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气象:2013,39(4):466-477
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GRAPES_RAFS系统研发
(1.国家气象中心,北京 100081;2.中国气象局广州热带气象研究所,广州 510080;3.中国气象科学研究院,北京 100081)
On the Research and Development of GRAPES_RAFS
(1.National Meteorological Centre, Beijing 100081;2.Guangzhou Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080;3.Chinese Academy of Meteorological Sciences, Beijing 100081)
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投稿时间:2012-01-27    修订日期:2012-12-06
中文摘要: 基于GRAPES (Global and Regional Assimilation and Prediction System)模式的GRAPES_RAFS(Rapid Analysis and Forecast System)系统是一个向前的间歇性同化分析的分析系统,能将多种高时空分辨率的观测资料充分利用起来,同时也是一个不断更新数值预报产品的中尺度数值预报系统。本文从该系统的结构、流程所涉及的各技术环节进行阐述,通过与业务GRAPES_MESO的预报效果对比分析对该系统的短时临近预报能力以及影响该系统短临预报性能的关键技术进行研究。研究结果表明:利用我国新一代数值预报系统GRAPES模式及GRAPES_3Dvar建立的全国稠密资料快速更新同化分析预报系统(GRAPES_RAFS系统)具有一定短时临近预报能力。同化系统的背景误差协方差准确描述、模式系统动力框架及物理过程精确度的提高能有效提高该系统的预报能力,而局地稠密资料的合理使用是该系统提供高质量预报的另一个关键技术,在资料相对稀少的情况下,该系统的短临预报性能面临严重挑战。
Abstract:The GRAPES_RAFS (Rapid Analysis and Forecast System) is based on GRAPES (Global and Regional Assimilation and Prediction System) model and GRAPES_3DVAR system, running on a high intermittent assimilation cycle to provide high resolution mesoscale analyses and short time numerical weather predication guidance for weather forecasting. The GRAPES_RAFS assimilates radiosonde observation and a lot of observations with high temporal and spatial resolution, such as aircraft, VAD wind profiles, surface station observation data, et al. Herein, the framework and flowchart of GRAPES_RAFS are technically described, and compared with the forecasting products of GRAPES_MESO, the short time nowcasting capability of this system and the critical techniques influencing its forecasting performance are also discussed. The research results show that the GRAPES_RAFS system is effective in providing more accurate short time nowcasting forecasts initialized with recent data than GRAPES_MESO system forecasts. The results also show that, 〖JP2〗high resolution observations, the background error covariance of GRAPES_3DVAR system,〖JP〗 the dynamical framework and physical processes of GRAPES model are keys to GRAPES_RAFS. The short time nowcasting performance of GRAPES_RAFS is a challenging task in the case that the assimilated observation data for GRAPES_RAFS are sparse.
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基金项目:中国气象局基建项目“全国稠密资料融合同化系统建设”、气象关键技术集成与应用重点项目(CMAGJ2011Z07)和公益性行业(气象)科研专项(GYHY201006016、GYHY201006001和GYHY201106044)共同资助
引用文本:
徐枝芳,郝民,朱立娟,龚建东,万齐林,陶士伟,薛纪善,陈德辉,2013.GRAPES_RAFS系统研发[J].气象,39(4):466-477.
XU Zhifang,HAO Min,ZHU Lijuan,GONG Jiandong,WAN Qilin,TAO Shiwei,XUE Jishan,CHEN Dehui,2013.On the Research and Development of GRAPES_RAFS[J].Meteor Mon,39(4):466-477.