An observational study of drizzle formation in stratocumulus clouds for general circulation model (GCM) parameterizations

[1] Climate model parameterization of precipitation formation in boundary layer stratocumulus clouds is a challenge that needs to be carefully addressed for simulations of the aerosol impact on precipitation and on cloud life time and extent, the so-called second indirect effect of aerosol on climate. Existing schemes are generally tuned against global observations of the liquid water path, as very few in situ observations are available for their validation. This issue is addressed here with data collected during the second Aerosol Characterization Experiment. The methodology is different from previous experimental studies in the sense that each case study is first analyzed for retrieving properties that are representative of the observed cloud system as a whole, such as the cloud system geometrical thickness, droplet concentration, precipitation flux, etc. Special attention is given to the characterization of the droplet number concentration by deriving a value that is representative of the aerosol activation process instead of the mean value over the cloud system. The analysis then focuses on the variability of these cloud system values for eight case studies with different aerosol backgrounds. The data set reveals that precipitation forms when the maximum mean volume droplet radius in the cloud layer reaches values >10 μm, the same critical value as previously used in cloud resolving models. This maximum radius can be predicted with an adiabatic diagnostic on the basis of cloud geometrical thickness and droplet number concentration. The measured reduction rate of drizzle water content by precipitation is also compared to predictions of auto-conversion and accretion production rates derived from existing bulk parameterizations initialized with the measured values of cloud droplet and drizzle water content. The good agreement with the parameterizations suggests that the cloud layer reaches a nearly steady state characterized by a balance between the production and reduction rates of cloud and drizzle water content. Finally, it is shown that the cloud system precipitation rate can be expressed as a power law of cloud geometrical thickness and cloud droplet number concentration, hence providing a simple large-scale parameterization of the precipitation process in boundary layer clouds.

[1]  S. Twomey The Influence of Pollution on the Shortwave Albedo of Clouds , 1977 .

[2]  G. Vali,et al.  Finescale Structure and Microphysics of Coastal Stratus , 1998 .

[3]  Hanna Pawlowska,et al.  Cloud microphysical and radiative properties for parameterization and satellite monitoring of the indirect effect of aerosol on climate , 2003 .

[4]  Olivier Boucher,et al.  The sulfate‐CCN‐cloud albedo effect , 1995 .

[5]  E. Berry,et al.  Cloud Droplet Growth by Collection , 1967 .

[6]  J. Bartlett The effect of revised collision efficiencies on the growth of cloud droplets by coalescence , 1970 .

[7]  L. Schüller,et al.  Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration , 2000 .

[8]  D. Randall,et al.  Liquid and Ice Cloud Microphysics in the CSU General Circulation Model , 1996 .

[9]  H. Gerber,et al.  Microphysics of Marine Stratocumulus Clouds with Two Drizzle Modes , 1996 .

[10]  Damian R. Wilson,et al.  A microphysically based precipitation scheme for the UK meteorological office unified model , 1999 .

[11]  Leon D. Rotstayn,et al.  A physically based scheme for the treatment of stratiform clouds and precipitation in large‐scale models. I: Description and evaluation of the microphysical processes , 1997 .

[12]  J. Brenguier,et al.  Cloud condensation nuclei and cloud droplet measurements during ACE-2 , 2000 .

[13]  L. Schüller,et al.  Retrieval of microphysical, geometrical, and radiative properties of marine stratocumulus from remote sensing , 2003 .

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

[15]  Leon D. Rotstayn,et al.  On the “tuning” of autoconversion parameterizations in climate models , 2000 .

[16]  W. Cotton,et al.  Radiative impacts on the growth of a population of drops within simulated summertime Arctic stratus , 2000 .

[17]  Jean-Louis Brenguier,et al.  Droplet Spectra Broadening in Cumulus Clouds. Part I: Broadening in Adiabatic Cores , 2001 .

[18]  Leon D. Rotstayn,et al.  Indirect forcing by anthropogenic aerosols: A global climate model calculation of the effective‐radius and cloud‐lifetime effects , 1999 .

[19]  J. Brenguier,et al.  Microphysical properties of stratocumulus clouds during ACE‐2 , 2000 .

[20]  M. Khairoutdinov,et al.  A New Cloud Physics Parameterization in a Large-Eddy Simulation Model of Marine Stratocumulus , 2000 .

[21]  George Tselioudis,et al.  GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden , 2002 .

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

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

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

[25]  S. Ghan,et al.  Application of cloud microphysics to NCAR community climate model , 1997 .

[26]  Jacques Pelon,et al.  An overview of the ACE2 CLOUDYCOLUMN closure experiment , 2000 .

[27]  J. Brenguier,et al.  Aerosol activation in marine stratocumulus clouds: 1. Measurement validation for a closure study , 2003 .

[28]  Sonia M. Kreidenweis,et al.  The Impact of Giant Cloud Condensation Nuclei on Drizzle Formation in Stratocumulus: Implications for Cloud Radiative Properties , 1999 .

[29]  K. D. Beheng A parameterization of warm cloud microphysical conversion processes , 1994 .

[30]  J. Putaud,et al.  Aerosol activation in marine stratocumulus clouds: 2. Köhler and parcel theory closure studies , 2003 .

[31]  B. Stevens,et al.  An explicit cloud microphysics/LES model designed to simulate the Twomey effect , 1994 .

[32]  B. Stevens,et al.  On the relationship among cloud turbulence, droplet formation and drizzle as viewed by Doppler radar, microwave radiometer and lidar , 1999 .

[33]  Jean-Louis Brenguier,et al.  Improvements of Droplet Size Distribution Measurements with the Fast-FSSP (Forward Scattering Spectrometer Probe) , 1998 .

[34]  D. Lilly,et al.  Modeling of Stratocumulus Cloud Layers in a Large Eddy Simulation Model with Explicit Microphysics. , 1995 .

[35]  B. Albrecht Aerosols, Cloud Microphysics, and Fractional Cloudiness , 1989, Science.

[36]  J. Klett,et al.  Microphysics of Clouds and Precipitation , 1978, Nature.

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

[38]  Ulrike Lohmann,et al.  Design and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model , 1996 .

[39]  J. L. Brenguier Parameterization of the Condensation Process: A Theoretical Approach , 1991 .

[40]  Philip J. Rasch,et al.  A Comparison of the CCM3 Model Climate Using Diagnosed and Predicted Condensate Parameterizations , 1998 .

[41]  Jorgen B. Jensen,et al.  Microphysical and short‐wave radiative structure of stratocumulus clouds over the Southern Ocean: Summer results and seasonal differences , 1998 .

[42]  Steven J. Ghan,et al.  Impact of aerosol size representation on modeling aerosol‐cloud interactions , 2002 .