Role of Convective Entrainment in Spatial Distributions of and Temporal Variations in Precipitation over Tropical Oceans

Nagio Hirota National Institute of Polar Research, and Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan

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Yukari N. Takayabu Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan

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Masahiro Watanabe Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan

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Masahide Kimoto Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan

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Minoru Chikira Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

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Abstract

The authors demonstrate that an appropriate treatment of convective entrainment is essential for determining spatial distributions of and temporal variations in precipitation. Four numerical experiments are performed using atmospheric models with different entrainment characteristics: a control experiment (Ctl), a no-entrainment experiment (NoEnt), an original Arakawa–Schubert experiment (AS), and an AS experiment with a simple empirical suppression of convection depending on cloud-layer humidity (ASRH). The fractional entrainment rates of AS and ASRH are constant for each cloud type and are very small in the lower troposphere compared with those in the Ctl, in which half of the buoyancy-generated energy is consumed by entrainment. Spatial and temporal variations in the observed precipitation are satisfactorily reproduced in the Ctl, but their amplitudes are underestimated with a so-called double intertropical convergence zone bias in the NoEnt and AS. The spatial variation is larger in the Ctl because convection is more active over humid ascending regions and more suppressed over dry subsidence regions. Feedback processes involving convection, the large-scale circulation, free tropospheric moistening by congestus, and radiation enhance the variations. The temporal evolution of precipitation events is also more realistic in the Ctl, because congestus moistens the midtroposphere, and large precipitation events occur once sufficient moisture is available. The large entrainment in the lower troposphere, increasing free tropospheric moistening by congestus and enhancing the coupling of convection to free tropospheric humidity, is suggested to be important for the realistic spatial and temporal variations.

Corresponding author address: Nagio Hirota, National Institute of Polar Research, 10-3, Midoricho, Tachikawa, Tokyo 190-8518, Japan. E-mail: nagio@aori.u-tokyo.ac.jp

Abstract

The authors demonstrate that an appropriate treatment of convective entrainment is essential for determining spatial distributions of and temporal variations in precipitation. Four numerical experiments are performed using atmospheric models with different entrainment characteristics: a control experiment (Ctl), a no-entrainment experiment (NoEnt), an original Arakawa–Schubert experiment (AS), and an AS experiment with a simple empirical suppression of convection depending on cloud-layer humidity (ASRH). The fractional entrainment rates of AS and ASRH are constant for each cloud type and are very small in the lower troposphere compared with those in the Ctl, in which half of the buoyancy-generated energy is consumed by entrainment. Spatial and temporal variations in the observed precipitation are satisfactorily reproduced in the Ctl, but their amplitudes are underestimated with a so-called double intertropical convergence zone bias in the NoEnt and AS. The spatial variation is larger in the Ctl because convection is more active over humid ascending regions and more suppressed over dry subsidence regions. Feedback processes involving convection, the large-scale circulation, free tropospheric moistening by congestus, and radiation enhance the variations. The temporal evolution of precipitation events is also more realistic in the Ctl, because congestus moistens the midtroposphere, and large precipitation events occur once sufficient moisture is available. The large entrainment in the lower troposphere, increasing free tropospheric moistening by congestus and enhancing the coupling of convection to free tropospheric humidity, is suggested to be important for the realistic spatial and temporal variations.

Corresponding author address: Nagio Hirota, National Institute of Polar Research, 10-3, Midoricho, Tachikawa, Tokyo 190-8518, Japan. E-mail: nagio@aori.u-tokyo.ac.jp
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  • Arakawa, A., 2004: The cumulus parameterization problem: Past, present, and future. J. Climate, 17, 24932525, doi:10.1175/1520-0442(2004)017<2493:RATCPP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Arakawa, A., and W. H. Schubert, 1974: Interaction of cumulus cloud ensemble with the large-scale environment, Part I. J. Atmos. Sci., 31, 674701, doi:10.1175/1520-0469(1974)031<0674:IOACCE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bechtold, P., M. Köhler, T. Jung, F. Doblas-Reyes, M. Leutbecher, M. J. Rodwell, F. Vitart, and G. Balsamo, 2008: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Quart. J. Roy. Meteor. Soc., 134, 13371351, doi:10.1002/qj.289.

