首页|A Comparison Study of the Methods of Conditional Nonlinear Optimal Perturbations and Singular Vectors in Ensemble Prediction
A Comparison Study of the Methods of Conditional Nonlinear Optimal Perturbations and Singular Vectors in Ensemble Prediction
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NSTL
维普
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The authors apply the technique of conditional nonlinear optimal perturbations (CNOPs) as a means of providing initial perturbations for ensemble forecasting by using a barotropic quasi-gcostrophic (QG) model in a perfect-model scenario. Ensemble forecasts for the medium range (14 days) are made from the initial states perturbed by CNOPs and singular vectors (SVs). 13 different cases have been chosen when analysis error is a kind of fast growing error. Our experiments show that the introduction of CNOP provides better forecast skill than the SV method. Moreover, the spread-skill relationship reveals that the ensemble samples in which the first SV is replaced by CNOP appear supcrior to those obtained by SVs from day 6 to day 14. Rank diagrams are adopted to compare the new method with the SV approach. The results illustrate that the introduction of CNOP has higher reliability for medium-range ensemble forecasts.
State Key Laboratory of Severe Weather ( LaSW), Chinese Academy of Meteorological Sciences, Beijing 100081
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics ( LASG),Institute of Atmospheric Physics, Chinese
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics ( LASG),Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences Program for Basic Research of China中国科学院资助项目国家自然科学基金
NETL
NSTL
维普
万方数据
