GRAPES Regional Ensemble Forecast Side Boundary And Model Disturbance Test

Since atmospheric motion is a nonlinear dynamic system with chaotic properties,small errors in initial conditions(IC)or model can cause uncertainty in a single deterministic numerical prediction model.Ensemble prediction is an effective way to solve the uncertainty of single numerical prediction.For the high-resolution regional ensemble forecasting that meteorologists are currently focusing on,the error of the lateral boundary condition(LBC)will lead to the uncertainty of regional ensemble prediction.The existing research proves that the introduction of the lateral boundary perturbation(LBP)technique is to solve the uncertainty of the LBC.Effective methods,but at present,there are few studies on regional ensemble prediction LBP.At the same time,in the regional ensemble prediction model perturbation,the numerical weather model has less consideration of forecast uncertainty near the subgrid scale.Therefore,it is important to study the effects of LBP and model perturbation on regional ensemble prediction.Based on the GRAPES-REPS(Global and Regional Assimilation and Prediction Enhanced System-Regional Ensemble Prediction System)region ensemble prediction model,this paper studies two parts:(1)LBP method and its influence on regional ensemble forecasting;(2)model perturbation methods and their impact on regional ensemble prediction.Through these two parts of research,in order to improve the GRAPES region set probability prediction techniques.For the LBC uncertainty problem,the Dynamic Downscaling and Scaled Lagged Average Forecasting(SLAF)schemes were designed and developed in July 2015.On the 7th,7th,19 th,19th,and 25 th,a total of 6 days of ensemble prediction experiments were conducted using a probabilistic forecast test method to analyze the effects of two different LBC schemes on regional ensemble forecasting techniques.The following conclusions were obtained:(1)The total perturbation energy of the dynamic downscaling LBP scheme is larger than the SLAF method LBP scheme at each vertical level,so that the dispersion of the former on the boundary is larger than the latter,and the aggregate spread growth is more reasonable.Combining the probability prediction scores of the isobaric surface elements and the ground elements of the two schemes,the dispersion of the dynamic downscaling LBP scheme,the outliers and the Continuous Ranked Probability Score(CRPS)are better than the SLAF method LBP.The disturbance scheme indicates that the LBP of the dynamic downscaling LBP scheme is more reasonable;in the precipitation probability prediction technique,the SLAF method LBP scheme is in the TS and the grading precipitation ensemble AROC score.There is a certain advantage,but the improvement of the score does not pass the significance test,so the two schemes are considered to be equivalent to the improvement of precipitation forecast.In order to solve the problem of excessive energy dissipation near the subgrid scale in numerical weather model,the Stochastic Kinetic Energy Backscatter(SKEB)method is introduced into the GRAPES-REPS regional ensemble prediction system,and the first-order autoregressive stochastic process is used at the level.Calculate the random type obtained by spherical harmonic expansion in the direction,calculate the local dynamic energy dissipation rate caused by the numerical diffusion scheme,construct the random flow function forcing,and convert it into horizontal wind speed disturbance,compensate the dissipated kinetic energy,and carry out A 10-day ensemble prediction test and a randomized time and space scale sensitivity test in September and October 2018(choose 1st,7th,13 th,19th,and 25th),and evaluate the test results.The main conclusions of the research work are as follows:(1)By comparing the ensemble prediction results of the test using the SKEB method and the test without the SKEB method,the use of the SKEB scheme increases the large aerodynamic energy of the GRAPES regional model in the small and mediumscale region,and improves the GRAPES model to the actual atmosphere to some extent.The simulation ability of kinetic energy spectrum;the introduction of SKEB scheme in regional ensemble prediction can significantly improve the dispersion of U and V in horizontal wind field of regional model,and the problem of insufficient dispersion of large-scale dynamic energy dissipation rate in Qinghai-Tibet Plateau region is improved.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,reducing the outliers scores of the horizontal wind field,temperature,and 10 m wind speed;the introduction of the SKEB method can improve the light rain.The precipitation probability prediction skill score,but the improvement of the score did not pass the significance test,so it is considered that the SKEB method is difficult to effectively improve the probability prediction technique of precipitation.(2)Sensitivity tests based on the SKEB method for five time scales of random type(1h,3h,6h,9h and 12 h of the time series ?)show that the ensemble prediction is sensitive to the five time scales of the stochastic model of the SKEB method.Sexuality,in which the SKEB random type ensemble prediction score is the best on the 12 h time scale,and the probability prediction technique is better;the stochastic five spatial scales based on the SKEB method(the maximum truncated wave number Lmax is 80,100,120,160 and 200)The sensitivity test shows that the ensemble prediction has certain sensitivity to the five spatial scales of the stochastic model of the SKEB method.The SKEB random type with the largest truncated wave number Lmax of 200 has the best ensemble prediction score and the probabilistic forecasting technique is better.