Downloads

Plant, R.S.; Yano, J.-I. Parameterization of Atmospheric Convection; Imperial College Press: London, UK, 2014; Volumes I and II, in press. 2. McFarlane, N. Parameterizations: Representing key processes in climate models without resolving them. WIREs Clim. Chang. 2011, 2, 482–497. 3. Arakawa, A. The cumulus parameterization problem: Past, present, and future. J. Clim. 2004, 17, 2493–2525. 4. Yano, J.-I.; Vlad, M.; Derbyshire, S.H.; Geleyn, J.-F.; Kober, K. Generalization, consistency, and unification in the parameterization problem. Bull. Amer. Meteor. Soc. 2014, 95, 619–622. 5. Lesieur, M. Turbulence in Fluids; Martinus Nijhoff Publisher: Dordrecht, Netherlands, 1987. 6. Orszag, S.A. Analytical theories of turbulence. J. Fluid Mech. 1970, 41, 363–386. 7. Guichard, F.; Petch, J.C.; Redelsperger, J.L.; Bechtold, P.; Chaboureau, J.-P.; Cheinet, S.; Grabowski, W.; Grenier, H.; Jones, C.G.; Kohler, M.; et al. Modelling the diurnal cycle of deep precipitating convection over land with cloud-resolving models and single-column models. Quart. J. R. Meteor. Soc. 2004, 604, 3139–3172. 8. Lenderink, G.; Siebesma, A.P.; Cheinet, S.; Irons, S.; Jones, C.G.; Marquet, P.; Müller, F.; Olmeda, D.; Calvo, J.; Sánchez, E.; et al. The diurnal cycle of shallow cumulus clouds over land: A single-column model intercomparison study. Quart. J. R. Meteor. Soc. 2004, 130, 3339–3364. 9. Yano, J.-I.; Plant, R.S. Coupling of shallow and deep convection: A key missing element in atmospheric modelling. J. Atmos. Sci. 2012, 69, 3463–3470. Atmosphere 2015, 6 137 10. Bechtold, P.; Semane, N.; Lopez, P.; Chaboureau, J.-P.; Beljaars, A.; Bormann, N. Representing equilibrium and non-equilibrium convection in large-scale models. J. Atmos. Sci. 2014, 71, 734–753. 11. Yano, J.-I.; Graf, H.-F.; Spineanu, F. Theoretical and operational implications of atmospheric convective organization. Bull. Am. Meteor. Soc. 2012, 93, ES39–ES41 12. Yano, J.-I. Formulation structure of the mass–flux convection parameterization. Dyn. Atmos. Ocean 2014, 67, 1–28. 13. Yano, J.-I. Formulation of the mass–flux convection parameterization. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume I, in press. 14. Marquet, P. Definition of a moist entropy potential temperature: Application to FIRE-I data flights. Quart. J. R. Meteor. Soc. 2011, 137, 768–791. 15. Marquet, P. On the computation of moist-air specific thermal enthalpy. Quart. J. R. Meteor. Soc. 2014, doi:10.1002/qj.2335. 16. Marquet, P.; Geleyn, J.-F. Formulations of moist thermodynamics for atmospheric modelling. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 17. Donner, L.J. A cumulus parameterization including mass fluxes, vertical momentum dynamics, and mesoscale effects. J. Atmos. Sci. 1993, 50, 889–906. 18. Yano, J.-I. Convective vertical velocity. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume I, in press. 19. Yano, J.-I. Interactive comment on “Simulating deep convection with a shallow convection scheme” by Hohenegger, C., and Bretherton, C. S., On PBL-based closure. Atmos. Chem. Phys. Discuss. 2011, 11, C2411–C2425. 20. Yano, J.I.; Bister, M.; Fuchs, Z.; Gerard, L.; Phillips, V.; Barkidija, S.; Piriou, J.M. Phenomenology of convection-parameterization closure. Atmos. Phys. Chem. 2013, 13, 4111–4131. 21. Del Genio, A.D.; Wu, J. The role of entrainment in the diurnal cycle of continental convection. J. Clim. 2010, 23, 2722–2738. 22. Stratton, R.A.; Stirling, A. Improving the diurnal cycle of convection in GCMs. Quart. J. R. Meteor. Soc. 2012, 138, 1121–1134. 23. Raymond, D.J. Regulation of moist convection over the warm tropical oceans. J. Atmos. Sci. 1995, 52, 3945–3959. 24. Zhang, G.J. Convective quasi-equilibrium in midlatitude continental environment and its effect on convective parameterization. J. Geophys. Res. 2002, doi:10.1029/2001JD001005. 25. Zhang, G.J. The concept of convective quasi–equilibrium in the tropical western Pacific: Comparison with midlatitude continental environment. J. Geophys. Res. 2003, doi:10.1029/ 2003JD003520. 