The basic reproduction number R-0-the number of individuals directly infected by an infectious person in an otherwise susceptible population-is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Omega. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R-0 and Omega. However, if one considers disease spreading on a temporal contact network-where one knows when contacts happen, not only between whom-then larger R-0 does not necessarily imply larger Omega. In this paper, we numerically investigate the relationship between R-0 and Omega for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R-0 an imperfect predictor of Omega. We find that descriptors related to both temporal and topological aspects affect the relationship between R-0 and Omega, but in different ways.