Stochastic and deterministic multicloud parameterizations for tropical convection

详细信息    查看全文

• 作者：Yevgeniy Frenkel ; Andrew J. Majda ; Boualem Khouider
• 关键词：Stochastic convective parameterization ; Multicloud models ; Tropical atmospheric dynamics ; Convectively coupled waves
• 刊名：Climate Dynamics
• 出版年：2013
• 出版时间：September 2013
• 年：2013
• 卷：41
• 期：5-6
• 页码：1527-1551
• 全文大小：1940KB
• 参考文献：1. Arakawa A, Schubert WH (1974) Interaction of a cumulus cloud ensemble with the large-scale environment, part I. J Atmos Sci 31:674-01 CrossRef
  2. Betts AK, Miller MJ (1986) A new convective adjustment scheme. Part II: single column tests using GATE wave, BOMEX, ATEX and Arctic air-mass data sets. Q J R Meteorol Soc 112(473):693-09
  3. Buizza R, Miller M, Palmer TN (1999) Stochastic representation of model uncertainties in the ECMWF ensemble prediction system. Q J R Meteorol Soc 125:2887-908 CrossRef
  4. ECMWF (2003) Proceedings ECMWF/CLIVAR workshop on simulation and prediction of intraseasonal variability with emphasis on the MJO, pp 3-
  5. Frenkel Y, Majda AJ, Khouider B (2012) Using the stochastic multicloud model to improve tropical convective parameterization: a paradigm example. J Atmos Sci 69(3):1080-105 CrossRef
  6. Gillespie DT (1975) An exact method for numerically simulating the stochastic coalescence process in a cloud. J Atmos Sci 32:1977-989 CrossRef
  7. Gillespie DT (1977) Exact stochastic simulation of couple chemical reactions. J Phys Chem 81:2340-361
  8. Grabowski WW (2001) Coupling cloud processes with the large-scale dynamics using the cloud-resolving convection parameterization. J Atmos Sci 58(9):978-97 CrossRef
  9. Grabowski WW (2004) An improved framework for superparameterization. J Atmos Sci 61(15):1940-952 CrossRef
  10. Grabowski WW, Smolarkiewicz PK (1999) CRCP: a cloud resolving convection parameterization for modeling the tropical convecting atmosphere. Phys D Nonlinear Phenom 133:171-78 CrossRef
  11. Han Y, Khouider B (2010) Convectively coupled waves in a sheared environment. J Atmos Sci 67:2913-942 CrossRef
  12. Hendon HH, Liebmann B (1994) Organization of convection within the Madden–Julian oscillation. J Geophys Res 99:8073-084 CrossRef
  13. Hohenegger C, Stevens B (2012) Preconditioning deep convection with cumulus congestus. J Atmos Sci. doi:10.1175/JAS-D-12-089.1
  14. Holloway CE, Neelin JD (2009) Moisture vertical structure, column water vapor, and tropical deep convection. J Atmos Sci 66:1665 CrossRef
  15. Holloway CE, Neelin JD (2010) Temporal relations of column water vapor and tropical precipitation. J Atmos Sci 67:1091-105 CrossRef
  16. Horenko I (2011) Nonstationarity in multifactor models of discrete jump processes, memory and application to cloud modeling. J Atmos Sci 68:1493-506 CrossRef
  17. Johnson RH, Rickenbach TM, Rutledge SA, Ciesielski PE, Schubert WH (1999) Trimodal characteristics of tropical convection. J Clim 12(8):2397-418 CrossRef
  18. Kain JS, Fritsch JM (1990) A one-dimensional entraining/detraining plume model and its application in convective parameterization. J Atmos Sci 47:2784-802
  19. Katsoulakis MA, Majda AJ, Vlachos DG (2003a) Coarse-grained stochastic processes for microscopic lattice systems. Proc Natl Acad Sci USA 100(3):782-87 CrossRef
  20. Katsoulakis MA, Majda AJ, Vlachos DG (2003b) Coarse-grained stochastic processes and monte carlo simulations in lattice systems. J Comput Phys 186(1):250-78 CrossRef
  21. Khouider B, Majda AJ (2005a) A non oscillatory balanced scheme for an idealized tropical climate model; part I: algorithm and validation. Theor Comput Fluid Dyn 19:331-54 CrossRef
  22. Khouider B, Majda AJ (2005b) A non oscillatory balanced scheme for an idealized tropical climate model; part II: nonlinear coupling and moisture effects. Theor Comput Fluid Dyn 19:355-75 CrossRef
