A physically based scheme for the treatment of stratiform clouds and precipitation in large‐scale models. I: Description and evaluation of the microphysical processes

A stratiform-cloud and precipitation scheme, incorporating prognostic variables for cloud liquid water and cloud ice, has been developed for the CSIRO global climate model (GCM). the scheme includes physically based treatments of key microphysical processes, turbulent mixing and semi-Lagrangian advection of cloud-water species and interactive cloud radiative properties. Objectives in the development of the scheme were to improve upon the physical realism of parametrizations used in earlier schemes, whilst also trying to provide a scheme with moderate computational overheads. The parametrized microphysical processes are evaluated in relation to observations and theory, and are compared to treatments used in earlier schemes in a series of short GCM experiments. It is argued that the treatment of precipitation formation in warm, and mixed-phase, stratiform clouds is more realistic in the present scheme than in earlier schemes, which used crude methods for the parametrization of autoconversion, and did not treat key ice-processes in a consistent way. In the present scheme, accretion processes are more important, whereas autoconversion is less important than in earlier schemes. To determine whether the cloud scheme requires the use of a reduced (split) time-step, the sensitivity of the various terms to the time-step is evaluated in another series of short GCM experiments. It is shown that the various terms are not very sensitive to the time-step, so the scheme can be efficiently implemented without the use of a split time-step. Overall, analytical or time-centred treatments perform better than implicit or explicit schemes, especially in the calculation of the precipitation of cloud ice, where only an accurate analytical treatment is found to perform satisfactorily at large time-steps. As a preliminary validation of the scheme, zonal-mean fields from a six-year model-run are presented for the month of July. the results generally agree well with observations; in particular, the modelled cloudiness and long-wave cloud-forcing fields are more realistic than those obtained with the standard version of the CSIRO GCM.

[1]  R. Davies,et al.  Observational evidence of plane parallel model biases: Apparent dependence of cloud optical depth on solar zenith angle , 1996 .

[2]  R. Rasmussen,et al.  A Wind Tunnel Investigation of the Rate of Evaporation of Small Water Drops Falling at Terminal Velocity in Air , 1971 .

[3]  D. Randall,et al.  Liquid and Ice Cloud Microphysics in the CSU General Circulation Model. Part 1: Model Description and Simulated Microphysical Processes , 1996 .

[4]  J. Royer,et al.  A statistical cloud scheme for use in an AGCM , 1993 .

[5]  Paul W. Stackhouse,et al.  The Relevance of the Microphysical and Radiative Properties of Cirrus Clouds to Climate and Climatic Feedback , 1990 .

[6]  Peter V. Hobbs,et al.  Fall speeds and masses of solid precipitation particles , 1974 .

[7]  William R. Cotton,et al.  A Numerical Investigation of Several Factors Contributing to the Observed Variable Intensity of Deep Convection over South Florida , 1980 .

[8]  B. J. Mason,et al.  The evaporation of ice spheres and ice crystals , 1966 .

[9]  S. Ghan,et al.  Computationally Efficient Approximations to Stratiform Cloud Microphysics Parameterization , 1992 .

[10]  D. E. Shaw,et al.  The Growth Rates and Densities of Ice Crystals between −3°C and −21°C , 1976 .

[11]  G. L. Stephens,et al.  The Interpretation of Remotely Sensed High Cloud Emittances , 1980 .

[12]  M. Tiedtke.  Parameterization of Cumulus Convection in Large-Scale Models , 1988 .

[13]  Edwin X. Berry,et al.  An Analysis of Cloud Drop Growth by Collection: Part I. Double Distributions , 1974 .

[14]  H. Treut,et al.  Sensitivity of the LMD General Circulation Model to Greenhouse Forcing Associated with Two Different Cloud Water Parameterizations , 1994 .

[15]  Andrew J. Heymsfield,et al.  Relative Humidity and Temperature Influences on Cirrus Formation and Evolution: Observations from Wave Clouds and FIRE II , 1995 .

[16]  A. Simmons,et al.  The calculation of geopotential and the pressure gradient in the ECMWF atmospheric model: Influence on the simulation of the polar atmosphere and on temperature analyses , 1991 .

[17]  P. Hobbs,et al.  Ice particle concentrations and precipitation development in small continental cumuliform clouds , 1994 .

[18]  R. M. Welch,et al.  Stratocumulus Cloud Field Reflected Fluxes: The Effect of Cloud Shape , 1984 .

[19]  A. Semtner.  A MODEL FOR THE THERMODYNAMIC GROWTH OF SEA ICE IN NUMERICAL INVESTIGATIONS OF CLIMATE , 1975 .

[20]  P. Krummel,et al.  A soil-canopy scheme for use in a numerical model of the atmosphere: 1D stand-alone model , 1991 .

[21]  R. Chervin,et al.  Global distribution of total cloud cover and cloud type amounts over the ocean , 1988 .

[22]  Albert A. M. Holtslag,et al.  Local Versus Nonlocal Boundary-Layer Diffusion in a Global Climate Model , 1993 .

[23]  J. Hansen,et al.  A parameterization for the absorption of solar radiation in the earth's atmosphere , 1974 .

[24]  David A. Randall,et al.  Cloud Parameterization for Climate Modeling: Status and Prospects , 1989 .

[25]  H. Pruppacher,et al.  A Numerical Investigation of Collision Efficiencies of Simple Ice Plates Colliding With Supercooled Water Drops , 1974 .

[26]  Peter N. Francis,et al.  An observational and theoretical study of the radiative properties of cirrus: Some results from ICE'89 , 1994 .

[27]  Robert F. Cahalan,et al.  The albedo of fractal stratocumulus clouds , 1994 .

