, P., Coauthors, 2016: Observing system simulation experiments (OSSEs) using a regional air quality application for evaluation. Air Pollution Modeling and its Application XXIV, D. G. Steyn and N. Chaumerliac, Eds., Springer, 599-605. https://doi.org/10.1007/978-3-319-24478-5_97
Lord S. J.,E. Kalnay, R. Daley, G. D. Emmitt, and R. Atlas, 1997: Using OSSEs in the design of the future generation of integrated observing systems. Proc. 1st Symposium on Integrated Observing Systems, American Meteorological Society, Long Beach, CA.
Masutani, M., Coauthors, 2010: Observing system simulation experiments Data Assimilation,W. Lahoz, B. Khattatov, and R. Menard, Eds., Springer, 647-679. https://doi.org/10.1007/978-3-540-74703-1_24
McCreary J. P.,1981: A linear stratified ocean model of the equatorial undercurrent. Philos. Trans. Roy. Soc. London,298, 603-635. https://doi.org/10.1098/rsta.1981.0002
McPhaden, M. J.,Coauthors, 1998: The tropical ocean-global atmosphere observing system: A decade of progress. J. Geophys. Res.,103, 14169-14240. https://doi.org/10.1029/97JC02906
McPhaden M. J.,S. E. Zebiak, and M. H. Glantz, 2006: ENSO as an integrating concept in Earth science. Science,314, 1740-1745. https://doi.org/10.1126/science.1132588
Moore A. M.,R. Kleeman, 1996: The dynamics of error growth and predictability in a coupled model of ENSO. Quart. J. Roy. Meteor. Soc., 122, 1405- 1446.
Moore A. M.,R. Kleeman, 1997a: The singular vectors of a coupled ocean - atmosphere model of ENSO, Part I: Thermodynamics, energetics and error growth. Quart. [J]. Roy. Meteor. Soc., 123, 953- 981.
Moore A. M.,R. Kleeman, 1997b: The singular vectors of a coupled ocean-atmosphere model of ENSO, Part II: Sensitivity studies and dynamical interpretation. Quart. [J]. Roy. Meteor. Soc., 123, 983- 1006.
Moore A. M.,R. Kleeman, 2001: The differences between the optimal perturbations of coupled models of ENSO. [J]. Climate, 14, 138- 163.
Moore, A. M. J. Vialard, A. Weaver, D. L. T. Anderson, R. Kleeman, J. R. Johnson, 2003: The role of air-sea interaction in controlling the optimal perturbations of low-frequency tropical coupled ocean-atmosphere modes. [J]. Climate, 16, 951- 968.
Morss R. E.,D. S. Battisti, 2004a: Designing efficient observing networks for ENSO prediction.J. Climate,17, 3074-3089. https://doi.org/10.1175/1520-0442(2004)017<3074:DEONFE>2.0.CO;2
Morss R. E.,D. S. Battisti, 2004b: Evaluating observing requirements for ENSO prediction: Experiments with an intermediate coupled model. J. Climate,17, 3057-3073. https://doi.org/10.1175/1520-0442(2004)017<3057:EORFEP>2.0.CO;2
Mu M.,W. S. Duan, and B. Wang, 2003: Conditional nonlinear optimal perturbation and its applications. Nonlinear Processes in Geophysics,10, 493-501. https://doi.org/10.5194/npg-10-493-2003
Mu M.,W. S. Duan, and B. Wang, 2007a: Season-dependent dynamics of nonlinear optimal error growth and El Niño-Southern Oscillation predictability in a theoretical model. J. Geophys. Res.,112. https://doi.org/10.1029/2005JD006981
Mu M.,H. Xu, and W. S. Duan, 2007b: A kind of initial errors related to "spring predictability barrier" for El Niño events in Zebiak-Cane model. Geophys. Res. Lett.,34. https://doi.org/10.1029/2006GL027412
Mu M.,F. F. Zhou, and H. L. Wang, 2009: A method for identifying the sensitive areas in targeted observations for tropical cyclone prediction: Conditional nonlinear optimal perturbation. Mon. Wea. Rev.,137, 1623-1639. https://doi.org/10.1175/2008MWR2640.1
Mu M.,Y. S. Yu, H. Xu, and T. T. Gong, 2014: Similarities between optimal precursors for ENSO events and optimally growing initial errors in El Niño predictions. Theor. Appl. Climatol.,115, 461-469. https://doi.org/10.1007/s00704-013-0909-x
