Climate Dynamics

, Volume 48, Issue 3–4, pp 767–781 | Cite as

Convectively coupled Kelvin waves in CMIP5 coupled climate models

  • Lu Wang
  • Tim LiEmail author


This study provided a quantitative evaluation of convectively coupled Kelvin waves (CCKWs) over the Indian Ocean and the Pacific Ocean simulated by 20 coupled climate models that participated in Coupled Model Intercomparison Project phase 5. The two leading empirical orthogonal function (EOF) modes of filtered daily precipitation anomalies are used to represent the eastward propagating CCKWs in both observations and simulations. The eigenvectors and eigenvalues of the EOF modes represent the spatial patterns and intensity of CCKWs respectively, and the lead–lag relationship between the two EOF principle components describe the phase propagation of CCKWs. A non-dimensional metric was designed in consideration of all the three factors (i.e., pattern, amplitude and phase propagation) for evaluation. The relative rankings of the models based on the skill scores calculated by the metric are conducted for the Indian Ocean and the Pacific Ocean, respectively. Two models (NorESM1-M and MPI-ESM-LR) are ranked among the best 20 % for both the regions. Three models (inmcm4, MRI-CGCM3 and HadGEM2-ES) are ranked among the worst 20 % for both the regions. While the observed CCKW amplitude is greater north of the equator in the Pacific, some models overestimate the CCKW ampliutde in the Southern Hemisphere. This bias is related to the mean state precipitation bias along the south Pacific convergence zone.


Kelvin wave Precipitation Climate model CMIP5 



This study is jointly supported by China National 973 Project 2015CB453200, NSFC Grant 41475084, ONR Grant N00014-16-12260, Jiangsu Natural Science Foundation Key project (BK20150062), Jiangsu Shuang-Chuang Team (R2014SCT001), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) and the International Pacific Research Center sponsored partially by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). This is SOEST Contribution Number 9609, IPRC Contribution Number 1184 and ESMC Number 100.


