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To investigate future variations in high-impact weather events, numerous samples are required. For the detailed assessment in a specific region, a high spatial resolution is also required. A simple ensemble simulation technique is proposed in this paper. In the proposed technique, new ensemble members were generated from one basic state vector and two perturbation vectors, which were obtained by lagged average forecasting simulations. Sensitivity experiments with different numbers of ensemble members, different simulation lengths, and different perturbation magnitudes were performed. Experimental application to a global warming study was also implemented for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric conditions showed similar characteristics across the sensitivity experiments. The frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the proposed technique. On the other hand, considerable ensemble spread was found in each ensemble experiment. In addition, the results of the application to a global warming study showed possible variations in the future. These results indicate that the proposed technique is useful for investigating various meteorological phenomena and the impacts of global warming. The results of the ensemble simulations also enable the stochastic evaluation of differences in high-impact weather events. In addition, the impacts of a spectral nudging technique were also examined. The tracks of a typhoon were quite different between cases with and without spectral nudging; however, the ranges of the tracks among ensemble members were comparable. It indicates that spectral nudging does not necessarily suppress ensemble spread.

Plain Language Summary To investigate future variations in high-impact weather events, numerous samples of similar weather phenomena are indispensable. A high spatial resolution is also required in future projections for the detailed assessment of global warming effects in a specific region, river basin, or city. A simple and robust ensemble simulation technique for a numerical weather model was proposed in this study. Experiments with different numbers of ensemble members and different simulation lengths were performed for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric temperature, and maximum wind speed showed similar characteristics among these experiments. Frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the ensemble simulations. The proposed method has a broad utility and can be applied to any type of weather event. The ensemble simulation technique was applied to simulations with future pseudo global warming conditions. Comparison of ensemble simulation results of a high-impact weather event under current and future climate reveals whether variations were caused by global warming or meteorological chaotic behaviors. In addition, ensemble simulations enable the stochastic evaluation of differences in high-impact weather events between current and future climates.