26. Mapes, B.E. Convective inhibition, subgrid-scale triggering energy, and stratiform instability in a toy tropical wave model. J. Atmos. Sci. 2000, 57, 1515–1535. Atmosphere 2015, 6 138 27. Bretherton, C.S.; McCaa, J.R.; Grenier, H. A new parameterization for shallow cumulus convection and its application to marine subtropical cloud-topped boundary layers. Part I: Description and 1D results. Mon. Weather Rev. 2004, 132, 864–882. 28. Hohenegger, C.; Bretherton, C.S. Simulating deep convection with a shallow convection scheme. Atmos. Chem. Phys. 2011, 11, 10389–10406 29. Donner, L.J.; Phillips, V.T. Boundary layer control on convective available potential energy: Implications for cumulus parameterization. J. Geophys. Res. 2003, doi:10.1029/2003JD003773. 30. Rio, C.; Hourdin, F.; Grandpeix, J.-Y.; Lafore, J.-P. Shifting the diurnal cycle of parameterized deep convection over land. Geophys. Res. Lett. 2009, doi:10.1029/2008GL036779. 31. Rio, C.; Hourdin, F.; Grandpeix, J.-Y.; Hourdin, H.; Guichard, F.; Couvreux, F.; Lafore, J.-P.; Fridlind, A.; Mrowiec, A.; Roehrig, R.; et al. Control of deep convection by sub-cloud lifting processes: The ALP closure in the LMDD5B general circulation model. Clim. Dyn. 2012, 40, 2271–2292. 32. Mapes, B.; Neale, R. Parameterizing convective organization to escape the entrainment dilemma. J. Adv. Model. Earth Syst. 2011, doi:10/1029/211MS00042. 33. Birch, C.E.; Parker, D.J.; O’Leary, A.; Marsham, J.H.; Taylor, C.M.; Harris, P.P.; Lister, G.M.S. Impact of soil moisture and convectively generated waves on the initiation of a West African mesoscale convective system. Quart. J. R. Meteor. Soc. 2013, 139, 1712–1730. 34. Bechtold, P. ECMWF, Reading, UK. Personal communication, 2014. 35. Semane, N. ECMWF, Reading, UK. Personal communication, 2013. 36. De Rooy, W. KNMI, De Bilt, the Netherlands. Personal communication, 2014. 37. Arakawa, A.; Schubert, W.H. Interaction of a cumulus cloud ensemble with the large-scale environment, pt. I. J. Atmos. Sci. 1974, 31, 674–701. 38. Yano, J.-I.; Plant, R.S. Convective quasi-equilibrium. Rev. Geophys. 2012, 50, RG4004. 39. Leith, C.E. Nonlinear normal mode initialization and quasi–geostrophic theory. J. Atmos. Sci. 1980, 37, 958–968. 40. Davies, L.; Plant, R.S.; Derbyshire, S.H. Departures from convective equilibrium with a rapidly-varying forcing. Q.J. R. Meteorol. Soc. 2013, 139, 1731–1746. 41. Yano, J.-I.; Plant, R.S. Finite departure from convective quasi-equilibrium: Periodic cycle and discharge-recharge mechanism. Quator. J. Roy. Meteor. Soc 2012, doi:10.1002/qj.957. 42. Plant, R.S.; Yano, J.-I. The energy-cycle analysis of the interactions between shallow and deep atmospheric convection. Dyn. Atmos. Ocean 2013, 64, 27–52. 43. Yano, J.-I.; Cheedela, S.K.; Roff, G.L. Towards compressed super–parameterization: Test of NAM–SCA under single–column GCM configurations. Atmos. Chem. Phys. Discuss. 2012, 12, 28237–28303. 44. Randall, D.A.; Pan, D.-M. Implementation of the Arakawa-Schubert cumulus parameterization with a prognostic closure. In The Representation of Cumulus Convection in Numerical Models; Emanuel, K.A., Raymond, D.J., Eds.; American Meteor Society: Boston, MA, USA, 1993; pp. 137–144. 45. Pan, D.-M.; Randall, D.A. A cumulus parameterization with prognostic closure. Quart. J. R. Meteor. Soc. 1998, 124, 949–981. Atmosphere 2015, 6 139 46. Chen, D.H.; Bougeault, P. A simple prognostic closure assumption to deep convective parameterization. Acta Meteorol. Sin. 1992, 7, 1–18. 47. Wagner, T.M.; Graf, H.F. An ensemble cumulus convection parameterisation with explicit cloud treatment. J. Atmos. Sci. 2010, 67, 3854–3869. 48. Plant, R.S.; Yano, J.-I. Comment on “An ensemble cumulus convection parameterisation with explicit cloud treatment” by T.M. Wagner and H.-F. Graf. J. Atmos. Sci. 2011, 68, 1541–1544. 49. Kuo, H.L. Further studies of the parameterization of the influence of cumulus convection on the large–scale flow. J. Atmos. Sci. 1974, 31, 1232–1240. 