A Meso-scale Ensemble Forecasting Research Based On Perturbation Of Surface Conditions

Considering the uncertainty of terrain height and surface temperature and humidity in meso-scale numerical weather forecasting, basing on the idea of initial disturbance in ensemble prediction, using WRF model do topographic sensitivity test and land surface perturbation ensemble forecasting experiments to research a heavy rain occurred in Huaihe River during July 8th and 9th in 2007. The main conclusions are the followings:(1) The results of topographic sensitivity test show that the terrain of Dabie Mountain and Hongtong Mountain area can significantly influence the extent, center and the maximum amount of precipitation. Considering the inaccuracies of the initial terrain height data and the model error of the terrain height, we structure two kinds of terrain disturbance. Both of them display better forecasting of the precipitation centers and magnitude, which make marked improvement than the control. For the two kinds of terrain disturbance, they can improve the effects of possible forecasting on rainstorm and heavy rain, but the programe 2 can do better skills on high possible forecasting. Form the extent of the divergence of members, option 2 option 1 is more than able to seize the pattern of terrain error distribution in the model, but the divergence of two ensemble prediction system are a little small.(2) The ensemble mean precipitation of doing perturbations on SMOIS and TSLB appeals that the rain belt in Hubei,Anhui and Henan has been made up for the shortcomings of the control test. The average RMSE of smois, tslb and the atmospheric general physical field have been reduced. The initial disturbance of land surface results show that surface conditions and the atmosphere exits interactions, surface disturbance has obvious feedback to atmosphere, which can change the atmospheric elements and model predictions, including the circulation, distribution and extent of precipitation and so on.(3) Perturbing terrain height and elements of land surface simultaneously, the results show that the terrain disturbance mainly affects the distribution of precipitation error, while perturbing SMOIS and TSLB mainly change the range and the size of rainfall error, which increase with the amplitude of perturbation, so are the spread of U10, V10 and T2. The ensemble mean corrects the shortcomings of bias score in control test effectively. ETS scores show that ensemble forecast can reach higher skill in heavy rain and rainstorm, but lower skill in heavy rainstorm.(4) Comparing the three ensemble forecast systems, the DTE of the three increases steadily with time, but perturbing terrain height produce more contribution. The probability forecast of perturbing terrain height and elements of land surface simultaneously has better result in general characteristics of the occurrence time and distribution of precipitation. The three systems can reach higher skill in every level of rainfall, while perturbing SMOIS and TSLB show better skill of rainfall and rainstorm, perturbing terrain is not dominant relatively, and the third system has a distinct advantage than the other two.