Study on Multi-Scale Blending Initial Condition Perturbations for a Regional Ensemble Prediction System

• Published in: Advances in atmospheric sciences Vol. 32; no. 8; pp. 1143 - 1155
• Main Authors: Zhang, Hanbin, Chen, Jing, Zhi, Xiefei, Wang, Yi, Wang, Yanan
• Format: Journal Article
• Language: English
• Published: Heidelberg Science Press 01.08.2015; Springer Nature B.V; College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044%Numerical Weather Prediction Center, China Meteorological Administration, Beijing 100081%Key Laboratory of Meteorological Disaster, Ministry of Education,Nanjing University of Information Science and Technology, Nanjing 210044%Earth and Atmospheric Sciences, University of Nebraska Lincoln, Lincoln, Nebraska, 68588, USA%Center of Meteorological Service of Zhejiang,Hangzhou,310017
• Subjects: Atmospheric Sciences; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; ICS; Meteorology; Regions; Weather forecasting; 作战区域; 多尺度; 扰动; 混合; 销售代表; 集合预报系统; 集成电路; multi-scale blending; spectral analysis; initial condition perturbations; regional ensemble prediction system
• ISSN: 0256-1530; 1861-9533
• DOI: 10.1007/s00376-015-4232-6

An initial conditions （ICs） perturbation method was developed with the aim to improve an operational regional ensemble prediction system （REPS）. Three issues were identified and investigated： （1） the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; （2） the scale characteristic of the IC perturbations of the REPS; and （3） whether the REPS＇s skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system （GEPS） were analyzed. A ＂multi-scale blending＂ （MSB） IC perturbation scheme was developed, and the main findings can be summarized as follows： The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.