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Climate Dynamics

, Volume 40, Issue 3–4, pp 637–650 | Cite as

A study of vertical cloud structure of the Indian summer monsoon using CloudSat data

  • M. Rajeevan
  • P. Rohini
  • K. Niranjan Kumar
  • J. Srinivasan
  • C. K. Unnikrishnan
Article

Abstract

Precise specification of the vertical distribution of cloud optical properties is important to reduce the uncertainty in quantifying the radiative impacts of clouds. The new global observations of vertical profiles of clouds from the CloudSat mission provide opportunities to describe cloud structures and to improve parameterization of clouds in the weather and climate prediction models. In this study, four years (2007–2010) of observations of vertical structure of clouds from the CloudSat cloud profiling radar have been used to document the mean vertical structure of clouds associated with the Indian summer monsoon (ISM) and its intra-seasonal variability. Active and break monsoon spells associated with the intra-seasonal variability of ISM have been identified by an objective criterion. For the present analysis, we considered CloudSat derived column integrated cloud liquid and ice water, and vertically profiles of cloud liquid and ice water content. Over the South Asian monsoon region, deep convective clouds with large vertical extent (up to 14 km) and large values of cloud water and ice content are observed over the north Bay of Bengal. Deep clouds with large ice water content are also observed over north Arabian Sea and adjoining northwest India, along the west coast of India and the south equatorial Indian Ocean. The active monsoon spells are characterized by enhanced deep convection over the Bay of Bengal, west coast of India and northeast Arabian Sea and suppressed convection over the equatorial Indian Ocean. Over the Bay of Bengal, cloud liquid water content and ice water content is enhanced by ~90 and ~200 % respectively during the active spells. An interesting feature associated with the active spell is the vertical tilting structure of positive CLWC and CIWC anomalies over the Arabian Sea and the Bay of Bengal, which suggests a pre-conditioning process for the northward propagation of the boreal summer intra-seasonal variability. It is also observed that during the break spells, clouds are not completely suppressed over central India. Instead, clouds with smaller vertical extent (3–5 km) are observed due to the presence of a heat low type of circulation. The present results will be useful for validating the vertical structure of clouds in weather and climate prediction models.

Keywords

Clouds Indian monsoon Intra-seasonal Oscillation Active-break cycle 

Notes

Acknowledgments

We are thankful to the NASA CloudSat project and CloudSat data processing centre for providing us the CloudSat data used in this study. We are grateful to Dr. Karen Milberger and Dr. Donald L. Reinke, CloudSat data processing centre, Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University in their kind help in sending us the CloudSat data in tape drives. We also thank the Global Modeling and Assimilation Office (GMAO) and the GES DISC for dissemination of MERRA. We are also thankful to three anonymous reviewers for their constructive comments and suggestions, which helped us to improve the quality of the paper. We also thank Dr. X. Jiang for his useful suggestions on CloudSat data sampling.