  23. Khouider B, Majda AJ (2006a) Multicloud convective parametrizations with crude vertical structure. Theor Comp Fluid Dyn 20:351-75 CrossRef
  24. Khouider B, Majda AJ (2006b) Multicloud convective parametrizations with crude vertical structure. Theor Comp Fluid Dyn 20:351-75 CrossRef
  25. Khouider B, Majda AJ (2007) A simple multicloud parametrization for convectively coupled tropical waves. Part II: nonlinear simulations. J Atmos Sci 64:381-00 CrossRef
  26. Khouider B, Majda AJ (2008a) Equatorial convectively coupled waves in a simple multicloud model. J Atmos Sci 65:3376-397 CrossRef
  27. Khouider B, Majda AJ (2008b) Multicloud models for organized tropical convection: enhanced congestus heating. J Atmos Sci 65:897-14
  28. Khouider B, Majda AJ, Katsoulakis MA (2003) Coarse-grained stochastic models for tropical convection and climate. Proc Natl Acad Sci 100:11941-1946 CrossRef
  29. Khouider B, Biello J, Majda AJ (2010a) A stochastic multicloud model for tropical convection. Commun Math Sci 8(1):187-16 CrossRef
  30. Khouider B, St-Cyr A, Majda AJ, Tribbia J (2010b) MJO and convectively coupled waves in a coarse resolution GCM with a simple multicloud parametrization. J Atmos Sci 68:240-64 CrossRef
  31. Kuang Z, Bretherton CS (2006) A mass-flux scheme view of a high-resolution simulation of a transition from shallow to deep cumulus convection. J Atmos Sci 63:1895-909. doi:10.1175/JAS3723.1 CrossRef
  32. Kuo HL (1974) Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J Atmos Sci 31:1232-240 CrossRef
  33. Lau WKM, Waliser DE (2005) Intraseasonal variability in the atmosphere–ocean climate system. Springer, Berlin
  34. Lin J, Neelin JD (2003) Toward stochastic deep convective parameterization in general circulation models. Geophys Res Lett 30(4):1162 CrossRef
  35. Lin JL, Kiladis GN, Mapes BE, Weickmann KM, Sperber KR, Lin W, Wheeler MC, Schubert SD, Del Genio A, Donner LJ, Emori S, Gueremy JF, Hourdin F, Rasch PJ, Roeckner E, Scinocca JF (2006) Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: convective signals. J Clim 19(12):2665-690 CrossRef
  36. Lintner BR, Holloway CE, Neelin JD (2011) Column water vapor statistics and their relationship to deep convection, vertical and horizontal circulation, and moisture structure at Nauru. J Clim 24:5454-466 CrossRef
  37. Majda AJ (2007) Multiscale models with moisture and systematic strategies for superparameterization. J Atmos Sci 64(7):2726-734 CrossRef
  38. Majda AJ, Khouider B (2002) Stochastic and mesoscopic models for tropical convection. Proc Natl Acad Sci 99:1123-128 CrossRef
  39. Majda AJ, Stechmann S, Khouider B (2007) Madden–Julian Oscillation analog and intraseasonal variability in a multicloud model above the equator. Proc Natl Acad Sci 104:9919-924 CrossRef
  40. Majda AJ, Franzke C, Khouider B (2008) An applied mathematics perspective on stochastic modelling for climate. Philos Trans R Soc A Math Phys Eng Sci 366(1875):2427-453 CrossRef
  41. Majda AJ, Stechmann SN (2008) Stochastic models for convective momentum transport. Proc Natl Acad Sci 105(46):17614-7619 CrossRef
  42. Manabe S, Smagorinsky J, Strickler RF (1965) Simulated climatology of a general circulation model with a hydrologic cycle1. Mon Weather Rev 93(12):769-98 CrossRef
  43. Mapes BE (2000) Convective inhibition, subgrid-scale triggering energy, and stratiform instability in a toy tropical wave model. J Atmos Sci 57(10):1515-535 CrossRef
  44. Mapes B, Tulich S, Lin J, Zuidema P (2006) The mesoscale convection life cycle: building block or prototype for large-scale tropical waves? Dyn Atmos Ocean 42:3-9
  45. Moncrieff MW, Klinker E (1997) Organized convective systems in the tropical western Pacific as a process in general circulation models: a TOGA COARE case-study. Q J R Meteorol Soc 123:805-27 CrossRef
