We carried out time-series analysis in 12 U.S. cities to estimate both the acute effects and the lagged influence of weather on total daily deaths. We fit generalized additive Poisson regressions for each city using nonparametric smooth functions to control for long time trend and barometric pressure. We also controlled for day of the week. We estimated the effect and the lag structure of both temperature and humidity on the basis of a distributed lag model. In cold cities, both high and low temperatures were associated with increased deaths. In general, the effect of cold temperatures persisted for days, whereas the effect of high temperatures was restricted to the day of the death or the immediately preceding day and was twice as large as the cold effect. The hot temperature effect appears to be primarily harvesting. In hot cities, neither hot nor cold temperatures had much effect on deaths. The magnitude of the effect of hot temperature varied with central air conditioning use and the variance of summertime temperatures. We saw no clear pattern for humidity effect. These dissimilarities indicate that analysis of the impact of any climatic change should take into account regional weather differences and harvesting.