Because of the lack of data on past hurricanes, empirical evaluations of the statistics needed for risk management are very uncertain. An alternative strategy is to use a hurricane model to produce large sets of synthetic hurricane tracks. This method provides, for 11 regions of the U.S. Atlantic and Gulf coast, the annual landfall probabilities of hurricanes from each category of the Saffir-Simpson scale. This model can be used to investigate the future of hurricane risks. As a first step, the model is run with a 10-percent increase in potential intensity. Annual landfall probabilities increase in all regions, especially for the strongest hurricanes. The vulnerability of each U.S. coastal county is then calibrated using data on past hurricanes and their normalized economic losses. Annual hurricane damages increase by +54 percent in response to a 10 percent increase in potential intensity, meaning that the average normalized losses caused by hurricanes would increase from approximately $8 billion to about $12 billion a year. More importantly, an analysis of indirect economic impacts shows that total economic losses due to an event are increasing nonlinearly as a function of its direct losses, because destructions both increase reconstruction needs and reduce reconstruction capacity. As a consequence, the increase in frequency of the very rare events with large-scale losses may be more problematic than the change in annual mean losses. These results suggest that hurricane losses are very sensitive to changes in potential intensity and may rise significantly in response to climate change. This paper calls, therefore, for taking into account hurricane damages in the analysis of climate policies, even though other factors like population evolution, economic growth and preparedness may remain the main drivers of hurricane damages.