| GRAPES_GFS全球中期预报系统的研发和业务化 |
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| 引用本文： | 沈学顺,苏勇,胡江林,王金成,孙健,薛纪善,韩威,张红亮,陆慧娟,张华,陈起英,刘艳,刘奇俊,马占山,金之雁,李兴良,刘琨,赵滨,周斌,龚建东,陈德辉,王建捷.GRAPES_GFS全球中期预报系统的研发和业务化[J].应用气象学报,2017,28(1):1-10. |
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| 作者姓名： | 沈学顺 苏勇 胡江林 王金成 孙健 薛纪善 韩威 张红亮 陆慧娟 张华 陈起英 刘艳 刘奇俊 马占山 金之雁 李兴良 刘琨 赵滨 周斌 龚建东 陈德辉 王建捷 |
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| 作者单位： | 中国气象局数值预报中心, 北京 100081 |
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| 基金项目： | 资助项目： “十二五”国家科技支撑计划（2012BAC22B00），公益性行业（气象）科研专项（GYHY201006013，〖JP2〗GYHY201106008，GYHY20 〖JP〗1206007，GYHY201406005），中国气象局数值预报GRAPES发展专项（GRAPES FZZX 2016 15） |
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| 摘 要： | 该文回顾了中国气象局全球中期数值天气预报系统GRAPES_GFS的研发历程，重点介绍了近年来在GRAPES_GFS研发过程中的重要进展，概要阐述了这些进展对GRAPES_GFS业务:化的贡献。动力框架方面的改进主要包括位温垂直平流的算法、极区滤波方案、标量平流方案、垂直速度衰减（damping）算法、提高模式分辨率等，改善了模式框架的稳定性、计算精度以及质量守恒性。物理过程方面的改进主要包括RRTMG辐射方案、CoLM陆面过程方案、积云对流、边界层过程、双参数云物理方案，以及物理过程的调用计算等，全面提升了模式物理过程的预报能力。全球三维变分同化方面，研发了模式空间三维变分（3DVar）系统、资料质量控制和偏差订正技术、卫星资料同化方面的相关技术等。同时，对目前GRAPES_GFS2.0的预报能力进行了评估，总体来说，该系统各项预报指标全面超越GRAPES_GFS1.0，与T639相比等压面要素预报在对流层也有明显优势，降水、2 m温度等预报也优势明显。
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| 关 键 词： | GRAPES_GFS 动力框架 物理过程 三维变分同化 |
| 收稿时间： | 2106/3/22 0:00:00 |
| 修稿时间： | 2016/10/12 0:00:00 |
Development and Operation Transformation of GRAPES Global Middle range Forecast System |
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| Shen Xueshun,Su Yong,Hu Jianglin,Wang Jincheng,Sun Jian,Xue Jishan,Han Wei,Zhang Hongliang,Lu Huijuan,Zhang Hu,Chen Qiying,Liu Yan,Liu Qijun,Ma Zhanshan,Jin Zhiyan,Li Xingliang,Liu Kun,Zhao Bin,Zhou Bin,Gong Jiandong,Chen Dehui and Wang Jianjie.Development and Operation Transformation of GRAPES Global Middle range Forecast System[J].Quarterly Journal of Applied Meteorology,2017,28(1):1-10. |
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| Authors: | Shen Xueshun Su Yong Hu Jianglin Wang Jincheng Sun Jian Xue Jishan Han Wei Zhang Hongliang Lu Huijuan Zhang Hu Chen Qiying Liu Yan Liu Qijun Ma Zhanshan Jin Zhiyan Li Xingliang Liu Kun Zhao Bin Zhou Bin Gong Jiandong Chen Dehui and Wang Jianjie |
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| Institution: | Numerical Weather Prediction Center of CMA, Beijing 100081 |
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| Abstract: | The developing history of GRAPES global middle-range numerical weather prediction system (GRAPES_GFS) of China Meteorological Administration is reviewed. Important progresses in recent years are summarized and their contributions to GRAPES_GFS operation are introduced.From the aspect of dynamic frame aspect, an algorithm for vertical advection of temperature and the polar filter scheme are improved. New algorithms are introduced, including terrain filtering algorithm, scalar advection scheme with conservation and high accuracy, w-damping noise suppression algorithm, and Rayleigh friction in the stratosphere, etc. Besides, horizontal and vertical resolutions are enhanced. These improvements significantly improve the stability, accuracy and mass conservation of the dynamic core.From the aspect of physical process, the RRTMG radiation program is upgraded, the CoLM land surface process scheme is introduced, the cumulus convective scheme and boundary layer scheme are improved, and a two-parameter cloud physics scheme is developed. On these basis, the prediction cloud scheme is further developed, the interface between dynamic and physics is adjusted, the calculation of sea ice and surface albedo are also optimized. These improvements and optimizations improve the prediction ability of the physical package.From the aspect of global three-dimensional variational assimilation (3DVar), the model space 3DVar is developed to avoid the interpolation error of the analysis space to the model space, fine quality control and deviation correction techniques are developed to achieve high quality observation data assimilation, and more satellite data assimilation techniques are adopted especially using satellite hyperspectral infrared detector as the focus.At the same time, the prediction ability of GRAPES_GFS2.0 is being evaluated based on results of two-year assimilation forecast cycle test, and compared with T639. Generally speaking, the forecast indicators of the system are fully beyond the GRAPES_GFS 1.0 version. Model outputs of isobaric elements in the troposphere forecast, including precipitation and 2 m temperature, have obvious advantages comparing with T639. |
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