A method of developing scenarios of future temperature conditions resulting from climatic change is presented. The method is straightforward and can be used to provide information about daily temperature variations and diurnal ranges, monthly average high and low temperatures, and the frequency with which user-selected high- and low-temperature thresholds are crossed. Linear regressions between monthly average temperature and these various attributes are established by using the observational record of daily maximum and minimum temperature. These regressions are then used to estimate values from the monthly average temperatures estimated by General Circulation Models to occur as a result of a doubling of atmospheric CO(2). Values can be established for any location having daily temperature records. For the United States the station density is sufficient to allow the creation of detailed regional scenarios on the spatial and temporal scales required for impact assessment. The assumptions, scientific and statistical, inherent in this regression-based approach are reviewed. The method has been incorporated into a self-contained PC-based computer program requiring only the actual temperature data to be input by the user. A demonstration of the use of the program, incorporating discussion of techniques for evaluating the quality of the resultant scenario, is provided.