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enough to enable the plant to survive a long dry period later jn the year. While the study does not alter observed temperatures, it does show the effect of temperature stress in reducing grain yield. Temperature stress can sometimes offset the positive effects of adequate or even abundant precipi- tation. These findings apply both to observed conditions and to the precipi- tation enhancement scenarios. Study results have implications for weather modification plannjng and opera- tions. Those scenarios which treat a broad spectrum of precipitation events are more effective in increasing yield than those which treat only particular ranges of precipitation amount. The broad-spectrum scenarios provide more additional precipitation and also have a higher probability of' an event occurring at the "right" time. The model analyses show that additional precipitation is usually useful whenever it occurs, even in many years with above-normal precipitati'on. The need for additional precipitation, however, is not necessarily accompanied by meteorological opportunity. Furthermore, the ability to forecast low precipitation years (or seasons) is less than perfect. These factors suggest that the most practical weather modification program is one that is designed to operate every year and is prepared to treat each suitable event whenever it occurs. THE GRAIN SORGHUM MODEL The grain sorghum model used was developed by Arkin, Vanderlip, and Ritchie (1976). It is a physiological model which simulates the growth and develop- ment of a single grain sorghum plant representative of a sorghum crop from planting to physiological maturity. ' The model requires both meteorological and agricultural data. The meteoro- logical data are daily values of precipitation, solar radiation, and maximum and minimum temperature. The agricultural data relate to the plant and the soil in which it grows. These data describe the particular variety being modeled by stating the maximum number of leaves on the plant and the maximum area of each leaf. For this study, the variety-related data as well as plant population were not changed from those originally used by the developers. Other agricultural data required for a given site are the row Spacing, the planting depth, the soil water initially available, the maximum available soil water, parameters that describe the evaporative properties of the soil, and the latitude of the site. The agricultural variables are fixed for a given site so that only the effects of the meteorological variables are investigated. . In operation, the model uses the combined effects of heat, radiation, and soil water to grow the plant. The importance of precipitation is reflected through its impact on the soil water level. After planting, an adequate amount of soil water and heat must be present to permit germination and subsequent emergence of the plant. After emergence, photosynthesis begins. As the plant grows and develops, the rate of total photosynthate production increases. Production of photosynthate is reduced if the plant experiences water stress or temperature stress. Water stress is calculated through an algorithm which determines the soil water available as a function of precipi- tation received and evaporation from the plant and soil surface. The stress 2