Operational and research applications generally use the consensus approach for forecasting the track and intensity of tropical cyclones (TCs) due to the spatial displacement of the TC location and structure in ensemble member forecasts. This approach simply averages the location and intensity information for TCs in individual ensemble members, which is distinct from the traditional pointwise arithmetic mean (AM) method for ensemble forecast fields. The consensus approach, despite having improved skills relative to the AM in predicting the TC intensity, cannot provide forecasts of the TC spatial structure. We introduced a unified TC ensemble mean forecast based on the feature-oriented mean (FM) method to overcome the inconsistency between the AM and consensus forecasts. FM spatially aligns the TC-related features in each ensemble field to their geographical mean positions before the amplitude of their features is averaged.We select 219 TC forecast samples during the summer of 2017 for an overall evaluation of the FM performance. The results show that the TC track consensus forecasts can differ from AM track forecasts by hundreds of kilometers at long lead times. AM also gives a systematic and statistically significant underestimation of the TC intensity compared with the consensus forecast. By contrast, FM has a very similar TC track and intensity forecast skill to the consensus approach. FM can also provide the corresponding ensemble mean forecasts of the TC spatial structure that are significantly more accurate than AM for the low- and upper-level circulation in TCs. The FM method has the potential to serve as a valuable unified ensemble mean approach for the TC prediction.