Climate Dynamics

, Volume 48, Issue 7–8, pp 2507–2528 | Cite as

Tropical intraseasonal oscillation simulated in an AMIP-type experiment by NICAM

  • Kazuyoshi KikuchiEmail author
  • Chihiro Kodama
  • Tomoe Nasuno
  • Masuo Nakano
  • Hiroaki Miura
  • Masaki Satoh
  • Akira T. Noda
  • Yohei Yamada


It is the first time for the non-hydrostatic icosahedral atmospheric model (NICAM), at a horizontal mesh size of approximately 14-km, to conduct a continuous long-term Atmospheric Model Intercomparison Project-type simulation. This study examines the performance of NICAM in simulating the tropical intraseasonal oscillation (ISO) from a statistical point of view using 30-year data (1979–2008) in the context of the bimodal ISO representation concept proposed by Kikuchi et al., which allows us to examine the seasonally varying behavior of the ISO in great detail, in addition to the MJO working group level 2 diagnostics. It is found that many of the fundamental features of the ISO are well captured by NICAM. The evolution of the ISO convection as well as large-scale circulation over the course of its life cycle is reasonably well reproduced throughout the year. As in the observation, the Madden–Julian oscillation (MJO) mode, characterized by prominent eastward propagation of convection, is predominant during boreal winter, whereas the boreal summer ISO (BSISO) mode, by a combination of pronounced eastward and northward propagation, during summer. The overall shape of the seasonal cycle as measured by the numbers of significant MJO and BSISO days in a month is relatively well captured. Two major biases, however, are also identified. The amplitude of the simulated ISO is weaker by a factor of ~2. Significant BSISO events sometimes appear even during winter (December–April), amounting to ~30 % of the total significant ISO days as opposed to ~2 % in the observation. The results here warrant further studies using the simulation dataset to understand not only many aspects of the dynamics and physics of the ISO but also its role in weather and climate. It is also demonstrated that the concept of the bimodal ISO representation provides a useful framework for assessing model’s capability to simulate, and illuminating model’s deficiencies in reproducing, the ISO. The nature and causes of the two major biases are also discussed.





We thank anonymous reviewers for their valuable comments that helped improve the quality of the original manuscript. KK acknowledge the support of NOAA Grant NA13OAR4310165 and NSF Grant AGS-1005599. Additional support was provided by the JAMSTEC through its sponsorship of research activities at the IPRC (JICS). The NICAM simulation was performed on the K computer at the RIKEN Advanced Institute for Computational Science (Proposal number hp120279, hp130010 and hp140219) and supported by Strategic Programs for Innovative Research (SPIRE) Field 3 (Projection of Planet Earth Variations for Mitigating Natural Disasters), which is promoted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.


  1. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie PP, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeor 4:1147–1167CrossRefGoogle Scholar
  2. Annamalai H, Sperber KR (2005) Regional heat sources and the active and break phases of boreal summer intraseasonal (30–50 day) variability. J Atmos Sci 62:2726–2748CrossRefGoogle Scholar