50. Yano, J.-I., and R. S. Plant, 2014: Closure. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume I, in press. 51. Plant, R.S.; Bengtsson, L. Stochastic aspects of convection parameterization. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 52. Grant, A.L.M. Cloud–base fluxes in the cumulus–capped boundary layer. Quart. J. R. Meteor. Soc. 2001, 127, 407–421. 53. Neggers, R.A.J.; Siebesma, A.P.; Lenderink, G.; Holtslag, A.A.M. An evaluation of mass flux closures for diurnal cycles of shallow cumulus. Mon. Wea. Rev. 2004, 132, 2525–2538. 54. Soares, P.M.M.; Miranda, P.M.A.; Siebesma, A.P.; Teixeira, J. An eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus convection. Quart. J. R. Meteor. Soc. 2004, 130, 3365–3383. 55. Penland, C. A stochastic approach to nonlinear dynamics: A review. Bull. Am. Meteor. Soc. 2003, 84, 925–925. 56. Melbourne, I.; Stuart, A. A note on diffusion limits of chaotic skew product flows. Nonlinearity 2011, 24, 1361–1367. 57. Gottwald, G.A.; Melbourne, I. Homogenization for deterministic maps and multiplicative noise. Proc. R. Soc. A 2013, doi:10.1098/rspa.2013.0201. 58. De Rooy, W.C.; Bechtold, P.; Fröhlich, K.; Hohenegger, C.; Jonker, H.; Mironov, D.; Siebesma, A.P.; Teixeira, J.; Yano, J.-I. Entrainment and detrainment in cumulus convection: An overview. Quart. J. R. Meteor. Soc. 2013, 139, 1–19. 59. Romps, D.M. A direct measurement of entrainment. J. Atmos. Sci. 2010, 67, 1908–1927. 60. Dawe, J.T.; Austin, P.H. The influence of the cloud shell on tracer budget measurements of LES cloud entrainment. J. Atmos. Sci. 2011, 68, 2909–2920. 61. Siebesma, A.P.; Cuijpers, J.W.M. Evaluation of parametric assumptions for shallow cumulus convection. J. Atmos. Sci. 1995, 52, 650–666. 62. Swann, H. Evaluation of the mass–flux approach to parameterizing deep convection. Quart. J. R. Meteor. Soc. 2001, 127, 1239–1260. 63. Yano, J.-I.; Guichard, F.; Lafore, J.-P.; Redelsperger, J.-L.; Bechtold, P. Estimations of massfluxes for cumulus parameterizations from high-resolution spatial data. J. Atmos. Sci. 2004, 61, 829–842. 64. Yano, J.-I.; Baizig, H. Single SCA-plume dynamics. Dyn. Atmos. Ocean. 2012, 58, 62–94. Atmosphere 2015, 6 140 65. Korczyka, P.M.; Kowalewskia, T.A.; Malinowski, S.P. Turbulent mixing of clouds with the environment: Small scale two phase evaporating flow investigated in a laboratory by particle image velocimetry. Physica D 2011, 241, 288–296. 66. Diwan, S.S.; Prasanth, P.; Sreenivas, K.R.; Deshpande, S.M.; Narasimha, R. Cumulus-type flows in the laboratory and on the computer: Simulating cloud form, evolution and large-scale structure. Bull. Am. Meteor. Soc. 2014, doi:10.1175/BAMS-D-12-00105.1. 67. Squires, P. The spatial variation of liquid water content and droplet concentration in cumuli. Tellus 1958, 10, 372–380. 68. Squires, P. Penetrative downdraughts in cumuli. Tellus 1958, 10, 381–389. 69. Paluch, I.R. The entrainment mechanism of Colorado cumuli. J. Atmos. Sci. 1979, 36, 2467–2478. 70. Kain, J.S.; Fritsch, J.L. A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci. 1990, 47, 2784–2802. 71. Bechtold, P.; Kohler, M.; Jung, T.; Doblas-Reyes, F.; Leutbecher, M.; Rodwell, M.; Vitart, F.; Balsamo, G. Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Quart. J. R. Meteor. Soc. 2008, 134, 1337–1351. 72. Derbyshire, S.H.; Maidens, A.V.; Milton, S.F.; Stratton, R.A.;Willett, M.R. Adaptive detrainment in a convective parameterization. Quart. J. R. Meteor. Soc. 2011, 137, 1856–1871. 73. De Rooy, W.C.; Siebesma, A.P. A simple parameterization for detrainment in shallow cumulus. Mon. Wea. Rev. 2008, 136, 560–576. 74. Böing, S.J.; Siebesma, A.P.; Korpershoek, J.D.; Jonker, H.J.J. Detrainment in deep convection. Geophys. Res. Lett. 2012, doi:10.1029/2012GL053735. 75. De Rooy, W.C.; Siebesma, A.P. Analytical expressions for entrainment and detrainment in cumulus convection. Quart. J. R. Meteor. Soc. 2010, 136, 1216–1227. 