Abstract:The horizontal diffusion term is often used in the model to suppress nonlinear calculation instability or dampen of false short waves, but this will cause excessive dissipation of small-scale kinetic energy in the numerical model near the truncation scale. To compensate the excessively dissipated small-scale kinetic energy back to the model, a stochastic kinetic energy backscatter (SKEB) method is introduced into the CMA-REPS regional ensemble prediction system. First, based on the random field obtained in the first-order autoregressive random process in the horizontal direction expanding the spherical harmonic function we calculate the local kinetic energy dissipation rate caused by numerical diffusion scheme. Then, we construct the random flow function forcing, transform it into horizontal wind speed disturbance, and make random compensation for the dissipated kinetic energy. We carried out a 10 d ensemble prediction test and a randomized time and space scale sensitivity test in September and October 2018 (choose 1st, 7th, 13th, 19th, and 25th), and evaluated the test results here. The main conclusions of the research work are as follows. By comparing the ensemble prediction results of the test using the SKEB scheme and the test without the SKEB scheme, we see that the use of the SKEB scheme can increase the kinetic energy spectrum of the CMA-REPS regional model in the small scale region, improving the CMA-REPS ensemble prediction system to the actual atmosphere to some extent. The introduction of SKEB scheme in regional ensemble prediction can significantly improve the spread of U and V in horizontal wind field of regional model. The SKEB program has improved the forecasting skills to a certain extent, such as reducing the CRPS scores of the horizontal wind fields U and V, and also reducing the outlier scores of the horizontal wind field, temperature and 10 m wind speed. The sensitivity tests based on the SKEB method for six time scales of random pattern (1, 3, 6, 9,12, 15 h of the time series τ) and five spatial correlation scales (the maximum cutoff wave number Lmax is selected as 80, 100, 120, 160, 200, 240) show that the ensemble prediction is sensitive to the six time scales of the stochastic model of the SKEB method. And the experiment whose time scale is set to 12 h and the maximum truncation wave number is set to 240 show the best performance. Therefore, we can draw the conclusion that the SKEB scheme can compensate for the small-scale kinetic energy dissipated at the truncated scale, and effectively improve forecasting skills.