  3. Arakawa A (2004) The cumulus parameterization problem: past, present, and future. J Clim 17:2493–2525CrossRefGoogle Scholar
  4. Arakawa A, Wu CM (2013) A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I. J Atmos Sci 70:1977–1992. doi: 10.1175/jas-d-12-0330.1 CrossRefGoogle Scholar
  5. Arakawa A, Jung JH, Wu CM (2011) Toward unification of the multiscale modeling of the atmosphere. Atmos Chem Phys 11:3731–3742. doi: 10.5194/acp-11-3731-2011 CrossRefGoogle Scholar
  6. Benedict JJ, Randall DA (2009) Structure of the Madden–Julian oscillation in the superparameterized CAM. J Atmos Sci 66:3277–3296CrossRefGoogle Scholar
  7. DeMott CA, Stan C, Randall DA, Kinter JL III, Khairoutdinov M (2011) The Asian monsoon in the superparameterized CCSM and its relationship to tropical wave activity. J Clim 24:5134–5156CrossRefGoogle Scholar
  8. DeMott CA, Stan C, Randall DA (2013) Northward propagation mechanisms of the boreal summer intraseasonal oscillation in the ERA-interim and SP-CCSM. J Clim 26:1973–1992. doi: 10.1175/jcli-d-12-00191.1 CrossRefGoogle Scholar
  9. Fu X, Wang B, Li T, McCreary JP (2003) Coupling between northward-propagating, intraseasonal oscillations and sea surface temperature in the Indian Ocean. J Atmos Sci 60:1733–1753CrossRefGoogle Scholar
  10. Fudeyasu H, Wang YQ, Satoh M, Nasuno T, Miura H, Yanase W (2008) Global cloud-system-resolving model NICAM successfully simulated the lifecycles of two real tropical cyclones. Geophys Res, Lett 35 Google Scholar
  11. Fukutomi Y, Kodama C, Yamada H, Noda AT, Satoh M (2015) Tropical synoptic-scale wave disturbances over the western Pacific simulated by a global cloud-system resolving model. Theor Appl Clim. doi: 10.1007/s00704-015-1456-4 Google Scholar
  12. Grabowski WW (2001) Coupling cloud processes with the large-scale dynamics using the cloud-resolving convection parameterization (CRCP). J Atmos Sci 58:978–997CrossRefGoogle Scholar
  13. Grabowski WW, Smolarkiewicz PK (1999) CRCP: a cloud resolving convection parameterization for modeling the tropical convecting atmosphere. Physica D 133:171–178. doi: 10.1016/s0167-2789(99)00104-9 CrossRefGoogle Scholar
  14. Hendon HH, Liebmann B (1990) A composite study of onset of the Australian summer monsoon. J Atmos Sci 47:2227–2240CrossRefGoogle Scholar
  15. Hendon HH, Salby ML (1994) The life cycle of the Madden–Julian oscillation. J Atmos Sci 51:2225–2237CrossRefGoogle Scholar
  16. Holloway CE, Woolnough SJ, Lister GMS (2013) The effects of explicit versus parameterized convection on the MJO in a large-domain high-resolution tropical case study. Part I: characterization of large-scale organization and propagation. J Atmos Sci 70:1342–1369. doi: 10.1175/jas-d-12-0227.1 CrossRefGoogle Scholar
  17. Huffman GJ, Adler RF, Bolvin DT, Gu G (2009) Improving the global precipitation record: GPCP Version 2.1. Geophys Res Lett. doi: 10.1029/2009gl040000 Google Scholar
  18. Hung MP, Lin JL, Wang WQ, Kim D, Shinoda T, Weaver SJ (2013) MJO and convectively coupled equatorial waves simulated by CMIP5 climate models. J Clim 26:6185–6214. doi: 10.1175/jcli-d-12-00541.1 CrossRefGoogle Scholar
  19. Inness PM, Slingo JM, Guilyardi E, Cole J (2003) Simulation of the Madden–Julian oscillation in a coupled general circulation model. Part II: the role of the basic state. J Clim 16:365–382CrossRefGoogle Scholar