76. Neggers, R.A.J. A dual mass flux framework for boundary layer convection. Part II: Clouds. J. Atmos. Sci. 2009, 66, 1489–1506. 77. Morton, B.R.; Taylor, G.; Turner, J.S. Turbulent gravitational convection from maintained and instantaneous sources. Proc. Roy. Meteor. Soc. 1956, 234, 1–33. 78. Morton, B.R. Discreet dry convective entities: II Thermals and deflected jets. In The Physics and Parameterization of Moist Atmospheric Convection; Smith, R.K., Ed.; NATO ASI, Kloster Seeon, Kluwer Academic Publishers: Dordrecht, The Netherlands, 1997; pp. 175–210. 79. Yano, J.-I. Basic convective element: Bubble or plume?: A historical review. Atmos. Phys. Chem. Dis. 2014, 14, 3337–3359. 80. Squires, P.; Turner, J.S. An entraining jet model for cumulo–nimbus updraught. Tellus 1962, 16, 422–434. 81. Bringi, V.N.; Knupp, K.; Detwiler, A.; Liu, L.; Caylor, I.J.; Black, R.A. Evolution of a Florida thunderstorm during the Convection and Precipitation/Electrification Experiment: The case of 9 August 1991. Mon. Wea. Rev. 1997, 125, 2131–2160. 82. Jonker, H.; His Collaborators. University of Deft, Deft, the Netherlands. Personal communication, 2009. Atmosphere 2015, 6 141 83. Heus, T.; Jonker, H.J.J.; van den Akker, H.E.A.; Griffith, E.J.; Koutek, M.; Post, F.H. A statistical approach to the life cycle analysis of cumulus clouds selected in a vitual reality environment. J. Geophys. Res. 2009, doi:10.1029/2008JD010917. 84. Levine, J. Spherical vortex theory of bubble-like motion in cumulus clouds. J. Meteorol. 1959, 16, 653–662. 85. Gerard, L.; Geleyn, J.-F. Evolution of a subgrid deep convection parameterization in a limited–area model with increasing resolution. Quart. J. R. Meteor. Soc. 2005, 131, 2293–2312. 86. Stanley, H.E. Introduction to Phase Transitions and Critical Phenomena; Oxford University Press: London, UK, 1971. 87. Vattay, G.; Harnos, A. Scaling behavior in daily air humidity fluctuations. Phys. Rev. Lett. 1994, 73, 768–771. 88. Peters, O.; Hertlein, C.; Christensen, K. A complexity view of rainfall. Phys. Rev. Lett. 2002, 88, 018701. 89. Newman, M.E.J. Power laws, Pareto distributions and Zipf’s law. Cont. Phys. 2005, 46, 323–351. 90. Peters, O.; Neelin, J.D. Critical phenomena in atmospheric precipitation. Nat. Phys 2006, 2, 393–396. 91. Peters, O.; Deluca, A.; Corral, A.; Neelin, J.D.; Holloway, C.E. Universality of rain event size distributions. J. Stat. Mech. 2010, 11, P11030. 92. J. D. Neelin, O. Peters, J. W.-B. Lin, K. Hales, and C. E. Holloway. Rethinking convective quasi-equilibrium: Observational constraints for stochastic convective schemes in climate models. Phil. Trans. R. Soc. A 2008, 366, 2581–2604. 93. Peters, O.; Neelin, J.D.; Nesbitt, S.W. Mesoscale convective systems and critical clusters. J. Atmos. Sci. 2009, 66, 2913–2924. 94. Wood, R.; Field, P.R. The distribution of cloud horizontal sizes. J. Clim. 2011, 24, 4800–4816. 95. Muller, C.J.; Back, L.E.; O’Gorman, P.A.; Emanuel, K.A. A model for the relationship between tropical precipitation and column water vapor. Geophys. Res. Lett. 2009, doi:10.1029/ 2009GL039667. 96. Krueger, S. University of Utah, Salt Lake, UT, USA. Personal communication, 2014. 97. Seo, E.-K.; Sohn, B.-J.; Liu, G. How TRMM precipitation radar and microwave imager retrieved rain rates differ. Geophys. Res. Lett. 2007, doi:10.1029/2007GL032331. 98. Yano, J.-I.; Liu, C.; Moncrieff, M.W. Atmospheric convective organization: Homeostasis or self-organized criticality? J. Atmos. Sci. 2012, 69, 3449–3462, 99. Raymond, D.J. Thermodynamic control of tropical rainfall. Quart. J. Roy. Meteor. Soc. 2000, 126, 889–898. 100. Peters, O.; Pruessner, G. Tuning- and Order Parameter in the SOC Ensemble. arXiv:0912.2305v1, 11 December 2009. 101. Yano, J.-I.; Redelsperger, J.-L.; Guichard, F.; Bechtold, P. Mode decomposition as a methodology for developing convective-scale representations in global models. Quart. J. R. Meteor. Soc. 2005, 131, 2313–2336. 102. Yano, J.