Climate Dynamics

, Volume 48, Issue 1–2, pp 313–333 | Cite as

Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1) for operational seasonal forecasting

  • Yuhei TakayaEmail author
  • Tamaki Yasuda
  • Yosuke Fujii
  • Satoshi Matsumoto
  • Taizo Soga
  • Hirotoshi Mori
  • Masayuki Hirai
  • Ichiro Ishikawa
  • Hitoshi Sato
  • Akihiko Shimpo
  • Masafumi Kamachi
  • Tomoaki Ose


This paper describes the operational seasonal prediction system of the Japan Meteorological Agency (JMA), the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1), which was in operation at JMA during the period between February 2010 and May 2015. The predictive skill of the system was assessed with a set of retrospective seasonal predictions (reforecasts) covering 30 years (1981–2010). JMA/MRI-CPS1 showed reasonable predictive skill for the El Niño–Southern Oscillation, comparable to the skills of other state-of-the-art systems. The one-tiered approach adopted in JMA/MRI-CPS1 improved its overall predictive skills for atmospheric predictions over those of the two-tiered approach of the previous uncoupled system. For 3-month predictions with a 1-month lead, JMA/MRI-CPS1 showed statistically significant skills in predicting 500-hPa geopotential height and 2-m temperature in East Asia in most seasons; thus, it is capable of providing skillful seasonal predictions for that region. Furthermore, JMA/MRI-CPS1 was superior overall to the previous system for atmospheric predictions with longer (4-month) lead times. In particular, JMA/MRI-CPS1 was much better able to predict the Asian Summer Monsoon than the previous two-tiered system. This enhanced performance was attributed to the system’s ability to represent atmosphere–ocean coupled variability over the Indian Ocean and the western North Pacific from boreal winter to summer following winter El Niño events, which in turn influences the East Asian summer climate through the Pacific–Japan teleconnection pattern. These substantial improvements obtained by using an atmosphere–ocean coupled general circulation model underpin its success in providing more skillful seasonal forecasts on an operational basis.


Seasonal prediction Coupled model ENSO Asian monsoon 



We would thank H. Kawai, M. Hosaka and T. Nakaegawa at MRI and S. Yabu at JMA for their contributions to the development of JMA/MRI-CPS1, and S. Maeda and H. Kamahori for their support and encouragement. We would also thank two anonymous reviewers for their constructive comments to improve the manuscript.


  1. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P (2003) The version 2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeorol 4:1147–1167CrossRefGoogle Scholar
  2. Alexander MA, Blade I, Newman M, Lanzante JR, Lau NC, Scott JD (2002) The atmospheric bridge: the influence of ENSO teleconnections on air–sea interaction over the global oceans. J Clim 15(16):2205–2231CrossRefGoogle Scholar
  3. Arakawa O, Kitoh A (2004) Comparison of local precipitation–SST relationship between the observation and a reanalysis dataset. Geophys Res Lett 31:L12206. doi: 10.1029/2004GL020283 CrossRefGoogle Scholar
  4. Arribas A, Glover M, Maidens A, Peterson K, Gordon M, MacLachlan C, Graham R, Fereday D, Camp J, Scaife AA, Xavier P, McLean P, Colman A, Cusack S (2011) The GloSea4 ensemble prediction system for seasonal forecasting. Mon Weather Rev 139(6):1891–1910. doi: 10.1175/2010MWR3615.1 CrossRefGoogle Scholar
