References

ACP

Atmospheric Chemistry and Physics

ACP

1680-7324

Copernicus GmbH

Göttingen, Germany

10.5194/acp-6-2793-2006

Development of a cloud microphysical model and parameterizations to describe the effect of CCN on warm cloud

Kuba

¹ Fujiyoshi

Frontier Research Center for Global Change (FRCGC), Japan Agency for Marin-Earth Science and Technology (JAMSTEC), Yokohama, Japan

Frontier Research Center for Global Change (FRCGC), Japan Agency for Marin-Earth Science and Technology (JAMSTEC)/Inst. Low. Temp. Sci., Hokkaido Univ., Sapporo, Japan

10 07 2006

6 10 2793 2810

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First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN) on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points. Results from the cloud model show that an increase in the number of CCN affects both the amount and the area of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared. Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example). It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CSk, or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and for a global model. The effects of sea salt, sulfate, and organic carbon particles were also studied with these parameterizations and global model.

References 1

Albrecht, B. A., Bretherton, C. S., Johnson, D., Scubert, W. H., and Frisch, A. S.: The Atlantic stratocumulus transition experiment – ASTEX, Bull. Am. Meteorol. Soc., 76, 889–904, 1995.

Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A. A., Frank, G. P., Longo, K. M., and Silva-Dias, M. A. F.: Smoking rain clouds over the Amazon, Science, 303, 1337–1342, 2004.

Bott, A.: A flux method for the numerical solution of the stochastic collection equation, J. Atmos. Sci., 55, 2284–2293, 1998.

Chen, J. -P. and Lamb, D.: Simulation of cloud microphysics and chemical processes using a multicomponent framework. Part I Description of the microphysical model, J. Atmos. Sci. 51, 2613–2630, 1994.

Chen, J. -P. and Lamb, D.: Simulation of cloud microphysics and chemical processes using a multicomponent framework. Part II Microphysical evolution of a wintertime orographic cloud, J. Atmos. Sci., 56, 2293–2312, 1999.

Chen, J.-P. and Liu, S.-T.: Physically based two-moment bulkwater parametrization for warm-cloud microphysics, Q. J. R. Meteorol. Soc., 130, 51–78, 2004.

Chuang, P. Y., Charlson, R. J., and Seinfeld, J. H.: Kinetic limitations on droplet formation in clouds, Nature, 390, 11, 595–596, 1997.

Clark, T. L.: Numerical modeling of the dynamics and microphysics of warm cumulus convection, J. Atmos. Sci., 30, 857–878, 1973.

Cooper, W. A., Bruintjes, R. T., and Mather, G. K.: Calculating pertaining to hygrospic seeding with flares, J. Appl. Meteor., 36, 1449–1469, 1997.

Cotton, W. R. and Anthes, R. A.: Storm and Cloud Dynamics (Chapter 4), Academic Press, 880pp., 1989.

Cotton, W. R., Pielke, R. A. Sr., Walco, R. L., Liston G. E., Tremback, C. J., Jiang, H., McAnelly, R. L., Harringto, J. Y., Nicholls, M. E., Carrio, G. G., and McFadde, J. P.: RAMS 2001: Current status and future directions, Meteorol. Atmos. Phys., 82, 5–29, 2003.

Feingold, G., Cotton, W. R., Kreidenwei, S. M., and Davis, J. T.: The impact of giant cloud condensation nuclei on drizzle formation in stratocumulus: Implications for cloud radiative properties, J. Atmos. Sci., 56, 15, 4100–4117, 1999.

Fitzgerald, J. W.: Effect of aerosol composition on cloud droplets size distribution: a numerical study, J. Atmos. Sci., 31, 1358–1367, 1974.

Ghan, S., Easter, R., Hudson, J., and Breon, F. M.: Evaluation of aerosol indirect radiative forcing in MIRAGE, J. Geophys. Res., 106(D6), 5317–5334, 2001.

Givati, A. and Rosenfeld, D.: Quantifying precipitation suppression due to air pollution, J. Appl. Meteor., 43, 1038–1056, 2004.

Hall, W. D.: A detailed microphysical model within a two-dimensional dynamic framework: Model description and preliminary results, J. Atmos. Sci., 37, 2486–2507, 1980.

Harshvardhan, S., Schwartz, E., Benkovitz, C. M., and Guo, G.: Aerosol influence on cloud microphysics examined by satellite measurements and chemical transport modeling, J. Atmos. Sci., 59, 714–725, 2002.

Kawamoto, K., Nakajima, T., and Nakajima, T. Y.: A global determination of cloud microphysics with AVHRR remote sensing, J. Climate, 14, 2054–2068, 2001.

Khain, A., Pokrovsky, A., and Sednev, I.: Some effects of cloud-aerosol interaction on cloud microphysics structure and precipitation formation: numerical experiments with a spectral microphysics cloud ensemble model, Atmos. Res., 52, 195–220, 1999.

Khairoutdinov, M. F. and Kogan, Y. L.: A large eddy simulation model with explicit microphysics: Validation against aircraft observations of a stratocumulus-topped boundary layer, J. Atmos. Sci., 56, 1, 2115–2131, 1999.