Mu M.,W. S. Duan, D. K. Chen, and W. D. Yu, 2015: Target observations for improving initialization of high-impact ocean-atmospheric environmental events forecasting. National Science Review,2, 226-236. https://doi.org/10.1093/nsr/nwv021
Newman M.,M. A. Alexand er, and J. D. Scott, 2011: An empirical model of tropical ocean dynamics. Climate Dyn.,37, 1823-1841. https://doi.org/10.1007/s00382-011-1034-0
Palmer T. N.,R. Gelaro, J. Barkmeijer, and R. Buizza, 1998: Singular vectors, metrics, and adaptive observations.J. Atmos. Sci.,55, 633-653. https://doi.org/10.1175/1520-0469(1998)055<0633:SVMAAO>2.0.CO;2
Penland, C., L. Matrosova, 1994: A balance condition for stochastic numerical models with application to the El Niño-Southern Oscillation. J. Climate,7, 1352-1372. https://doi.org/10.1175/1520-0442(1994)007<1352:ABCFSN>2.0.CO;2
Penland, C., P. D. Sardeshmukh, 1995: The optimal growth of tropical sea surface temperature anomalies.J. Climate,8, 1999-2024. https://doi.org/10.1175/1520-0442(1995)008<1999:TOGOTS>2.0.CO;2
Penland, C., L. Matrosova, 2006: Studies of El Niño and interdecadal variability in tropical sea surface temperatures using a nonnormal filter. J. Climate,19, 5796-5815. https://doi.org/10.1175/JCLI3951.1
Philand er, S. G. H., 1983: El-Niño southern oscillation phenomena. Nature,302, 295-301. https://doi.org/10.1038/302295a0
Rosati A.,K. Miyakoda, and R. Gudgel, 1997: The impact of ocean initial conditions on ENSO forecasting with a coupled model.Mon. Wea. Rev.,125, 754-772. https://doi.org/10.1175/1520-0493(1997)125<0754:TIOOIC>2.0.CO;2
Snyder C.,1996: Summary of an informal workshop on adaptive observations and FASTEX. Bull. Amer. Meteorol. Soc., 77, 953- 961.
Tang Y.,2002: Hybrid coupled models of the tropical Pacific: I Interannual variability. Climate Dyn.,19, 331-342. https://doi.org/10.1007/s00382-002-0230-3
Tang Y.,W. Hsieh, 2002: Hybrid coupled models of the tropical Pacific-II ENSO prediction. Climate Dyn.,19, 343-353. https://doi.org/10.1007/s00382-002-0231-2
Tang Y.,R. Kleeman, and S. Miller, 2006: ENSO predictability of a fully coupled GCM model using singular vector analysis. Journal of Climate, 19( 14), 3361- 3377.
Tao L. J.,R. H. Zhang, and C. Gao, 2017: Initial error-induced optimal perturbations in ENSO predictions,as derived from an intermediate coupled model. Adv. Atmos. Sci., 34(6), 791-803. https://doi.org/10.1007/s00376-017-6266-4
Thompson C. J.,1998: Initial conditions for optimal growth in a coupled ocean-atmosphere model of ENSO. J. Atmos. Sci., 55, 537- 557.
Toth Z.,E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method.Mon. Wea. Rev.,125, 3297-3319. https://doi.org/10.1175/1520-0493(1997)125<3297:EFANAT>2.0.CO;2
Wang B.,Z. Fang, 1996: Chaotic oscillations of tropical climate: A dynamic system theory for ENSO.J. Atmos. Sci.,53, 2786-2802. https://doi.org/10.1175/1520-0469(1996)053<2786:COOTCA>2.0.CO;2
Wang J.,Y. Lu, F. Wang, and R. H. Zhang, 2017: Surface current in "hotspot" serves as a new and effective precursor for El Niño prediction. Scientific Reports, 7( 1), 166.
Webster P. J.,1995: The annual cycle and the predictability of the tropical coupled ocean-atmosphere system. Meteor. Atmos. Phys.,56, 33-55. https://doi.org/10.1007/BF01022520
Wu C. C.,J. H. Chen, P. H. Lin, and K. H. Chou, 2007: Targeted observations of tropical cyclone movement based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci.,64, 2611-2626. https://doi.org/10.1175/JAS3974.1
Xue Y.,M. A. Cane, and S. E. Zebiak, 1997a: Predictability of a coupled model of ENSO using singular vector analysis. Part I: Optimal growth in seasonal background and ENSO cycle. Mon. Wea. Rev., 125, 2043- 2056.