    • Search Google Scholar
    • Export Citation
  • Bechtold, P., N. Semane, P. Lopez, J.-P. Chaboureau, A. Beljaars, and N. Bormann, 2014: Representing equilibrium and nonequilibrium convection in large-scale models. J. Atmos. Sci., 71, 734753, doi:10.1175/JAS-D-13-0163.1.

    • Search Google Scholar
    • Export Citation
  • Bellucci, A., S. Gualdi, and A. Navarra, 2010: The double-ITCZ syndrome in coupled general circulation models: The role of large-scale vertical circulation regimes. J. Climate, 23, 11271145, doi:10.1175/2009JCLI3002.1.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., 2010: A cumulus parameterization with state-dependent entrainment rate. Part II: Impact on climatology in a general circulation model. J. Atmos. Sci., 67, 21942211, doi:10.1175/2010JAS3317.1.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., 2014: Eastward-propagating intraseasonal oscillation represented by Chikira–Sugiyama cumulus parameterization. Part II: Understanding moisture variation under weak temperature gradient balance. J. Atmos. Sci., 71, 615639, doi:10.1175/JAS-D-13-038.1.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., and M. Sugiyama, 2010: A cumulus parameterization with state-dependent entrainment rate. Part I: Description and sensitivity to temperature and humidity profiles. J. Atmos. Sci., 67, 21712193, doi:10.1175/2010JAS3316.1.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., and M. Sugiyama, 2013: Eastward-propagating intraseasonal oscillation represented by Chikira–Sugiyama cumulus parameterization. Part I: Comparison with observation and reanalysis. J. Atmos. Sci., 70, 39203939, doi:10.1175/JAS-D-13-034.1.

    • Search Google Scholar
    • Export Citation
  • Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 46054630, doi:10.1175/JCLI3884.1.

  • Del Genio, A. D., and J. Wu, 2010: The role of entrainment in the diurnal cycle of continental convection. J. Climate, 23, 27222738, doi:10.1175/2009JCLI3340.1.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., Y. Chen, D. Kim, and M.-S. Yao, 2012: The MJO transition from shallow to deep convection in CloudSat/CALIPSO data and GISS GCM simulations. J. Climate, 25, 37553770, doi:10.1175/JCLI-D-11-00384.1.

    • Search Google Scholar
    • Export Citation
  • Derbyshire, S., I. Beau, P. Bechtold, J.-Y. Grandpeix, J.-M. Piriou, J.-L. Redelsperger, and P. Soares, 2004: Sensitivity of moist convection to environmental humidity. Quart. J. Roy. Meteor. Soc., 130, 30553079, doi:10.1256/qj.03.130.

    • Search Google Scholar
    • Export Citation
  • de Rooy, W. C., and Coauthors, 2013: Entrainment and detrainment in cumulus convection: An overview. Quart. J. Roy. Meteor. Soc., 139, 119, doi:10.1002/qj.1959.

    • Search Google Scholar
    • Export Citation
  • de Szoeke, S. P., and S.-P. Xie, 2008: The tropical eastern Pacific seasonal cycle: Assessment of errors and mechanisms in IPCC AR4 coupled ocean–atmosphere general circulation models. J. Climate, 21, 25732590, doi:10.1175/2007JCLI1975.1.

    • Search Google Scholar
    • Export Citation
  • Emori, S., T. Nozawa, A. Numaguti, and I. Uno, 2001: Importance of cumulus parameterization for precipitation simulation over East Asia in June. J. Meteor. Soc. Japan, 79, 939947, doi:10.2151/jmsj.79.939.

    • Search Google Scholar
    • Export Citation
  • Esbensen, S., 1978: Bulk thermodynamic effects and properties of small tropical cumuli. J. Atmos. Sci., 35, 826837, doi:10.1175/1520-0469(1978)035<0826:BTEAPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Grant, A., and A. Brown, 1999: A similarity hypothesis for shallow-cumulus transports. Quart. J. Roy. Meteor. Soc., 125, 19131936, doi:10.1002/qj.49712555802.

