Tropical cyclones in the western North Pacific (typhoons) that make landfall on the East Asian coast are a very dangerous natural hazard. There are many densely populated coastal regions that are susceptible to high fatalities and costly damages every year due to the frequent landfall of typhoons that occur in the Pacific. One of the main climate influences on typhoons is the El Nino-Southern Oscillation (ENSO), which has been previously shown to have impacts on cyclogenesis location, track propagation, intensity, and landfall. We use a statistical tropical cyclone track model based on the IBTrACS best track data in order to model the full lifecycle of typhoons. The model components that simulate genesis and track propagation can be separately made dependent on ENSO state. We use this property of our model to isolate the changes in tracks and genesis location that cause changes in landfall. The impact of ENSO-dependent genesis is discussed in Yonekura and Hall (2011). Here, we highlight the impact of ENSO-dependent track propagation. Mean track displacements at a given location are determined by linear regression of local historical track displacements on ENSO state. This results in changes in the mean track, depending on the phase of ENSO. For typhoons that form in the southeast part of the basin or near the Philippines, the mean tracks are straight moving. Among those, the tracks that occur during a strong El Nino propagate significantly more southward compared to a strong La Nina track, which impacts the landfall locations occurring on Southeast Asia. Further, the typhoons that form in the eastern part of the basin around 10 degrees North, recurve and propagate significantly more westward during a strong El Nino year. This impacts the likelihood of a landfall on Japan. The ENSO-genesis effect shows increased landfall rates during the La Nina phases on nearly all coastlines. Overall, the combined effects of genesis and tracks in the model are able to generate realistic regional changes in landfall rates when compared to historically strong El Nino and La Nina years.