  20. Inoue T, Satoh M, Miura H, Mapes B (2008) Characteristics of cloud size of deep convection simulated by a global cloud resolving model over the western tropical Pacific. J Meteorol Soc Jpn 86:1–15CrossRefGoogle Scholar
  21. Jiang X, Waliser DE, Xavier PK, Petch J, Klingaman NP, Woolnough SJ, Guan B, Bellon G, Crueger T, DeMott C, Hannay C, Lin H, Hu W, Kim D, Lappen C-L, Lu M-M, Ma H-Y, Miyakawa T, Ridout JA, Schubert SD, Scinocca J, Seo K-H, Shindo E, Song X, Stan C, Tseng W-L, Wang W, Wu T, Wu X, Wyser K, Zhang GJ, Zhu H (2015) Vertical structure and physical processes of the Madden–Julian oscillation: exploring key model physics in climate simulations. J Geophys Res 120:4718–4748. doi: 10.1002/2014jd022375 Google Scholar
  22. Johnson RH, Ciesielski PE (2013) Structure and properties of Madden–Julian oscillations deduced from DYNAMO sounding arrays. J Atmos Sci 70:3157–3179CrossRefGoogle Scholar
  23. Jung JH, Arakawa A (2010) Development of a quasi-3D multiscale modeling framework: motivation, basic algorithm and preliminary results. J Adv Model Earth Syst. doi: 10.3894/james.2010.2.11 Google Scholar
  24. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  25. Kemball-Cook S, Wang B (2001) Equatorial waves and air-sea interaction in the boreal summer intraseasonal oscillation. J Clim 14:2923–2942CrossRefGoogle Scholar
  26. Kemball-Cook S, Wang B, Fu XH (2002) Simulation of the intraseasonal oscillation in the ECHAM-4 model: the impact of coupling with an ocean model. J Atmos Sci 59:1433–1453CrossRefGoogle Scholar
  27. Khairoutdinov M, Randall D, DeMott C (2005) Simulations of the atmospheric general circulation using a cloud-resolving model as a superparameterization of physical processes. J Atmos Sci 62:2136–2154CrossRefGoogle Scholar
  28. Kikuchi K, Takayabu YN (2003) Equatorial circumnavigation of moisture signal associated with the Madden–Julian Oscillation (MJO) during boreal winter. J Meteorol Soc Jpn 81:851–869CrossRefGoogle Scholar
  29. Kikuchi K, Takayabu YN (2004) The development of organized convection associated with the MJO during TOGA COARE IOP: trimodal characteristics. Geophys Res Lett 31:L10101. doi: 10.1029/2004GL019601 CrossRefGoogle Scholar
  30. Kikuchi K, Wang B, Kajikawa Y (2012) Bimodal representation of the tropical intraseasonal oscillation. Clim Dyn 38:1989–2000. doi: 10.1007/s00382-011-1159-1 CrossRefGoogle Scholar
  31. Kiladis GN, Straub KH, Haertel PT (2005) Zonal and vertical structure of the Madden–Julian oscillation. J Atmos Sci 62:2790–2809CrossRefGoogle Scholar
  32. Kiladis GN, Dias J, Straub KH, Wheeler MC, Tulich SN, Kikuchi K, Weickmann KM, Ventrice MJ (2014) A comparison of olr and circulation-based indices for tracking the MJO. Mon Weather Rev 142:1697–1715. doi: 10.1175/mwr-d-13-00301.1 CrossRefGoogle Scholar
  33. Kim D, Sperber K, Stern W, Waliser D, Kang IS, Maloney E, Wang W, Weickmann K, Benedict J, Khairoutdinov M, Lee MI, Neale R, Suarez M, Thayer-Calder K, Zhang G (2009) Application of MJO simulation diagnostics to climate models. J Clim 22:6413–6436. doi: 10.1175/2009jcli3063.1 CrossRefGoogle Scholar
  34. Kim D, Sobel AH, Maloney ED, Frierson DMW, Kang IS (2011) A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J Clim 24:5506–5520. doi: 10.1175/2011jcli4177.1 CrossRefGoogle Scholar
  35. Kim D, Xavier P, Maloney E, Wheeler M, Waliser D, Sperber K, Hendon H, Zhang C, Neale R, Hwang Y-T, Liu H (2014) Process-oriented MJO simulation diagnostic: moisture sensitivity of simulated convection. J Clim 27:5379–5395. doi: 10.1175/jcli-d-13-00497.1 CrossRefGoogle Scholar