References

  1. Austin RT, Stephens GL (2001) Retrieval of stratus cloud microphysical parameters using millimeter-wave radar and visible optical depth in preparation for CloudSat 1. Algoirthm formulation. J Geophys Res 106:28233–28242CrossRefGoogle Scholar
  2. Gadgil S, Sajani S (1998) Monsoon precipitation in the AMIP runs. Clim Dyn 14:659–689CrossRefGoogle Scholar
  3. Gambheer AV, Bhat GS (2000) Life cycle characteristics of deep cloud systems over the Indian region using INSAT-1B pixel data. Mon Weather Rev 128:4071–4083CrossRefGoogle Scholar
  4. Goswami BN (2005) Intraseasonal variability (ISV) of south Asian summer monsoon. In: Lau K, Waliser D (eds) Intraseasonal variability of the atmosphere-ocean climate system. Springer-Praxis, ChichesterGoogle Scholar
  5. Heymsfield AJ, Wang Z, Matrosov S (2005) Improved radar ice water content retrieval algorithms using coincident microphysical and radar measurements. J Appl Meteorol 44:1391–1412CrossRefGoogle Scholar
  6. Hu Y-X, Rodier S, Xu KM, Sun W, Huang J, Lin B, Zhai P, Josset D (2010) Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements. J Geophys Res 115. doi: 10.1029/2009JD012384
  7. Jiang X, Waliser DE, Li J, Woods C (2010) Vertical cloud structures of the boreal summer intraseasonal variability based on CloudSat observations and ERA-interim reanalysis. Clim Dyn. doi: 10.1007/s00382-010-0853-8
  8. Kang IS, Jin K, Wang B, Lau KM, Shukla J, Krishnamurthy V, Schubert SD, Waliser DE, Stern WF, Kitoh A, Meehl GA, Kanamitsu M, Galin VY, Satyan V, Park CK, Liu Y (2002) Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Clim Dyn 19:383–395CrossRefGoogle Scholar
  9. Krishnamurti TN, Kishtawal CM (2000) A pronounced continental-scale diurnal model of the Asian summer monsoon. Mon Weather Rev 128:462–473CrossRefGoogle Scholar
  10. Kubar TL, Hartmann DL (2008) Vertical structure of tropical oceanic convective clouds and its relation to precipitation. Geophys Res Lett 35:L03804. doi: 10.1029/2007GL032811 CrossRefGoogle Scholar
  11. L’Ecuyer TS, Wood NB, Haladay T, Stephens GL, Stackhouse PW (2008) Impact of clouds on atmospheric heating based on the R04 CloudSat fluxes and heating rates data set. J Geophys Res 113. doi: 10.1029/2008JD009951
  12. Mace GG, Marchand R, Zhang Q, Stephens G (2007) Global hydrometeor occurrence as observed by CloudSat: initial observations from summer 2006. Geophys Res Lett 34:L09808. doi: 10.1029/2006GL029017 CrossRefGoogle Scholar
  13. Manoj MG, Devara PCS, Safai PD, Goswami BN (2010) Absorbing aerosols facilitate transition of Indian monsoon breaks to active spells. Clim Dyn. doi: 10.1007/s00382-010-0971-3
  14. Mitrescu C, Miller S, Hawkins J, L’Ecuyer T, Turk J, Partain P, Stephens GL (2008) Near-real-time applications of CloudSat data. J Appl Met Clim 47:1982–1994CrossRefGoogle Scholar
  15. Nair AKM, Rajeev K, Sijikumar K, Meenu S (2011) Characteristics of a persistent pool of inhibited cloudiness and its genesis over the Bay of Bengal associated with the Asian summer monsoon. Ann Geophys 29:1247–1252CrossRefGoogle Scholar
  16. Raghavan K (1973) Break monsoon over India. Mon Weather Rev 101:33–43CrossRefGoogle Scholar
  17. Rajeevan M, Nanjundiah R (2010) Coupled model simulations of twentieth century climate of the Indian summer monsoon. In: Current trends in science, Indian Academy of Sciences, Platinum Jubilee Publication, Bangalore, pp 537–567 (available at http://www.ias.ac.in)
  18. Rajeevan M, Srinivasan J (2000) Net Cloud Radiative forcing at the top of the atmosphere in the Asian monsoon region. J Clim 13:650–657CrossRefGoogle Scholar
  19. Rajeevan M, Bhate J, Kale JD, Lal B (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Curr Sci 91:296–306Google Scholar
  20. Rajeevan M, Gadgil S, Bhate J (2010) Active and break spells of the Indian summer monsoon. J Earth Syst Sci 3:229–247CrossRefGoogle Scholar
  21. Ramamurthy K (1969) Monsoon of India: some aspects of the “break” in the Indian southwest monsoon during July and August. Forecasting manual, 1–57 No IV 18.3, India Met Department, Pune, IndiaGoogle Scholar
  22. Ravi Kiran V, Rajeevan M, Vijaya Bhaskara Rao S, Prabhakara Rao N (2009) Analysis of variations of cloud and aerosol properties associated with active and break spells of Indian summer monsoon using MODIS data. Geophys Res Lett 36:L09706. doi: 10.1029/2008GL037135 CrossRefGoogle Scholar
  23. 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
  24. Sikka DR, Gadgil S (1980) On the maximum Cloud Zone and the ITCs over Indian longitudes during the southwest monsoon. Mon Weather Rev 108:1840–1853CrossRefGoogle Scholar
  25. Stein THM, Delanoë J, Hogan RJ (2011) A comparison among four different retrieval methods for ice-cloud properties using data from CloudSat, CALIPSO, and MODIS. J Appl Meteor Climatol 50:1952–1969. doi: 10.1175/2011JAMC2646.1 Google Scholar
  26. Stephens GL et al (2002) The CloudSat mission and the A-Train: a new dimension of spacebased observations of clouds and precipitation. Bull Am Meteorol Soc 83:1771–1790CrossRefGoogle Scholar
  27. Su H, Jiang JH, Teixeira J, Gettelman A, Huang X, Stephens G, Vane D, Perun VS (2011) Comparison of regime-sorted tropical cloud profiles observed by CloudSat with GEOS5 analyses and two general circulation model simulations. J Geophys Res 116:D09104. doi: 10.1029/2010JD014971
  28. Waliser DE, Lau KM, Stern W (2003) Potential predictability of the MJO. Bull Am Meteorol Soc. doi: 10.1175/BAMS-84-1-33
  29. Wang B, Kang IS, Lee JY (2004) Ensemble simulation of Asian-Australian monsoon variability by 11 AGCMs. J Clim 17:699–710CrossRefGoogle Scholar
  30. Wild M (2008) Shortwave and longwave surface-radiation budgets in GCMs: a review based on the IPCC-AR4/CMIP3 models. Tellus 60:932–945CrossRefGoogle Scholar
  31. Williams M, Houze RA Jr (1987) Satellite-observed characteristics of winter monsoon cloud clusters. Mon Weather Rev 115:505–519CrossRefGoogle Scholar
  32. Wonsick MM, Pinker RT, Govaerts Y (2009) Cloud variability over the Indian monsoon region as observed from satellites. J Appl Met Climatol 48:1803–1821CrossRefGoogle Scholar
  33. Yuan JRA, Jr Houze, Heymsfield AJ (2011) Vertical Structures of anvil clouds of tropical mesoscale convective systems observed by CloudSat. J Atmos Sci 68:1653–1674CrossRefGoogle Scholar
  34. Zhang Y, Klein S, Mace GG, Boyle J (2007) Cluster analysis of tropical clouds using CloudSat data. Geophys Res Lett 34:L12813. doi: 10.1029/2007GL029336 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • M. Rajeevan
    • 1
    • 3
  • P. Rohini
    • 2
  • K. Niranjan Kumar
    • 1
  • J. Srinivasan
    • 2
  • C. K. Unnikrishnan
    • 1
  1. 1.National Atmospheric Research LaboratoryGadankiIndia
  2. 2.Centre for Atmospheric and Oceanic SciencesIndian Institute of ScienceBangaloreIndia
  3. 3.Ministry of Earth Sciences (MoES)New DelhiIndia

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