Abstract
Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloudresolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quantitative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes.
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Cess, R. D., and Coauthors, 1990: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res., 95, 16 601–16 615.
Cess, R. D, and Coauthors, 1991: Interpretation of snowclimate feedback as produced by 17 general circulation models. Science, 253, 888–892.
Cheng, A., and K.-M. Xu, 2006: Simulation of shallow cumuli and their transition to deep c onvecitve clouds by cloud-resolving models with different their-order turbulence closures. Quart. J. Roy. Meteor. Soc., 132, 359–382.
Chou, M.-D., and M. J. Suarez, 1994: An efficient thermal infrared radiation parameterization for use in general circulation model. NASA Tech. Memo. 104606, Vol. 3, 85pp. [Available from NASA/Goddard Space Flight Center, Code 913, Greenbelt, MD 20771.]
Chou, M.-D., D. P. Kratz, and W. Ridgway, 1991: Infrared radiation parameterization in numerical climate models. J. Climate, 4, 424–437.
Chou, M.-D., M. J. Suarez, C.-H. Ho, M. M.-H. Yan, and K.-T. Lee, 1998: Parameterizations for cloud overlapping and shortwave single scattering properties for use in general circulation and cloud ensemble models. J. Atmos. Sci., 55, 201–214.
Cui, X., and X. Li, 2006: Role of surface evaporation in surface rainfall processes. J. Geophys. Res., 111, D17112, doi: 10.1029/2005JD006876.
Donner, L. J., C. J. Semen, and R. S. Hemler, 1999: Three-dimensional cloud-system modeling of GATE convection. J. Atmos. Sci., 56, 1885–1912.
Gao, S., and X. Li, 2008a: Cloud-Resolving Modeling of Convective Processes. Springer, Dordrecht, 206pp.
Gao, S., and X. Li, 2008b: Impacts of initial conditions on cloud-resolving simulations. Adv. Atmos. Sci., 25, 737–747, doi: 10.1007/s00376-008-0737-6.
Gao, S., X. Cui, Y. Zhu, and X. Li, 2005: Surface rainfall processes as simulated in a cloud resolving model. J. Geophys. Res., 110, D10202, doi: 10.1029/2004JD005467.
Grabowski, W. W., 2001: Coupling cloud processes with the large-scale dynamics using the cloud-resolving convection parameterization (CRCP). J. Atmos. Sci., 58, 978–997.
Grabowski, W. W., 2003: MJO-like coherent structures: Sensitivity simulations using the cloud-resolving convection parameterization (CRCP). J. Atmos. Sci., 60, 847–864.
Grabowski, W. W., X. Wu, M. W. Moncrieff, and W. D. Hall, 1998: Cloud-resolving model of tropical cloud systems during Phase III of GATE. Part II: Effects of resolution and the third spatial dimension. J. Atmos. Sci., 55, 3264–3282.
Guichard, F., J.-L. Redelsperger, and J.-P. Lafore, 2000: Cloud resolving simulations of convective activity during TOGA-COARE: Sensitivity to external sources of uncertainties. Quart. J. Roy. Meteor. Soc., 126, 3067–3095.
Khairoutdinov, M. F., and D. A. Randall, 2001: A cloud resolving model as a cloud parameterization in the NCAR Community Climate System Model parameterizations. Geophys. Res. Lett., 28, 3617–3620.
Khairoutdinov, M. F., and D. A. Randall, 2003: Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities. J. Atmos. Sci., 60, 607–625.
Krueger, S. K., Q. Fu, K. N. Liou, and H.-N. S. Chin, 1995: Improvement of an ice-phase microphysics parameterization for use in numerical simulations of tropical convection. J. Appl. Meteor., 34. 281–287.
Li, X., C.-H. Sui, K.-M. Lau, and M.-D. Chou, 1999: Large-scale forcing and cloud-radiation interaction in the tropical deep convective regime. J. Atmos. Sci., 56, 3028–3042.
Li, X., S. Zhang, and D.-L. Zhang, 2006: Thermodynamic, cloud microphysics and rainfall responses to initial moisture perturbations in the tropical deep convective regime. J. Geophys. Res., 111, D14207, doi: 10.1029/2005JD006968.
Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092.
Petch, J. C., 2004: The predictability of deep convection in cloud-resolving simulations over land. Quart. J. Roy. Meteor. Soc., 130, 3173–3187.
Petch, J. C., 2006: Sensitivity studies of developing convection in a cloud-resolving model. Quart. J. Roy. Meteor. Soc., 132, 345–358.
Petch, J. C., and M. E. B. Gray, 2001: Sensitivity studies using a cloud-resolving model simulation of the tropical west Pacific. Quart. J. Roy. Meteor. Soc., 127, 2287–2306.
Petch, J. C., A. R. Brown, and M. E. B. Gray, 2002: The impact of horizontal resolution on the simulations of convective development over land. Quart. J. Roy. Meteor. Soc., 128, 2031–2044.
Petch, J. C., P. N. Blossey, and C. S. Bretherton, 2008: Differences in the lower troposphere in two- and three-dimensional cloud-resolving model simulations of deep convection. Quart. J. Roy. Meteor. Soc., 134, 1941–1946.
Phillips, V. T., and L. J. Donner, 2006: Cloud microphysics, radiation and vertical velocities in twoand three-dimensional simulations of deep convection. Quart. J. Roy. Meteor. Soc., 132, 3011–3033.
Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part VIII: A model for the “seeder-feeder” process in warmfrontal rainbands. J. Atmos. Sci., 40, 1185–1206.
Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci., 41, 2949–2972.
Satoh, M., H. Tomita, H. Miura, S. Iga, and T. Nasumo, 2005: Development of a global resolving model-A multi-scale structure of tropical convections. Journal of the Earth Simulator, 3, 1–9.
Soong, S. T., and Y. Ogura, 1980: Response of tradewind cumuli to large-scale processes. J. Atmos. Sci., 37, 2035–2050.
Soong, S. T., and W. K. Tao, 1980: Response of deep tropical cumulus clouds to mesoscale processes. J. Atmos. Sci., 37, 2016–2034.
Tao, W.-K., and J. Simpson, 1993: The Goddard Cumulus Ensemble model. Part I: Model description. Terr. Atmos. Oceanic Sci., 4, 35–72.
Tao, W.-K, J. Simpson, and M. McCumber, 1989: An icewater saturation adjustment. Mon. Wea. Rev., 117, 231–235.
Tomita, H., H. Miura, S. Iga, T. Nasuno, and M. Satoh, 2005: A global cloud-resolving simulation: Preliminary results from an aqua planetary experiment. Geophys. Res. Lett., 32, L08805, 10.1029/2005GL022459.
Wentz, F. J., C. Gentemann, D. Smith, and D. Chelton, 2000: Satellite measurements of sea surface temperature through clouds. Science, 288, 847–850.
Xu, K.-M., and Coauthors, 2002: An intercomparison of cloud resolving models with the Atmospheric Radiation Measurement summer 1997 Intensive Observation Period data. Quart. J. Roy. Meteor. Soc., 128, 593–624.
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Gao, S., Li, X. Dependence of the accuracy of precipitation and cloud simulation on temporal and spatial scales. Adv. Atmos. Sci. 26, 1108–1114 (2009). https://doi.org/10.1007/s00376-009-8143-2
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DOI: https://doi.org/10.1007/s00376-009-8143-2