Editorial Type:
Article
Article Type:
Research Article

Deep Convective Transition Characteristics in the Community Climate System Model and Changes under Global Warming

Sandeep Sahany Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California

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J. David Neelin Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California

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Katrina Hales Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California

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Richard B. Neale National Center for Atmospheric Research, Boulder, Colorado

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Print Publication:
15 Dec 2014
DOI:
https://doi.org/10.1175/JCLI-D-13-00747.1
Page(s):
9214–9232
Restricted access

Abstract

Tropical deep convective transition characteristics, including precipitation pickup, occurrence probability, and distribution tails related to extreme events, are analyzed using uncoupled and coupled versions of the Community Climate System Model (CCSM) under present-day and global warming conditions. Atmospheric Model Intercomparison Project–type simulations using a 0.5° version of the uncoupled model yield good matches to satellite retrievals for convective transition properties analyzed as a function of bulk measures of water vapor and tropospheric temperature. Present-day simulations with the 1.0° coupled model show transition behavior not very different from that seen in the higher-resolution uncoupled version. Frequency of occurrence of column water vapor (CWV) for precipitating points shows reasonable agreement with the retrievals, including the longer-than-Gaussian tails of the distributions. The probability density functions of precipitating grid points collapse toward similar form when normalized by the critical CWV for convective onset in both historical and global warming cases. Under global warming conditions, the following statements can be made regarding the precipitation statistics in the simulation: (i) as the rainfall pickup shifts to higher CWV with warmer temperatures, the critical CWV for the current climate is a good predictor for the same quantity under global warming with the shift given by straightforward conditional instability considerations; (ii) to a first approximation, the probability distributions shift accordingly, except that (iii) frequency of occurrence in the longer-than-Gaussian tail increases considerably, with implications for occurrences of extreme events; and, thus, (iv) precipitation conditional averages on CWV and tropospheric temperature tend to extend to higher values.

Corresponding author address: Sandeep Sahany, Dept. of Atmospheric and Oceanic Sciences, University of California, Los Angeles, 405 Hilgard Ave., Los Angeles, CA 90095-1565. E-mail: sandeep@atmos.ucla.edu

Abstract

Tropical deep convective transition characteristics, including precipitation pickup, occurrence probability, and distribution tails related to extreme events, are analyzed using uncoupled and coupled versions of the Community Climate System Model (CCSM) under present-day and global warming conditions. Atmospheric Model Intercomparison Project–type simulations using a 0.5° version of the uncoupled model yield good matches to satellite retrievals for convective transition properties analyzed as a function of bulk measures of water vapor and tropospheric temperature. Present-day simulations with the 1.0° coupled model show transition behavior not very different from that seen in the higher-resolution uncoupled version. Frequency of occurrence of column water vapor (CWV) for precipitating points shows reasonable agreement with the retrievals, including the longer-than-Gaussian tails of the distributions. The probability density functions of precipitating grid points collapse toward similar form when normalized by the critical CWV for convective onset in both historical and global warming cases. Under global warming conditions, the following statements can be made regarding the precipitation statistics in the simulation: (i) as the rainfall pickup shifts to higher CWV with warmer temperatures, the critical CWV for the current climate is a good predictor for the same quantity under global warming with the shift given by straightforward conditional instability considerations; (ii) to a first approximation, the probability distributions shift accordingly, except that (iii) frequency of occurrence in the longer-than-Gaussian tail increases considerably, with implications for occurrences of extreme events; and, thus, (iv) precipitation conditional averages on CWV and tropospheric temperature tend to extend to higher values.

Corresponding author address: Sandeep Sahany, Dept. of Atmospheric and Oceanic Sciences, University of California, Los Angeles, 405 Hilgard Ave., Los Angeles, CA 90095-1565. E-mail: sandeep@atmos.ucla.edu
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  • Allan, R. P., and B. J. Soden, 2008: Atmospheric warming and the amplification of precipitation extremes. Science, 321, 1481–1484, doi:10.1126/science.1160787.

    • Search Google Scholar
    • Export Citation

  • Bourlioux, A., and A. J. Majda, 2002: Elementary models with probability distribution function intermittency for passive scalars with a mean gradient. Phys. Fluids, 14, 881–897, doi:10.1063/1.1430736.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C. S., M. E. Peters, and L. E. Back, 2004: Relationships between water vapor path and precipitation over the tropical oceans. J. Climate, 17, 1517–1528, doi:10.1175/1520-0442(2004)017<1517:RBWVPA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Brown, R. G., and C. Zhang, 1997: Variability of midtropospheric moisture and its effect on cloud-top height distribution during TOGA COARE. J. Atmos. Sci., 54, 2760–2774, doi:10.1175/1520-0469(1997)054<2760:VOMMAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Chen, M., R. E. Dickinson, X. Zeng, and A. N. Hahmann, 1996: Comparison of precipitation observed over the continental United States to that simulated by a climate model. J. Climate, 9, 2223–2249, doi:10.1175/1520-0442(1996)009<2233:COPOOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Chou, C., and J. D. Neelin, 2004: Mechanisms of global warming impacts on regional tropical precipitation. J. Climate, 17, 2688–2701, doi:10.1175/1520-0442(2004)017<2688:MOGWIO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Chou, C., J. D. Neelin, C.-A. Chen, and J.-Y. Tu, 2009: Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J. Climate, 22, 1982–2005, doi:10.1175/2008JCLI2471.1.