-I.; Benard, P.; Couvreux, F.; Lahellec, A. NAM–SCA: Nonhydrostatic Anelastic Model under Segmentally–Constant Approximation. Mon. Wea. Rev. 2010, 138, 1957–1974. Atmosphere 2015, 6 142 103. Yano, J.-I. Mass–flux subgrid–scale parameterization in analogy with multi–component flows: A formulation towards scale independence. Geosci. Model Dev. 2012, 5, 1425–2440. 104. Arakawa, A.;Wu, C.-M. A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I. J. Atmos. Sci. 2013, 70, 1977–1992. 105. Arakawa, A.; Jung, J.-H.; Wu, C.-M. Toward unification of the multiscale modeling of the atmosphere. Atmos. Chem. Phys. 2011, 11, 3731–3742. 106. Bihlo, A. A Tutorial on Hamiltonian Mechanics. COST Document, 2011. Available online: http://convection.zmaw.de/fileadmin/user_upload/convection/Convection/COST_Documents/ Search_for_New_Frameworks/A_Tutorial_on_Hamiltonian_Mechanics.pdf (accessed on 4 December 2014). 107. Cardoso-Bihlo, E.; Popovych, R.O. Invariant Parameterization Schemes. COST Document, 2012. Available online: http://convection.zmaw.de/fileadmin/user_upload/convection/Convection/ COST_Documents/Search_for_New_Frameworks/Invariant_Parameterization_Schemes.pdf (accessed on 4 December 2014). 108. Popovych, R.O.; Bihlo, A. Symmetry perserving parameterization schemes. J. Math. Phycs. 2012, 53, 073102. 109. Bihlo, A.; Bluman, G. Conservative parameterization schemes. J. Math. Phys. 2013, 54, 083101. 110. Bihlo, A.; Dos Santos Cardoso-Bihlo, E.M.; Popovych, R.O. Invariant parameterization and turbulence modeling on the beta-plane. Physica D 2014, 269, 48–62. 111. Grant, A.L.M. Cumulus convection as a turbulent flow. In Parameterization of Atmospheric Convection; Plant, R.S.; Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 112. Grant, A.L.M. Precipitating convection in cold air: Virtual potential temperature structure. Quart. J. R. Meteor. Soc. 2007, 133, 25–36. 113. Seifert, A.; Stevens, B. Microphysical scaling relations in a kinematic model of isolated shallow cumulus clouds. J. Atmos. Sci. 2010, 67, 1575–1590. 114. Seifert, A.; Zänger, G. Scaling relations in warm-rain orographic precipitation. Meteorol. Z. 2010, 19, 417–426. 115. Stevens, B.; Seifert, A. Understanding microphysical outcomes of microphysical choices in simulations of shallow cumulus convection. J. Met. Soc. Jpn. 2008, 86A, 143–162. 116. Yano, J.-I.; Phillips, V.T.J. Ice–ice collisions: An ice multiplication process in atmospheric clouds. J. Atmos. Sci. 2011, 68, 322–333. 117. Chandrasekahr, S. Hydrodynamic and Hydromagnetic Instability; Oxford University Press: London, UK, 1961. 118. Marquet, P.; Geleyn, J.-F. On a general definition of the squared Brunt–Väisälä frequency associated with the specific moist entropy potential temperature. Quart. J. R. Meteor. Soc. 2013, 139, 85–100. 119. Durran, D.R.; Klemp, J.B. On the effects of moisture on the Brunt-Vaisala frequency. J. Atmos. Sci. 1982, 39, 2152–2158. Atmosphere 2015, 6 143 120. Machulskaya, E. Clouds and convection as subgrid–scale distributions. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 121. Bony, S.; Emanuel, K.A. A parameterization of the cloudness associated with cumulus convection: Evaluation using TOGA COARE data. J. Atmos. Sci. 2001, 58, 3158–3183. 122. Tompkins, A.M. A prognostic parameterization for the subgrid–scale variability of water vapor and clouds in large–scale models and its use to diagnose cloud cover. J. Atmos. Sci. 2002, 59, 1917–1942. 123. Larson, V.E.; Wood, R.; Field, P.R.; Goraz, J.-C.; Haar, T.H.V.; Cotton,W.R. Systematic biases in the microphysics and thermodynamics of numerical models that ignore subgrid–scale variability. J. Atmos. Sci. 2002, 58, 1117–1128. 124. Wilson, D.R.; Bushell, A.C.; Kerr-Munslow, A.M.; Price, J.D.; Morcrette, C.J. PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description. Quart. J. R. Meteor. Soc. 2008, 134, 2093–2107. 125. Klein, S.A.; Pincus, R.; Hannay, C.; Xu, K.-M. How might a statistical cloud scheme be coupled to a mass–flux convection scheme? J. Geophys. Res. 2005, 110, D15S06. 126. Golaz, J.