The sea-ice models should be required to provide an adequate simulation of the seasonal cycle of surface temperature, sea-ice thickness, and ice advection and production—all quantities that are qualitatively known from observations (e.g., Walsh et al., 1985). The ocean models must be able to simulate the climatological annual mean circulation and hydrographic structure. In the tropics there is a significant and well-documented annual cycle in the upper-level currents and hydrography that provides additional constraints on the model. Especially important is the accurate simulation of the global SST. Until recently the SST was constrained in many ocean modeling studies by a rapid forced relaxation to a prescribed climatology.

A relaxation to a climatologically observed hydrography has also been used in and below the thermocline in many numerical studies of ocean general circulation (Hibler and Bryan, 1987; Semtner and Chervin, 1988); in some instances maintenance of the thermocline is avoided by limiting the length of integrations, so equilibrium is never achieved. This practice has been useful for short-term simulations of the upper-ocean circulation away from convective regions (e.g., Philander et al., 1987) but is clearly inappropriate for the study of climate and intermediate-scale climate fluctuations. The limited observational data indicate that the entire ocean domain can be involved in climate variations on these time scales (e.g., Levitus, 1989a), although it is not clear, for instance, whether the deep ocean is necessarily an active player or just a barometer for the changing surface processes via the resultant convection.

Independent tests of the component models should also include constraints that can de deduced from certain tracers that are well observed and whose annual cycle and mean distributions are understood. For the atmosphere, these include the 85Kr, Freons, and CO2, which have already been used to independently validate the mean cross-equatorial exchange rate of one AGCM (Tans et al., 1989). For the ocean, the bomb-produced tracer 14C can be utilized to assess the accuracy of the simulated Atlantic Ocean circulation and the concomitant mixing processes (Toggweiler et al., 1989). Further insights into the oceanic mixing processes and convection, both of which are parameterized in ocean models, may be obtained by comparing the Lagrangian transport in models with observed distributions of other tracers, including the chlorofluorocarbons.

Finally, there are well-observed phenomena in the atmosphere and ocean that occur on interannual time scales that can be used to help validate the models. For the atmosphere models these include the QBO and the Southern Oscillation, and for the Pacific Ocean models, the El Niño.

There is a tremendous amount of work to be done on documenting the impact of the parameterization of unresolved physics on the simulated large-scale, low-frequency climate. Recent studies have demonstrated that different parameterizations for convection in both atmosphere and ocean GCMs can result in qualitatively different mean circulations and climate variability; an example is discussed below. Similarly, the recent advances in understanding the dynamics and thermodynamics of individual clouds must be extended to yield quantitative descriptions and parameterizations of the energy and mass transport by an ensemble of clouds on the scale of an AGCM grid.

Recent Results: Overturning the Rocks

In this section I will use three examples that I believe presage the results that will be achieved during the 1990s in modeling intermediate-time-scale climate variations.

Example 1. Over the last decade, studies have been published on the response of the wintertime Northern Hemisphere atmosphere to the principal mode of the observed interannual SST anomaly in the North Pacific Ocean (e.g., Pitcher et al., 1988). In these studies, which utilized AGCMs, investigators prescribed a perpetual January insolation to ensure statistically significant results with limited computational resources. The model's response to the prescribed SST anomaly in each of these experiments was contrary to that observed (e.g., Wallace and Jiang, 1987). The polarity of the model's geopotential anomaly was independent of the polarity of the forcing anomaly. Recently, Lau and Nath (1990; hereafter LN) examined the response of the GFDL AGCM to the observed 1950-1979 SST and an annual cycle in insolation.7 Upon isolating the circulation anomalies associated with the North Pacific SST anomalies, LN found that the model anomalies were indeed consistent with those observed (i.e., a quasi-linear relationship between anomalies in SST and geopotential). Kushnir and Lau (1992) used the same model as LN and repeated the perpetual-January experiments of Pitcher et al. (1988). The results of this study were consistent with those of the earlier perpetual-January experiments, and contrary to LN and the observational data. Thus, the discrepancies between the physics of the observed atmospheric response to SST anomalies and that found in the simulations of Pitcher et al. and of Kushnir and Lau can be explained by the prescribed unrealistic (perpetual-January) forcing. The moral here is that compromises in the experimental plan that are made because of computational constraints may lead to fallacious conclusions.

Example 2. James and James (1989) employed a primitive-equation model of the atmosphere (T21, five layers), prescribing the annual cycle as the only long-term forcing; slow variations in SST or insolation were not permitted in their experiment. In this model, the variance in the largest-scale structures in the circulation was on a decadal or longer

7  

The reader is cautioned there are significant differences between the SST forcing used by LN and that used in the earlier perpetual-January studies. Also, a different AGCM is employed.



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