Study on the application of Stochastic Perturbed Physics Tendency perturbation in Regional Ensemble Prediction System of KelamaySHI Yongqiang1, ZHANG Hanbin2,LIU Yujue2, ZHANG Xinran3

1.Kelamayi Meteorological Bureau;2.Institute of Urban Meteorology, China Meteorological Administration;3.Chinese Academy of Meteorological Sciences

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    At present, a Regional Ensemble Prediction System has been developed by Kelamayi Meteorological Bureau. The system has only adopted initial condition perturbation of Ensemble Transform Kalman Filter(ETKF), and the system is lack of spread. In order to improve the skill of this Ensemble Prediction System, the model perturbation method of Stochastic Physics Parameterization Tendency(SPPT) is adopted and tested. This paper conducted sensitivity test on critical parameter of SPPT and parameter setting of SPPT is determined. Ensemble forecast experiment test is conducted and compared for both ETKF scheme and ETKF-SPPT scheme. The results show that the ETKF method can generate initial condition perturbation with dynamic structure, but the spread will saturated within short forecast lead time and will decrease due to the constraint of identical LBC for all members. With SPPT model perturbation method adopted, the ensemble spread can significantly improved. Ensemble verification scores indicate that the reliability of ETKF without model perturbation is small, and the root mean square error(RMSE) is relatively large, while add model perturbation to initial condition perturbation will improve the probabilistic forecast skill with larger forecast reliability and smaller(RMSE) . The results of gale forecast show that the adoption of model perturbation method can significantly improve the ensemble forecast that it has more accurate forecast on the magnitude and time period of local gale.

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  • Received:November 21,2021
  • Revised:June 19,2022
  • Adopted:September 15,2022
  • Online: September 15,2022
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