The Effect of Environmental Conditions on Tropical Deep Convective Systems Observed from the TRMM Satellite

Bing Lin Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Bruce A. Wielicki Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Patrick Minnis Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Lin Chambers Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Kuan-Man Xu Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Yongxiang Hu Sciences Directorate, NASA Langley Research Center, Hampton, Virginia

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Alice Fan SAIC, Hampton, Virginia

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Abstract

This study uses measurements of radiation and cloud properties taken between January and August 1998 by three Tropical Rainfall Measuring Mission (TRMM) instruments, the Clouds and the Earth’s Radiant Energy System (CERES) scanner, the TRMM Microwave Imager (TMI), and the Visible and Infrared Scanner (VIRS), to evaluate the variations of tropical deep convective systems (DCSs) with sea surface temperature and precipitation. The authors find that DCS precipitation efficiency increases with SST at a rate of ∼2% K−1. Despite increasing rainfall efficiency, the cloud areal coverage rises with SST at a rate of about 7% K−1 in the warm tropical seas. There, the boundary layer moisture supply for deep convection and the moisture transported to the upper troposphere for cirrus anvil cloud formation increase by ∼6.3% and ∼4.0% K−1, respectively. The changes in cloud formation efficiency, along with the increased transport of moisture available for cloud formation, likely contribute to the large rate of increasing DCS areal coverage. Although no direct observations are available, the increase of cloud formation efficiency with rising SST is deduced indirectly from measurements of changes in the ratio of DCS ice water path and boundary layer water vapor amount with SST. Besides the cloud areal coverage, DCS cluster effective sizes also increase with precipitation. Furthermore, other cloud properties, such as cloud total water and ice water paths, increase with SST. These changes in DCS properties will produce a negative radiative feedback for the earth’s climate system due to strong reflection of shortwave radiation by the DCS. These results significantly differ from some previously hypothesized dehydration scenarios for warmer climates, partially support the thermostat hypothesis but indicate a smaller magnitude of the negative feedback, and have great potential in testing current cloud-system-resolving models and convective parameterizations of general circulation models.

Corresponding author address: Dr. Bing Lin, MS 420, NASA Langley Research Center, Hampton, VA 23681-2199. Email: bing.lin@nasa.gov

Abstract

This study uses measurements of radiation and cloud properties taken between January and August 1998 by three Tropical Rainfall Measuring Mission (TRMM) instruments, the Clouds and the Earth’s Radiant Energy System (CERES) scanner, the TRMM Microwave Imager (TMI), and the Visible and Infrared Scanner (VIRS), to evaluate the variations of tropical deep convective systems (DCSs) with sea surface temperature and precipitation. The authors find that DCS precipitation efficiency increases with SST at a rate of ∼2% K−1. Despite increasing rainfall efficiency, the cloud areal coverage rises with SST at a rate of about 7% K−1 in the warm tropical seas. There, the boundary layer moisture supply for deep convection and the moisture transported to the upper troposphere for cirrus anvil cloud formation increase by ∼6.3% and ∼4.0% K−1, respectively. The changes in cloud formation efficiency, along with the increased transport of moisture available for cloud formation, likely contribute to the large rate of increasing DCS areal coverage. Although no direct observations are available, the increase of cloud formation efficiency with rising SST is deduced indirectly from measurements of changes in the ratio of DCS ice water path and boundary layer water vapor amount with SST. Besides the cloud areal coverage, DCS cluster effective sizes also increase with precipitation. Furthermore, other cloud properties, such as cloud total water and ice water paths, increase with SST. These changes in DCS properties will produce a negative radiative feedback for the earth’s climate system due to strong reflection of shortwave radiation by the DCS. These results significantly differ from some previously hypothesized dehydration scenarios for warmer climates, partially support the thermostat hypothesis but indicate a smaller magnitude of the negative feedback, and have great potential in testing current cloud-system-resolving models and convective parameterizations of general circulation models.

Corresponding author address: Dr. Bing Lin, MS 420, NASA Langley Research Center, Hampton, VA 23681-2199. Email: bing.lin@nasa.gov

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  • Albritton, D., and Coauthors, 2001: Summary for policymakers. Climate Change 2001: The Scientific Basis, J. T. Houghton et al., Eds., Cambridge University Press, 20 pp.

    • Search Google Scholar
    • Export Citation
  • Braham Jr., R. R., 1952: The water and energy budgets of the thunderstorm and their relation to thunderstorm development. J. Meteor., 9 , 227242.

    • Search Google Scholar
    • Export Citation
  • Breon, F-M., D. Tanre, and S. Generoso, 2002: Aerosol effect on cloud droplet size monitored from satellite. Science, 295 , 834838.

  • Chambers, L., B. Lin, and D. Young, 2002: New CERES data examined for evidence of tropical iris feedback. J. Climate, 15 , 37193726.

