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Journal of Meteorological Research

, Volume 33, Issue 1, pp 46–65 | Cite as

ENSO Features, Dynamics, and Teleconnections to East Asian Climate as Simulated in CAMS-CSM

  • Bo Lu
  • Hong-Li RenEmail author
Special Collection on CAMS-CSM
  • 5 Downloads

Abstract

This study evaluates the performance of CAMS-CSM (the climate system model of the Chinese Academy of Meteorological Sciences) in simulating the features, dynamics, and teleconnections to East Asian climate of the El Niño–Southern Oscillation (ENSO). In general, fundamental features of ENSO, such as its dominant patterns and phase-locking features, are reproduced well. The two types of El Niño are also represented, in terms of their spatial distributions and mutual independency. However, the skewed feature is missed in the model and the simulation of ENSO is extremely strong, which is found—based on Bjerknes index assessment—to be caused by underestimation of the shortwave damping effect. Besides, the modeled ENSO exhibits a regular oscillation with a period shorter than observed. By utilizing the Wyrtki index, it is suggested that this periodicity bias results from an overly quick phase transition induced by feedback from the thermocline and zonal advection. In addition to internal dynamics of ENSO, its external precursors—such as the North Pacific Oscillation with its accompanying seasonal footprinting mechanism, and the Indian Ocean Dipole with its 1-yr lead correlation with ENSO—are reproduced well by the model. Furthermore, with respect to the impacts of ENSO on the East Asian summer monsoon, although the anomalous Philippine anticyclone is reproduced in the post-El Niño summer, it exhibits an eastward shift compared with observation; and as a consequence, the observed flooding of the Yangtze River basin is poorly represented, with unrealistic air–sea interaction over the South China Sea being the likely physical origin of this bias. The response of wintertime lowertropospheric circulation to ENSO is simulated well, in spite of an underestimation of temperature anomalies in central China. This study highlights the dynamic processes that are key for the simulation of ENSO, which could shed some light on improving this model in the future.

Key words

model evaluation ENSO dynamics teleconnection CAMS-CSM 

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Notes

Acknowledgments

We would like to thank the editors and reviewers for their valuable comments.

