| description abstract | Assuming that SST provides the major lower boundary forcing for the atmosphere, observed SSTs are prescribed for an ensemble of atmospheric general circulation model (GCM) simulations. The ensemble consists of 9 ?decadal? runs with different initial conditions chosen between 1 January 1979 and 1 January 1981 and integrated about 10 years. The main objective is to explore the feasibility of seasonal forecasts using GCMS. The extent to which the individual members of the ensemble reproduce the solutions of each other (i.e., reproducibility) may be taken as an indication of potential predictability. In addition, the ability of a particular GCM to produce realistic solutions, when compared with observation, must also be addressed as part of the predictability problem. A measure of reproducibility may be assessed from the spread among ensemble members. A normalized spread index, σn/σs, can be defined at any point in space and time, as the variability of the ensemble (σn) normalized by the climatological seasonal variability (σs). In the time mean it is found that the reproducibility is significantly below unity for certain regions. Low values of the spread index are seen generally in the Tropics, whereas the extratropies does not exhibit a high degree of reproducibility. However, if one examines plots in time of seasonal mean σn/σs for the U.S. region, for example, it is found that for certain periods this index is much less than unity, perhaps implying ?occasional potential predictability.? In this regard, time series of ensemble mean soil moisture and precipitation over the United States are compared with corresponding observations. This study reveals some marginal skill in simulating periods of drought and excessive wetness over the United States during the 1980s (i.e., the droughts of 1981 and 1988 and the excessive wetness during the 1982/83 El Niño). In addition, by focusing on regions of better time-averaged reproducibility-that is, the southeast United States and northeast Brazil-a clearer indication of a relationship between good reproducibility and seasonal predictability seems to emerge. | |
