The quality of ensemble forecasting is seriously affected by sample quality. In this study, the distributions of ensemble members based on the observed track and intensity of tropical cyclones (TCs) were optimized and their influence on the simulation results was analyzed. Simulated and observed tracks and intensities of TCs were compared and these two indicators were combined and weighted to score the sample. Samples with higher scores were retained and samples with lower scores were eliminated to improve the overall quality of the ensemble forecast. For each sample, the track score and intensity score were added as the final score of the sample with weight proportions of 10 to 0, 9 to 1, 8 to 2, 7 to 3, 6 to 4, 5 to 5. These were named as “tr”, “91”, “82”, “73”, “64”, and “55”, respectively. The WRF model was used to simulate five tropical cyclones in the northwestern Pacific to test the ability of this scheme to improve the forecast track and intensity of these cyclones. The results show that the sample optimization effectively reduced the track and intensity error, “55” usually had better performance on the short-term intensity prediction, and “tr” had better performance in short-term track prediction. From the overall performance of the track and intensity simulation, “91” was the best and most stable among all sample optimization schemes. These results may provide some guidance for optimizing operational ensemble forecasting of TCs.