Scarcity of available records is a major hindrance in hurricane hazard assessment. In addition, frequency analysis on maximum intensities of all historical storms is incapable of analyzing very rare phenomena. Ensemble generation is crucial for circumventing these difficulties, targeted at this study. We will show here that ensembles like Sandy can be statistically generated even by removing its trajectory from historical records. We began with historical compilations of NOAA National Climatic Data Center (NCDC) tropical cyclone (TC) database. TC reaching a hurricane strength and making landfall in or passing close to the United States were identified. The geographical area influenced by these hurricanes was discretized and the parameters of Markov chains and multivariate distributions were derived for each discretized area. Synthetic tracks were generated using repetitive random draws from the spatiotemporal distribution of historical genesis and storm motion, conditioned by Markov chains for each 6-hour displacement. The proposed algorithm is validated in macro and micro scales. In macro scale, tracks coming within the specified radius of an area of interest were counted for a given hurricane scale. The results revealed that the general pattern of hits conforms well to historical observations. In micro scale, the model was evaluated for Miami and New York City with quite different hurricane climatology. The track generator produces a history of potential wind and translational speeds for both of these regions as well.