References

  1. AchutaRao, K., and K. R. Sperber, 2006: ENSO simulation in coupled ocean–atmosphere models: Are the current models better? Climate Dyn., 27: 1–15, doi: 10.1007/s00382-006-0119-7.Google Scholar
  2. Alexander, M. A., D. J. Vimont, P. Chang, et al., 2010: The impact of extratropical atmospheric variability on ENSO: Testing the seasonal footprinting mechanism using coupled model experiments. J. Climate, 23: 2885–2901, doi: 10.1175/2010JCLI3205.1.Google Scholar
  3. Annamalai, H., S.-P. Xie, J.-P. McCreary, et al., 2005: Impact of Indian Ocean sea surface temperature on developing El Niño. J. Climate, 18: 302–319, doi: 10.1175/JCLI-3268.1.Google Scholar
  4. Ashok, K., S. K. Behera, S. A. Rao, et al., 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res. Oceans, 112, C11007, doi: 10.1029/2006JC003798.Google Scholar
  5. Battisti, D. S., and A. C. Hirst, 1989: Interannual variability in a tropical atmosphere–ocean model: Influence of the basic state, ocean geometry and nonlinearity. J. Atmos. Sci., 46: 1687–1712, doi: 10.1175/1520-0469(1989)046<1687:IVIA TA>2.0.CO;2.Google Scholar
  6. Behringer, D. W., M. Ji, and A. Leetmaa, 1998: An improved coupled model for ENSO prediction and implications for ocean initialization. Part I: The ocean data assimilation system. Mon. Wea. Rev., 126: 1013–1021, doi: 10.1175/1520-0493(1998)126<1013:AICMFE>2.0.CO;2.Google Scholar
  7. Bellenger, H., E. Guilyardi, J. Leloup, et al., 2014: ENSO representation in climate models: From CMIP3 to CMIP5. Climate Dyn., 42: 1999–2018, doi: 10.1007/s00382-013-1783-z.Google Scholar
  8. Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97: 163–172, doi: 10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2.Google Scholar
  9. Chen, L., and Y. Q. Yu, 2014: Preliminary evaluations of ENSOrelated cloud and water vapor feedbacks in FGOALS. Flexible Global Ocean–Atmosphere–Land System Model: A Modeling Tool for the Climate Change Research Community, T. J. Zhou, Y. Q. Yu, Y. M. Liu, et al., Eds., Springer, Berlin, 189–197, doi: 10.1007/978-3-642-41801-3_23.Google Scholar
  10. Chen, L., Y. Q. Yu, and D.-Z. Sun, 2013: Cloud and water vapor feedbacks to the El Niño warming: Are they still biased in CMIP5 models? J. Climate, 26: 4947–4961, doi: 10.1175/JCLID-12-00575.1.Google Scholar
  11. Chen, L., T. Li, S. K. Behera, et al., 2016a: Distinctive precursory air–sea signals between regular and super El Niños. Adv. Atmos. Sci., 33: 996–1004, doi: 10.1007/s00376-016-5250-8.Google Scholar
  12. Chen, L., Y. Q. Yu, and W. P. Zheng, 2016b: Improved ENSO simulation from climate system model FGOALS-g1.0 to FGOALS-g2. Climate Dyn., 47: 2617–2634, doi: 10.1007/s00382-016-2988-8.Google Scholar
  13. Chen, L., T. Li, B. Wang, et al., 2017: Formation mechanism for 2015/16 super El Niño. Sci. Rep., 7: 2975, doi: 10.1038/s41598-017-02926-3.Google Scholar
  14. Chen, L. X., M. Dong, and Y. N. Shao, 1992: The characteristics of interannual variations on the East-Asian monsoon. J. Meteor. Soc. Japan, 70: 397–421, doi: 10.2151/jmsj1965. 70.1B_397.Google Scholar
  15. Chen, M. C., and T. Li, 2018: Why 1986 El Niño and 2005 La Niña evolved different from a typical El Niño and La Niña. Climate Dyn., 51: 4309–4327, doi: 10.1007/s00382-017-3852-1.Google Scholar
  16. Chen, M. C., T. Li, X. Y. Shen, et al., 2016: Relative roles of dynamic and thermodynamic processes in causing evolution asymmetry between El Niño and La Niña. J. Climate, 29: 2201–2220, doi: 10.1175/JCLI-D-15-0547.1.Google Scholar