  46. Moncrieff M, Shapiro M, Slingo J, Molteni F (2007) Collaborative research at the intersection of weather and climate. WMO Bull 56:204-11
  47. Nakazawa T (1974) Tropical super clusters within intraseasonal variation over the western pacific. J Meteorol Soc Jpn 66:823-39
  48. Neelin JD, Peters O, Lin JWB, Hales K, Holloway CE (2008) Rethinking convective quasi-equilibrium: observational constraints for stochastic convective schemes in climate models. Phil Trans R Soc A 366:2579-602 CrossRef
  49. Palmer TN (2001) A nonlinear dynamical perspective on model error: a proposal for non-local stochastic-dynamic parametrization in weather and climate prediction models. Q J R Meteorol Soc 127:279-04
  50. Peters O, Neelin JD (2009) Atmospheric convection as a continuous phase transition: further evidence. Int J Mod Phys B 23:5453-465 CrossRef
  51. Peters O, Neelin JD, Nesbitt S (2009) Mesoscale convective systems and critical clusters. AGU Spring Meeting Abstracts, p. A5
  52. Peters O, Deluca A, Corral A, Neelin JD, Holloway CE (2010) Universality of rain event size distributions. J Stat Mech Theory Exp 11:30
  53. Randall D, Khairoutdinov M, Arakawa A, Grabowski W (2003) Breaking the cloud parameterization deadlock. Bull Am Meteorol Soc 84(11):1547-564 CrossRef
  54. Rapp AD, Kummerow CD, Fowler L (2011) Interactions between warm rain clouds and atmospheric preconditioning for deep convection in the tropics. J Geophys Res 116:D23210. doi:10.1029/2011JD016143
  55. Scinocca JF, McFarlane NA (2004) The variability of modeled tropical precipitation. J Atmos Sci 61:1993-015 CrossRef
  56. Slawinska J, Pauluis O, Majda A, Grabowski W (2013) Multi-scale interactions in an idealized walker circulation: mean circulation and intra-seasonal variability. J Atmos Sci (submitted)
  57. Slingo JM, Sperber KR, Boyle JS, Ceron J, Dix M, Dugas B, Ebisuzaki W, Fyfe J, Gregory D, Gueremy J, Hack J, Harzallah A, Inness P, Kitoh A, Lau W, McAvaney B, Madden R, Matthews A, Palmer TN, Parkas C, Randall D, Renno N (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Clim Dyn 12:325-57 CrossRef
  58. Stechmann SN, Majda AJ (2009) Gravity waves in shear and implications for organized convection. J Atmos Sci 66:2579-599 CrossRef
  59. Stechmann SN, Neelin JD (2011) A stochastic model for the transition to strong convection. J Atmos Sci 68:2955-970 CrossRef
  60. Takayabu YN (1994) Large-scale cloud disturbances associated with equatorial waves. Part I: spectral features of the cloud disturbances. J Meteorol Soc Jpn 72:433-48
  61. Takemi T, Hirayama O, Liu CH (2004) Factors responsible for the vertical development of tropical oceanic cumulus convection. Geophys Res Lett 31:L11109. doi:10.1029/2004GL020225 CrossRef
  62. Tulich S, Mapes B (2008) Multi-scale convective wave disturbances in the tropics: insights from a two-dimensional cloud-resolving model. J Atmos Sci 65(1):140-55 CrossRef
  63. Waite ML, Khouider B (2010) The deepening of tropical convection by congestus preconditioning. J Atmos Sci 67:2601-615. doi: 10.1175/2010JAS3357.1
  64. Wheeler M, Kiladis GN (1999) Convectively coupled equatorial waves: analysis of clouds and temperature in the wavenumber–frequency domain. J Atmos Sci 56(3):374-99 CrossRef
  65. Wu CM, Stevens B, Arakawa A (2009) What controls the transition from shallow to deep convection? J Atmos Sci 66:1793-806. doi:10.1175/2008JAS2945.1 CrossRef
  66. Xing Y, Majda AJ, Grabowski WW (2009) New efficient sparse space time algorithms for superparameterization on mesoscales. Mon Weather Rev 137(12):4307-324 CrossRef
  67. Zhang C (2005) Madden–Julian oscillation. Rev Geophys 43:RG2003 CrossRef
  68. Zhang GJ, McFarlane NA (1995) Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre General Circulation Model. Atmos Ocean 33:406-46 CrossRef
  
