Weather forecast agencies periodically provide information on potential typhoon behavior from its formation to dissipation. This information can be used to pre-position relief goods in areas that are potentially affected by a strong incoming typhoon. The uncertainty of the typhoon behavior with respect to a point location decreases over time, thus showing the trade-off between forecast accuracy and lead time available for pre-positioning. This thesis paper presents a iterative methodology that uses a forecast-driven facility location model for pre-positioning over large networks where lead time available for pre-positioning at each location can differ. By periodically generating damage scenarios based on new forecast data and eliciting the strategic preference of the decision maker, the model determines where, when, and how much relief goods to pre-position. The model is implemented in a case study to design the pre-positioning actions in anticipation of typhoon Haiyan in the Philippines.