  5. Barnston AG, Tippett MK, L’Heureux ML, Li S, DeWitt DG (2012) Skill of real-time seasonal ENSO model predictions during 2002–11: Is our capability increasing? Bull Am Meteorol Soc 93:631–651. doi: 10.1175/BAMS-D-11-00111.1 CrossRefGoogle Scholar
  6. Bellenger H, Guilyardi E, Leloup J, Lengaigne M, Vialard J (2014) ENSO representation in climate models: from CMIP3 to CMIP5. Clim Dyn 42:1999–2018. doi: 10.1007/s00382-013-1783-z CrossRefGoogle Scholar
  7. Bengtsson L, Schlese U, Roeckner U, Latif M, Barnett T, Graham N (1993) A two-tiered approach to long-range climate forecasting. Science 261(5124):1026–1029CrossRefGoogle Scholar
  8. Buizza R, Tribbia J, Molteni F, Palmer T (1993) Computation of optimal unstable structures for a numerical weather prediction model. Tellus 45A:388–407CrossRefGoogle Scholar
  9. Charney JG, Shukla J (1981) Predictability of monsoons. In: Lighthill J, Pearce RP (eds) Monsoon dynamics. Cambridge University Press, Cambridge, p 99109Google Scholar
  10. Chen M, Wang W, Kumar A (2013) Lagged ensembles, forecast configuration, and seasonal predictions. Mon Weather Rev 141:3477–3497CrossRefGoogle Scholar
  11. Chikamoto Y, Mukougawa H, Kubota T, Sato H, Ito A, Maeda S (2007) Evidence of growing bred vector associated with the tropical intraseasonal oscillation. Geophys Res Lett 34:L04806. doi: 10.1029/2006GL028450 CrossRefGoogle Scholar
  12. Chowdary JS, Xie S-P, Lee J-Y, Kosaka Y, Wang B (2010) Predictability of summer northwest Pacific climate in 11 coupled model hindcasts: local and remote forcing. J Geophys Res 115:D22121. doi: 10.1029/2010JD014595 CrossRefGoogle Scholar
  13. Compo GP, Sardeshmukh PD (2009) Oceanic influences on recent continental warming. Clim Dyn 32:333–342CrossRefGoogle Scholar
  14. Doblas-Reyes FJ, Hagedorn R, Palmer TN, Morcrette J-J (2006) Impact of increasing greenhouse gas concentrations in seasonal ensemble forecasts. Geophys Res Lett 33:L07708. doi: 10.1029/2005GL025061 CrossRefGoogle Scholar
  15. Doblas-Reyes FJ, García J, Lienert F, Biescas AP, Rodrigues LRL (2013) Seasonal climate predictability and forecasting: status and prospects. Wiley Interdiscip Rev Clim Change 4(4):245–268. doi: 10.1002/wcc.217 CrossRefGoogle Scholar
  16. Du Y, Yang L, Xie S-P (2010) Tropical Indian Ocean influence on Northwest Pacific tropical cyclones in summer following strong El Niño. J Clim 24:315–322CrossRefGoogle Scholar
  17. Fujii Y, Kamachi M (2003) Three-dimensional analysis of temperature and salinity in the equatorial Pacific using a variational method with vertical coupled temperature-salinity EOF modes. J Geophys Res 108(C9):3297. doi: 10.1029/2002JC001745 CrossRefGoogle Scholar
  18. Fujii Y, Kamachi M, Nakaegawa T, Yasuda T, Yamanaka G, Toyoda T, Ando K, Matsumoto S (2012) Assimilating ocean observation data for ENSO monitoring and forecasting. Clim Var Some Asp Chall Prospects. doi: 10.5772/1103 Google Scholar
  19. Fujii Y, Nakaegawa T, Matsumoto S, Yasuda T, Yamanaka G, Kamachi M (2009) Coupled climate simulation by constraining ocean fields in a coupled model with ocean data. J Clim 22:5541–5557CrossRefGoogle Scholar
  20. Gent PR, McWilliams JC (1990) Isopycnal mixing in ocean circulation models. J Phys Oceanogr 20:150–155CrossRefGoogle Scholar
  21. Gibson JK, Kållberg P, Uppala S, Nomura S, Hernandez A, Serrano E (1997) ERA description. In: ECMWF re-analysis project report series 1Google Scholar
  22. Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106(449):447–462. doi: 10.1002/qj.49710644905