  • Chong, M., and D. Hauser, 1989: A tropical squall line observed during the COPT 81 experiment in West Africa. Part II: Water budget. Mon. Wea. Rev., 117 , 728744.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., and A. Wolf, 2000: Climatic implications of the observed temperature dependence of the liquid water path of low clouds in the southern Great Plains. J. Climate, 13 , 34653486.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., and W. Kovari, 2002: Climatic properties of tropical precipitating convection under varying environmental conditions. J. Climate, 15 , 25972615.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., W. Kovari, M-S. Yao, and J. Jonas, 2005: Cumulus microphysics and climate sensitivity. J. Climate, 18 , 23762387.

  • Fairall, C., E. F. Bradley, D. P. Rogers, J. B. Edson, and G. S. Young, 1996: Bulk parameterization of air-sea fluxes for TOGA COARE. J. Geophys. Res., 101 , 37473764.

    • Search Google Scholar
    • Export Citation
  • Fankhauser, J. C., 1988: Estimates of thunderstorm precipitation efficiency from field measurements in CCOPE. Mon. Wea. Rev., 116 , 663684.

    • Search Google Scholar
    • Export Citation
  • Ferrier, B. S., J. Simpson, and W-K. Tao, 1996: Factors responsible for different precipitation efficiencies between midlatitude and tropical squall simulations. Mon. Wea. Rev., 124 , 21002125.

    • Search Google Scholar
    • Export Citation
  • Fu, R., A. DelGenio, B. Rossow, and W. T. Liu, 1992: Cirrus-cloud thermostat for tropical sea surface temperatures tested using satellite data. Nature, 358 , 394.

    • Search Google Scholar
    • Export Citation
  • Gamache, J. F., and R. A. Houze Jr., 1983: Water budget of a mesoscale convective system in the tropics. J. Atmos. Sci., 40 , 18351850.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and M. L. Michelsen, 1993: Large-scale effects on the regulation of tropical sea surface temperature. J. Climate, 6 , 20492062.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and M. L. Michelsen, 2002: No evidence for iris. Bull. Amer. Meteor. Soc., 83 , 249254.

  • Ho, S-P., B. Lin, P. Minnis, and T-F. Fan, 2003: Estimates of cloud vertical structure and water amount over tropical oceans using VIRS and TMI data. J. Geophys. Res., 108 .4419, doi:10.1029/2002JD003298.

    • Search Google Scholar
    • Export Citation
  • Houze, R., 1993: Cloud Dynamics. Vol. 53, International Geophysics Series, Academic Press, 573 pp.

  • Kummerow, C., and Coauthors, 2001: The evolution of the Goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors. J. Appl. Meteor., 40 , 18011820.

    • Search Google Scholar
    • Export Citation
  • Lau, K. M., and H. T. Wu, 2003: Warm rain processes over tropical oceans and climate implications. Geophys. Res. Lett., 30 .2290, doi:10.1029/2003GL018567.

    • Search Google Scholar
    • Export Citation
  • Lin, B., and W. B. Rossow, 1996: Seasonal variation of liquid and ice water path in nonprecipitating clouds over oceans. J. Climate, 9 , 28902902.

    • Search Google Scholar
    • Export Citation
  • Lin, B., and W. B. Rossow, 1997: Precipitation water path and rainfall rate estimates over oceans using Special Sensor Microwave Imager and International Satellite Cloud Climatology Project data. J. Geophys. Res., 102 , 93599374.

    • Search Google Scholar
    • Export Citation
  • Lin, B., B. Wielicki, P. Minnis, and W. B. Rossow, 1998a: Estimation of water cloud properties from satellite microwave, infrared, and visible measurements in oceanic environments. I: Microwave brightness temperature simulations. J. Geophys. Res., 103 , 38733886.

    • Search Google Scholar
    • Export Citation
  • Lin, B., P. Minnis, B. Wielicki, D. R. Doelling, R. Palikonda, D. F. Young, and T. Uttal, 1998b: Estimation of water cloud properties from satellite microwave, infrared, and visible measurements in oceanic environments. II: Results. J. Geophys. Res., 103 , 38873905.

    • Search Google Scholar
    • Export Citation
  • Lin, B., P. Minnis, A. Fan, J. A. Curry, and H. Gerber, 2001: Comparison of cloud liquid water paths derived from in situ and microwave radiometer data taken during the SHEBA/FIREACE. Geophys. Res. Lett., 28 , 975978.

    • Search Google Scholar
    • Export Citation
  • Lin, B., B. Wielicki, L. Chambers, Y. Hu, and K-M. Xu, 2002: The iris hypothesis: A negative or positive cloud feedback? J. Climate, 15 , 37.

    • Search Google Scholar
    • Export Citation
  • Lin, B., P. Minnis, and A. Fan, 2003: Cloud liquid water amount variations with temperature observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. J. Geophys. Res., 108 .4427, doi:10.1029/2002JD002851.

    • Search Google Scholar
    • Export Citation
  • Lindzen, R. S., M-D. Chou, and A. Hou, 2001: Does the Earth have an adaptive infrared iris? Bull. Amer. Meteor. Soc., 82 , 417432.