    • Search Google Scholar
    • Export Citation
  • Gregory, D., 2001: Estimation of entrainment rate in simple models of convective clouds. Quart. J. Roy. Meteor. Soc., 127, 5372, doi:10.1002/qj.49712757104.

    • Search Google Scholar
    • Export Citation
  • Gregory, D., and P. R. Rowntree, 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 14831506, doi:10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hirons, L., P. Inness, F. Vitart, and P. Bechtold, 2013: Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part II: The application of process-based diagnostics. Quart. J. Roy. Meteor. Soc., 139, 14271444, doi:10.1002/qj.2059.

    • Search Google Scholar
    • Export Citation
  • Hirota, N., and M. Takahashi, 2012: A tripolar pattern as an internal mode of the East Asian summer monsoon. Climate Dyn., 39, 22192238, doi:10.1007/s00382-012-1416-y.

    • Search Google Scholar
    • Export Citation
  • Hirota, N., and Y. N. Takayabu, 2012: Inter-model differences of future precipitation changes in CMIP3 and MIROC5 climate models. J. Meteor. Soc. Japan, 90A, 307316, doi:10.2151/jmsj.2012-A16.

    • Search Google Scholar
    • Export Citation
  • Hirota, N., and Y. N. Takayabu, 2013: Reproducibility of precipitation distribution over the tropical oceans in CMIP5 multi-climate models compared to CMIP3. Climate Dyn.,41, 2909–2920, doi:10.1007/s00382-013-1839-0.

  • Hirota, N., Y. N. Takayabu, M. Watanabe, and M. Kimoto, 2011: Precipitation reproducibility over tropical oceans and its relationship to the double ITCZ problem in CMIP3 and MIROC5 climate models. J. Climate, 24, 48594873, doi:10.1175/2011JCLI4156.1.

    • Search Google Scholar
    • Export Citation
  • Holloway, C. E., and J. D. Neelin, 2009: Moisture vertical structure, column water vapor, and tropical deep convection. J. Atmos. Sci., 66, 16651683, doi:10.1175/2008JAS2806.1.

    • Search Google Scholar
    • Export Citation
  • Jensen, M. P., and A. D. Del Genio, 2006: Factors limiting convective cloud-top height at the ARM Nauru Island climate research facility. J. Climate, 19, 21052117, doi:10.1175/JCLI3722.1.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schubert, 1999: Trimodal characteristics of tropical convection. J. Climate, 12, 23972418, doi:10.1175/1520-0442(1999)012<2397:TCOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M., and D. Randall, 2006: High-resolution simulation of shallow-to-deep convection transition over land. J. Atmos. Sci., 63, 34213436, doi:10.1175/JAS3810.1.

    • Search Google Scholar
    • Export Citation
  • Kim, D., A. H. Sobel, E. D. Maloney, D. M. Frierson, and I.-S. Kang, 2011: A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J. Climate, 24, 55065520, doi:10.1175/2011JCLI4177.1.

    • Search Google Scholar
    • Export Citation
  • Kim, D., A. H. Sobel, A. D. Del Genio, Y. Chen, S. J. Camargo, M.-S. Yao, M. Kelley, and L. Nazarenko, 2012: The tropical subseasonal variability simulated in the NASA GISS general circulation model. J. Climate, 25, 46414659, doi:10.1175/JCLI-D-11-00447.1.

    • Search Google Scholar
    • Export Citation
  • Kuang, Z., and C. S. Bretherton, 2006: A mass flux scheme view of a high-resolution simulation of a transition from shallow to deep cumulus convection. J. Atmos. Sci., 63, 18951909, doi:10.1175/JAS3723.1.