  36. Kodama C, Yamada Y, Noda AT, Kikuchi K, Kajikawa Y, Nasuno T, Tomita T, Yamaura T, Takahashi H, Hara M, Kawatani Y, Satoh M, Sugi M (2015) 20-year climatology of a NICAM AMIP-type simulation. J Meteorol Soc Jpn 93:393–424. doi: 10.2151/jmsj.2015-024 CrossRefGoogle Scholar
  37. Lau KM, Chan PH (1986) Aspects of the 40–50 day oscillation during the northern summer as inferred from outgoing longwave radiation. Mon Weather Rev 114:1354–1367CrossRefGoogle Scholar
  38. Lau WKM, Waliser D (eds) (2012) Intraseasonal variability in the atmosphere-ocean climate system, 2nd edn. Springer, New YorkGoogle Scholar
  39. Lawrence DM, Webster PJ (2002) The boreal summer intraseasonal oscillation: relationship between northward and eastward movement of convection. J Atmos Sci 59:1593–1606CrossRefGoogle Scholar
  40. Lee J-Y, Wang B, Wheeler MC, Fu X, Waliser DE, Kang I-S (2013) Real-time multivariate indices for the boreal summer intraseasonal oscillation over the Asian summer monsoon region. Clim Dyn 40:493–509. doi: 10.1007/s00382-012-1544-4 CrossRefGoogle Scholar
  41. Liebmann B, Smith CA (1996) Description of a complete (interpolated) outgoing longwave radiation dataset. Bull Am Meteorol Soc 77:1275–1277Google Scholar
  42. Lin H (2013) Monitoring and predicting the intraseasonal variability of the east Asian-western North Pacific summer monsoon. Mon Weather Rev 141:1124–1138. doi: 10.1175/mwr-d-12-00087.1 CrossRefGoogle Scholar
  43. Liu P, Satoh M, Wang B, Fudeyasu H, Nasuno T, Li T, Miura H, Taniguchi H, Masunaga H, Fu XH, Annamalai H (2009) An MJO simulated by the NICAM at 14-and 7-km resolutions. Mon Weather Rev 137:3254–3268CrossRefGoogle Scholar
  44. Madden RA, Julian PR (1971) Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J Atmos Sci 28:702–708CrossRefGoogle Scholar
  45. Madden RA, Julian PR (1972) Description of global-scale circulation cells in tropics with a 40–50 day period. J Atmos Sci 29:1109–1123CrossRefGoogle Scholar
  46. Maloney ED, Hartmann DL (2000) Modulation of eastern North Pacific hurricanes by the Madden-Julian oscillation. J Clim 13:1451–1460CrossRefGoogle Scholar
  47. Maloney ED, Jiang X, Xie S-P, Benedict JJ (2014) Process-oriented diagnosis of east Pacific warm pool intraseasonal variability. J Clim 27:6305–6324. doi: 10.1175/jcli-d-14-00053.1 CrossRefGoogle Scholar
  48. Masunaga H, Satoh M, Miura H (2008) A joint satellite and global cloud-resolving model analysis of a Madden–Julian oscillation event: model diagnosis. J Geophys Res. doi: 10.1029/2008jd009986 Google Scholar
  49. Matsueda M, Endo H (2011) Verification of medium-range MJO forecasts with TIGGE. Geophys Res Lett. doi: 10.1029/2011gl047480 Google Scholar
  50. Matthews AJ (2008) Primary and successive events in the Madden–Julian oscillation. Q J R Meteorol Soc 134:439–453CrossRefGoogle Scholar
  51. Miura H, Satoh M, Nasuno T, Noda AT, Oouchi K (2007) A Madden–Julian oscillation event realistically simulated by a global cloud-resolving model. Science 318:1763–1765CrossRefGoogle Scholar
  52. Miura H, Satoh M, Katsumata M (2009) Spontaneous onset of a Madden–Julian oscillation event in a cloud-system-resolving simulation. Geophys Res Lett. doi: 10.1029/2009gl039056 Google Scholar
