coupled to the ocean model that forecasts tropical Pacific SST or on the scale of the model used afterward to forecast from the SST forecast to the global effects of ENSO. This level of spatial resolution (on the order of 400km) is adequate for some practical purposes, but in regions with significant variations in elevation or terrain, a more finely grained regional forecast is often needed. For example, in the U.S. Pacific Northwest, weather systems come from the Pacific over the Olympic mountains leaving large rain shadows on the eastern slopeslocations no more than 50km apart can have annually averaged precipitation differing by a factor of five. Since precipitation is generally specific to spatial patterns of elevation and since many applications require specific locations for rainfall (e.g., rain falling on opposite sides of a mountain divide will fall in different catchment basins and therefore raise different reservoirs), these applications require finer spatial resolution. To make the forecasts useful for these purposes will require the use of finer-grained atmospheric models. This approach is under considerable development (Giorgi and Mearns, 1991) and these so-called mesoscale atmospheric models promise to be the tool of choice in downscaling seasonal-to-interannual forecasts.
Mesoscale models are also useful for examining the evolution of predicted extreme events. In some regions of the United States, the most important type of forecast is that of severe storms (e.g., tornadoes and hailstorms in the Great Plains in summer, hurricanes on the Atlantic and Gulf coasts in fall). Although no climate forecast scheme can predict a specific storm even a season in advance, mesoscale models embedded in larger-scale climate prediction models can indicate that the conditions under which storms form may be present and give some indications of where they might form and of their likely frequency.
ENSO forecasts have been used most where their skill is highest and weather variations are relatively small. In Peru, Ecuador, Australia, and the Pacific Islands, precipitation and temperature are tightly tied to the variations of tropical Pacific SST connected with ENSO, and the skill of predicting SST variations is relatively high (Figure 2-2). It is not surprising that these forecasts are used extensively. In the United States, however, the skill of the forecasts is lower and the variability in the phenomena to be predicted is higher. At least before the 1997-1998 ENSO events, the forecasts were not uniformly used in the sectors affected by seasonal-to-interannual climate variability.
An industry that has used the forecasts is California squid fishing. A forecast of warm water in the tropical Pacific implies warm water off the coast of California and therefore also implies declines in the squid catch.