[28]  Hilding Sundqvist,et al.  A parameterization scheme for non-convective condensation including prediction of cloud water content , 1978 .

[29]  Yefim L. Kogan,et al.  Evaluation of radiative parameterizations using an explicit cloud microphysical model , 1995 .

[30]  R. Gunn,et al.  THE TERMINAL VELOCITY OF FALL FOR WATER DROPLETS IN STAGNANT AIR , 1949 .

[31]  A. Slingo.  A GCM Parameterization for the Shortwave Radiative Properties of Water Clouds , 1989 .

[32]  A. Simmons,et al.  The ECMWF medium-range prediction models development of the numerical formulations and the impact of increased resolution , 1989 .

[33]  John F. B. Mitchell,et al.  Carbon Dioxide and Climate. The Impact of Cloud Parameterization , 1993 .

[34]  Andrew J. Heymsfield,et al.  Precipitation Development in Stratiform Ice Clouds: A Microphysical and Dynamical Study , 1977 .

[35]  John F. B. Mitchell,et al.  Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models , 1990 .

[36]  K. E. Taylor,et al.  Response of the climate system to atmospheric aerosols and greenhouse gases , 1994, Nature.

[37]  H. Gordon.  A Flux Formulation of the Spectral Atmospheric Equations Suitable for Use in Long-Term Climate Modeling , 1981 .

[38]  Leon D. Rotstayn,et al.  The CSIRO 9-level atmospheric general circulation model , 1993 .

[39]  S. Clough,et al.  The evaporation of frontal and other stratiform precipitation , 1991 .

[40]  J. Marshall,et al.  THE DISTRIBUTION OF RAINDROPS WITH SIZE , 1948 .

[41]  Harshvardhan,et al.  Comments on ``The Parameterization of Radiation for Numerical Weather Prediction and Climate Models'' , 1985 .

[42]  N. Fletcher.  The Physics of Rainclouds , 1962 .

[43]  R. Rauber,et al.  Numerical Simulation of the Effects of Varying Ice Crystal Nucleation Rates and Aggregation Processes on Orographic Snowfall , 1986 .

[44]  T. Ose.  An examination of the effects of explicit cloud water in the UCLA GCM , 1993 .

[45]  J. Mitchell,et al.  C02 and climate: a missing feedback? , 1989, Nature.

[46]  J. McGregor,et al.  Economical Determination of Departure Points for Semi-Lagrangian Models , 1993 .

[47]  M. Ek,et al.  A formulation for boundary-layer cloud cover , 1991 .

[48]  John Latham,et al.  A parametrization of the ice water content observed in frontal and convective clouds , 1996 .

[49]  Henri Sauvageot,et al.  The Shape of Averaged Drop Size Distributions , 1995 .

[50]  M. Tiedtke.  An Extension of Cloud-Radiation Parameterization in the ECMWF Model: The Representation of Subgrid-Scale Variations of Optical Depth , 1996 .

[51]  Edwin X. Berry,et al.  An Analysis of Cloud Drop Growth by Collection Part II. Single Initial Distributions , 1974 .

[52]  Darren L. Jackson,et al.  A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations , 1993 .

[53]  R. Smith.  A scheme for predicting layer clouds and their water content in a general circulation model , 1990 .

[54]  J. Morcrette,et al.  Comparison of general circulation models to Earth Radiation Budget Experiment data: Computation of clear‐sky fluxes , 1992 .

[55]  Stephen B. Fels,et al.  The simplified exchange method revisited: An accurate, rapid method for computation of infrared cooling rates and fluxes , 1991 .

[56]  E. Kessler.  On the distribution and continuity of water substance in atmospheric circulations , 1969 .

[57]  D. W. Johnson,et al.  The Measurement and Parameterization of Effective Radius of Droplets in Warm Stratocumulus Clouds , 1994 .

[58]  B. Ryan,et al.  On the Global Variation of Precipitating Layer Clouds , 1996 .

[59]  J. Louis.  A parametric model of vertical eddy fluxes in the atmosphere , 1979 .

[60]  H. D. Orville,et al.  Bulk Parameterization of the Snow Field in a Cloud Model , 1983 .

[61]  D. Gregory.  A Consistent Treatment of the Evaporation of Rain and Snow for Use in Large-Scale Models , 1995 .

[62]  M. Tiedtke,et al.  Representation of Clouds in Large-Scale Models , 1993 .

[63]  Zhian Sun,et al.  Studies of the radiative properties of ice and mixed-phase clouds , 1994 .

[64]  Robert Sausen,et al.  Simulation of the present-day climate with the ECHAM model: Impact of model physics and resolution , 1992 .

[65]  J. Kristjánsson.  Tests of a new cloud treatment in an atmospheric general circulation model , 1994 .

[66]  Rodolfo Bermejo,et al.  The Conversion of Semi-Lagrangian Advection Schemes to Quasi-Monotone Schemes , 1992 .

[67]  J. Kristjánsson,et al.  Condensation and Cloud Parameterization Studies with a Mesoscale Numerical Weather Prediction Model , 1989 .

[68]  J. Curry,et al.  Cloud overlap statistics , 1989 .

[69]  S. Rutledge,et al.  The Mesoscale and Microscale Structure and Organization of Clouds and Precipitation in Midlatitude Cyclones. VIII: A Model for the “Seeder-Feeder” Process in Warm-Frontal Rainbands , 1983 .

[70]  D. L. Roberts,et al.  A climate model study of indirect radiative forcing by anthropogenic sulphate aerosols , 1994, Nature.

[71]  H. Treut,et al.  Using meteosat data to validate a prognostic cloud generation scheme , 1988 .