  53. Miyakawa T, Takayabu YN, Nasuno T, Miura H, Satoh M, Moncrieff MW (2012) Convective momentum transport by rainbands within a Madden–Julian oscillation in a global nonhydrostatic model with explicit deep convective processes. Part I: methodology and general results. J Atmos Sci 69:1317–1338. doi: 10.1175/jas-d-11-024.1 CrossRefGoogle Scholar
  54. Miyakawa T, Satoh M, Miura H, Tomita H, Yashiro H, Noda AT, Yamada Y, Kodama C, Kimoto M, Yoneyama K (2014) Madden–Julian oscillation prediction skill of a new-generation global model demonstrated using a supercomputer. Nat Commun. doi: 10.1038/ncomms4769 Google Scholar
  55. Miyazaki H, Kusano Y, Shinjou N, Shoji F, Yokokawa M, Watanabe T (2012) Overview of the K computer System. Fujitsu Sci Techn J 48:255–265Google Scholar
  56. Molinari J, Vollaro D (2000) Planetary- and synoptic-scale influences on eastern Pacific tropical cyclogenesis. Mon Weather Rev 128:3296–3307CrossRefGoogle Scholar
  57. Nakano M, Sawada M, Nasuno T, Satoh M (2015) Intraseasonal variability and tropical cyclogenesis in the western North Pacific simulated by a global nonhydrostatic atmospheric model. Geophys Res Lett 42:565–571. doi: 10.1002/2014gl062479 CrossRefGoogle Scholar
  58. Nakazawa T (1988) Tropical super clusters within intraseasonal variations over the western Pacific. J Meteorol Soc Jpn 66:823–839Google Scholar
  59. Nasuno T, Tomita H, Iga S, Miura H, Satoh M (2007) Multiscale organization of convection simulated with explicit cloud processes on an aquaplanet. J Atmos Sci 64:1902–1921CrossRefGoogle Scholar
  60. Nasuno T, Miura H, Satoh M, Noda AT, Oouchi K (2009) Multi-scale organization of convection in a global numerical simulation of the December 2006 MJO event using explicit moist processes. J Meteorol Soc Jpn 87:335–345. doi: 10.2151/jmsj.87.335 CrossRefGoogle Scholar
  61. Okumura YM, Deser C (2010) Asymmetry in the duration of El Nino and La Nina. J Clim 23:5826–5843. doi: 10.1175/2010jcli3592.1 CrossRefGoogle Scholar
  62. Oouchi K, Noda AT, Satoh M, Miura H, Tomita H, Nasuno T, Iga S-I (2009) A simulated preconditioning of typhoon genesis controlled by a boreal summer Madden–Julian oscillation event in a global cloud-system-resolving model. Sola 5:65–68. doi: 10.2151/sola.2009-017 CrossRefGoogle Scholar
  63. Randall DA (2013) Beyond deadlock. Geophys Res Lett 40:5970–5976. doi: 10.1002/2013gl057998 CrossRefGoogle Scholar
  64. Randall D, Khairoutdinov M, Arakawa A, Grabowski W (2003) Breaking the cloud parameterization deadlock. Bull Am Meteorol Soc 84:1547CrossRefGoogle Scholar
  65. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res. doi: 10.1029/2002jd002670 Google Scholar
  66. Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK, Bloom S, Chen JY, Collins D, Conaty A, Da Silva A, Gu W, Joiner J, Koster RD, Lucchesi R, Molod A, Owens T, Pawson S, Pegion P, Redder CR, Reichle R, Robertson FR, Ruddick AG, Sienkiewicz M, Woollen J (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24:3624–3648. doi: 10.1175/jcli-d-11-00015.1 CrossRefGoogle Scholar
  67. Sabeerali CT, Ramu Dandi A, Dhakate A, Salunke K, Mahapatra S, Rao SA (2013) Simulation of boreal summer intraseasonal oscillations in the latest CMIP5 coupled GCMs. J Geophys Res 118:4401–4420. doi: 10.1002/jgrd.50403 Google Scholar
  68. Sato T (2004) The Earth Simulator: roles and impacts. Parallel Comput 30:1279–1286. doi: 10.1016/j.parco.2004.09.003 CrossRefGoogle Scholar
