Two recent cloud resolving model (CRM) simulations involving studies of tropi- cal water and energy cycles have shown remarkably different hydrodynamic equi- librium (climate) states even with similar 2-D models and initial sounding data. Sui et al. (1994, hereafter S94) generated a cold/dry statistical equilibrium state, while Grabowski et al. (1996, hereafter G96) produced a warm/moist equilibrium state. By investigating a series of sensitivity experiments using a 2-D Goddard Cumulus Ensemble (GCE) model, we conclude that the drama- tically different climates can mainly be attributed to the so-called "nudging" effect (Tao et al., 1998). The horizontal wind shear employed in S94 was much weaker due to the strongly mixed winds by convective processes, while the wind shear was maintained nearly constant and strong in G96 through a geostrophic balance. This almost constant wind shear can similarly be obtained by adding an extra "nudging" (relaxation) term to the horizontal winds, which is therefore termed as a "nudging" effect.
It is also found that the minimum surface wind speed (imposed in the bulk for- mula for computing surface fluxes) plays a crucial role in climate change for experiments with mixed wind shear (as in S94). In general, the equilibrium state reaches a warmer and more humid regime as the minimum wind speed increa- ses that accounts for a larger latent heat flux supply. On the other hand, the nudging wind shear exerts a greater impact on the climate change as the imposed minimum wind speed becomes weaker. Aforementioned features are all based on results from a 2-D CRM model. Robe and Emanuel (1996) pointed out that the convection in the 3-D simulations was biased toward 2-D structure due to the prescribed vertical wind shear and maintained 2-D temperature disturbance, and claimed the necessity of 3-D simulations for at least the unsheared case. Some interesting questions about dimensionality may then be raised in this study. First, will the 3-D simulations also reach equilibrium states as their 2-D counterparts do? If so, then do they reach the same states, and do they take a longer or shorter time? Second, will the 3-D simulations modify the impact on climate changes by the vertical wind shear condition, which is found in the 2-D simulations? Then, are the involved physical processes affected as well? Answers for these posed questions will be presented at the conference.
References:
Grabowski, W. W., M. W. Moncrieff, and J. T. Kiehl, 1996: Long-term behavior of precipitating tropical cloud systems: A numerical study. Quart. J. Roy. Meteor. Soc., 122, 1019-1042.
Robe, F. R., and K. A. Emanuel, 1996: Moist convective scaling: some inferen- ces from three-dimensional cloud ensembles simulations. J. Atmos. Sci., 53, 3265-3275.
Sui, C.-H., K. M. Lau, W.-K. Tao, and J. Simpson, 1994: The tropical water and energy cycles in a cumulus ensemble model. Part I: Equilibrium climate. J. Atmos. Sci., 51, 711-728.
Tao, W.-K., J. Simpson, C.-H. Sui, C.-L. Shie, B. Zhou, K. M. Lau, and M. Moncrieff, 1998: On equilibrium States simulated by cloud-resolving models. J. of Atmos. Sci. (modified)