Model Uncertainty Representation for a Convection-Allowing Ensemble Prediction System Based on CNOP-P  

作　　者：Lu WANG Xueshun SHEN Juanjuan LIU Bin WANG 

机构地区：[1]Asset Operation Centre,China Meteorological Administration,Beijing 100081,China [2]State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing 100081,China [3]Numerical Weather Prediction Center/National Meteorological Center,China Meteorological Administration,Beijing 100081,China [4]Institute of Atmosphere Physics,Chinese Academy of Sciences,Beijing 100029,China [5]Center for Earth System Science,Tsinghua University,Beijing 100084,China

出　　处：《Advances in Atmospheric Sciences》2020年第8期817-831,共15页大气科学进展（英文版）

摘　　要：Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is proposed and tested through assuming that the model uncertainty should reasonably describe the fast nonlinear error growth of the convection-allowing model,due to the fast developing character and strong nonlinearity of convective events.The Conditional Nonlinear Optimal Perturbation related to Parameters(CNOP-P)is applied in this study.Also,an ensemble approach is adopted to solve the CNOP-P problem.By using five locally developed strong convective events that occurred in pre-rainy season of South China,the most sensitive parameters were detected based on CNOP-P,which resulted in the maximum variations in precipitation.A formulation of model uncertainty is designed by adding stochastic perturbations into these sensitive parameters.Through comparison ensemble experiments by using all the 13 heavy rainfall cases that occurred in the flood season of South China in 2017,the advantages of the CNOP-P-based method are examined and verified by comparing with the well-utilized stochastically perturbed physics tendencies(SPPT)scheme.The results indicate that the CNOP-P-based method has potential in improving the under-dispersive problem of the current CAEPS.

关 键 词：CNOP-P convective scale model uncertainty ensemble forecastforecast 

分 类 号：P45[天文地球—大气科学及气象学]