Editorial Type:
Article
Article Type:
Research Article

Response of Atmospheric Convection to Vertical Wind Shear: Cloud-System-Resolving Simulations with Parameterized Large-Scale Circulation. Part II: Effect of Interactive Radiation

Usama Anber Lamont-Doherty Earth Observatory, Palisades, and Department of Earth and Environmental Sciences, Columbia University, New York, New York

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Shuguang Wang Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York

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Adam Sobel Lamont-Doherty Earth Observatory, Palisades, and Department of Applied Physics and Applied Mathematics, and Department of Earth and Environmental Sciences, Columbia University, New York, New York

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Print Publication:
01 Jan 2016
DOI:
https://doi.org/10.1175/JAS-D-15-0151.1
Page(s):
199–209
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Abstract

The authors investigate the effects of cloud–radiation interaction and vertical wind shear on convective ensembles interacting with large-scale dynamics in cloud-resolving model simulations, with the large-scale circulation parameterized using the weak temperature gradient approximation. Numerical experiments with interactive radiation are conducted with imposed surface heat fluxes constant in space and time, an idealized lower boundary condition that prevents wind–evaporation feedback. Each simulation with interactive radiation is compared to a simulation in which the radiative heating profile is held constant in the horizontal and in time and is equal to the horizontal-mean profile from the interactive-radiation simulation with the same vertical shear profile and surface fluxes. Interactive radiation is found to reduce mean precipitation in all cases. The magnitude of the reduction is nearly independent of the vertical wind shear but increases with surface fluxes. Deep shear also reduces precipitation, though by approximately the same amount with or without interactive radiation. The reductions in precipitation due to either interactive radiation or deep shear are associated with strong large-scale ascent in the upper troposphere, which more strongly exports moist static energy and is quantified by a larger normalized gross moist stability.

Corresponding author address: Usama Anber, Lamont-Doherty Earth Observatory, 61 Route 9W, Palisades, NY 10964. E-mail: uanber@ldeo.columbia.edu

Abstract

The authors investigate the effects of cloud–radiation interaction and vertical wind shear on convective ensembles interacting with large-scale dynamics in cloud-resolving model simulations, with the large-scale circulation parameterized using the weak temperature gradient approximation. Numerical experiments with interactive radiation are conducted with imposed surface heat fluxes constant in space and time, an idealized lower boundary condition that prevents wind–evaporation feedback. Each simulation with interactive radiation is compared to a simulation in which the radiative heating profile is held constant in the horizontal and in time and is equal to the horizontal-mean profile from the interactive-radiation simulation with the same vertical shear profile and surface fluxes. Interactive radiation is found to reduce mean precipitation in all cases. The magnitude of the reduction is nearly independent of the vertical wind shear but increases with surface fluxes. Deep shear also reduces precipitation, though by approximately the same amount with or without interactive radiation. The reductions in precipitation due to either interactive radiation or deep shear are associated with strong large-scale ascent in the upper troposphere, which more strongly exports moist static energy and is quantified by a larger normalized gross moist stability.

Corresponding author address: Usama Anber, Lamont-Doherty Earth Observatory, 61 Route 9W, Palisades, NY 10964. E-mail: uanber@ldeo.columbia.edu
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  • Anber, U., S. Wang, and A. Sobel, 2014: Response of atmospheric convection to vertical wind shear: Cloud-system-resolving simulations with parameterized large-scale circulation. Part I: Specified radiative cooling. J. Atmos. Sci., 71, 2976–2993, doi:10.1175/JAS-D-13-0320.1.

    • Search Google Scholar
    • Export Citation

  • Anber, U., S. Wang, and A. Sobel, 2015: Effect of surface fluxes versus radiative heating on tropical deep convection. J. Atmos. Sci., 72, 3378–3388, doi:10.1175/JAS-D-14-0253.1.

    • Search Google Scholar
    • Export Citation

  • Bony, S., and K. A. Emanuel, 2005: On the role of moist processes in tropical intraseasonal variability: Cloud–radiation and moisture–convection feedbacks. J. Atmos. Sci., 62, 2770–2789, doi:10.1175/JAS3506.1.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C. S., and A. H. Sobel, 2002: A simple model of a convectively coupled Walker circulation using the weak temperature gradient approximation. J. Climate, 15, 2907–2920, doi:10.1175/1520-0442(2002)015<2907:ASMOAC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C. S., P. N. Blossey, and M. Khairoutdinov, 2005: An energy-balance analysis of deep convective self-aggregation above uniform SST. J. Atmos. Sci., 62, 4273–4292, doi:10.1175/JAS3614.1.

    • Search Google Scholar
    • Export Citation

  • Bu, Y. P., R. G. Fovell, and K. L. Corbosiero, 2014: Influence of cloud–radiative forcing on tropical cyclone structure. J. Atmos. Sci., 71, 1644–1662, doi:10.1175/JAS-D-13-0265.1.