-C.; Larson, V.E.; Cotton, W.R. A PDF–based model for boundary layer clouds. Part I: Method and model description. J. Atmos. Sci. 2002, 59, 3540–3551. 127. Plant, R. S. Statistical properties of cloud lifecycles in cloud-resolving models. Atmos. Chem. Phys. 2009, 9, 2195–2205. 128. Sakradzija, M.; Seifert, A.; Heus, T. Fluctuations in a quasi-stationary shallow cumulus cloud ensemble, Nonlin. Processes Geophys. Discuss. 2014, 1, 1223–1282. 129. Marquet, P. On the definition of a moist-air potential vorticity. Quart. J. R. Meteor. Soc. 2014, 140, 917–929. 130. Gerard, L. Model resolution issues and new approaches in the grey zone. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 131. Bechtold, P. ECMWF, Reading, UK. Personal communication, 2014. 132. Bengtsson, L.; Körnich, H.; Källén, E.; Svensson, G. Large-scale dynamical response to subgrid scale organization provided by cellular automata. J. Atmos. Sci. 2011, 68, 3132–3144. 133. Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.-F. A stochastic parameterization using cellular automata. Quart. J. R. Meteor. Soc. 2013, 139, 1533–1543. 134. Gerard, L. An integrated package for subgrid convection, clouds and precipitation compatible with the meso-gamma scales. Quart. J. R. Meteor. Soc. 2007, 133, 711–730 135. Gerard, L.; Piriou, J.-M.; Brožková, R.; Geleyn, J.-F.; Banciu, D. Cloud and precipitation parameterization in a meso-gamma-scale operational weather prediction model. Mon. Weather Rev. 2009, 137, 3960–3977. 136. Plant, R.S.; Craig, G.C. A stochastic parameterization for deep convection based on equilibrium statistics. J. Atmos. Sci. 2008, 65, 87–105. 137. Machulskaya, E.; Mironov, D. Implementation of TKE–Scalar Variance Mixing Scheme into COSMO. Available online: http://www.cosmo-model.org (accessed on 4 December 2014). Atmosphere 2015, 6 144 138. Mironov, D. Turbulence in the lower troposphere: Second-order closure and mass-flux modelling frameworks. Lect. Notes. Phys. 2009, 756, 161–221. 139. Smagorinsky, J. General circulation experiments with the primitive equations. I. The basic equations. Mon. Wea. Rev. 1963, 91, 99–164. 140. Jaynes, E.T. Probability Theory, The Logic of Science; Cambridge University Press: Cambridge, UK, 2003. 141. Gregory, P.C. Bayesian Logical Data Analysis for the Physical Sciences; Cambridge University Press: Cambridge, UK, 2005. 142. Khain, A.P.; Beheng, K.D.; Heymsfield, A.; Korolev, A.; Krichak, S.O.; Levin, Z.; Pinsky, M.; Phillips, V.; Prabhakaran, T.; Teller, A.; et al. Representation of microphysical processes in cloud–resolving models: Spectral (bin) microphysics vs. bulk–microphysics. Rev. Geophys. 2014, submitted. 143. Phillips, V.T.J. Microphysics of convective cloud and its treatment in parameterization. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 144. Khain, A.P.; Lynn, B.; Shpund, J. Simulation of intensity and structure of hurricane Irene: Effects of aerosols, ocean coupling and model resolution. In Proceedings of the 94-th AMS Conference, Atlanta, GA, USA, 2–6 February 2014. 145. Lynn, B.H.; Khain, A.P.; Bao, J.W.; Michelson, S.A.; Yuan, T.; Kelman, G.; Shpund, J.; Benmoshe, N. The Sensitivity of the Hurricane Irene to aerosols and ocean coupling: Simulations with WRF with spectral bin microphysics. J. Atmos. Sci. 2014, submitted. 146. Phillips, V.T.J.; Khain, A.; Benmoshe, N.; Ilotovich, E. Theory of time-dependent freezing and its application in a cloud model with spectral bin microphysics. I: Wet growth of hail. J. Atmos. Sci. 2014, in press. 147. Phillips, V.T.J.; Khain, A.; Benmoshe, N.; Ilotovich, E.; Ryzhkov, A. Theory of time-dependent freezing and its application in a cloud model with spectral bin microphysics. II: Freezing raindrops and simulations. J. Atmos. Sci. 2014, in press. 148. Ilotoviz, E.; Khain, A.P.; Phillips, V.T.J.; Benmoshe, N.; Ryzhkov, A.V. Effect of aerosols on formation and growth regime of hail and freezing drops. J. Atmos. Sci. 2014, submitted. 