Climate Dynamics

, Volume 43, Issue 3–4, pp 911–924 | Cite as

Role of interaction between dynamics, thermodynamics and cloud microphysics on summer monsoon precipitating clouds over the Myanmar Coast and the Western Ghats



Indian summer monsoon circulation can be characterized by mean tropospheric temperature (TT) gradient between ocean and land. Two major heat sources, one near the Myanmar Coast and the other near the Western Ghats play seminal role in defining this TT gradient. While both regions are characterized by very similar orographic features, there are significant differences in frequency of occurrence of precipitating clouds and their characteristics even when the amount of rain in June–July months is almost same in the two regions. Deeper (shallower) clouds appear more frequently over the Myanmar Coast (the Western Ghats). There is a sharp decrease in amount of rainfall from June–July to August–September in both the areas. Rather counter intuitively, during the June–July–August–September season, low and moderate rains contribute more to the total rain in the Myanmar Coast while heavy rains contribute more to the total rain in the Western Ghats. Western Ghats also gets more intense rains but less frequently. With significant differences in moisture availability, updraft, amount and characteristics of cloud condensate in the two regions, this study proposes that the nontrivial differences in features between them could be explained by linkages between cloud microphysics and large scale dynamics. Presence of more cloud liquid water and the role of giant cloud condensation nuclei reveals dominance of warm rain process in the Western Ghats whereas more cloud ice, snow and graupel formation in the Myanmar Coast indicates stronger possibility of cold rain coming from mixed phase processes. Stronger heating caused by mixed phase process in the mid and upper troposphere in the Myanmar Coast and its feedback on buoyancy of air parcel explains the appearance of deeper clouds. Thus, our study highlights importance of mixed phase processes, a major cause of uncertainty in GCMs.


Summer monsoon Microphysics Dynamics Latent heating Aerosol 



Indian Institute of Tropical Meteorology (IITM), Pune, is fully funded by the Ministry of Earth Sciences, Government of India, New Delhi. Authors duly acknowledge NASA for the data sets TRMM, AIRS, MERRA etc. We also acknowledge the MODIS mission scientists and associated NASA personnel for the production of the data used in this research effort. Some data used in this study were produced with the Giovanni online data system, developed and maintained by the NASA GES DISC. Authors duly acknowledge Dr. X. Jiang of JPL, NASA for providing CloudSat data. Authors also sincerely thank Mr. M. Mahakur for providing OLR data from Kalpana Satellite and Mr. V. Sasane for helping in drawing the Schematic Diagram.