  • Lipps, F. B., and R. S. Hemler, 1986: Numerical simulation of deep tropical convection associated with large-scale convergence. J. Atmos. Sci., 43 , 17961816.

    • Search Google Scholar
    • Export Citation
  • Loeb, N., and Coauthors, 2003: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Tropical Rainfall Measuring Mission satellite. Part I: Methodology. J. Appl. Meteor., 42 , 240265.

    • Search Google Scholar
    • Export Citation
  • Lucas, C., E. J. Zipser, and B. S. Ferrier, 2000: Sensitivity of tropical west Pacific oceanic squall lines to temperature, wind, and moisture profiles. J. Atmos. Sci., 57 , 23512373.

    • Search Google Scholar
    • Export Citation
  • Machado, L. A. T., W. B. Rossow, R. L. Guedes, and A. W. Walker, 1998: Life cycle variations of mesoscale convective systems over the Americas. Mon. Wea. Rev., 126 , 16301654.

    • Search Google Scholar
    • Export Citation
  • Mapes, B., 1993: Gregarious tropical convection. J. Atmos. Sci., 50 , 20262037.

  • Minnis, P., and Coauthors, 1995: Cloud optical property retrieval (subsystem 4.3). Clouds and the Earth’s Radiant Energy System (CERES) Algorithm Theoretical Basis Document, Volume III: Cloud Analyses and Radiance Inversions (Subsystem 4), CERES Science Team, Eds., NASA Rep. 1376, Vol. 3, 135–176.

  • Minnis, P., and Coauthors, 1997: Cloud optical property retrieval (subsystem 4.3). Clouds and the Earth’s Radiant Energy System (CERES) Algorithm Theoretical Basis Document, Release 2.2, Update to Minnis et al. (1995). [Available online at http://asd-www.larc.nasa.gov/ATBD/ATBD.html.].

  • Minnis, P., D. F. Young, B. A. Wielicki, P. W. Heck, X. Dong, L. L. Stowe, and R. Welch, 1999: CERES cloud properties derived from multispectral VIRS data. Proceedings of the EOS/SPIE Symposium on Remote Sensing, Vol. 3867, EOS/SPIE, 91–102.

  • Minnis, P., D. F. Young, B. A. Wielicki, S. Sun-Mack, Q. Z. Trepte, Y. Chen, P. Heck, and X. Dong, 2002: A global cloud database from VIRS and MODIS for CERES. Proceedings of the SPIE 3rd International Asia-Pacific Environmental Remote Sensing Symposium 2002: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, Vol. 4891, SPIE, 115–126.

  • Oury, S., X. Dou, and J. Testud, 2000: Estimate of precipitation from the dual-beam airborne radars in TOGA COARE. Part II: Precipitation efficiency in the 9 February 1993 MCS. J. Appl. Meteor., 39 , 23712384.

    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351 , 2732.

    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., P. J. Crutzen, J. T. Kiehl, and D. Rosenfeld, 2001: Aerosols, climate and the hydrological cycle. Science, 294 , 21192124.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analysis. J. Climate, 7 , 929948.

  • Schulz, J., P. Schluessel, and H. Grassl, 1993: Water vapour in the atmospheric boundary layer over oceans from SSM/I measurements. Int. J. Remote Sens., 14 , 27732789.

    • Search Google Scholar
    • Export Citation
  • Schulz, J., J. Meywerk, S. Ewald, and P. Schlussel, 1997: Evaluation of satellite-derived latent heat fluxes. J. Climate, 10 , 27822795.

    • Search Google Scholar
    • Export Citation
  • Shepherd, J. M., B. S. Ferrier, and P. S. Ray, 2001: Rainfall morphology in Florida convergence zones: A numerical study. Mon. Wea. Rev., 129 , 177197.

    • Search Google Scholar
    • Export Citation
  • Stephens, G., 2005: Cloud feedbacks in the climate system: A critical review. J. Climate, 18 , 237273.

  • Sud, Y. C., and G. K. Walker, 1999: Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS). Part I: Design and evaluation with GATE phase III data. J. Atmos. Sci., 56 , 31963220.

    • Search Google Scholar
    • Export Citation
  • Tao, W-K., D. Johnson, C-L. Shie, and J. Simpson, 2004: The atmospheric energy budget and large-scale precipitation efficiency of convective systems during TOGA COARE, GATE, SCSMEX, and ARM: Cloud-resolving model simulations. J. Atmos. Sci., 61 , 24052423.

    • Search Google Scholar
    • Export Citation
  • Tompkins, A. M., 2001: On the relationship between tropical convection and sea surface temperature. J. Climate, 14 , 633637.

  • Tselioudis, G., D. Rind, and W. Rossow, 1992: Global patterns of cloud optical thickness variation with temperature. J. Climate, 5 , 16421657.

    • Search Google Scholar
    • Export Citation
  • Wallace, J., 1992: Effect of deep convection on the regulation of tropical sea surface temperature. Nature, 357 , 230231.

  • Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110 , 504520.

    • Search Google Scholar
    • Export Citation
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