  69. Sato T, Miura H, Satoh M, Takayabu YN, Wang Y (2009) Diurnal cycle of precipitation in the tropics simulated in a global cloud-resolving model. J Clim 22:4809–4826. doi: 10.1175/2009jcli2890.1 CrossRefGoogle Scholar
  70. Satoh M, Matsuno T, Tomita H, Miura H, Nasuno T, Iga S (2008) Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations. J Comput Phys 227:3486–3514CrossRefGoogle Scholar
  71. Satoh M, Oouchi K, Nasuno T, Taniguchi H, Yamada Y, Tomita H, Kodama C, Kinter J, Achuthavarier D, Manganello J, Cash B, Jung T, Palmer T, Wedi N (2012) The intra-seasonal oscillation and its control of tropical cyclones simulated by high-resolution global atmospheric models. Clim Dyn. doi: 10.1007/s00382-011-1235-6 Google Scholar
  72. Satoh M, Tomita H, Yashiro H, Miura H, Kodama C, Seiki T, Noda AT, Yamada Y, Goto D, Sawada M, Miyoshi T, Niwa Y, Hara M, Ohno T, Iga S-I, Arakawa T, Inoue T, Kubokawa H (2014) The non-hydrostatic icosahedral atmospheric model: description and Development. Prog Earth Planet Sci 1:18CrossRefGoogle Scholar
  73. Satoh M, Yamada Y, Sugi M, Kodama C, Noda A (2015) Constraint on future change in global frequency of tropical cyclones due to global warming. J Meteorol Soc Jpn. doi: 10.2151/jmsj.2015-025 Google Scholar
  74. Slingo JM, Sperber KR, Boyle JS, Ceron JP, Dix M, Dugas B, Ebisuzaki W, Fyfe J, Gregory D, Gueremy JF, Hack J, Harzallah A, Inness P, Kitoh A, Lau WKM, McAvaney B, Madden R, Matthews A, Palmer TN, Park CK, Randall D, Renno N (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Clim Dyn 12:325–357CrossRefGoogle Scholar
  75. Sperber KR (2003) Propagation and the vertical structure of the Madden–Julian oscillation. Mon Weather Rev 131:3018–3037CrossRefGoogle Scholar
  76. Sperber KR, Annamalai H (2008) Coupled model simulations of boreal summer intraseasonal (30–50 day) variability, Part I: systematic errors and caution on use of metrics. Clim Dyn 31:345–372CrossRefGoogle Scholar
  77. Sperber KR, Gualdi S, Legutke S, Gayler V (2005) The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models. Clim Dyn 25:117–140. doi: 10.1007/s00382-005-0026-3 CrossRefGoogle Scholar
  78. Sperber K, Slingo JM, Inness PM (2012) Modeling intraseasonal variability. In: Lau WKM, Waliser D (eds) Intraseasonal variability in the atmosphere-ocean climate system, 2nd edn. Springer, New York, pp 399–431Google Scholar
  79. Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2013) The Asian summer monsoon: an intercomparison of CMIP5 versus CMIP3 simulations of the late 20th century. Clim Dyn 41:2711–2744. doi: 10.1007/s00382-012-1607-6 CrossRefGoogle Scholar
  80. Straub KH (2013) MJO initiation in the real-time multivariate MJO index. J Clim 26:1130–1151. doi: 10.1175/jcli-d-12-00074.1 CrossRefGoogle Scholar
  81. Suhas E, Neena JM, Goswami BN (2013) An Indian monsoon intraseasonal oscillations (MISO) index for real time monitoring and forecast verification. Clim Dyn 40:2605–2616. doi: 10.1007/s00382-012-1462-5 CrossRefGoogle Scholar
  82. Szekely E, Giannakis D, Majda AJ (2015) Extraction and predictability of coherent intraseasonal signals in infrared brightness temperature data. Clim Dyn. doi: 10.1007/s00382-015-2658-2 Google Scholar
  83. Tao W-K, Chern J-D, Atlas R, Randall D, Khairoutdinov M, Li J-L, Waliser DE, Hou A, Lin X, Peters-Lidard C, Lau W, Jiang J, Simpson J (2009) A multiscale modeling system developments, applications, and critical issues. Bull Am Meteorol Soc 90:515. doi: 10.1175/2008bams2542.1 CrossRefGoogle Scholar
