| 基于GRAPES_Meso的集合预报扰动方案设计与比较 |
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| 引用本文： | 张涵斌,;陈静,;智协飞,;龙柯吉,;王亚男.基于GRAPES_Meso的集合预报扰动方案设计与比较[J].南京气象学院学报,2014(3):276-284. |
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| 作者姓名： | 张涵斌 ;陈静 ;智协飞 ;龙柯吉 ;王亚男 |
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| 作者单位： | [1]南京信息工程大学大气科学学院,江苏南京210044; [2]中国气象局数值预报中心,北京100081; [3]气象灾害教育部重点实验室(南京信息工程大学),江苏南京210044; [4]四川省气象台,四川成都610072; [5]浙江省气象服务中心,浙江杭州310017 |
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| 基金项目： | 公益性行业（气象）科研专项（GYHY200906007）;国家重点基础研究发展计划（973计划）项目（2012CB417204）;科技部国家科技支撑计划（2009BAC51B00）;国家自然科学基金资助项目（41075035） |
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| 摘 要： | 基于GRAPES_Meso区域集合预报系统,设计了三种集合预报扰动方案,即多初值、多初值多物理、多初值多物理多边值,并针对三种方案进行了连续一个月的批量试验,重点分析了2008年7月23日江淮暴雨过程.结果表明,对于降水预报,三种集合扰动方案均相对于控制预报均有所改善,多初值多物理与多初值多物理多边值方案对小雨、中雨预报改进效果显著,对暴雨预报略有改进;多初值方案仅能产生有限的集合离散度且难以增长,引入物理参数方案扰动及边界条件扰动能显著提高集合离散度,改善各物理量场的预报效果;通过比较,多初值多物理多边值为最优方案.该批量试验表明,模式物理过程及边界条件是影响GRAPES _Meso区域集合预报不确定性的不可忽视因素.
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| 关 键 词： | 数值预报 集合预报 GRAPES_Meso 扰动方案 |
Design and comparison of perturbation schemes for GRAPES_Meso based ensemble forecast |
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| Institution: | ZHANG Han-bin, CHEN Jing, ZHI Xie-fei, LONG Ke-ji, WANG Ya-nan ( 1.School of Atmospheric Sciences, NUIST, Nanjing 210044, China; 2.Center of Numerical Weather Prediction of CMA,Beijing 100081 ,China; 3.Key Laboratory of Meteorological Disaster(NUIST) ,Ministry of Education,Nanjing 210044, China; 4. Sichuan Meteorological Observatory, Chengdu 610072, China; 5.Zhejiang Meteorological Service Center, Hangzhou 310017, China ) |
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| Abstract: | Based on the GRAPES_Meso regional ensemble forecast system,three ensemble perturbation schemes are designed and compared,namely,multi-initial,multi-initial-physics and multi-initial-physicsboundary.Consecutive experiments for a period of one month in July 2008,during which heavy rainfall processes occurred in Jianghuai,are conducted in this paper.The results are as follows：All ensemble schemes can outperform the control forecast,the improvement for small rain forecast is obvious whereas the improvement for heavy rain forecast is slight;the multi-initial scheme can only produce limited ensemble spread;the introduction of physical parameterization perturbation and lateral boundary perturbation could significantly amplify ensemble spread and improve the ensemble forecast of each quantity.After all,the scheme of multi-initial-physics-boundary is the best.The results indicate that model physics and lateral boundary are important factors for GRAPES_Meso regional ensemble forecast uncertainty. |
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| Keywords: | numerical weather prediction ensemble forecast GRAPES_Meso perturbation scheme |
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