149. Kumjian, M.R.; Khain, A.P.; Benmoshe, N.; Ilotoviz, E.; Ryzhkov, A.V.; Phillips, V.T.J. The anatomy and physics of ZDR columns: Investigating a polarimetric radar signature with a spectral bin microphysical model. J. Appl. Meteorol. Climatol. 2014, in press. 150. Khain, A.P.; Ilotoviz, E.; Benmoshe, N.; Phillips, V.T.J.; Kumjian, M.R.; Ryzhkov, A.V. 2014 Application of the theory of time-dependent freezing and hail growth to analysis of hail storm using a cloud model with SBM. In Proceedings of the 94-th AMS Conference, Atlanta, GA, USA, 2–6 February 2014. 151. Zipser, E.J. The role of unsaturated convective downdrafts in the structure and rapid decay of an equatorial disturbance. J. Appl. Met. 1969, 8, 799–814. 152. Zipser, E.J. Mesoscale and convective–scale downdrafts as distinct components of squall–line circulation. Mon. Wea. Rev. 1977, 105, 1568–1589. Atmosphere 2015, 6 145 153. Houze, R.A., Jr.; Betts, A.K. Convection in GATE. Rev. Geophys. Space Phys. 1981, 19, 541–576. 154. Emanuel, K.A. The finite-amplitude nature of tropical cyclogenesis. J. Atmos. Sci. 1989, 46, 3431–3456. 155. Yano, J.-I.; Emanuel, K.A. An improved model of the equatorial troposphere and its coupling with the stratosphere. J. Atmos. Sci. 1991, 48, 377–389. 156. Fritsch, J.M.; Chappell, C.F. Numerical prediction of convectively driven mesoscale pressure systems: Part I: Convective parameterization. J. Atmos. Sci. 1980, 37, 1722–1733. 157. Tiedtke, M. A comprehensive mass flux scheme of cumulus parameterization in large–scale models. Mon. Wea. Rev. 1989, 117, 1779–1800. 158. Zhang, G.J.; McFarlane, N.A. Sensitivity of climate simulations of the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos. Ocean 1995, 33, 407–446. 159. Bechtold, P.; Bazile, E.; Guichard, F.; Mascart, P.; Richard, E. A mass-flux convection scheme for regional and global models. Quart. J. R. Meteor. Soc. 2001, 127, 869–889. 160. Yano, J.-I. Downdraught. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume I; in press. 161. Warner, C.; Simpson, J.; Martin, D.W.; Suchman, D.; Mosher, F.R.; Reinking, R.F. Shallow convection on day 261 of GATE: Mesoscale arcs. Mon. Wea. Rev. 1979, 107, 1617–1635. 162. Zuidema, P.; Li, Z.; Hill, R.J.; Bariteau, L.; Rilling, B.; Fairall, C. Brewer, W.A.; Albrecht, B.; Hare, J. On trade wind cumulus cold pools. J. Atmos. Sci. 2012, 69, 258–280. 163. Barnes, G.M.; Garstang, M. Subcloud layer energetics of precipitating convection. Mon. Wea. Rev. 1982, 110, 102–117. 164. Addis, R.P.; Garstang, M.; Emmitt, G.D. Downdrafts from tropical oceanic cumuli. Bound. Layer Meteorol. 1984, 28, 23–49. 165. Young, G.S.; Perugini, S.M.; Fairall, C.W. Convective wakes in the Equatorial Western Pacific during TOGA. Mon. Wea. Rev. 1995, 123, 110–123. 166. Lima, M.A.; Wilson, J.W. Convective storm initiation in a moist tropical environment. Mon. Wea. Rev. 2008, 136, 1847–1864. 167. Flamant, C.; Knippertz, P.; Parker, D.J.; Chaboureau, J.-P.; Lavaysse, C.; Agusti-Panareda, A.; Kergoat, L. The impact of a mesoscale convective system cold pool on the northward propagation of the intertropical discontinuity overWest Africa. Quart. J. R. Meteor. Soc. 2009, 135, 139–159. 168. Lothon, M.; Campistron, B.; Chong, M.; Couvreux, F.; Guichard, F.; Rio, C.; Williams, E. Life cycle of a mesoscale circular gust front observed by a C-band doppler radar in West Africa. Mon. Wea. Rev. 2011, 139, 1370–1388. 169. Dione, C.; Lothon, M.; Badiane, D.; Campistron, B.; Couvreux, F.; Guichard, F.; Sall, S.M. Phenomenology of Sahelian convection observed in Niamey during the early monsoon. Quart. J. R. Meteor. Soc. 2013, doi:10.1002/qj.2149. 170. Khairoutdinov, M.; Randall, D. High-resolution simulations of shallow-to-deep convection transition over land. J. Atmos. Sci. 2006, 63, 3421–3436. Atmosphere 2015, 6 146 171. Böing, S.J.; Jonker, H.J.J.; Siebesma, A.P.; Grabowski, W.W. Influence of the subcloud layer on the development of a deep convective ensemble. J. Atmos. Sci. 2012, 69, 2682–2698. 172. Schlemmer, L.; Hohenegger, C. The formation of wider and deeper clouds as a result of cold-pool dynamics. J. Atmos. Sci. 2014, submitted. 