Climate Dynamics

, Volume 44, Issue 5–6, pp 1487–1503 | Cite as

Resolving the upper-ocean warm layer improves the simulation of the Madden–Julian oscillation

  • Wan-Ling Tseng
  • Ben-Jei Tsuang
  • Noel S. Keenlyside
  • Huang-Hsiung Hsu
  • Chia-Ying Tu
Article

Abstract

Here we show that coupling a high-resolution one-column ocean model to an atmospheric general circulation model dramatically improves simulation of the Madden–Julian oscillation (MJO) to have realistic strength, period, and propagation speed. The mechanism for the simulated MJO involves both frictional wave-convective conditional instability of the second kind (Frictional wave-CISK) and air–sea convective intraseasonal interaction (ASCII). In particular, better resolving the fine structure of upper ocean temperature, especially the warm layer, produces more vigorous atmosphere–ocean interaction and strengthens intraseasonal variations in both SST and atmospheric circulation. This helps organize and strengthen deep convection, inducing a stronger Kelvin-wave like perturbation and frictional near-surface convergence to the east. In addition, the warmer SST ahead of the MJO also acts to destabilize the boundary layer and enhance frictional convergence. These lead to a more realistic eastward-propagating MJO. A suite of sensitivity experiments were performed to show the robustness of the mechanisms and to demonstrate: (1) that mean state differences are not the main contributors to the improved simulation of our coupled model; (2) the role of SST variability in enhancing frictional convergence and intraseasonal variations in precipitation, and (3) that the simulation is significantly degraded when the first ocean model layer is thicker than 10 m. Our coupled model results are consistent with observations and demonstrate a simple but effective means to significantly improve MJO simulation and potentially also forecasts.

Keywords

MJO Coupling Warm layer One column ocean model 

Supplementary material

382_2014_2315_MOESM1_ESM.docx (72 kb)
Supplementary material 1 (DOCX 72 kb)