  1. Bellenger H, Duvel J-P, Lengaigne M, Levan P (2009) Impact of organized intraseasonal convective perturbations on the tropical circulation. Geophys Res Lett. doi: 10.1029/2009gl039584 Google Scholar
  2. Bessafi M, Wheeler MC (2006) Modulation of South Indian Ocean tropical cyclones by the Madden–Julian oscillation and convectively coupled equatorial waves. Mon Weather Rev 134:638–656CrossRefGoogle Scholar
  3. Dai A (2006) Precipitation characteristics in eighteen coupled climate models. J Clim 19:4605–4630. doi: 10.1175/jcli3884.1 CrossRefGoogle Scholar
  4. Dunkerton TJ, Crum FX (1995) Eastward propagating ~2- to 15-day equatorial convection and its relation to the tropical intraseasonal oscillation. J Geophys Res Atmos 100(D2):25781–25790CrossRefGoogle Scholar
  5. Emanuel KA (1987) An air–sea interaction model of intraseasonal oscillations in the tropics. J Atmos Sci 44:2324–2340CrossRefGoogle Scholar
  6. Emanuel KA, David Neelin J, Bretherton CS (1994) On large-scale circulations in convecting atmospheres. Q J R Meteorol Soc 120:1111–1143CrossRefGoogle Scholar
  7. Flatau MK, Flatau PJ, Schmidt J, Kiladis GN (2003) Delayed onset of the 2002 Indian monsoon. Geophys Res Lett 30:1768. doi: 10.1029/2003gl017434 CrossRefGoogle Scholar
  8. Frank WM, Roundy PE (2006) The role of tropical waves in tropical cyclogenesis. Mon Weather Rev 134:2397–2417. doi: 10.1175/mwr3204.1 CrossRefGoogle Scholar
  9. Guo Y, Waliser DE, Jiang X (2015) A systematic relationship between the representations of convectively coupled equatorial wave activity and the Madden–Julian oscillation in climate model simulations. J Clim 28:1881–1904. doi: 10.1175/jcli-d-14-00485.1 CrossRefGoogle Scholar
  10. Haertel PT, Straub KH (2010) Simulating convectively coupled Kelvin waves using Lagrangian overturning for a convective parametrization. Q J R Meteorol Soc 136:1598–1613. doi: 10.1002/qj.666 CrossRefGoogle Scholar
  11. Hsu P-C, Li T, Tsou C-H (2011) Interactions between boreal summer intraseasonal oscillations and synoptic-scale disturbances over the Western North Pacific. Part I: energetics diagnosis*. J Clim 24:927–941. doi: 10.1175/2010jcli3833.1 CrossRefGoogle Scholar
  12. Huffman GJ et al (2001) Global precipitation at one-degree daily resolution from multisatellite observations. J Hydrometeorol 2:36–50. doi: 10.1175/1525-7541(2001)002<0036:gpaodd>;2 CrossRefGoogle Scholar
  13. Hung M-P, Lin J-L, Wang W, 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
  14. Jiang X, Li T, Wang B (2004) Structures and mechanisms of the northward propagating boreal summer intraseasonal oscillation*. J Clim 17:1022–1039CrossRefGoogle Scholar
  15. Khouider B, Majda AJ (2008) Equatorial convectively coupled waves in a simple multicloud model. J Atmos Sci 65:3376–3397. doi: 10.1175/2008jas2752.1 CrossRefGoogle Scholar
  16. Kikuchi K, Takayabu YN (2003) Equatorial circumnavigation of moisture signal associated with the Madden–Julian oscillation (MJO) during boreal winter. J Meteorol Soc Jp Ser II 81:851–869. doi: 10.2151/jmsj.81.851 CrossRefGoogle Scholar
  17. Kiladis GN, Wheeler MC, Haertel PT, Straub KH, Roundy PE (2009) Convectively coupled equatorial waves. Rev Geophys. doi: 10.1029/2008rg000266 Google Scholar
  18. Kiladis GN et al (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
  19. Lau K-M, Waliser DE (2011) Intraseasonal variability in the atmosphere–ocean climate system. Springer, HeidelbergGoogle Scholar
  20. Li G, Xie S-P (2014) Tropical biases in CMIP5 multimodel ensemble: the excessive equatorial Pacific cold tongue and double ITCZ problems*. J Clim 27:1765–1780. doi: 10.1175/jcli-d-13-00337.1 CrossRefGoogle Scholar
  21. Li J, Zhang X, Yu Y, Dai F (2004) Primary reasoning behind the double ITCZ phenomenon in a coupled ocean-atmosphere general circulation model. Adv Atmos Sci 21:857–867. doi: 10.1007/bf02915588 CrossRefGoogle Scholar
  22. Lin J-L et al (2006) Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: convective signals. J Clim 19:2665–2690. doi: 10.1175/jcli3735.1 CrossRefGoogle Scholar
  23. Liu P (2014) MJO structure associated with the higher-order CEOF modes. Clim Dyn 43:1939–1950. doi: 10.1007/s00382-013-2017-0 CrossRefGoogle Scholar
  24. 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
  25. Mapes BE (2000) Convective inhibition, subgrid-scale triggering energy, and stratiform instability in a toy tropical wave model. J Atmos Sci 57:1515–1535. doi: 10.1175/1520-0469(2000)057<1515:cisste>;2 CrossRefGoogle Scholar
  26. Matsuno T (1966) Quasi-geostrophic motions in the equatorial area. J Meteor Soc Japan 44:25–43Google Scholar
  27. Mekonnen A, Thorncroft CD, Aiyyer AR, Kiladis GN (2008) Convectively coupled Kelvin waves over tropical Africa during the boreal summer: structure and variability. J Clim 21:6649–6667. doi: 10.1175/2008jcli2008.1 CrossRefGoogle Scholar