  1. Albrecht BA (1989) Aerosols, cloud microphysics and fractional cloudiness. Science 245:1227–1230. doi: 10.1126/science.245.4923.1227 CrossRefGoogle Scholar
  2. Cess RD et al (1990) Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J Geophys Res 95:16601–16615CrossRefGoogle Scholar
  3. Chattopadhyay R, Goswami BN, Sahai AK, Fraedrich K (2009) Role of stratiform rainfall in modifying the northward propagation of monsoon intraseasonal oscillation. J Geophys Res 114:D19114. doi: 10.1029/2009JD011869 CrossRefGoogle Scholar
  4. Cheng C-T, Wang W-C, Chen J-P (2007) A modeling study of aerosol impacts on cloud microphysics and radiative properties. Quart J Roy Meteor Soc 133:283–297CrossRefGoogle Scholar
  5. Cheng C-T, Wang W-C, Chen J-P (2010) Simulation of the effects of increasing cloud condensation nuclei on mixed-phase clouds and precipitation of a front system. Atmos Res 96:461–476CrossRefGoogle Scholar
  6. Gadgil S, Sajani S (1998) Monsoon precipitation in the AMIP runs. Clim Dyn 14:659–689CrossRefGoogle Scholar
  7. Goswami BN (1998) Interannual variation of Indian summer monsoon in a GCM: external conditions versus internal feedbacks. J Clim 11:501–522CrossRefGoogle Scholar
  8. Goswami BN, Ajaya Mohan RS (2001) Intra-seasonal oscillations and inter-annual variability of the Indian summer monsoon. J Clim 14:1180–1198CrossRefGoogle Scholar
  9. Goswami BN, Wu G, Yasunari T (2006) Annual cycle, intraseasonal oscillations and roadblock to seasonal predictability of the Asian summer monsoon. J Clim 19:5078–5099CrossRefGoogle Scholar
  10. Houze RA, Jr (2012) Orographic effects on precipitating clouds. Rev Geophys 50:RG1001. doi: 10.1029/2011RG000365
  11. Kang I-S, Shukla J (2006) Dynamic seasonal prediction and predictability of the monsoon. In: B Wang (ed) The Asian monsoon, Ch. 15. Springer/Praxis Publishing Co., New YorkGoogle Scholar
  12. Kaufman YJ, Tanré D (1998) Algorithm for remote sensing of tropospheric aerosol from MODIS. NASA MODIS Algorithm Theoretical Basis Document, Goddard Space Flight Center 85Google Scholar
  13. Kaufman YJ, Tanre D, Remer LA, Vermote EF, Chu A, Holben BN (1997) Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. J Geophys Res 102:17051–17067CrossRefGoogle Scholar
  14. Khain AP, Phillips V, Benmoshe N, Pokrovsky A (2012) The role of small soluble aerosols in the microphysics of deep maritime clouds. J Atmos Sci 69:2787–2807CrossRefGoogle Scholar
  15. Konwar M, Maheshkumar RS, Kulkarni JR, Padmakumari B, Morwal SB, Deshpande CG, Axisa D, Burger R, Piketh S, Rosenfeld D, Goswami BN (2012) Contrasting polluted and pristine cloud microphysical properties over the Arabian Sea and Bay of Bengal. International conference on OCHAMP-2012, OC-000112Google Scholar
  16. Kummerow C, Hong Y, Olson WS, Yang S, Adler RF, McCollum J, Ferraro R, Petty G, Shin DB, Wilheit TT (2001) The evolution of the Goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors. J Appl Meteor 40:1801–1840CrossRefGoogle Scholar
  17. Meneghini R et al (1998) Estimates of path attenuation for the TRMM radar. Geoscience and remote sensing symposium proceedings. IGARSS’98, IEEE International, 4 IEEEGoogle Scholar
  18. Meneghini R, Jones JA (1993) An approach to estimate the areal rain-rate distribution from spaceborne radar by the use of multiple thresholds. J Appl Meteorol 32:386–398CrossRefGoogle Scholar
  19. Parthasarathy B, Munot AA, Kothawale DR (1994) All India monthly and seasonal rainfall series: 1871–1993. Theor Appl Climtol 49:217–224CrossRefGoogle Scholar
  20. Pokhrel S, Sikka DR (2012) Variability of the TRMM-PR total and convective and stratiform rain fractions over the Indian region during the summer monsoon. Clim Dyn. doi: 10.1007/s00382-012-1502-1 Google Scholar
  21. Pruppacher HR, Klett JD (1997) Microphysics of clouds and precipitation. Kluwer Acad, NorwellGoogle Scholar
  22. Rajeevan M, Srinivasan J (2000) Net cloud radiative forcing at the top of the atmosphere in the Asian monsoon region. J Clim 13(3):650–657CrossRefGoogle Scholar
  23. Rajeevan M, Rohini P, Niranjan Kumar K, Srinivasan J, Unnikrishnan CK (2012) A study of vertical cloud structure of the Indian summer monsoon using CloudSat data. Clim Dyn. doi: 10.1007/s00382-012-1374-4 Google Scholar