  17. Chen, S. F., B. Yu, and W. Chen, 2014: An analysis on the physical process of the influence of AO on ENSO. Climate Dyn., 42: 973–989, doi: 10.1007/s00382-012-1654-z.Google Scholar
  18. Chen, W., H.-F. Graf, and R.-H. Huang, 2000: The interannual variability of East Asian winter monsoon and its relation to the summer monsoon. Adv. Atmos. Sci., 17: 48–60, doi: 10.1007/s00376-000-0042-5.Google Scholar
  19. Chen, W., X. Q. Lan, L. Wang, et al., 2013: The combined effects of the ENSO and the Arctic Oscillation on the winter climate anomalies in East Asia. Chinese Sci. Bull., 58: 1355–1362, doi: 10.1007/s11434-012-5654-5.Google Scholar
  20. Chen, Z., R. G. Wu, and W. Chen, 2014: Distinguishing interannual variations of the northern and southern modes of the East Asian winter monsoon. J. Climate, 27: 835–851, doi: 10.1175/JCLI-D-13-00314.1.Google Scholar
  21. Chung, P. H., and T. Li, 2013: Interdecadal relationship between the mean state and El Niño types. J. Climate, 26: 361–379, doi: 10.1175/JCLI-D-12-00106.1.Google Scholar
  22. Fedorov, A. V., and S. G. Philander, 2001: A stability analysis of tropical ocean–atmosphere interactions: Bridging measurements and theory for El Niño. J. Climate, 14: 3086–3101, doi: 10.1175/1520-0442(2001)014<3086:ASAOTO>2.0.CO;2.Google Scholar
  23. Gong, D. Y., S. W. Wang, and J. H. Zhu, 2001: East Asian winter monsoon and Arctic oscillation. Geophys. Res. Lett., 28: 2073–2076, doi: 10.1029/2000GL012311.Google Scholar
  24. Gong, H. N., L. Wang, W. Chen, et al., 2014: The climatology and interannual variability of the East Asian winter monsoon in CMIP5 models. J. Climate, 27: 1659–1678, doi: 10.1175/JCLI-D-13-00039.1.Google Scholar
  25. Gong, H. N., L. Wang, W. Chen, et al., 2015: Diverse influences of ENSO on the East Asian–western Pacific winter climate tied to different ENSO properties in CMIP5 models. J. Climate, 28: 2187–2202, doi: 10.1175/JCLI-D-14-00405.1.Google Scholar
  26. Gong, H. N., L. Wang, W. Chen, et al., 2018: Diversity of the Pacific–Japan pattern among CMIP5 models: Role of SST anomalies and atmospheric mean flow. J. Climate, 31: 6857–6877, doi: 10.1175/JCLI-D-17-0541.1.Google Scholar
  27. Griffies, S. M., M. J. Harrison, R. C. Pacanowski, et al., 2004: A Technical Guide to MOM4. GFDL Ocean Group Technical Report No. 5, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, 339 pp.Google Scholar
  28. Guilyardi, E., 2006: El Niño-mean state-seasonal cycle interactions in a multi-model ensemble. Climate Dyn., 26: 329–348, doi: 10.1007/s00382-005-0084-6.Google Scholar
  29. Guilyardi, E., A. Wittenberg, A. Fedorov, et al., 2009: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Amer. Meteor. Soc., 90: 325–340, doi: 10.1175/2008BAMS2387.1.Google Scholar
  30. Ham, Y. G., and J. S. Kug, 2012: How well do current climate models simulate two types of El Niño? Climate Dyn., 39: 383–398, doi: 10.1007/s00382-011-1157-3.Google Scholar
  31. He, S. P., and H. J. Wang, 2013: Oscillating relationship between the East Asian winter monsoon and ENSO. J. Climate, 26: 9819–9838, doi: 10.1175/JCLI-D-13-00174.1. Hwang, Y.-T., and D. M. W. Frierson, 2013: Link between the double-intertropical convergence zone problem and cloud biases over the Southern Ocean. Proc. Natl. Acad. Sci. USA, 110: 4935–4940, doi: 10.1073/pnas.1213302110.Google Scholar
  32. Izumo, T., J. Vialard, M. Lengaigne, et al., 2010: Influence of the state of the Indian Ocean Dipole on the following year’s El Niño. Nat. Geosci., 3: 168–172, doi: 10.1038/ngeo760.Google Scholar