  23. Glahn HR, Lowry DA (1972) The use of model output statistics (MOS) in objective weather forecasting. J Appl Meteorol 11:1203–1211CrossRefGoogle Scholar
  24. Graham RJ, Gordon M, McLean PJ, Ineson S, Huddleston MR, Davey MK, Brookshaw A, Barnes RTH (2005) A performance comparison of coupled and uncoupled versions of the Met Office seasonal prediction general circulation model. Tellus 57A:320–339. doi: 10.1111/j.1600-0870.2005.00116.x CrossRefGoogle Scholar
  25. Graham RJ, Yun W-T, Kim J, Kumar A, Jones D, Bettio L, Gagnon N, Kolli RK, Smith D (2011) Long-range forecasting and the global framework for climate services. Clim Res 47:47–55. doi: 10.3354/cr00963 CrossRefGoogle Scholar
  26. Guilyardi E, Wittenberg A, Fedorov A, Collins M, Wang CZ, Capotondi A, van Oldenborgh GJ, Stockdale T (2009) Understanding El Niño in ocean–atmosphere general circulation models: progress and challenges. Bull Am Meteorol Soc 90:325–340CrossRefGoogle Scholar
  27. Han W, Vialard J, McPhaden MJ, Lee T, Masumoto Y, Feng M, de Ruijter WPM (2014) Indian Ocean decadal variability: a review. Bull Am Meteorol Soc 95:1679–1703. doi: 10.1175/BAMS-D-13-00028.1 CrossRefGoogle Scholar
  28. Hansen J, Sato M (2004) Greenhouse gas growth rates. Proc Natl Acad Sci 101:16109–16114CrossRefGoogle Scholar
  29. Hendon HH, Wheeler MC, Zhang C (2007) Seasonal dependence of the MJO–ENSO relationship. J Clim 20:531–543CrossRefGoogle Scholar
  30. Hoffman RN, Kalnay E (1983) Lagged averaged forecasting, an alternative to Monte Carlo forecasting. Tellus 35A:100–118CrossRefGoogle Scholar
  31. Horel JD, Wallace JM (1981) Planetary-scale atmospheric phenomena associated with the Southern Oscillation. Mon Weather Rev 109:813–829CrossRefGoogle Scholar
  32. Hudson D, Marshall AG, Yin Y, Alves O, Hendon HH (2013) Improving intraseasonal prediction with a new ensemble generation strategy. Mon Weather Rev 141:4429–4449. doi: 10.1175/MWR-D-13-00059.1 CrossRefGoogle Scholar
  33. Huffman GJ, Adler RF, Bolvin DT, Gu G (2009) Improving the global precipitation record: GPCP version 2.1. Geophys Res Lett 36:L17808. doi: 10.1029/2009GL040000 CrossRefGoogle Scholar
  34. IPCC (2013) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  35. Ishii M, Shouji A, Sugimoto S, Matsumoto T (2005) Objective analyses of sea–surface temperature and marine meteorological variables for the 20th century using ICOADS and the Kobe Collection. Int J Climatol 25(7):865–879. doi: 10.1002/joc.1169 CrossRefGoogle Scholar
  36. Japan Meteorological Agency (2007) Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO Numerical weather prediction progress report, Tokyo. Accessed 29 Sept 2015
  37. Japan Meteorological Agency (2013) Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO numerical weather prediction progress report, Tokyo. Accessed 29 Sept 2015
  38. Jhun J-G, Lee E-J (2004) A new East Asian winter monsoon index and associated characteristics of the winter monsoon. J Clim 17:711–726. doi: 10.1175/1520-0442(2004)017<0711:ANEAWM>2.0.CO;2 CrossRefGoogle Scholar
  39. Jiang X, Yang S, Li Y, Kumar A, Liu X, Zuo Z, Jha B (2013) Seasonal-to-interannual prediction of the Asian summer monsoon in the NCEP climate forecast system version 2. J Clim 26:3708–3727. doi: 10.1175/JCLI-D-12-00437.1 CrossRefGoogle Scholar
  40. Jin EK, James L, Kinter III, Wang B, Park C-K, Kang I-S, Kirtman BP, Kug J-S, Kumar A, Luo J-J, Schemm J, Shukla J, Yamagata T (2008) Current status of ENSO prediction skill in coupled oceanatmosphere models. Clim Dyn 31(6):647–664. doi: 10.1007/s00382-008-0397-3 CrossRefGoogle Scholar