  84. Tomita H, Satoh M (2004) A new dynamical framework of nonhydrostatic global model using the icosahedral grid. Fluid Dyn Res 34:357–400. doi: 10.1016/j.fluiddyn.2004.03.003 CrossRefGoogle Scholar
  85. Tomita H, Miura H, Iga S, Nasuno T, Satoh M (2005) A global cloud-resolving simulation: preliminary results from an aqua planet experiment. Geophys Res Lett 32. doi: 10.1029/2005gl022459
  86. Tulich SN (2015) A strategy for representing the effects of convective momentum transport in multiscale models: evaluation using a new superparameterized version of the weather research and forecast model (SP-WRF). J Adv Model Earth Syst 7:938–962. doi: 10.1002/2014ms000417 CrossRefGoogle Scholar
  87. Waliser D, Sperber K, Hendon H, Kim D, Wheeler M, Weickmann K, Zhang C, Donner L, Gottschalck J, Higgins W, Kang IS, Legler D, Moncrieff M, Vitart F, Wang B, Wang W, Woolnough S, Maloney E, Schubert S, Stern W (2009) MJO simulation diagnostics. J Clim 22:3006–3030CrossRefGoogle Scholar
  88. Wang B (2011) Theory. In: Lau WKM, Waliser D (eds) Intraseasonal variability in the atmosphere-ocean climate system, 2nd edn. Praxis Publishing, Chichester, pp 335–398Google Scholar
  89. Wang B, Rui H (1990) Synoptic climatology of transient tropical intraseasonal convection anomalies: 1975–1985. Meteorol Atmos. Phys 44:43–61CrossRefGoogle Scholar
  90. Wang B, Xie X (1997) A model for the boreal summer intraseasonal oscillation. J Atmos Sci 54:72–86CrossRefGoogle Scholar
  91. Wheeler MC, Hendon HH (2004) An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon Weather Rev 132:1917–1932CrossRefGoogle Scholar
  92. Yanai M, Esbensen S, Chu JH (1973) Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets. J Atmos Sci 30:611–627CrossRefGoogle Scholar
  93. Yanai M, Chen B, Tung WW (2000) The Madden–Julian oscillation observed during the TOGA COARE IOP: global view. J Atmos Sci 57:2374–2396. doi: 10.1175/1520-0469(2000)057 CrossRefGoogle Scholar
  94. Yasunari T (1979) Cloudiness fluctuations associated with the northern hemisphere summer monsoon. J Meteorol Soc Jpn 57:227–242Google Scholar
  95. Yoneyama K, Masumoto Y, Kuroda Y, Katsumata M, Mizuno K, Takayabu YN, Yoshizaki M, Shareef A, Fujiyoshi Y, McPhaden MJ, Murty VSN, Shirooka R, Yasunaga K, Yamada H, Sato N, Ushiyama T, Moteki Q, Seiki A, Fujita M, Ando K, Hase H, Ueki I, Horii T, Yokoyama C, Miyakawa T (2008) MISMO field experiment in the equatorial Indian Ocean. Bull Am Meteorol Soc 89:1889. doi: 10.1175/2008bams2519.1 CrossRefGoogle Scholar
  96. Zhang CD (2005) Madden–Julian oscillation. Rev Geophys 43:RG2003. doi: 10.1029/2004RG000158 Google Scholar
  97. Zhang CD (2013) Madden–Julian oscillation: bridging weather and climate. Bull. Am Meteorol Soc 94:1849–1870. doi: 10.1175/bams-d-12-00026.1 CrossRefGoogle Scholar
  98. Zhao C, Li T, Zhou T (2013) Precursor signals and processes associated with MJO initiation over the tropical Indian Ocean. J Clim 26:291–307. doi: 10.1175/jcli-d-12-00113.1 CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.International Pacific Research CenterUniversity of Hawai‘iHonoluluUSA
  2. 2.Japan Agency for Marine-Earth Science and TechnologyYokohamaJapan
  3. 3.University of TokyoTokyoJapan
  4. 4.Atmosphere and Ocean Research InstituteUniversity of TokyoKashiwaJapan

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