References

  1. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P-P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeorol 4(6):1147–1167CrossRefGoogle Scholar
  2. Ajayamohan R, Khouider B, Majda AJ (2013) Realistic initiation and dynamics of the Madden–Julian oscillation in a coarse resolution aquaplanet GCM. Geophys Res Lett 40(23):6252–6257CrossRefGoogle Scholar
  3. Andersen JA, Kuang Z (2012) Moist static energy budget of MJO-like disturbances in the atmosphere of a zonally symmetric aquaplanet. J Clim 25(8):2782–2804CrossRefGoogle Scholar
  4. Bernie D, Woolnough S, Slingo J, Guilyardi E (2005) Modeling diurnal and intraseasonal variability of the ocean mixed layer. J Clim 18(8):1190–1202CrossRefGoogle Scholar
  5. Bernie D, Guilyardi E, Madec G, Slingo J, Woolnough S, Cole J (2008) Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 2: a diurnally coupled CGCM. Clim Dyn 31(7–8):909–925CrossRefGoogle Scholar
  6. Chen SS, Houze RA Jr, Mapes BE (1996) Multiscale variability of deep convection in realation to large-scale circulation in TOGA COARE. J Atmos Sci 53(10):1380–1409CrossRefGoogle Scholar
  7. CLIVAR MJOWG (2009) MJO simulation diagnostics. J Clim 22(11):3006–3030CrossRefGoogle Scholar
  8. Crueger T, Stevens B, Brokopf R (2013) The Madden–Julian Oscillation in ECHAM6 and the introduction of an objective MJO metric. J Clim 26(10):3241–3257Google Scholar
  9. Dee D, Uppala S, Simmons A, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M, Balsamo G, Bauer P (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597CrossRefGoogle Scholar
  10. Deng L, Wu X (2010) Effects of convective processes on GCM simulations of the Madden–Julian oscillation. J Clim 23(2):352–377CrossRefGoogle Scholar
  11. Emanuel KA (1987) An air–sea interaction model of intraseasonal oscillations in the tropics. J Atmos Sci 44(16):2324–2340CrossRefGoogle Scholar
  12. Fairall C, Bradley EF, Godfrey J, Wick G, Edson JB, Young G (1996) Cool-skin and warm-layer effects on sea surface temperature. J Geophys Res 101(C1):1295–1308CrossRefGoogle Scholar
  13. Flatau M, Flatau PJ, Phoebus P, Niiler PP (1997) The feedback between equatorial convection and local radiative and evaporative processes: the implications for intraseasonal oscillations. J Atmos Sci 54(19):2373–2386CrossRefGoogle Scholar
  14. Gaspar P, Gregoris Y, Lefevre J-M (1990) A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: tests at station papa and long-term upper ocean study site. J Geophys Res 95(C9):16179–16193CrossRefGoogle Scholar
  15. Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106(449):447–462CrossRefGoogle Scholar
  16. Hendon HH (2000) Impact of air–sea coupling on the Madden–Julian oscillation in a general circulation model. J Atmos Sci 57(24):3939–3952CrossRefGoogle Scholar
  17. Hendon HH, Liebmann B (1994) Organization of convection within the Madden–Julian oscillation. J Geophys Res Atmos (1984–2012) 99(D4):8073–8083CrossRefGoogle Scholar
  18. Hendon HH, Salby ML (1994) The life cycle of the Madden–Julian oscillation. J Atmos Sci 51(15):2225–2237CrossRefGoogle Scholar
  19. Hsu H-H, Weng C-H, Wu C-H (2004) Contrasting characteristics between the northward and eastward propagation of the intraseasonal oscillation during the boreal summer. J Clim 17(4):727–743CrossRefGoogle Scholar
  20. 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(17):6185–6214CrossRefGoogle Scholar
  21. Inness PM, Slingo JM (2003) Simulation of the Madden–Julian oscillation in a coupled general circulation model. Part I: comparison with observations and an atmosphere-only GCM. J Clim 16(3):345–364CrossRefGoogle Scholar
  22. 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, Wyser K, Wu X, Zhang GJ, Zhu H (2014) Exploring key processes of the Madden–Julian Oscillation (MJO): a joint WGNE MJO task force/GEWEX GASS project on the vertical structure and diabatic processes of the MJO—part I. Climate Simulations. J Geophys Res Atmos (submitted)Google Scholar
  23. Kang I-S, Liu F, Ahn M-S, Yang Y-M, Wang B (2013) The role of SST structure in convectively coupled Kelvin–Rossby waves and its implications for MJO formation. J Clim 26(16):5915–5930Google Scholar
  24. Kim D, Sperber K, Stern W, Waliser D, Kang I-S, Maloney E, Wang W, Weickmann K, Benedict J, Khairoutdinov M (2009) Application of MJO simulation diagnostics to climate models. J Clim 22(23):6413–6436CrossRefGoogle Scholar
  25. Kim D, Sobel AH, Maloney ED, Frierson DM, Kang I-S (2011) A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J Clim 24(21):5506–5520CrossRefGoogle Scholar
  26. Kiranmayi L, Maloney ED (2011) Intraseasonal moist static energy budget in reanalysis data. J Geophys Res 116:D21117. doi:10.1029/2011JD016031
  27. Klingaman NP, Woolnough SJ, Weller H, Slingo JM (2011) The impact of finer-resolution air–sea coupling on the intraseasonal oscillation of the Indian monsoon. J Clim 24(10):2451–2468CrossRefGoogle Scholar
  28. Lin J-L, Kiladis GN, Mapes BE, Weickmann KM, Sperber KR, Lin W, Wheeler MC, Schubert SD, Del Genio A, Donner LJ (2006) Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: convective signals. J Clim 19(12):2665–2690Google Scholar
  29. Lindzen RS, Nigam S (1987) On the role of sea surface temperature gradients in forcing low-level winds and convergence in the tropics. J Atmos Sci 44(17):2418–2436CrossRefGoogle Scholar
  30. Liu P, Wang B, Sperber KR, Li T, Meehl GA (2005) MJO in the NCAR CAM2 with the Tiedtke convective scheme. J Clim 18(15):3007–3020CrossRefGoogle Scholar
  31. Madden RA, Julian PR (1972) Description of global-scale circulation cells in the tropics with a 40–50 day period. J Atmos Sci 29(6):1109–1123CrossRefGoogle Scholar