    • Search Google Scholar
    • Export Citation

  • Chou, C., C.-A. Chen, P.-H. Tan, and K. T. Chen, 2012: Mechanisms for global warming impacts on precipitation frequency and intensity. J. Climate, 25, 3291–3306, doi:10.1175/JCLI-D-11-00239.1.

    • Search Google Scholar
    • Export Citation

  • Chou, C., T.-C. Wu, and P.-H. Tan, 2013: Changes in gross moist stability in the tropics under global warming. Climate Dyn., 41, 2481–2496, doi:10.1007/s00382-013-1703-2.

    • Search Google Scholar
    • Export Citation

  • Covey, C., K. M. AchutaRao, U. Cubasch, P. Jones, S. J. Lambert, M. E. Mann, T. J. Phillips, and K. E. Taylor, 2003: An overview of results from the Coupled Model Intercomparison Project. Global Planet. Change, 37, 103–133, doi:10.1016/S0921-8181(02)00193-5.

    • Search Google Scholar
    • Export Citation

  • Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 4605–4630, doi:10.1175/JCLI3884.1.

  • Dai, A., and K. E. Trenberth, 2004: The diurnal cycle and its depiction in the Community Climate System Model. J. Climate, 17, 930–951, doi:10.1175/1520-0442(2004)017<0930:TDCAID>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dai, A., F. Giorgi, and K. E. Trenberth, 1999: Observed and model-simulated diurnal cycles of precipitation over the contiguous United States. J. Geophys. Res., 104, 6377–6402, doi:10.1029/98JD02720.

    • Search Google Scholar
    • Export Citation

  • Del Genio, A. D., and J. Wu, 2010: The role of entrainment in the diurnal cycle of continental convection. J. Climate, 23, 2722–2738, doi:10.1175/2009JCLI3340.1.

    • Search Google Scholar
    • Export Citation

  • Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 5686–5699, doi:10.1175/JCLI3990.1.

    • Search Google Scholar
    • Export Citation

  • Hilburn, K. A., and F. J. Wentz, 2008: Intercalibrated passive microwave rain products from the Unified Microwave Ocean Retrieval Algorithm (UMORA). J. Appl. Meteor. Climatol., 47, 778–794, doi:10.1175/2007JAMC1635.1.

    • 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, 1665–1683, doi:10.1175/2008JAS2806.1.

    • 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, 1895–1909, doi:10.1175/JAS3723.1.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C., and Coauthors, 2000: The status of the Tropical Rainfall Measuring Mission (TRMM) after two years in orbit. J. Appl. Meteor., 39, 1965–1982, doi:10.1175/1520-0450(2001)040<1965:TSOTTR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lintner, B. R., C. E. Holloway, and J. D. Neelin, 2011: Column water vapor statistics and their relationship to deep convection and vertical horizontal circulation, and moisture structure at Nauru. J. Climate, 24, 5454–5466, doi:10.1175/JCLI-D-10-05015.1.

    • Search Google Scholar
    • Export Citation

  • Majda, A. J., and B. Gershgorin, 2013: Elementary models for turbulent diffusion with complex physical features: Eddy diffusivity, spectrum and intermittency. Philos. Trans. Roy. Soc. London,A371, 20120184, doi:10.1098/rsta.2012.0184.

    • Search Google Scholar
    • Export Citation

  • Mather, J. H., T. P. Ackerman, W. E. Clements, F. J. Barnes, M. D. Ivey, L. D. Hatfield, and R. M. Reynolds, 1998: An atmospheric radiation and cloud station in the tropical western Pacific. Bull. Amer. Meteor. Soc., 79, 627–642, doi:10.1175/1520-0477(1998)079<0627:AARACS>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, 89–93, doi:10.1175/BAMS-86-1-89.

    • Search Google Scholar
    • Export Citation

  • Muller, C. J., L. E. Back, P. A. O’Gorman, and K. A. Emanuel, 2009: A model for the relationship between tropical precipitation and column water vapor. Geophys. Res. Lett., 36, L16804, doi:10.1029/2009GL039667.

    • Search Google Scholar
    • Export Citation

  • Muller, C. J., P. A. O’Gorman, and L. E. Back, 2011: Intensification of precipitation extremes with warming in a cloud-resolving model. J. Climate, 24, 2784–2800, doi:10.1175/2011JCLI3876.1.

    • Search Google Scholar
    • Export Citation

  • Neale, R. B., J. H. Richter, and M. Jochum, 2008: The impact of convection on ENSO: From a delayed oscillator to a series of events. J. Climate, 21, 5904–5924, doi:10.1175/2008JCLI2244.1.

    • Search Google Scholar
    • Export Citation

  • Neelin, J. D., O. Peters, J. W.-B. Lin, K. Hales, and C. E. Holloway, 2008: Rethinking convective quasi-equilibrium: Observational constraints for stochastic convective schemes in climate models. Philos. Trans. Roy. Soc. London, A366, 2579–2602, doi:10.1098/rsta.2008.0056.