    • Search Google Scholar
    • Export Citation

  • Chen, S. S., R. A. Houze Jr., and B. E. Mapes, 1996: Multiscale variability of deep convection in relation to large-scale circulation in TOGA COARE. J. Atmos. Sci., 53, 1380–1409, doi:10.1175/1520-0469(1996)053<1380:MVODCI>2.0.CO;2.

    • 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, 615–639, doi:10.1175/JAS-D-13-038.1.

    • Search Google Scholar
    • Export Citation

  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model: CAM3.0. NCAR Tech. Rep. NCAR/TN-464+STR, 226 pp. [Available online at http://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf.]

  • de Szoeke, S. P., J. B. Edson, J. R. Marion, C. W. Fairall, and L. Bariteau, 2015: The MJO and air–sea interaction in TOGA COARE and DYNAMO. J. Climate, 28, 597–622, doi:10.1175/JCLI-D-14-00477.1.

    • Search Google Scholar
    • Export Citation

  • Emanuel, K., A. A. Wing, and E. M. Vincent, 2014: Radiative-convective instability. J. Adv. Model. Earth Syst., 6, 75–90, doi:10.1002/2013MS000270.

    • Search Google Scholar
    • Export Citation

  • Grabowski, W. W., and M. W. Moncrieff, 2002: Large-scale organization of tropical convection in two-dimensional explicit numerical simulations: Effects of interactive radiation. Quart. J. Roy. Meteor. Soc., 128, 2349–2375, doi:10.1256/qj.01.104.

    • Search Google Scholar
    • Export Citation

  • Hakim, G. J., 2013: The variability and predictability of axisymmetric hurricanes in statistical equilibrium. J. Atmos. Sci., 70, 993–1005, doi:10.1175/JAS-D-12-0188.1.

    • Search Google Scholar
    • Export Citation

  • Hartmann, D. L., L. A. Moy, and Q. Fu, 2001: Tropical convection and the energy balance at the top of the atmosphere. J. Climate, 14, 4495–4511, doi:10.1175/1520-0442(2001)014<4495:TCATEB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Houze, R. A., Jr., 1989: Observed structure of mesoscale convective systems and implications for large-scale heating. Quart. J. Roy. Meteor. Soc., 115, 425–461, doi:10.1002/qj.49711548702.

    • Search Google Scholar
    • Export Citation

  • Inoue, K., and L. E. Back, 2015a: Column-integrated moist static energy analysis on various time scales during TOGA COARE. J. Atmos. Sci., 72, 1856–1871, doi:10.1175/JAS-D-14-0249.1.

    • Search Google Scholar
    • Export Citation

  • Inoue, K., and L. E. Back, 2015b: Gross moist stability assessment during TOGA COARE: Various interpretations of gross moist stability. J. Atmos. Sci., 72, 4148–4166, doi:10.1175/JAS-D-15-0092.1.

    • Search Google Scholar
    • Export Citation

  • Johnson, R. H., and P. E. Ciesielski, 2013: Structure and properties of Madden–Julian oscillations deduced from DYNAMO sounding arrays. J. Atmos. Sci., 70, 3157–3179, doi:10.1175/JAS-D-13-065.1.

    • Search Google Scholar
    • Export Citation

  • Kim, D., A. H. Sobel, and I.-S. Kang, 2011: A mechanism denial study on the Madden-Julian oscillation. J. Adv. Model. Earth Syst., 3, M12007, doi:10.1029/2011MS000081.

    • Search Google Scholar
    • Export Citation

  • Kim, D., J.-S. Kug, and A. H. Sobel, 2014: Propagating vs. nonpropagating Madden–Julian oscillation events. J. Climate, 27, 111–125, doi:10.1175/JCLI-D-13-00084.1.

    • Search Google Scholar
    • Export Citation

  • Kiranmayi, L., and E. D. Maloney, 2011: Intraseasonal moist static energy budget in reanalysis data. J. Geophys. Res., 116, D21117, doi:10.1029/2011JD016031.

    • Search Google Scholar
    • Export Citation

  • Lin, J.-L., and B. E. Mapes, 2004: Radiation budget of the tropical intraseasonal oscillation. J. Atmos. Sci., 61, 2050–2062, doi:10.1175/1520-0469(2004)061<2050:RBOTTI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lin, X., and R. H. Johnson, 1996: Kinematic and thermodynamic characteristics of the flow over the western Pacific warm pool during TOGA COARE. J. Atmos. Sci., 53, 695–715, doi:10.1175/1520-0469(1996)053<0695:KATCOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Mapes, B., S. Tulich, J. Lin, and P. Zuidema, 2006: The mesoscale convection life cycle: Building block or prototype for large-scale tropical waves? Dyn. Atmos. Oceans, 42, 3–29, doi:10.1016/j.dynatmoce.2006.03.003.

