Abstract: To improve the objective prediction of aircraft turbulence, a new aviation turbulence ensemble prediction algorithm based on the energy dissipation rate (referred to as EDR) is designed. The forecast value can be directly compared and verified with the new turbulence data (EDR) obtained by airborne detection, and the forecast intensity is unaffected by the difference in aircraft type. The algorithm calculates multiple forecast indices representing clear air turbulence (CAT) and mountain wave turbulence (MWT) using the basic meteorological elements of the Mesoscale Weather Numerical Forecast System of CMA (CMA-MESO). Under the assumption that the EDR observations and predicted turbulence diagnostics both approximately follow a normal distribution. According to the probability density matching relationship between previous forecast indices and EDR observations, the original forecast index is converted into the forecast value with EDR in the real-time numerical forecast. Multiple forecast indices are given different weights according to the forecast scores, and they are integrated into EDR turbulence forecast products, including CAT and MWT. The subjective and objective verification results show that this turbulence forecast product can roughly reflect the turbulence in different regions and types. The integration prediction of multiple algorithms is generally better than that of a single index forecast. The resulting relative operating characteristics curves show that the forecast results of light-or-greater intensity turbulence increase the hit rate and reduce the false alarm rate, and the aviation turbulence ensemble prediction algorithm has high forecasting capability.