Kuba, N. and Takeda T.: Numerical study of the effect of CCN on the size distribution of cloud droplets. Part II. Formation of large droplets, J. Meteorol. Soc. Japan, 61, 3, 375–387, 1983.

Kuba, N. and Iwabuchi, H.: Revised parameterization to predict cloud droplet concentration and a retrieval method to predict CCN concentration, Supplement, J. Meteorol. Soc. Japan, 81, 1485–1487, 2003.

Kuba, N., Iwabuchi, H., Maruyama, K., Hayasaka, T., Takeda, T., and Fujiyoshi, Y.: Parameterization of the effect of cloud condensation nuclei on the optical properties of a non-precipitating water layer cloud, J. Meteorol. Soc. Japan, 81, 393–414, 2003.

Lohmann, U., Feichter, J., Chuang, C. C., and Penner, J. E.: Prediction of the number of cloud droplets in the ECHAM GCM, J. Goephys. Res., 104, 9169–9198, 1999.

Mordy, W.: Computation of the growth by condensation of a population of cloud droplets, Tellus, XI, 16–44, 1959.

Nakajima, T. Y. and Nakajima, T.: Wide-area determination of cloud microphysical properties from NOAA AVHRR measurements for FIRE and ASTEX regions, J. Atmos. Sci., 52, 4043–4095, 1995.

Numaguti, A.: Dynamics and energy balance of the Hadley circulation and the tropical precipitation zones: Significance of the distribution of evaporation, J. Atmos. Sci., 50, 1874–1887, 1993.

Numaguti, A., Takahashi, M., Nakajima, T., and Sumi, A.: Development of an atmospheric general circulation model, in: Reports of a New Program for Creative Basic Research Studies, Studies of Global Environment Change with Special Reference to Asia and Pacific Regions, Rep., I-3, 1–27, CCSR, Tokyo, 1995.

Reisin, T. G., Levin, Z., and Tzivion, S.: Rain production in convective clouds as simulated in an axisymmetric model with detailed microphysics. Part I: Description of model, J. Atmos. Sci., 53, 3, 497–519, 1996.

Rosenfeld, D.: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall, Geophys. Res., Lett., 26, 3105–3108, 1999.

Rosenfeld, D.: Suppression of rain and snow by urban and industrial air pollution, Science, 287, 1973–1976, 2000.

Saleeby, S. M. and Cotton, W.: A large-droplet mode and prognostic number concentration of cloud droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part I: Module descriptions and supercell test simulations, J. Appl. Meteor., 43, 182–195, 2004.

Smolarkiewicz, P. K.: A fully multidimensional positive definite advection transport algorithm with small implicit diffusion, J. Comput. Phys., 54, 325–362, 1984.

Szumowski, M. J., Grabowski, W. W., and Ochs III, H. T.: Simple two-dimensional kinematic framework designed to test warm rain microphysical models, Atmos. Res., 45, 299–326, 1998.

Takahashi, T.: Hail in an axisymmetric cloud model, J. Atmos. Sci., 33, 1579–1601, 1976.

Takeda, T. and Kuba, N.: Numerical study of the effect of CCN on the size distribution of cloud droplets. Part I. Cloud droplets in the stage of condensation growth, J. Meteor. Soc. Japan, 60, 4, 978–993, 1982.

Takemura, T., Okamoto, H., Maruyama, Y., Numaguti, A., Higurashi, A., and Nakajima, T.: Global three-dimensional simulation of aerosol optical thickness distribution of various origins, J. Geophys. Res., 105, 17 853–17 873, 2000.

Takemura, T., Nakajima, T., Dubovik, O., Holben, B. N., and Kinne, S.: Single-scattering albedo and radiative forcing of various aerosol species with a global three-dimensional model, J. Climate, 15, 333–352, 2002.

Takemura, T., Nozawa, T., Emori, S., Nakajima, T. Y., and Nakajima, T.: Simulation of climate response to aerosol direct and indirect effects with aerosol transport-radiation model, J. Geophys. Res., 110, D02202, doi:10.1029/2004JD005029, 2005.

Tsuboki, K. and Sakakibara, A.: Large-scale parallel computing of Cloud Resolving Storm Simulator, High Performance Computing, Springer, edited by: Zima, H. P., Joe, K., Sato, M., Seo, Y., and Shimasaki, M., 243–259, 2002.

Twomey, S.: The nuclei of natural cloud formation, Part II: The supersaturation in natural clouds and the variation of cloud droplet concentration, Geofis. Pura. Appl., 43, 243–249, 1959.

Twomey, S.: Pollution and the planetary albedo, Atmos. Environ., 8, 1251–1256, 1974.

Twomey, S and Squires, P.: The influence of cloud nucleus population on the microstructure and stability of convective clouds, Tellus, XI, 4, 408–411, 1959.

Twomey, S. and Waner, J.: Comparison of measurements of cloud droplets and cloud nuclei, J. Atmos. Sci., 24, 702–703, 1967.

Yun, S. S. and Hudson, J.: Maritime/continental microphysical contrasts in stratus, Tellus, 54B, 61–73, 2002.