  33. Jiang, Z. H., H. Yang, Z. Y. Liu, et al., 2014: Assessing the influence of regional SST modes on the winter temperature in China: The effect of tropical Pacific and Atlantic. J. Climate, 27: 868–879, doi: 10.1175/JCLI-D-12-00847.1.Google Scholar
  34. Jin, F.-F., 1997a: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54: 811–829, doi: 10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2.Google Scholar
  35. Jin, F.-F., 1997b: An equatorial ocean recharge paradigm for ENSO. Part II: A stripped-down coupled model. J. Atmos. Sci., 54: 830–847, doi: 10.1175/1520-0469(1997)054<0830:AEORPF> 2.0.CO;2.Google Scholar
  36. Jin, F.-F., S. T. Kim, and L. Bejarano, 2006: A coupled-stability index for ENSO. Geophys. Res. Lett., 33, L23708, doi: 10.1029/2006GL027221.Google Scholar
  37. Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77: 437–472, doi: 10.1175/1520-0477(1996)077<0437:TNYR P>2.0.CO;2.Google Scholar
  38. Kim, J. W., S. W. Yeh, and E. C. Chang, 2014: Combined effect of El Niño–Southern Oscillation and Pacific decadal oscillation on the East Asian winter monsoon. Climate Dyn., 42: 957–971, doi: 10.1007/s00382-013-1730-z.Google Scholar
  39. Kim, S.-T., and F.-F. Jin, 2011: An ENSO stability analysis. Part II: Results from the twentieth and twenty-first century simulations of the CMIP3 models. Climate Dyn., 36: 1609–1627, doi: 10.1007/s00382-010-0872-5.Google Scholar
  40. Kim, S. T., W. J. Cai, F.-F. Jin, et al., 2014a: ENSO stability in coupled climate models and its association with mean state. Climate Dyn., 42: 3313–3321, doi: 10.1007/s00382-013-1833-6.Google Scholar
  41. Kim, S. T., W. J. Cai, F.-F. Jin, et al., 2014b: Response of El Niño sea surface temperature variability to greenhouse warming. Nat. Climate Change, 4: 786–790, doi: 10.1038/nclimate 2326.Google Scholar
  42. Kirtman, B. P., and P. S. Schopf, 1998: Decadal variability in ENSO predictability and prediction. J. Climate, 11: 2804–2822, doi: 10.1175/1520-0442(1998)011<2804:DVIEPA>2.0.CO;2.Google Scholar
  43. Kleeman, R., and A. M. Moore, 1997: A theory for the limitation of ENSO predictability due to stochastic atmospheric transients. J. Atmos. Sci., 54: 753–767, doi: 10.1175/1520-0469 (1997)054<0753:ATFTLO>2.0.CO;2.Google Scholar
  44. Knutson, T. R., S. Manabe, and D. F. Gu, 1997: Simulated ENSO in a global coupled ocean–atmosphere model: Multidecadal amplitude modulation and CO2 sensitivity. J. Climate, 10: 138–161, doi: 10.1175/1520-0442(1997)010<0138:SEIAGC> 2.0.CO;2.Google Scholar
  45. Kug, J. S., and Y. G. Ham, 2011: Are there two types of La Nina? Geophys. Res. Lett., 38, L16704, doi: 10.1029/2011GL048237.Google Scholar
  46. Kug, J. S., F. F. Jin, and S. I. An, 2009: Two types of El Niño events: Cold tongue El Niño and warm pool El Niño. J. Climate, 22: 1499–1515, doi: 10.1175/2008JCLI2624.1.Google Scholar
  47. Kug, J. S., Y. G. Ham, J. Y. Lee, et al., 2012: Improved simulation of two types of El Niño in CMIP5 models. Environ. Res. Lett., 7: 039502, doi: 10.1088/1748-9326/7/3/039502.Google Scholar
  48. Li, C. F., A. A. Scaife, R. Y. Lu, et al., 2016: Skillful seasonal prediction of Yangtze River valley summer rainfall. Environ. Res. Lett., 11: 094002, doi: 10.1088/1748-9326/11/9/094002.Google Scholar
  49. Li, C. Y., 1990: Interaction between anomalous winter monsoon in East Asia and El Niño events. Adv. Atmos. Sci., 7: 36–46, doi: 10.1007/BF02919166.Google Scholar