  28. Mounier F, Kiladis GN, Janicot S (2007) Analysis of the dominant mode of convectively coupled Kelvin waves in the West African Monsoon. J Clim 20:1487–1503. doi: 10.1175/jcli4059.1 CrossRefGoogle Scholar
  29. Murata F et al (2006) Dry intrusions following eastward-propagating synoptic-scale cloud systems over Sumatera Island. J Meteorol Soc Jpn Ser II 84:277–294. doi: 10.2151/jmsj.84.277 CrossRefGoogle Scholar
  30. Nakazawa T (1986) Mean features of 30–60 day variations as inferred from 8-year OLR data. J Mereor Soc Jpn 64:777–786Google Scholar
  31. Nakazawa T (1988) Tropical super clusters within intraseasonal variations over the western Pacific. J Mereor Soc Jpn 66:823–839Google Scholar
  32. Neelin JD, Held IM (1987) Modeling tropical convergence based on the moist static energy budget. Mon Weather Rev 115:3–12. doi: 10.1175/1520-0493(1987)115<0003:mtcbot>;2 CrossRefGoogle Scholar
  33. Neelin JD, Held IM, Cook KH (1987) Evaporation-wind feedback and low-frequency variability in the tropical atmosphere. J Atmos Sci 44:2341–2348. doi: 10.1175/1520-0469(1987)044<2341:ewfalf>;2 CrossRefGoogle Scholar
  34. Nguyen H, Duvel J-P (2008) Synoptic wave perturbations and convective systems over equatorial Africa. J Clim 21:6372–6388. doi: 10.1175/2008jcli2409.1 CrossRefGoogle Scholar
  35. North GR, Bell TL, Cahalan RF, Moeng FJ (1982) Sampling errors in the estimation of empirical orthogonal functions. Mon Weather Rev 110:699–706. doi: 10.1175/1520-0493(1982)110<0699:seiteo>;2 CrossRefGoogle Scholar
  36. Roundy PE (2008) Analysis of convectively coupled Kelvin waves in the Indian Ocean MJO. J Atmos Sci 65:1342–1359. doi: 10.1175/2007jas2345.1 CrossRefGoogle Scholar
  37. Roundy PE (2014) On the interpretation of EOF analysis of ENSO, atmospheric Kelvin waves, and the MJO. J Clim 28:1148–1165. doi: 10.1175/jcli-d-14-00398.1 CrossRefGoogle Scholar
  38. Roundy PE, Frank WM (2004) A climatology of waves in the equatorial region. J Atmos Sci 61:2105–2132. doi: 10.1175/1520-0469(2004)061<2105:acowit>;2 CrossRefGoogle Scholar
  39. Straub KH, Kiladis GN (2002) Observations of a convectively coupled Kelvin wave in the eastern Pacific ITCZ. J Atmos Sci 59:30–53. doi: 10.1175/1520-0469(2002)059<0030:ooacck>;2 CrossRefGoogle Scholar
  40. Straub KH, Kiladis GN, Ciesielski PE (2006) The role of equatorial waves in the onset of the South China Sea summer monsoon and the demise of El Niño during 1998. Dyn Atmos Oceans 42:216–238. doi: 10.1016/j.dynatmoce.2006.02.005 CrossRefGoogle Scholar
  41. Straub KH, Haertel PT, Kiladis GN (2010) An analysis of convectively coupled Kelvin waves in 20 WCRP CMIP3 global coupled climate models. J Clim 23:3031–3056. doi: 10.1175/2009jcli3422.1 CrossRefGoogle Scholar
  42. Takayabu YN, Murakami M (1991) The structure of super cloud clusters observed in 1–20 June 1986 and their relationship to easterly waves. J Mereor Soc Jpn 69:105–125Google Scholar
  43. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. doi: 10.1175/bams-d-11-00094.1 CrossRefGoogle Scholar
  44. Tulich SN, Mapes BE (2008) Multiscale convective wave disturbances in the tropics: insights from a two-dimensional cloud-resolving model. J Atmos Sci 65:140–155. doi: 10.1175/2007jas2353.1 CrossRefGoogle Scholar
  45. Tulich SN, Randall DA, Mapes BE (2007) Vertical-mode and cloud decomposition of large-scale convectively coupled gravity waves in a two-dimensional cloud-resolving model. J Atmos Sci 64:1210–1229. doi: 10.1175/jas3884.1 CrossRefGoogle Scholar
  46. Wang B (1988) Dynamics of tropical low-frequency waves: an analysis of the moist Kelvin wave. J Atmos Sci 45:2–051Google Scholar
  47. Wang H, Fu R (2007) The influence of Amazon rainfall on the Atlantic ITCZ through convectively coupled Kelvin waves. J Clim 20:1188–1201. doi: 10.1175/jcli4061.1 CrossRefGoogle Scholar
  48. Wheeler M, Kiladis GN (1999) Convectively coupled equatorial waves: analysis of clouds and temperature in the wavenumber-frequency domain. J Atmos Sci 56:374–399. doi: 10.1175/1520-0469(1999)056<0374:ccewao>;2 CrossRefGoogle Scholar
  49. Yang G-Y, Hoskins B, Slingo J (2007) Convectively coupled equatorial waves. Part I: horizontal and vertical structures. J Atmos Sci 64:3406–3423. doi: 10.1175/jas4017.1 CrossRefGoogle Scholar
  50. Zhang C, Dong M (2004) Seasonality in the Madden–Julian oscillation. J Clim 17:3169–3180CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME) / Joint International Research Laboratory of Climate and Environmental Change (ILCEC) / Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina
  2. 2.International Pacific Research Center, and School of Ocean and Earth Science and TechnologyUniversity of HawaiiHonoluluUSA

Personalised recommendations