173. Grandpeix, J-Y.; Lafore, J.-P. A density current parameterization coupled with emanuel’s convection scheme. Part I: The models. J. Atmos. Sci. 2010, 67, 881–897. 174. Yano, J.-I. Comments on “A density current parameterization coupled with emanuel’s convection scheme. Part I: The models”. J. Atmos. Sci. 2012, 69, 2083–2089. 175. Browning, K.A.; Hill, F.F.; Pardoe, C.W. Structure and mechanism of precipitation and the effect of orography in a wintertime warm sector. Quart. J. Roy. Meteor. Soc. 1974, 100, 309–330. 176. Fuhrer, O.; Schär, C. Embedded cellular convection in moist flow past topography. J. Atmos. Sci. 2005, 62, 2810–2828. 177. Yano, J.-I. Downscaling, parameterization, decomposition, compression: A perspective from the multiresolutional analysis. Adv. Geophy. 2010, 23, 65–71. 178. Rezacova, D.; Szintai, B.; Jakubiak, B.; Yano, J.I.; Turner, S. Verification of high resolution precipitation forecast by radar-based data. In Parameterization of Atmospheric Convection; Plant, R.S., Yano, J.I., Eds.; Imperial College Press: London, UK, 2014; Volume II, in press. 179. Vukicevic, T.; Rosselt, D. Analysis of the impact of model nonlinearities in inverse problem solving. J. Atmos. Sci. 2008, 65, 2803–2823. 180. Rosselt, D.; Bishop, C.H. Nonlinear parameter estimation: Comparison of an ensemble Kalman smoother with a Markov chain Monte Carlo algorithm. Mon. Wea. Rev. 2012, 140, 1957–1974. 181. Khain, A. Notes on state-of-the-art investigations of aerosol effects on precipitation: A critical review. Environ. Res. Lett. 2008, doi:10.1088/1748-9326/1/015004. 182. Rosenfeld, D.; Lohmann, U.; Raga, G.B.; O’Dowd, C.D.; Kulmala, M.; Fuzzi, S.; Reissell, A.; Andreae, M.O. Flood or drought: How do aerosols affect precipitation. Science 2008, 321, 1309–1313. 183. Boucher, O.; Quaas, J. Water vapour affects both rain and aerosol optical depth. Nat. Geosci. 2013, 6, 4–5. 184. Freud, E.; Rosenfeld, D. Linear relation between convective cloud drop number concentration and depth for rain initiation. J. Geophys. Res. 2012, 117, D02207. 185. Mewes, D. Test Einer Neuen Parametrisierung Konvektiven Niederschlags Im Klimamodell. Bachelor’s Thesis, University of Leipzig, Leipzig, Germany, 2013. 186. Lohmann, U.; Quaas, J.; Kinne, S.; Feichter, J. Different approaches for constraining global climate models of the anthropogenic indirect aerosol effect. Bull. Am. Meteorol. Soc. 2007, 88, 243–249. 187. Bodas-Salcedo, A.; Webb, M.J.; Bony, S.; Chepfer, H.; Dufresne, J.-L.; Klein, S.A.; Zhang, Y.; Marchand, R.; Haynes, J.M.; Pincus, R.; et al. COSP: Satellite simulation software for model assessment. Bull. Amer. Meteor. Soc. 2011, 92, 1023–1043. 188. Nam, C.; Quaas, J. Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat. J. Clim. 2012, 25, 4975–4992. Atmosphere 2015, 6 147 189. Nam, C.; Quaas, J.; Neggers, R.; Drian, C.S.; Isotta, F. Evaluation of boundary layer cloud parameterizations in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data. J. Adv. Model. Earth Syst. 2014, doi:10.1002/2013MS000277. 190. Gehlot, S.; Quaas, J. Convection-climate feedbacks in ECHAM5 general circulation model: A Lagrangian trajectory perspective of cirrus cloud life cycle. J. Clim. 2012, 25, 5241–5259. 191. Suzuki, K.; Stephens, G.L.; van den Heever, S.C.; Nakajima, T.Y. Diagnosis of the warm rain process in cloud-resolving models using joint CloudSat and MODIS observations. J. Atmos. Sci. 2011, 68, 2655–2670. 192. Schirber, S.; Klocke, D.; Pincus, R.; Quaas, J.; Anderson, J. Parameter estimation using data assimilation in an atmospheric general circulation model: From a perfect towards the real world, J. Adv. Model. Earth Syst. 2013, 5, 1942–2466. 193. Yano, J.-I.; Lane, T.P. Convectively-generated gravity waves simulated by NAM-SCA. J. Geophys. Res. 2014, doi:10.1002/2013JD021419. 194. Tobias, S.M.; Marston, J.B. Direct Statistical simulation of out-of-equilibrium jets. Phys. Rev. Lett. 2013, 110, 104502.