The Sensitivity of GCM Output to Aerosol Parameterization

Golaz et al. (2011) use the most recently released version of the Geophysical Fluid Dynamics Laboratory's (GFDL) Atmospheric General Circulation Model (AGCM) called AM3 (Donner et al. (2011) to explore the 'aerosol indirect effect' (AIE) using a prognostic parameterization scheme for cloud drop numbers. The AIE is simply the impact that particulates and chemicals have on the earth's radiation budget by their influence on cloud properties. Cloud properties such as composition (ice versus water), drop size, and drop density are critical determinants in how clouds influence the earth's radiation budget.

Past studies have shown that cloud droplet numbers are a function of aerosol types, temperature, pressure, and vertical motion (which is related to turbulence). Golaz et al. (2011) provide a 6 year control simulation of climate after allowing one year for model equilibration. Then they change the cloud drop numbers in a predictive cloud scheme by reducing the turbulence in the model (experiment 1). Then, in the second experiment an additional adjustment is made by allowing drop formation in new clouds and pre-existing clouds. The last experiment adjusts the vertical motion profile and the turbulence used in experiment 2.

When these experiments were run for one year, the latter two experiments produced more droplets making the clouds more reflective, resulting in less solar radiation coming in. Golaz et al. (2011) noted that the differences among all the experiments were similar to that of the radiative forcing differences between today and pre-industrial times. But they also observe that these short term experiments "could not be used for long-term coupled climate experiments, because the magnitude of their net top-of-the-atmosphere (TOA) radiation fluxes is unrealistically large." Then, the model configurations are re-adjusted to bring energy balance in line with the reference run.

The exact formulation of model physics and assumptions used for variables such as cloud drop numbers can have a large impact on the predicted drop number. These in turn can have a relatively large impact on the net radiation budgets. Golaz et al. (2011) then show that, in spite of these differences, there is only a small impact on the present-day climate overall. However, when the three formulations are applied between present day and pre-industrial climate, there is a large difference in the net radiation budgets, which can be attributed to the AEI (Fig. 1, below). This would likely result the model yielding "an unrealistic temperature evolution [from preindustrial to current times] compared to observations."

This paper shows that uncertainty in model formulations, especially processes like cloud parameterizations, can mean considerable uncertainty in climate projections and scenarios. The results also show that in some cases, we don't understand the output and have to adjust model physics back to our current understanding of a process or back toward our basic conservations laws. These precautions are exactly the type many scientists have advised taking when looking at future climate scenarios.

Additional Reference
Donner, L.J., Wyman, B.L., Hemler, R.S., Horowitz, L.W., Ming, Y., Zhao, M., Golaz, J.-C., Ginoux, P., Lin, S.-J., Schwarzkopf, M.D., Austin, J., Alaka, G., Cooke, W.F., Delworth, T.L., Freidenreich, S.M., Gordon, C.T., Griffies, S.M., Held, I.M., Hurlin, W.J., Klein, S.A., Knutson, T.R., Langenhorst, A.R., Lee, H.-C., Lin, Y., Magi, B.I., Malyshev, S.L., Milly, P.C.D., Naik, V., Nath, M.J., Pincus, R., Ploshay, J.J., Ramaswamy, V., Seman, C.J., Shevliakova, E., Sirutis, J.J., Stern, W.F., Stouffer, R.J., Wilson, R.J., Winton, M., Wittenberg, A.T. and Zenga, F. 2011. The dynamical core, physical parameterizations, and basic simulations characteristics of the atmospheric component of the GFDL Global Coupled Model CM3. Journal of Climate 24: 3484-3519.