  24. Rienecker MM et al (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
  25. Romatschke Ulrike, Houze Robert A Jr (2011) Characteristics of precipitating convective systems in the South Asian monsoon. J Hydrometeorol 12(1):3–26CrossRefGoogle Scholar
  26. Rosenfeld D (1999) TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophy Res Lett 26:3105–3108. doi: 10.1029/1999GL006066 CrossRefGoogle Scholar
  27. Satheesh SK, Krishnamoorthy K (1997) Aerosol characteristics over coastal regions of the Arabian Sea. Tellus 49B:417–428CrossRefGoogle Scholar
  28. Satheesh SK, Krishnamoorthy K, Das I (2001) Aerosol spectral optical depths over the Bay of Bengal, Arabian Sea and Indian Ocean. Curr Sci 81:1617–1625Google Scholar
  29. Slingo A (1987) The development and verification of cloud prediction scheme for the ECMWF model. Q J Roy Meteorol Soc 113:899–927CrossRefGoogle Scholar
  30. Sperber KR, Palmer TN (1996) Interannual tropical variability in general circulation model simulations associated with the atmospheric model intercomparison project. J Clim 9:2727–2750CrossRefGoogle Scholar
  31. Sperber KR, Brankovic C, Deque M, Frederiksen CS, Graham R, Kitoh A, Kobayashi C, Palmer T, Puri K, Tennant W, Volodin E (2001) Dynamical seasonal predictability of the Asian summer monsoon. Mon Weather Rev 129:2226–2248CrossRefGoogle Scholar
  32. Sperber KR, Annamalai H, Kang I-S, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2012) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn. doi: 10.1007/s00382-012-1607-6
  33. Squires P, Twomey S (1961) The relation between cloud drop numbers and the spectrum of cloud nuclei. Phys Precip. Monograph, no. 5, pp 211–219, AGU, Washington, DCGoogle Scholar
  34. Tao WK, Lang S, Olson WS, Meneghini R, Yang S, Simpson J, Kummerow C, Smith E, Halverson J (2001) Retrieved vertical profiles of latent heat release using TRMM rainfall products for february 1998. J Appl Meteorol 40:957–982CrossRefGoogle Scholar
  35. Tao W-K, Smith EA, Adler R, Haddad Z, Hou A, Kakar R, Krishnamurti T, Kummerow C, Lang S, Meneghini R, Olson W, Satoh S, Shige S, Simpson J, Takayabu Y, Tripoli G, Yang S (2006) Retrieval of latent heating from TRMM measurements. Bull Amer Meteor Soc 87:1555–1572CrossRefGoogle Scholar
  36. Tao W-K, Chen J-P, Li Z, Wang C, Zhang C (2012) Impact of aerosols on convective clouds and precipitation. Rev Geophys 50:RG2001. doi: 10.1029/2011RG000369
  37. Twomey S (1977) The influence of pollution on the shortwave albedo of clouds. J Atmos Sci 34:1149–1152CrossRefGoogle Scholar
  38. Twomey S, Piepgrass AM, Wolfe TL (1984) An assessment of the impact of pollution on global cloud albedo. Tellus 36B:356–366CrossRefGoogle Scholar
  39. Walcek CJ, Stockwell WR, Chang JS (1990) Theoretical estimates of the dynamic, radiative, and chemical effects of clouds on tropospheric trace gases. Atmos Res 25:53–69CrossRefGoogle Scholar
  40. Wang B, Ding Q, Fu X, Kang I-S, Jin K, Shukla J, Doblas-Reyes F (2005) Fundamental challenges in simulation and prediction of summer monsoon rainfall. Geophys Res Lett 32:L15711. doi: 10.1029/2005GL02273412 CrossRefGoogle Scholar
  41. Warner J (1968) A reduction in rainfall associated with smoke from sugar-cane fires: an inadvertent weather modification? J Appl Meteor 7:247–251CrossRefGoogle Scholar
  42. Warner J, Twomey S (1967) The production of cloud nuclei by cane fires and the effects on cloud droplet concentration. J Atmos Sci 24:704–706CrossRefGoogle Scholar
  43. Webster PJ, Magaña VO, Palmer TN, Shukla J, Tomas RA, Yanai M, Yasunari T (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophys Res 103:14451–14510CrossRefGoogle Scholar
  44. Xie S-P, Xu H, Saji NH, Wang Y (2006) Role of narrow mountains in large-scale organization of Asian monsoon convection. J Clim 19:3420–3429CrossRefGoogle Scholar
  45. Zhou YP, Tao W-K, Hou AY, Olson WS, Shie C-L, Lau K-M, Chou M-D, Lin X, Grecu M (2007) Use of high-resolution satellite observations to evaluate cloud and precipitation statistics from cloud-resolving model simulations. Part I: South China Sea monsoon experiment. J Atmos Sci 64:4309–4329CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Indian Institute of Tropical MeteorologyPuneIndia

Personalised recommendations