  50. Li, C. Y., 1996: A further study on interaction between anomalous winter monsoon in East Asia and El Nino. J. Meteor. Res., 10: 309–320. Li, G. and S.-P. Xie, 2014: Tropical biases in CMIP5 multimodel ensemble: The excessive equatorial pacific cold tongue and double ITCZ problems. J. Climate, 27: 1765–1780, doi: 10.1175/JCLI-D-13-00337.1.Google Scholar
  51. Li, S. L., and G. T. Bates, 2007: Influence of the Atlantic multidecadal oscillation on the winter climate of East China. Adv. Atmos. Sci., 24: 126–135, doi: 10.1007/s00376-007-0126-6.Google Scholar
  52. Li, T., B. Wang, B. Wu, et al., 2017: Theories on formation of an anomalous anticyclone in western North Pacific during El Niño: A review. J. Meteor. Res., 31: 987–1006, doi: 10.1007/s13351-017-7147-6.Google Scholar
  53. Li, T. M., 1997: Phase transition of the El Niño–Southern Oscillation: A stationary SST mode. J. Atmos. Sci., 54: 2872–2887, doi: 10.1175/1520-0469(1997)054<2872:PTOTEN>2.0.CO;2.Google Scholar
  54. Li, Y. Q., and S. Yang, 2010: A dynamical index for the East Asian winter monsoon. J. Climate, 23: 4255–4262, doi: 10.1175/2010JCLI3375.1.Google Scholar
  55. Lin, J.-L., 2007: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean–atmosphere feedback analysis. J. Climate, 20: 4497–4525, doi: 10.1175/JCLI4272.1.Google Scholar
  56. Liu, G., L.-R. Ji, S.-Q. Sun, et al., 2012: Low-and mid-high latitude components of the East Asian winter monsoon and their reflecting variations in winter climate over eastern China. Atmos. Ocean. Sci. Lett., 5: 195–200, doi: 10.1080/16742834. 2012.11446985.Google Scholar
  57. Liu, Y., H.-L. Ren, A. A. Scaife, et al., 2018: Evaluation and statistical downscaling of East Asian summer monsoon forecasting in BCC and MOHC seasonal prediction systems. Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.3405.Google Scholar
  58. Lloyd, J., E. Guilyardi, H. Weller, et al., 2009: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Atmos. Sci. Lett., 10: 170–176, doi: 10.1002/asl.227.Google Scholar
  59. Lloyd, J., E. Guilyardi, and H. Weller, 2011: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: Using AMIP runs to understand the heat flux feedback mechanisms. Climate Dyn., 37: 1271–1292, doi: 10.1007/s00382-010-0895-y.Google Scholar
  60. Lloyd, J., E. Guilyardi, and H. Weller, 2012: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: The shortwave flux feedback. J. Climate, 25: 4275–4293, doi: 10.1175/JCLI-D-11-00178.1.Google Scholar
  61. Lu, B., and H.-L. Ren, 2016: Improving ENSO periodicity simulation by adjusting cumulus entrainment in BCC_CSMs. Dyn. Atmos. Oceans, 76: 127–140, doi: 10.1016/j.dynatmoce.2016. 10.005.Google Scholar
  62. Lu, B., A. A. Scaife, N. Dunstone, et al., 2017: Skillful seasonal predictions of winter precipitation over southern China. Environ. Res. Lett., 12: 074021, doi: 10.1088/1748-9326/aa739a.Google Scholar
  63. Lu, B., F.-F. Jin, and H.-L. Ren, 2018: A coupled dynamic index for ENSO periodicity. J. Climate, 31: 2361–2376, doi: 10. 1175/JCLI-D-17-0466.1.Google Scholar
  64. Luo, J.-J., R. C. Zhang, S. K. Behera, et al., 2010: Interaction between El Niño and extreme Indian Ocean dipole. J. Climate, 23: 726–742, doi: 10.1175/2009JCLI3104.1.Google Scholar
  65. Ma, T. J., W. Chen, D. Nath, et al., 2018: East Asian winter monsoon impacts the ENSO-related teleconnections and North American seasonal air temperature prediction. Sci. Rep., 8: 6547, doi: 10.1038/s41598-018-24552-3.Google Scholar
  66. Misra, V., L. Marx, M. Brunke, et al., 2008: The equatorial Pacific cold tongue bias in a coupled climate model. J. Climate, 21: 5852–5869, doi: 10.1175/2008JCLI2205.1.Google Scholar