  41. Kang I-S, Jang P-H, Almazroui M (2014) Examination of multi-perturbation methods for ensemble prediction of the MJO during boreal summer. Clim Dyn 42:2627–2637. doi: 10.1007/s00382-013-1819-4 CrossRefGoogle Scholar
  42. Kawamura R, Matsumura T, Iizuka S (2001) Role of equatorially asymmetric sea surface temperature anomalies in the Indian Ocean in the Asian summer monsoon and El Niño–Southern Oscillation coupling. J Geophys Res 106:4681–4693CrossRefGoogle Scholar
  43. Kessler W, McPhaden M, Weickmann K (1995) Forcing of intraseasonal Kelvin waves in the equatorial Pacific. J Geophys Res 100:10613–10632CrossRefGoogle Scholar
  44. Kim HM, Webster PJ, Curry JA, Toma VE (2012) Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts. Clim Dyn 39:2975–2991. doi: 10.1007/s00382-012-1470-5 CrossRefGoogle Scholar
  45. Klein SA, Soden BJ, Lau NC (1999) Remote sea surface temperature variations during ENSO: evidence for a tropical atmospheric bridge. J Clim 12:917–932CrossRefGoogle Scholar
  46. Kobayashi C, Maeda S, Ito A, Matsushita Y, Takano K (2005) Relation between SSTs and predictability of seasonal mean precipitation over the western tropical Pacific. J Meteorol Soc Jpn 83(5):919–929CrossRefGoogle Scholar
  47. Kosaka Y, Nakamura H (2006) Structure and dynamics of the summertime Pacific–Japan teleconnection pattern. Q J R Meteorol Soc 132:2009–2030CrossRefGoogle Scholar
  48. Kosaka Y, Xie S-P, Lau N-C, Vecchi GA (2013) Origin of seasonal predictability for summer climate over the Northwestern Pacific. Proc Natl Acad Sci 110:7574–7579CrossRefGoogle Scholar
  49. Kucharski F, Bracco A, Yoo JH, Molteni F (2009) A Gill-Matsunotype mechanism explains the Tropical Atlantic influence on African and Indian monsoon rainfall. Q J R Meteorol Soc 135:569–579CrossRefGoogle Scholar
  50. Kug J-S, Kang I-S, Choi D-H (2008) Seasonal climate predictability with tier-one and tier-two prediction system. Clim Dyn 31:403–416. doi: 10.1007/s00382-007-0264-7 CrossRefGoogle Scholar
  51. Kumar A, Hoerling MP (1998) Annual cycle of Pacific–North American seasonal predictability associated with different phases of ENSO. J Clim 11:3295–3308CrossRefGoogle Scholar
  52. Kumar A, Zhang L, Wang W (2013) Sea surface temperature–precipitation relationship in different reanalyses. Mon Weather Rev 141:1118–1123CrossRefGoogle Scholar
  53. Lau N-C, Nath M (1996) The role of the “atmospheric bridge” linking tropical Pacific ENSO events to extratropical SST anomalies. J Clim 9:2036–2057CrossRefGoogle Scholar
  54. Lau N-C, Leetma A, Nath MJ, Wang HL (2005) Influences of ENSO-induced Indo-Western Pacific SST anomalies on extratropical atmospheric variability during the boreal summer. J Clim 18:2922–2942. doi: 10.1175/JCLI3445.1 CrossRefGoogle Scholar
  55. Li YQ, Yang S (2010) A dynamical index for the East Asian winter monsoon. J Clim 23(15):4255–4262. doi: 10.1175/2010JCLI3375.1 CrossRefGoogle Scholar
  56. Liniger MA, Mathis H, Appenzeller C, Doblas-Reyes FJ (2007) Realistic greenhouse gas forcing and seasonal forecasts. Geophys Res Lett 34:L04705. doi: 10.1029/2006GL028335 CrossRefGoogle Scholar
  57. Lopez H, Kirtman BP (2014) WWBs, ENSO predictability, the spring barrier and extreme events. J Geophys Res 119(17):10114–10138. doi: 10.1002/2014JD021908 Google Scholar
  58. Luo JJ, Masson S, Behera S, Shingu S, Yamagata T (2005) Seasonal climate predictability in a coupled OAGCM using a different approach for ensemble forecasts. J Clim 18:4474–4497. doi: 10.1175/JCLI3526.1 CrossRefGoogle Scholar
