Tropical Ice Cloud Simulations Using Scripps Single Column Model (SCM) Reveal Range of Model Uncertainties

McFarquhar, G., University of Oklahoma

General Circulation and Single Column Models/Parameterizations

Cloud Modeling

McFarquhar, G.M., S. Iacobellis, R.C.J. Somerville. SCM Simualtions of Tropical Ice Clouds Using Observationally Based Parameterizations of Microphysics, Journal of Climate: Vol 15, No. 11, pp. 1643-1664.


Sponsored by DOE's Office and Biological and Environmental Research, the ARM Program continues to improve and refine modeling information used in global climate research (ARM graphic).


Sponsored by DOE's Office and Biological and Environmental Research, the ARM Program continues to improve and refine modeling information used in global climate research (ARM graphic).

Key Contributors: S. Iacobellis, R.C.J. Somerville

Clouds are the single largest factor in regulating the absorption of solar energy by the earth. Climate models predict the amount of condensed water in a cloud based on model dynamics and water conservation, but they don't usually predict the size of the cloud particles. However, the size affects how much solar (shortwave) radiation is scattered back to space or is passed through to earth, and how much longwave radiation is emitted. Therefore, the size of the particles in the cloud is a critical factor in determining the effect of the cloud on the radiation budget (cloud radiative forcing).

Because particle sizes are not predicted, they are specified by approximate expressions, called parameterizations, that are based on some combination of theory and observation. These expressions are especially critical for ice clouds due to the irregular shape and large range of sizes of ice crystals. To improve the way ice clouds are treated in climate models, researchers sponsored by DOE's Atmospheric Radiation Measurement (ARM) Program conducted simulations of tropical clouds using observations from ARM's Tropical Western Pacific site and the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE).

Armed with data from in situ observations of the size and shape of ice crystals in tropical anvils, researchers implemented a range of empirical coefficients to describe the mean ice crystal size using the Scripps Institution of Oceanography single column model (SCM) in both interactive and non-interactive simulations. These coefficients vary with temperature. They found that where the size and shape of ice crytals is concerned, a simulation based on an average of the values of the coefficients does not give the same result as the average of a set of simulations using varying coefficients. They also concluded that, until multivariate dependences of the average cloud particle radius can be better described, parameterizations should provide a range of coefficients or ranges of possible average particle radius values. Whether the parameterization developed in this study can be used for non-tropical cloud types remains to be determined.

Experiments were conducted to illustrate the sensitivity of modeled cloud and radiative fields, and also to determine the mechanisms by which different parameterization schemes affect those fields. Interactive simulations (changes in microphysical properties produce changes in heating profiles that affect ice and cloud mass) and noninteractive simulations (forced values for microphysical properties provide no feedback) were performed. The interactive simulations helped to determine the net uncertainties associated with the different parameterization schemes, whereas the noninteractive simulations helped identify which factors cause variations in predicted cloud and radiative properties.