Abstract In this study, we developed two high-resolution future ocean regional projection datasets for coastal applications in Japan, in which we made use of dynamical downscaling via regional ocean models with atmospheric forcing from two climate models (i.e., MIROC5 and MRI-CGCM3) participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) under historical, representative concentration pathway (RCP) 2.6, and RCP8.5 scenarios. The first dataset was an eddy-resolving 10-km resolution product covering the North Pacific Ocean area and ranging continuously from 1981 to 2100, in which the Kuroshio current and mesoscale structures were reasonably resolved. The second dataset was a 2-km resolution product covering the regional domain surrounding Japan and comprising 10–15-year time slices, in which the coastal geometry and current structure were resolved even more realistically. An important feature of these datasets was the availability of reference datasets based on atmospheric and oceanic reanalysis data for cross-validation during the historical run period. Using these reference datasets, biases of regional surface thermal properties and the Kuroshio states during the historical run period were evaluated, which constitute important information for users of the datasets. In these downscaled datasets, the future surface thermal responses were generally consistent with those of their original data. Utilizing the high-resolution property of the downscaled data, possible future impact analyses regarding coastal phenomena such as strait throughflows, coastal sea level variability, and the Kuroshio intrusion phenomenon into bays (“Kyucho” phenomenon) were demonstrated and the important role of the Kuroshio state representation was indicated, which had proved difficult to analyze using the low-resolution projection data. Given these properties, the present datasets would be useful in climate change adaptation studies regarding the Japanese coastal region.