Abstract：Large scale parallel Computational Fluid Dynamics (CFD) simulation has posed high demand on the data I/O capabilities. Hierarchical Data Format version 5 (HDF5) can effectively manage large scale scientific data and has a good support to parallel I/O. The HDF5 data storage model for a parallel CFD application was designed. The parallel I/O method for the application's data was implemented based on the HDF5 parallel I/O API. Performance experiments were performed on a parallel computer system. The results show that the data writing speed of this HDF5 based parallel I/O method outperforms the parallel I/O methods (i.e. each process writes an ordinary data file independently) by 6.9 to 16.1 times, when 4 to 32 processes are used. The data reading speed of this HDF5 based parallel I/O method is slower than the parallel I/O methods, with a speed of 20% to 70% times of the latter. However, the cost of data reading time is much smaller than the cost of data writing time, hence has minor effect on the total performance.