  32. Maloney ED (2009) The moist static energy budget of a composite tropical intraseasonal oscillation in a climate model. J Clim 22(3):711–729CrossRefGoogle Scholar
  33. Maloney ED, Hartmann DL (1998) Frictional moisture convergence in a composite life cycle of the Madden–Julian oscillation. J Clim 11(9):2387–2403CrossRefGoogle Scholar
  34. Maloney ED, Sobel AH (2004) Surface fluxes and ocean coupling in the tropical intraseasonal oscillation. J Clim 17(22):4368–4386CrossRefGoogle Scholar
  35. Marshall AG, Alves O, Hendon HH (2008) An enhanced moisture convergence-evaporation feedback mechanism for MJO air–sea interaction. J Atmos Sci 65(3):970–986CrossRefGoogle Scholar
  36. Nakazawa T (1988) Tropical super clusters within intraseasonal variations over the western Pacific. J Meteorol Soc Jpn 66(6):823–839Google Scholar
  37. Neelin JD, Held IM, Cook KH (1987) Evaporation-wind feedback and low-frequency variability in the tropical atmosphere. J Atmos Sci 44(16):2341–2348CrossRefGoogle Scholar
  38. Nordeng TE (1994) Extended versions of the convective parametrization scheme at ECMWF and their impact on the mean and transient activity of the model in the tropics. European Centre for Medium-Range Weather ForecastsGoogle Scholar
  39. Paulson CA, Simpson JJ (1981) The temperature difference across the cool skin of the ocean. J Geophys Res 86(C11):11044–11054CrossRefGoogle Scholar
  40. Reynolds RW, Smith TM (1995) A high-resolution global sea surface temperature climatology. J Clim 8(6):1571–1583CrossRefGoogle Scholar
  41. Roeckner E (2003) The atmospheric general circulation model ECHAM5: part 1: model description. Max-Planck-Institut fuer Meteorologie, GermanyGoogle Scholar
  42. Saunders PM (1967) The temperature at the ocean–air interface. J Atmos Sci 24(3):269–273CrossRefGoogle Scholar
  43. Shinoda T, Hendon HH (1998) Mixed layer modeling of intraseasonal variability in the tropical western Pacific and Indian Oceans. J Clim 11(10):2668–2685CrossRefGoogle Scholar
  44. Sperber KR, Gualdi S, Legutke S, Gayler V (2005) The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models. Clim Dyn 25(2–3):117–140CrossRefGoogle Scholar
  45. Subramanian AC, Jochum M, Miller AJ, Murtugudde R, Neale RB, Waliser DE (2011) The Madden–Julian oscillation in CCSM4. J Clim 24(24):6261–6282. doi:10.1175/JCLI-D-11-00031.1 CrossRefGoogle Scholar
  46. Tiedtke M (1989) A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon Weather Rev 117(8):1779–1800CrossRefGoogle Scholar
  47. Tsuang B-J, Tu C-Y, Tsai J-L, Dracup JA, Arpe K, Meyers T (2009) A more accurate scheme for calculating Earths-skin temperature. Clim Dyn 32(2–3):251–272CrossRefGoogle Scholar
  48. Tu C-Y, Tsuang B-J (2005) Cool-skin simulation by a one-column ocean model. Geophys Res Lett 32:L22602. doi:10.1029/2005GL024252
  49. Waliser DE, Lau K, Kim J-H (1999) The influence of coupled sea surface temperatures on the Madden–Julian oscillation: a model perturbation experiment. J Atmos Sci 56(3):333–358CrossRefGoogle Scholar
  50. Wang B, Rui H (1990) Dynamics of the coupled moist Kelvin–Rossby wave on an equatorial-plane. J Atmos Sci 47(4):397–413CrossRefGoogle Scholar
  51. Watterson I (2002) The sensitivity of subannual and intraseasonal tropical variability to model ocean mixed layer depth. J Geophys Res Atmos (1984–2012) 107 (D2):ACL 12-11–ACL 12-15Google Scholar
  52. Watterson I, Syktus J (2007) The influence of air–sea interaction on the Madden–Julian oscillation: the role of the seasonal mean state. Clim Dyn 28(7–8):703–722CrossRefGoogle Scholar
  53. 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(8):1917–1932CrossRefGoogle Scholar
  54. Woolnough SJ, Slingo JM, Hoskins BJ (2000) The relationship between convection and sea surface temperature on intraseasonal timescales. J Clim 13(12):2086–2104CrossRefGoogle Scholar
  55. Woolnough S, Vitart F, Balmaseda M (2007) The role of the ocean in the Madden–Julian oscillation: implications for MJO prediction. Q J R Meteorol Soc 133(622):117–128CrossRefGoogle Scholar
  56. Wu J (1985) On the cool skin of the ocean. Bound-Layer Meteorol 31(2):203–207CrossRefGoogle Scholar
  57. Yanai M, Chen B, Tung W-w (2000) The Madden–Julian oscillation observed during the TOGA COARE IOP: global view. J Atmos Sci 57(15):2374–2396CrossRefGoogle Scholar
  58. Zhang C (2005) Madden–Julian Oscillation. Rev Geophys 43:RG2003. doi:10.1029/2004RG000158
  59. Zhang GJ, Mu M (2005) Simulation of the Madden–Julian oscillation in the NCAR CCM3 using a revised Zhang–McFarlane convection parameterization scheme. J Clim 18(19):4046–4064CrossRefGoogle Scholar
  60. Zhang C, Dong M, Gualdi S, Hendon HH, Maloney ED, Marshall A, Sperber KR, Wang W (2006) Simulations of the Madden–Julian oscillation in four pairs of coupled and uncoupled global models. Clim Dyn 27(6):573–592CrossRefGoogle Scholar
  61. Zhou L, Neale RB, Jochum M, Murtugudde R (2012) Improved Madden–Julian oscillations with improved physics: the impact of modified convection parameterizations. J Clim 25(4):1116–1136CrossRefGoogle Scholar
  62. Zhu H, Hendon H, Jakob C (2009) Convection in a parameterized and superparameterized model and its role in the representation of the MJO. J Atmos Sci 66(9):2796–2811CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Wan-Ling Tseng
    • 1
    • 2
  • Ben-Jei Tsuang
    • 3
  • Noel S. Keenlyside
    • 4
  • Huang-Hsiung Hsu
    • 1
  • Chia-Ying Tu
    • 1
  1. 1.Research Center for Environmental ChangesAcademia SinicaTaipeiTaiwan
  2. 2.GEOMAR Helmholtz Centre for Ocean Research KielKielGermany
  3. 3.Department of Environmental EngineeringNational Chung-Hsing UniversityTaichungTaiwan
  4. 4.Geophysical InstituteUniversity of Bergen and Bjerknes Centre for Climate ResearchBergenNorway

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