  59. MacLachlan C, Arribas A, Peterson KA, Maidens A, Fereday D, Scaife AA, Gordon M, Vellinga M, Williams A, Comer RE, Camp J, Xavier P, Madec G (2014) Global seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Q J R Meteorol Soc. doi: 10.1002/qj.2396 Google Scholar
  60. Magnusson L, Alonso-Balmaseda M, Corti S, Molteni F, Stockdale T (2013) Evaluation of forecast strategies for seasonal and decadal forecasts in presence of systematic model errors. Clim Dyn 41(910):2393–2409. doi: 10.1007/s00382-012-1599-2 CrossRefGoogle Scholar
  61. Matsuno T (1966) Quasi-geostrophic motions in the equatorial area. J Meteorol Soc Jpn 44(1):25–43Google Scholar
  62. McPhaden MJ (1999) Genesis and evolution of the 1997–98 El Niño. Science 283:950–954CrossRefGoogle Scholar
  63. McPhaden MJ (2008) Evolution of the 2006–2007 El Niño: the role of intraseasonal to interannual time scale dynamics. Adv Geosci 14:219–230. doi: 10.5194/adgeo-14-219-2008 CrossRefGoogle Scholar
  64. Molteni M, Ferranti L, Palmer TN, Vitterbo P (1993) A dynamical interpretation of the global response to equatorial Pacific SST anomalies. J Clim 6:777–795CrossRefGoogle Scholar
  65. Molteni F, Stockdale T, Balmaseda M, Balsamo G, Buizza R, Ferranti L, Magnusson L, Mogensen K, Palmer T, Vitart F (2011) The new ECMWF seasonal forecast system (System 4). ECMWF Technical Memorandum 656Google Scholar
  66. Molteni F, Stockdale TN, Vitart F (2015) Understanding and modelling extra-tropical teleconnections with the Indo-Pacific region during the northern winter. Clim Dyn. doi: 10.1007/s00382-015-2528-y Google Scholar
  67. National Academics (2010) Assessment of intraseasonal to interannual climate prediction and predictability. The National Academics, WashingtonGoogle Scholar
  68. Nitta T (1987) Convective activities in the tropical western Pacific and their impact on the Northern Hemisphere summer circulation. J Meteorol Soc Jpn 65:373–390Google Scholar
  69. Noh Y, Kim H-J (1999) Simulations of temperature and turbulence structure of the oceanic boundary layer with the improved near-surface process. J Geophys Res 104:15621–15634CrossRefGoogle Scholar
  70. Ohba M, Ueda H (2006) A role of zonal gradient of SST between the Indian Ocean and the western Pacific in localized convection around the Philippines. Sci Online Lett Atmos 2:176–179Google Scholar
  71. Onogi K, Tsutsui J, Koide H, Sakamoto M, Kobayashi S, Hatsushika H, Matsumoto T, Yamazaki N, Kamahori H, Takahashi K, Kadokura S, Wada K, Kato K, Oyama R, Ose T, Mannoji N, Taira R (2007) The JRA-25 reanalysis. J Meteorol Soc Jpn 85:369–432. doi: 10.2151/jmsj.85.369 CrossRefGoogle Scholar
  72. Ose T (2000) A biennially oscillating sea surface temperature and the western Pacific pattern. J Meteorol Soc Jpn 78:93–99Google Scholar
  73. Palmer TN, Anderson DLT (1994) The prospects for seasonal forecasting—a review paper. Q J R Meteorol Soc 120(518):755–793Google Scholar
  74. Rajendran K, Nanjundiah RS, Gadgil S, Srinivasan J (2012) How good are the simulations of tropical SST–rainfall relationship by IPCC AR4 atmospheric and coupled models? J Earth Sys Sci 121(3):595–610CrossRefGoogle Scholar
  75. Roxy M (2013) Sensitivity of precipitation to sea surface temperature over the tropical summer monsoon region and its quantification. Clim Dyn 43:1159–1169CrossRefGoogle Scholar