    • Search Google Scholar
    • Export Citation

  • Neelin, J. D., and I. M. Held, 1987: Modeling tropical convergence based on the moist static energy budget. Mon. Wea. Rev., 115, 3–12, doi:10.1175/1520-0493(1987)115<0003:MTCBOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science, 243, 57–63, doi:10.1126/science.243.4887.57.

    • Search Google Scholar
    • Export Citation

  • Raymond, D. J., 2001: A new model of the Madden–Julian oscillation. J. Atmos. Sci., 58, 2807–2819, doi:10.1175/1520-0469(2001)058<2807:ANMOTM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Raymond, D. J., and X. Zeng, 2005: Modelling tropical atmospheric convection in the context of the weak temperature gradient approximation. Quart. J. Roy. Meteor. Soc., 131, 1301–1320, doi:10.1256/qj.03.97.

    • Search Google Scholar
    • Export Citation

  • Raymond, D. J., S. L. Sessions, A. H. Sobel, and Ž. Fuchs, 2009: The mechanics of gross moist stability. J. Adv. Model. Earth Syst., 1 (9), doi:10.3894/JAMES.2009.1.9.

    • Search Google Scholar
    • Export Citation

  • Shinoda, T., H. H. Hendon, and J. Glick, 1998: Intraseasonal variability of surface fluxes and sea surface temperature in the tropical western Pacific and Indian Oceans. J. Climate, 11, 1685–1702, doi:10.1175/1520-0442(1998)011<1685:IVOSFA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sobel, A. H., 2007: Simple models of ensemble-averaged tropical precipitation and surface wind, given the sea surface temperature. The Global Circulation of the Atmosphere, T. Schneider and A. H. Sobel, Eds., Princeton University Press, 219–251.

  • Sobel, A. H., and C. S. Bretherton, 2000: Modeling tropical precipitation in a single column. J. Climate, 13, 4378–4392, doi:10.1175/1520-0442(2000)013<4378:MTPIAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sobel, A. H., and H. Gildor, 2003: A simple time-dependent model of SST hot spots. J. Climate, 16, 3978–3992, doi:10.1175/1520-0442(2003)016<3978:ASTMOS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sobel, A. H., and E. D. Maloney, 2013: Moisture modes and the eastward propagation of the MJO. J. Atmos. Sci., 70, 187–192, doi:10.1175/JAS-D-12-0189.1.

    • Search Google Scholar
    • Export Citation

  • Sobel, A. H., S. Wang, and D. Kim, 2014: Moist static energy budget of the MJO during DYNAMO. J. Atmos. Sci., 71, 4276–4291, doi:10.1175/JAS-D-14-0052.1.

    • Search Google Scholar
    • Export Citation

  • Su, H., and J. D. Neelin, 2002: Teleconnection mechanisms for tropical Pacific descent anomalies during El Nino. J. Atmos. Sci., 59, 2694–2712, doi:10.1175/1520-0469(2002)059<2694:TMFTPD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Tobin, I., S. Bony, C. E. Holloway, J.-Y. Grandpeix, G. Sèze, D. Coppin, S. J. Woolnough, and R. Roca., 2013: Does convective aggregation need to be represented in cumulus parameterizations? J. Adv. Model. Earth Syst., 5, 692–703, doi:10.1002/jame.20047.

    • Search Google Scholar
    • Export Citation

  • Wang, S., and A. H. Sobel, 2011: Response of convection to relative sea surface temperature: Cloud-resolving simulations in two and three dimensions. J. Geophys. Res., 116, D11119, doi:10.1029/2010JD015347.

    • Search Google Scholar
    • Export Citation

  • Wang, S., A. H. Sobel, F. Zhang, Y. Q. Sun, Y. Yue, and L. Zhou, 2015: Regional simulation of the October and November MJO events observed during the CINDY/DYNAMO field campaign at gray zone resolution. J. Climate, 28, 2097–2119, doi:10.1175/JCLI-D-14-00294.1.

    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., and R. Rotunno, 2004: “A theory for strong long-lived squall lines” revisited. J. Atmos. Sci., 61, 361–382, doi:10.1175/1520-0469(2004)061<0361:ATFSLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wing, A. A., and K. A. Emanuel, 2014: Physical mechanisms controlling self-aggregation of convection in idealized numerical modeling simulations. J. Adv. Model. Earth Syst., 6, 59–74, doi:10.1002/2013MS000269.

    • Search Google Scholar
    • Export Citation

  • Yasunaga, K., and B. E. Mapes, 2012: Differences between more divergent vs. more-rotational types of convectively coupled equatorial waves. Part I: Space–time spectral analyses. J. Atmos. Sci., 69, 3–16, doi:10.1175/JAS-D-11-033.1.

    • Search Google Scholar
    • Export Citation

  • Yokoi, S., and A. H. Sobel, 2015: Intraseasonal variability and seasonal march of the moist static energy budget over the eastern Maritime Continent during CINDY2011/DYNAMO. J. Meteor. Soc. Japan, doi:10.2151/jmsj.2015-041, in press.

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