    • Search Google Scholar
    • Export Citation
  • Lin, C., 1999: Some bulk properties of cumulus ensembles simulated by a cloud-resolving model. Part II: Entrainment profiles. J. Atmos. Sci., 56, 37363748, doi:10.1175/1520-0469(1999)056<3736:SBPOCE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., and Coauthors, 2006: Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals. J. Climate, 19, 26652690, doi:10.1175/JCLI3735.1.

    • Search Google Scholar
    • Export Citation
  • Lin, Y., and Coauthors, 2012: TWP-ICE global atmospheric model intercomparison: Convection responsiveness and resolution impact. J. Geophys. Res.,117, D09111, doi:10.1029/2011JD017018.

  • Maloney, E. D., and D. L. Hartmann, 2001: The sensitivity of intraseasonal variability in the NCAR CCM3 to changes in convective parameterization. J. Climate, 14, 20152034, doi:10.1175/1520-0442(2001)014<2015:TSOIVI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Manabe, S., J. Smagorinsky, and R. F. Strickler, 1965: Simulated climatology of a general circulation model with a hydrologic cycle. Mon. Wea. Rev., 93, 769798, doi:10.1175/1520-0493(1965)093<0769:SCOAGC>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mechoso, C. R., and Coauthors, 1995: The seasonal cycle over the tropical Pacific in coupled ocean–atmosphere general circulation models. Mon. Wea. Rev., 123, 28252838, doi:10.1175/1520-0493(1995)123<2825:TSCOTT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., C. Covey, B. McAvaney, M. Latif, and R. J. Stouffer, 2005: Overview of the Coupled Model Intercomparison Project. Bull. Amer. Meteor. Soc., 86, 8993, doi:10.1175/BAMS-86-1-89.

    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys., 20, 851875, doi:10.1029/RG020i004p00851.

    • Search Google Scholar
    • Export Citation
  • Miura, H., T. Maeda, and M. Kimoto, 2012: A comparison of the Madden–Julian oscillation simulated by different versions of the MIROC climate model. SOLA, 8, 165169, doi:10.2151/sola.2012-040.

    • Search Google Scholar
    • Export Citation
  • Möbis, B., and B. Stevens, 2012: Factors controlling the position of the intertropical convergence zone on an aquaplanet. J. Adv. Model. Earth Syst.,4, M00A04, doi:10.1029/2012MS000199.

  • Nakanishi, M., and H. Niino, 2004: An improved Mellor–Yamada level-3 model with condensation physics: Its design and verification. Bound.-Layer Meteor., 112, 131, doi:10.1023/B:BOUN.0000020164.04146.98.

    • Search Google Scholar
    • Export Citation
  • Oueslati, B., and G. Bellon, 2013: Convective entrainment and large-scale organization of tropical precipitation: Sensitivity of the CNRM-CM5 hierarchy of models. J. Climate, 26, 29312946, doi:10.1175/JCLI-D-12-00314.1.

    • Search Google Scholar
    • Export Citation
  • Pan, D.-M., and D. D. A. Randall, 1998: A cumulus parameterization with a prognostic closure. Quart. J. Roy. Meteor. Soc., 124, 949981, doi:10.1002/qj.49712454714.

    • Search Google Scholar
    • Export Citation
  • Philander, S. G. H., D. Gu, D. Halpern, G. Lambert, N.-C. Lau, T. Li, and R. C. Pacanowski, 1996: Why the ITCZ is mostly north of the equator. J. Climate, 9, 29582972, doi:10.1175/1520-0442(1996)009<2958:WTIIMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Redelsperger, J., D. Parsons, and F. Guichard, 2002: Recovery processes and factors limiting cloud-top height following the arrival of a dry intrusion observed during TOGA COARE. J. Atmos. Sci., 59, 24382457, doi:10.1175/1520-0469(2002)059<2438:RPAFLC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sekiguchi, M., and T. Nakajima, 2008: A k-distribution-based radiation code and its computational optimization for an atmospheric general circulation model. J. Quant. Spectrosc. Radiat. Transfer, 109, 27792793, doi:10.1016/j.jqsrt.2008.07.013.