  76. Saha S et al (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208. doi: 10.1175/JCLI-D-12-00823.1 CrossRefGoogle Scholar
  77. Sakai K, Kawamura R (2009) Remote response of the East Asian winter monsoon to tropical forcing related to El Niño–Southern Oscillation. J Geophys Res 114:D06105. doi: 10.1029/2008JD010824 CrossRefGoogle Scholar
  78. Sato N, Sellers PJ, Randall DA, Schneider EK, Shukla J, Kinter JL III, Hou Y-T, Albertazzi E (1989) Effects of implementing the simple biosphere model (SiB) in a general circulation model. J Atmos Sci 46:2757–2782. doi: 10.1175/1520-0469(1989)046<2757:EOITSB>2.0.CO;2 CrossRefGoogle Scholar
  79. Seiki A, Takayabu YN (2007) Westerly wind bursts and their relationship with intraseasonal variations and ENSO. Part I: statistics. Mon Weather Rev 135:3325–3345CrossRefGoogle Scholar
  80. Shukla J (1998) Predictability in the midst of chaos: a scientific basis for climate forecasting. Science 282(5389):728–731. doi: 10.1126/science.282.5389.728 CrossRefGoogle Scholar
  81. Stockdale TN, Anderson DLT, Albes JOS, Balmaseda MA (1998) Global seasonal rainfall forecasts using a coupled ocean–atmosphere model. Nature 392:370–373. doi: 10.1038/32861 CrossRefGoogle Scholar
  82. Stockdale TN, Anderson DLT, Balmaseda MA, Doblas-Reyes F, Ferranti L, Mogensen K, Palmer TN, Molteni F, Vitart F (2011) ECMWF seasonal forecast system 3 and its prediction of sea surface temperature. Clim Dyn 37:455–471. doi: 10.1007/s00382-010-0947-3 CrossRefGoogle Scholar
  83. Takaya Y, Yasuda T, Ose T, Nakaegawa T (2010) Predictability of the mean location of typhoon formation in a seasonal prediction experiment with a coupled general circulation model. J Meteorol Soc Jpn 88(5):799–812. doi: 10.2151/jmsj.2010-502 CrossRefGoogle Scholar
  84. Takayabu YN, Iguchi T, Kachi M, Shibata A, Kanzawa H (1999) Abrupt termination of the 1997–1998 El Niño in response to a Madden–Julian oscillation. Nature 402:279–282CrossRefGoogle Scholar
  85. Toth Z, Kalnay E (1997) Ensemble forecasting at NCEP and the breeding method. Mon Weather Rev 125:3297–3319CrossRefGoogle Scholar
  86. Tsujino H, Motoi T, Ishikawa I, Hirabara M, Nakano H, Yamanaka G, Yasuda T, Ishizaki H (2010) Reference manual for the Meteorological Research Institute Community Ocean Model (MRI-COM) version 3. Technical reports of the Meteorological Research Institute, No 59, Meteorol Res Inst, Tsukuba, Japan, pp 241. Accessed 29 Sept 2015
  87. Tsuyuki T, Kurihara K (1989) Impact of convective activity in the western tropical Pacific on the East Asian summer circulation. J Meteorol Soc Jpn 67:231-247Google Scholar
  88. Usui N, Ishizaki S, Fujii Y, Tsujino H, Yasuda T, Kamachi M (2006) Meteorological Research Institute multivariate ocean variational estimation (MOVE) system: some early results. Adv Space Res 37:806–822CrossRefGoogle Scholar
  89. van Oldenborgh GJ, Balmaseda MA, Ferranti L, Stockdale TN, Anderson DLT (2005) Evaluation of atmospheric fields from the ECMWF seasonal forecasts over a 15-year period. J Clim 18(16):3250–3269. doi: 10.1175/JCLI3421.1 CrossRefGoogle Scholar
  90. Ventrice MJ, Wheeler MC, Hendon HH, Schreck CJ, Thorncroft CD, Kiladis GN (2013) A modified multivariate Madden–Julian oscillation index using velocity potential. Mon Weather Rev 141(12):4197–4210CrossRefGoogle Scholar
  91. Waliser DE, Graham NE, Gautier C (1993) Comparison of the highly reflective cloud and outgoing longwave radiation datasets for use in estimating tropical deep convection. J Clim 6(2):331–353CrossRefGoogle Scholar