    • Search Google Scholar
    • Export Citation

  • Neelin, J. D., O. Peters, and K. Hales, 2009: The transition to strong convection. J. Atmos. Sci., 66, 2367–2384, doi:10.1175/2009JAS2962.1.

    • Search Google Scholar
    • Export Citation

  • Neelin, J. D., B. R. Lintner, B. Tian, Q. Li, L. Zhang, P. K. Patra, M. T. Chahine, and S. N. Stechmann, 2010: Long tails in deep columns of natural and anthropogenic tropospheric tracers. Geophys. Res. Lett., 37, L05804, doi:10.1029/2009GL041726.

    • Search Google Scholar
    • Export Citation

  • O’Gorman, P. A., 2012: Sensitivity of tropical precipitation extremes to climate change. Nat. Geosci., 5, 697–700, doi:10.1038/ngeo1568.

    • Search Google Scholar
    • Export Citation

  • O’Gorman, P. A., and T. Schneider, 2009: The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc. Natl. Acad. Sci. USA, 106, 14 773–14 777, doi:10.1073/pnas.0907610106.

    • Search Google Scholar
    • Export Citation

  • Osborn, T. J., and M. Hulme, 1998: Evaluation of the European daily precipitation characteristics from the atmospheric model intercomparison project. Int. J. Climatol., 18, 505–522, doi:10.1002/(SICI)1097-0088(199804)18:5<505::AID-JOC263>3.0.CO;2-7.

    • Search Google Scholar
    • Export Citation

  • Peters, O., and J. D. Neelin, 2006: Critical phenomena in atmospheric precipitation. Nat. Phys., 2, 393–396, doi:10.1038/nphys314.

  • Pierrehumbert, R. T., 2000: Lattice models of advection–diffusion. Chaos, 10, 61–74, doi:10.1063/1.166476.

  • Romps, D. M., 2011: Response of tropical precipitation to global warming. J. Atmos. Sci., 68, 123–138, doi:10.1175/2010JAS3542.1.

  • Sahany, S., J. D. Neelin, K. Hales, and R. B. Neale, 2012: Temperature–moisture dependence of the deep convective transition as a constraint on entrainment in climate models. J. Atmos. Sci., 69, 1340–1358, doi:10.1175/JAS-D-11-0164.1.

    • Search Google Scholar
    • Export Citation

  • Santer, B. D., and Coauthors, 2005: Amplification of surface temperature trends and variability in the tropical atmosphere. Science, 309, 1551–1556, doi:10.1126/science.1114867.

    • Search Google Scholar
    • Export Citation

  • Seo, E. K., B.-J. Sohn, and G. Liu, 2007: How TRMM precipitation radar and microwave imager retrieved rain rates differ. Geophys. Res. Lett., 34, L24803, doi:10.1029/2007GL032331.

    • Search Google Scholar
    • Export Citation

  • Soden, B. J., D. L. Jackson, V. Ramaswamy, M. D. Schwarzkopf, and X. Huang, 2005: The radiative signature of upper tropospheric moistening. Science, 310, 841–844, doi:10.1126/science.1115602.

    • Search Google Scholar
    • Export Citation

  • Stechmann, S., and J. D. Neelin, 2011: A stochastic model for the transition to strong convection. J. Atmos. Sci., 68, 2955–2970, doi:10.1175/JAS-D-11-028.1.

    • Search Google Scholar
    • Export Citation

  • Stechmann, S., and J. D. Neelin, 2014: First-passage-time prototypes for precipitation statistics. J. Atmos. Sci., 71, 3269–3291, doi:10.1175/JAS-D-13-0268.1.

    • Search Google Scholar
    • Export Citation

  • Stokes, G. M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) Program: Programmatic background and design of the cloud and radiation test bed. Bull. Amer. Meteor. Soc., 75, 1201–1221, doi:10.1175/1520-0477(1994)075<1201:TARMPP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sun, Y., S. Solomon, A. Dai, and R. Portmann, 2006: How often does it rain? J. Climate, 19, 916–934, doi:10.1175/JCLI3672.1.

  • Sun, Y., S. Solomon, A. Dai, and R. W. Portmann, 2007: How often will it rain? J. Climate, 20, 4801–4818, doi:10.1175/JCLI4263.1.

  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 1205–1217, doi:10.1175/BAMS-84-9-1205.

    • Search Google Scholar
    • Export Citation

  • Trenberth, K. E., J. Fasullo, and L. Smith, 2005: Trends and variability in column-integrated atmospheric water vapor. Climate Dyn., 24, 741–758, doi:10.1007/s00382-005-0017-4.

    • Search Google Scholar
    • Export Citation

  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 2961–3012, doi:10.1256/qj.04.176.

  • Wentz, F. J., and R. W. Spencer, 1998: SSM/I rain retrievals within a unified all-weather ocean algorithm. J. Atmos. Sci., 55, 1613–1627, doi:10.1175/1520-0469(1998)055<1613:SIRRWA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
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