1. There is a rapidly growing literature on how climate affects populations of vertebrates. For large herbivorous mammals, most attention has been paid to demographic responses to climate variation. Much less information is available regarding how climate affects animal behaviour, i.e. the climate mechanisms. Further, the appropriate measurement scale of climate variables remains debated. Here, we investigate how local climate variables determine home range sizes at four temporal scales using the Börger-method on GPS telemetry data from 47 female red deer Cervus elaphus L. in Norway. 2. If local climate operates directly on the immediate activity level of the animal, we predict home range sizes to show season-specific variation on short temporal scale (weekly-daily) related to temperature and precipitation. If local climate operate indirectly through plant growth, we rather predict variation in home range sizes to be apparent on longer time scales (biweekly-monthly), and during summer only. 3. At all time scales home range size was positively correlated with temperature during winter and negatively during summer, while the effect of precipitation was season- and scale-specific, except when accumulating as snow. Extensive snow cover decreased home range size, indicating direct effects of climate. 4. The effects of local climate was weaker at the shortest time scales (weekly-daily) compared to the longest time scales (monthly-biweekly), while the effects of day length on home range size was only apparent on the monthly and daily scale. At the longest time scales variation in local climate had a large effect on home range size. This is consistent with climatic variables operating indirectly through plant growth, but we cannot exclude a certain direct effect even at longer time scales. 5. We show how local climate-home range size correlations measured over different temporal scales can be used to infer direct and indirect climate mechanisms. Insight on the behavioural basis of responses to climate enables more accurate predictions of possible nonlinear relationships to future global warming.