  67. Morice, C. P., J. J. Kennedy, N. A. Rayner, et al., 2012: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The Had-CRUT4 data set. J. Geophys. Res. Atmos., 117, D08101, doi: 10.1029/2011JD017187.Google Scholar
  68. Murray, R. J., 1996: Explicit generation of orthogonal grids for ocean models. J. Comput. Phys., 126: 251–273, doi: 10.1006/jcph.1996.0136.Google Scholar
  69. Neelin, J. D., 1991: The slow sea surface temperature mode and the fast-wave limit: Analytic theory for tropical interannual oscillations and experiments in a hybrid coupled model. J. Atmos. Sci., 48: 584–606, doi: 10.1175/1520-0469(1991)048 <0584:TSSSTM>2.0.CO;2.Google Scholar
  70. Philander, S. G. H., D. Gu, G. Lambert, et al., 1996: Why the ITCZ is mostly north of the equator. J. Climate, 9: 2958–2972, doi: 10.1175/1520-0442(1996)009<2958:WTII MN>2.0.CO;2.Google Scholar
  71. Rayner, N. A., P. Brohan, D. E. Parker, et al., 2006: Improved analyses of changes and uncertainties in sea surface temperature measured in situ since the mid-nineteenth century: The HadSST2 dataset. J. Climate, 19: 446–469, doi: 10.1175/JCLI3637.1.Google Scholar
  72. Rong, X. Y., J. Li, H. M. Chen, et al., 2018: The CAMS climate system model and a basic evaluation of its climatology and climate variability simulation. J. Meteor. Res., 32: 839–861, doi: 10.1007/s13351-018-8058-x.Google Scholar
  73. Shi, N., 1996: Features of the East Asian winter monsoon intensity on multiple time scale in recent 40 years and their relation to climate. Quart. J. Appl. Meteor., 7: 175–182. (in Chinese)Google Scholar
  74. Stuecker, M. F., F.-F. Jin, A. Timmermann, et al. 2015: Combination mode dynamics of the anomalous northwest Pacific anticyclone. J. Climate, 28: 1093–1111, doi: 10.1175/JCLI-D-14-00225.1.Google Scholar
  75. Suarez, M. J., and P. S. Schopf, 1988: A delayed action oscillator for ENSO. J. Atmos. Sci., 45: 3283–3287, doi: 10.1175/1520-0469(1988)045<3283:ADAOFE>2.0.CO;2.Google Scholar
  76. Sun, D. Z., Y. Q. Yu, and T. Zhang, 2009: Tropical water vapor and cloud feedbacks in climate models: A further assessment using coupled simulations. J. Climate, 22: 1287–1304, doi: 10.1175/2008JCLI2267.1.Google Scholar
  77. Timmermann, A., J. Oberhuber, A. Bacher, et al., 1999: Increased El Niño frequency in a climate model forced by future greenhouse warming. Nature, 398: 694–697, doi: 10.1038/19505.Google Scholar
  78. Tokinaga, H., and S.-P. Xie, 2011: Wave-and anemometer-based sea surface wind (WASWind) for climate change analysis. J. Climate, 24: 267–285, doi: 10.1175/2010JCLI3789.1. van Oldenborgh, G. J., S. Y. Philip, and M. Collins, 2005: El Niño in a changing climate: A multi-model study. Ocean Sci., 1: 81–95, doi: 10.5194/os-1-81-2005.Google Scholar
  79. Vannière, B., E. Guilyardi, G. Madec, et al., 2013: Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO. Climate Dyn., 40: 963–981, doi: 10.1007/s00382-012-1429-6.Google Scholar
  80. Vimont, D. J., D. S. Battisti, and A. C. Hirst, 2001: Footprinting: A seasonal connection between the tropics and mid-latitudes. Geophys. Res. Lett., 28: 3923–3926, doi: 10.1029/2001 GL013435.Google Scholar
  81. Wang, B., R. G. Wu, and X. H. Fu, 2000: Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? J. Climate, 13: 1517–1536, doi: 10.1175/1520-0442(2000)013 <1517:PEATHD>2.0.CO;2.Google Scholar
  82. Wang, C. Z., W. Q. Wang, D. X. Wang, et al., 2006: Interannual variability of the South China Sea associated with El Niño. J. Geophys. Res. Oceans, 111, C03023, doi: 10.1029/2005JC 003333.Google Scholar