Xue Y.,M. A. Cane, S. E. Zebiak, and T. N. Palmer, 1997b: Predictability of a coupled model of ENSO using singular vector analysis. Part II: Optimal growth and forecast skill. Mon. Wea. Rev., 125, 2057- 2073.
Yu Y. S.,W. S. Duan, H. Xu, and M. Mu, 2009: Dynamics of nonlinear error growth and season-dependent predictability of El Niño events in the Zebiak-Cane model. Quart. J. Roy. Meteor. Soc.,135, 2146-2160. https://doi.org/10.1002/qj.526
Yu Y. S.,M. Mu, W. S. Duan, and T. T. Gong, 2012: Contribution of the location and spatial pattern of initial error to uncertainties in El Niño predictions. J. Geophys. Res.,117. https://doi.org/10.1029/2011JC007758
Zebiak S. E.,M. A. Cane, 1987: A model el Niño-southern oscillation.Mon. Wea. Rev.,115, 2262-2278. https://doi.org/10.1175/1520-0493(1987)115<2262:AMENO>2.0.CO;2
Zhang J.,W. S. Duan, and X. F. Zhi, 2015: Using CMIP5 model outputs to investigate the initial errors that cause the "spring predictability barrier" for El Niño events. Science China Earth Sciences,58, 685-696. https://doi.org/10.1007/s11430-014-4994-1
Zhang R. H.,L. M. Rothstein, and A. J. Busalacchi, 1998: Origin of upper-ocean warming and El Niño change on decadal scales in the tropical Pacific Ocean. Nature,391(6670),879-883 https://doi.org/10.1038/36081
Zhang R. H.,A. J. Busalacchi, and D. G. DeWitt, 2008: The roles of atmospheric stochastic forcing (SF) and oceanic entrainment temperature (T e) in decadal modulation of ENSO. J. Climate,21, 674-704. https://doi.org/10.1175/2007JCLI1665.1
Zhang R. H.,S. E. Zebiak, R. Kleeman, and N. Keenlyside, 2003: A new intermediate coupled model for El Niño simulation and prediction. Geophys. Res. Lett.,30. https://doi.org/10.1029/2003GL018010
Zhang R. H.,S. E. Zebiak, R. Kleeman, and N. Keenlyside, 2005b: Retrospective El Niño forecasts using an improved intermediate coupled model. Mon. Wea. Rev.,133, 2777-2802. https://doi.org/10.1175/MWR3000.1
Zhang R. H.,F. Zheng, J. Zhu, and Z. G. Wang, 2013: A successful real-time forecast of the 2010-11 La Niña event. Scientific Reports,3, 1108. https://doi.org/10.1038/srep01108
Zhang R. H.,A. J. Busalacchi, R. G. Murtugudde, E. C. Hackert, and J. Ballabrera-Poy, 2004: A new approach to improved SST anomaly simulations using altimeter data: Parameterizing entrainment temperature from sea level. Geophys. Res. Lett.,31. https://doi.org/10.1029/2003GL019237
Zhang R. H.,R. Kleeman, S. E. Zebiak, N. Keenlyside, and S. Raynaud, 2005a: An empirical parameterization of subsurface entrainment temperature for improved SST anomaly simulations in an intermediate ocean model. J. Climate,18, 350-371. https://doi.org/10.1175/JCLI-3271.1
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. Adv. Atmos. Sci.,23, 615-624. https://doi.org/10.1007/s00376-006-0615-z
Zhu H. Y.,A. Thorpe, 2006: Predictability of extratropical cyclones: The influence of initial condition and model uncertainties. J. Atmos. Sci.,63, 1483-1497. https://doi.org/10.1175/JAS3688.1
Zhu J. S.,B. H. Huang, L. Marx, J. L. Kinter III, M. A. Balmaseda, R. H. Zhang, and Z. Z. Hu, 2012: Ensemble ENSO hindcasts initialized from multiple ocean analyses. Geophys. Res. Lett.,39, L09602. https://doi.org/10.1029/2012GL051503