    • Search Google Scholar
    • Export Citation
  • Siebesma, A., and J. Cuijpers, 1995: Evaluation of parametric assumptions for shallow cumulus convection. J. Atmos. Sci., 52, 650666, doi:10.1175/1520-0469(1995)052<0650:EOPAFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Simpson, J., and V. Wiggert, 1969: Models of precipitating cumulus towers. Mon. Wea. Rev., 97, 471489, doi:10.1175/1520-0493(1969)097<0471:MOPCT>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Song, X., and G. Zhang, 2009: Convection parameterization, tropical pacific double ITCZ, and upper-ocean biases in the NCAR CCSM3. Part I: Climatology and atmospheric feedback. J. Climate, 22, 42994315, doi:10.1175/2009JCLI2642.1.

    • Search Google Scholar
    • Export Citation
  • Takata, K., S. Emori, and T. Watanabe, 2003: Development of the minimal advanced treatments of surface interaction and runoff. Global Planet. Change, 38, 209222, doi:10.1016/S0921-8181(03)00030-4.

    • Search Google Scholar
    • Export Citation
  • Takayabu, Y. N., S. Shige, W.-K. Tao, and N. Hirota, 2010: Shallow and deep latent heating modes over tropical oceans observed with TRMM PR spectral latent heating data. J. Climate, 23, 20302046, doi:10.1175/2009JCLI3110.1.

    • Search Google Scholar
    • Export Citation
  • Takemi, T., O. Hirayama, and C. Liu, 2004: Factors responsible for the vertical development of tropical oceanic cumulus convection. Geophys. Res. Lett., 31, L11109, doi:10.1029/2004GL020225.

    • Search Google Scholar
    • Export Citation
  • Takemura, T., T. Nozawa, S. Emori, T. Y. Nakajima, and T. Nakajima, 2005: Simulation of climate response to aerosol direct and indirect effects with aerosol transport-radiation model. J. Geophys. Res., 110, D02202, doi:10.1029/2004JD005029.

    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, doi:10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tokioka, T., K. Yamazaki, A. Kitoh, and T. Ose, 1988: The equatorial 30–60-day oscillation and the Arakawa–Schubert penetrative cumulus parameterization. J. Meteor. Soc. Japan, 66, 883901.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., L. Zhou, and K. Hamilton, 2007: Effect of convective entrainment/detrainment on the simulation of the tropical precipitation diurnal cycle. Mon. Wea. Rev., 135, 567585, doi:10.1175/MWR3308.1.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., S. Emori, M. Satoh, and H. Miura, 2009: A PDF-based hybrid prognostic cloud scheme for general circulation models. Climate Dyn., 33, 795816, doi:10.1007/s00382-008-0489-0.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and Coauthors, 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335, doi:10.1175/2010JCLI3679.1.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., M. Chikira, Y. Imada, and M. Kimoto, 2011: Convective control of ENSO simulated in MIROC. J. Climate, 24, 543562, doi:10.1175/2010JCLI3878.1.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M., and G. N. Kiladis, 1999: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain. J. Atmos. Sci., 56, 374399, doi:10.1175/1520-0469(1999)056<0374:CCEWAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., and Coauthors, 2007: A regional ocean–atmosphere model for eastern Pacific climate: Towards reducing tropical biases. J. Climate, 20, 15041522, doi:10.1175/JCLI4080.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G. J., and X. Song, 2010: Convection parameterization, tropical Pacific double ITCZ, and upper-ocean biases in the NCAR CCSM3. Part II: Coupled feedback and the role of ocean heat transport. J. Climate, 23, 800812, doi:10.1175/2009JCLI3109.1.

    • Search Google Scholar
    • Export Citation
  • Zipser, E. J., 2003: Some views on “hot towers” after 50 years of tropical field programs and two years of TRMM data. Cloud Systems, Hurricanes, and the Tropical Rainfall Measuring Mission (TRMM): A Tribute to Dr. Joanne Simpson, Meteor. Monogr., No 29, Amer. Meteor. Soc., 75116, doi:10.1175/0065-9401(2003)029<0049:CSVOHT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
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