Application of Stochastic Techniques to the ARM Cloud- Radiation Parameterization Problem

Stochastic shortwave radiative transfer through cloud fields has been shown to be a promising approach for modeling cloud-radiation interactions when the cloud field has a horizontal fraction between 0.2 and 0.8. The improvement of a stochastic technique over a plane-parallel one is that statistical information about the horizontal size and spacing of clouds may be incorporated in the radiative transfer calculations. However, several important factors must be considered in applying this approach to cloudradiation parameterization such as the impact of the new scheme on atmospheric dynamics, and interaction of the algorithm with the model environment. More significantly, most atmospheric models do not calculate horizontal cloud scale information. Therefore, the determination of when a stochastic approach is appropriate, given the information available in current atmospheric general circulation models, and how to apply that approach is critical. Results from preliminary studies exploring the coupling of the SIO single-column model with the stochastic model are shown. Recent work exploring the difficulties in incorporating horizontal cloud-scale information from an AGCM environment into the stochastic model using regional scale model cloud liquid water fields will also be discussed. The stochastic technique is also being explored as a method for modeling shortwave radiative transfer through mixed phase clouds.

[1]  G. McFarquhar,et al.  Single-Scattering Properties of Mixed-Phase Arctic Clouds at Solar Wavelengths: Impacts on Radiative Transfer , 2004 .

[2]  R. Somerville,et al.  Diagnostic Modeling of the Indian Monsoon Onset. Part I: Model Description and Validation , 1991 .

[3]  James O. Pinto,et al.  Autumnal Mixed-Phase Cloudy Boundary Layers in the Arctic , 1998 .

[4]  Minghua Zhang,et al.  Constrained Variational Analysis of Sounding Data Based on Column-Integrated Budgets of Mass, Heat, Moisture, and Momentum: Approach and Application to ARM Measurements. , 1997 .

[5]  J. Curry,et al.  Surface Heat Budget of the Arctic Ocean , 2002 .

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

[7]  R. Somerville,et al.  Diagnostic Modeling of the Indian Monsoon Onset. Part II: Budget and Sensitivity Studies , 1991 .

[8]  Edgar L. Andreas,et al.  An annual cycle of Arctic surface cloud forcing at SHEBA : The surface heat budget of arctic ocen (SHEBA) , 2002 .

[9]  M. Shupe,et al.  Cloud Radiative Forcing of the Arctic Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith Angle , 2004 .

[10]  M. Shupe,et al.  An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA , 2002 .

[11]  Dynamical controls on sub-global climate model grid-scale cloud variability for Atmospheric Radiation Measurement Program (ARM) case 4 , 2005 .

[12]  Richard C. J. Somerville,et al.  Radiative Transfer through Broken Clouds: Observations and Model Validation , 2002 .

[13]  M. H. Zhang,et al.  Objective Analysis of ARM IOP Data: Method and Sensitivity , 1999 .