  92. Wallace JM, Gutzler DS (1981) Teleconnections in the geopotential height field during the Northern Hemisphere winter. Mon Weather Rev 109:784–812Google Scholar
  93. Wang B, Fan Z (1999) Choice of South Asian summer monsoon indices. Bull Am Meteorol Soc 80:629–638. doi: 10.1175/1520-0477(1999)080<0629:COSASM>2.0.CO;2 CrossRefGoogle Scholar
  94. Wang B, Wu R, Fu X (2000) Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? J Clim 13:1517–1536CrossRefGoogle Scholar
  95. Wang B, Ding Q, Fu X, Kang IS, Jin K, Shukla J, Doblas-Reyes F (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett 32:L15711CrossRefGoogle Scholar
  96. Wang B, Wu Z, Chang CP, Liu J, Li J, Zhou T (2010) Another look at interannual-to-interdecadal variations of the East Asian winter monsoon: the northern and southern temperature modes. J Clim 23:1495–1512CrossRefGoogle Scholar
  97. Wang B, Xiang B, Lee JY (2013) Subtropical high predictability establishes a promising way for monsoon and tropical storm predictions. Proc Natl Acad Sci 110:2718–2722CrossRefGoogle Scholar
  98. Webster PJ, Yang S (1992) Monsoon and ENSO: selectively interactive systems. Q J R Meteorol Soc 118:877–926. doi: 10.1002/qj.49711850705 CrossRefGoogle Scholar
  99. WMO (2009) WMO WDCGG data summary, GAW DATA volume IV—greenhouse gases and other atmospheric gases, Japan Meteorological Agency in co-operation with World Meteorological Organization 33. Accessed 22 Mar 2016
  100. Wu R, Kirtman BP (2006) Changes in spread and predictability associated with ENSO in an ensemble coupled GCM. J Clim 19:4378–4396CrossRefGoogle Scholar
  101. Xie S-P, Hu K, Hafner J, Tokinaga H, Du Y, Huang G, Sampe T (2009) Indian Ocean capacitor effect on Indo-Western Pacific climate during the summer following El Niño. J Clim 22(3):730–74CrossRefGoogle Scholar
  102. Yang J, Liu Q, Xie S-P, Liu Z, Wu L (2007) Impact of the Indian Ocean SST basin mode on the Asian summer monsoon. Geophys Res Lett 34:L02708. doi: 10.1029/2006GL028571 Google Scholar
  103. Yasuda T, Takaya Y, Kobayashi C, Kamachi M, Kamahori H, Ose T (2007) Asian monsoon predictability in JMA/MRI seasonal forecast system. CLIVAR Exch 43:18–24Google Scholar
  104. Yukimoto S, Adachi Y, Hosaka M, Sakami T, Yoshimura H, Hirabara M, Tanaka TY, Shindo E, Tsujino H, Deushi M, Mizuta R, Yabu S, Obata A, Nakano H, Koshiro T, Ose T, Kitoh A (2012) A new global climate model of the Meteorological Research Institute: MRI-CGCM3—model description and basic performance—. J Meteorol Soc Jpn 90:23–64. doi: 10.2151/jmsj.2012-A02 CrossRefGoogle Scholar
  105. Zhang C (1993) Large-scale variability of atmospheric deep convection in relation to sea surface temperature in the tropics. J Clim 6:1898–1913CrossRefGoogle Scholar
  106. Zhu J, Shukla J (2013) The role of airsea coupling in seasonal prediction of Asia–Pacific summer monsoon rainfall. J Clim 26:5689–5697. doi: 10.1175/JCLI-D-13-00190.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Yuhei Takaya
    • 1
    Email author
  • Tamaki Yasuda
    • 1
  • Yosuke Fujii
    • 2
  • Satoshi Matsumoto
    • 2
  • Taizo Soga
    • 3
  • Hirotoshi Mori
    • 1
  • Masayuki Hirai
    • 1
  • Ichiro Ishikawa
    • 1
  • Hitoshi Sato
    • 1
  • Akihiko Shimpo
    • 1
  • Masafumi Kamachi
    • 2
  • Tomoaki Ose
    • 2
  1. 1.Japan Meteorological AgencyTokyoJapan
  2. 2.Meteorological Research InstituteTsukubaJapan
  3. 3.Faculty of MedicineUniversity of TsukubaTsukubaJapan

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