  83. Wang, L., and M.-M. Lu, 2016: The East Asian winter monsoon. The Global Monsoon System: Research and Forecast, 3rd Ed. C. P. Chang, H. C. Kuo, N. C. Lau, et al., Eds., World Scientific, Singapore, 51–61, doi: 10.1142/9789813200913_0005.Google Scholar
  84. Wang, L., W. Chen, and R. H. Huang, 2008: Interdecadal modulation of PDO on the impact of ENSO on the East Asian winter monsoon. Geophys. Res. Lett., 35, L20702, doi: 10.1029/2008GL035287.Google Scholar
  85. Watanabe, M., M. Chikira, Y. Imada, et al., 2011: Convective control of ENSO simulated in MIROC. J. Climate, 24: 543–562, doi: 10.1175/2010JCLI3878.1.Google Scholar
  86. Weng, H., K. Ashok, S. K. Behera, et al., 2007: Impacts of recent El Niño Modoki on dry/wet conditions in the Pacific rim during boreal summer. Climate Dyn., 29: 113–129, doi: 10.1007/s00382-007-0234-0.Google Scholar
  87. Weng, H., S. K. Behera, and T. Yamagata, 2009: Anomalous winter climate conditions in the Pacific rim during recent El Niño Modoki and El Niño events. Climate Dyn., 32: 663–674, doi: 10.1007/s00382-008-0394-6.Google Scholar
  88. Wu, B. Y., R. Zhang, and R. D’Arrigo, 2006: Distinct modes of the East Asian winter monsoon. Mon. Wea. Rev., 134: 2165–2179, doi: 10.1175/MWR3150.1.Google Scholar
  89. Wyrtki, K., 1985: Water displacements in the Pacific and the genesis of El Niño cycles. J. Geophys. Res. Oceans, 90: 7129–7132, doi: 10.1029/JC090iC04p07129.Google Scholar
  90. Xie, P. P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78: 2539–2558, doi: 10.1175/1520-0477(1997)078<2539: GPAYMA>2.0.CO;2.Google Scholar
  91. Xie, S.-P., K. M. Hu, J. Hafner, et al., 2009: Indian Ocean capacitor effect on Indo-western Pacific climate during the summer following El Niño. J. Climate, 22: 730–747, doi: 10.1175/2008JCLI2544.1.Google Scholar
  92. Xie, S.-P., Y. Kosaka, Y. Du, et al., 2016: Indo-western Pacific Ocean capacitor and coherent climate anomalies in post-ENSO summer: A review. Adv. Atmos. Sci., 33: 411–432, doi: 10.1007/s00376-015-5192-6.Google Scholar
  93. Yu, J.-Y., H.-Y. Kao, and T. Lee, 2010: Subtropics-related interannual sea surface temperature variability in the central equatorial Pacific. J. Climate, 23: 2869–2884, doi: 10.1175/2010 JCLI3171.1.Google Scholar
  94. Zebiak, S. E., and M. A. Cane, 1987: A model El Niño–Southern Oscillation. Mon. Wea. Rev., 115: 2262–2278, doi: 10.1175/1520-0493(1987)115<2262:AMENO>2.0.CO;2.Google Scholar
  95. Zhang, R., A. Sumi, and M. Kimoto, 1996: Impact of El Niño on the East Asian monsoon: A diagnostic study of the’ 86/87 and’ 91/92 events. J. Meteor. Soc. Japan, 74: 49–62, doi: 10.2151/jmsj1965.74.1_49.Google Scholar
  96. Zhang, W. J., F.-F. Jin, M. F. Stuecker, et al., 2016: Unraveling El Niño’s impact on the East Asian monsoon and Yangtze River summer flooding. Geophys. Res. Lett., 43: 11375–11382, doi: 10.1002/2016GL071190.Google Scholar
  97. Zheng, W., P. Braconnot, E. Guilyardi, et al., 2008: ENSO at 6ka and 21ka from ocean–atmosphere coupled model simulations. Climate Dyn., 30: 745–762, doi: 10.1007/s00382-007-0320-3.Google Scholar

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© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratory for Climate Studies & China Meteorological Administration–Nanjing University Joint Laboratory for Climate Prediction Studies, National Climate Center, China Meteorological AdministrationBeijingChina
  2. 2.Xinjiang Climate CenterUrumqiChina
  3. 3.Department of Atmospheric Science, School of Environmental StudiesChina University of GeoscienceWuhanChina

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