• 作者单位：Yevgeniy Frenkel (1)
  Andrew J. Majda (1)
  Boualem Khouider (2)
  
  1. Department of Mathematics, Center for Atmosphere-Ocean Science, Courant Institute, New York University, 251 Mercer Street, New York, NY, 10012, USA
  2. Department of Mathematics and Statistics, University of Victoria, PO BOX 3045 STN CSC, Victoria, BC, V8W 3P4, Canada
  
• ISSN：1432-0894

文摘

Despite recent advances in supercomputing, current general circulation models poorly represent the variability associated with organized tropical convection. In a recent study, the authors have shown, in the context of a paradigm two baroclinic mode system, that a stochastic multicloud convective parameterization based on three cloud types (congestus, deep and stratiform) can be used to improve the variability and the dynamical structure of tropical convection. Here, the stochastic multicloud model is modified with a lag type stratiform closure and augmented with an explicit mechanism for congestus detrainment moistening. These modifications improve the representation of intermittent coherent structures such as synoptic and mesoscale convective systems. Moreover, the new stratiform-lag closure allows for increased robustness of the coherent features of the model with respect to the amount of stochastic noise and leading to a multi-scale organization of slowly moving waves envelopes in which short-lived and chaotic convective events persist. Congestus cloud decks dominate the suppressed-dry phase of the wave envelopes. The simulations with the new closure have a higher amount of stochastic noise and result in a Walker type circulation with realistic mean and coherent variability which surpasses results of previous deterministic and stochastic multicloud models in the same parameter regime. Further, deterministic mean field limit equations (DMFLE) for the stochastic multicloud model are considered. Aside from providing a link to the deterministic multicloud parameterization, the DMFLE allow a judicious way of determining the amount of deterministic and stochastic “chaos-in the system. It is shown that with the old stratiform heating closure, the stochastic process accounts for most of the chaotic behavior. The simulations with the new stratiform heating closure exhibit a mixture of stochastic and deterministic chaos. The highly chaotic dynamics in the simulations with congestus detrainment mechanism is due to the strongly nonlinear and numerically stiff deterministic dynamics. In the latter two cases, the DMFLE can be viewed as a “standalone-parameterization, which is capable of capturing some dynamical features of the stochastic parameterization. Furthermore, it is shown that, in spatially extended simulations, the stochastic multicloud model can capture qualitatively two local statistical features of the observations: long and short auto-correlation times of moisture and precipitation, respectively and the approximate power-law in the probability density of precipitation event size for large precipitation events. The latter feature is not reproduced in the column simulations. This fact underscores the importance of gravity waves and large scale moisture convergence.