Development and Operation Transformation of GRAPES Global Middle-range Forecast System

Shen Xueshun; Su Yong; Hu Jianglin; Wang Jincheng; Sun Jian; Xue Jishan; Han Wei; Zhang Hongliang; Lu Huijuan; Zhang Hua; Chen Qiying; Liu Yan; Liu Qijun; Ma Zhanshan; Jin Zhiyan; Li Xingliang; Liu Kun; Zhao Bin; Zhou Bin; Gong Jiandong; Chen Dehui; Wang Jianjie

doi:10.11898/1001-7313.20170101

Vol.28, NO.1, 2017

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Shen Xueshun, Su Yong, Hu Jianglin, et al. Development and operation transformation of GRAPES global middle-range forecast system. J Appl Meteor Sci, 2017, 28(1): 1-10. DOI: 10.11898/1001-7313.20170101.

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Shen Xueshun, Su Yong, Hu Jianglin, et al. Development and operation transformation of GRAPES global middle-range forecast system. J Appl Meteor Sci, 2017, 28(1): 1-10. DOI: 10.11898/1001-7313.20170101.

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Development and Operation Transformation of GRAPES Global Middle-range Forecast System

DOI: 10.11898/1001-7313.20170101

Numerical Weather Prediction Center of CMA, Beijing 100081

Received Date: 2016-03-22
Rev Recd Date: 2016-10-12
Publish Date: 2017-01-31

Abstract

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.
- GRAPES_GFS;
- dynamic frame;
- physical process;
- 3DVar

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References(29)

Figures and Tables

Fig. 1 Annual mean of geopotential height root mean square error analyzed by GRAPES_3DVar against ERA-Interim averaged over the Northern Hemisphere

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Fig. 2 500 hPa geopotential height anomaly correlation coefficient (a) and root mean square error (b) for the 1st, 3rd, 7th-day forecast in one year cycle run over the Nothern Hemisphere

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Fig. 3 Two-year averaged ETS and Bias scores over mainland China for GRAPES_GFS2.0 and T639

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Table 1 The one-month averaged anomaly correlation coefficient for batch forecast test at different resolutions

积分时间/h	北半球500 hPa			东亚500 hPa
积分时间/h	L36a50	L60a50	L60a25	L36a50	L60a50	L60a25
0	1	1	1	1	1	1
24	0.99	0.99	0.99	0.99	0.99	0.99
48	0.97	0.98	0.98	0.96	0.98	0.98
72	0.94	0.96	0.96	0.92	0.94	0.95
96	0.89	0.92	0.93	0.84	0.89	0.89
120	0.79	0.83	0.84	0.75	0.82	0.82
144	0.69	0.75	0.75	0.67	0.75	0.74
168	0.58	0.66	0.66	0.58	0.69	0.69
192	0.48	0.57	0.57	0.47	0.62	0.59

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Table 2 Statistics verifcation for forecast experiments in Jul 2009

积分时间/h	北半球500 hPa				南半球500 hPa
	距平相关系数		均方根误差		距平相关系数		均方根误差
	ORI	NEW	ORI	NEW	ORI	NEW	ORI	NEW
0	1	1	2	2	1	1	4	3
24	0.97	0.98	8	8	0.98	0.99	13	11
48	0.96	0.97	17	15	0.97	0.98	24	22
72	0.93	0.95	26	23	0.94	0.96	39	36
96	0.86	0.89	36	32	0.89	0.91	55	50
120	0.76	0.80	46	41	0.80	0.83	73	67
144	0.67	0.72	56	50	0.72	0.76	91	84
163	0.54	0.60	63	57	0.61	0.65	104	97
192	0.45	0.52	69	63	0.49	0.54	118	111
注：ORI为未更新时的预报结果，NEW为更新积云对流和边界层参数化之后的预报结果。

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Table 3 The improvement of cumulus convection and boundary layer scheme

物理过程方案	改进点
深对流	①基于局地CFL条件的云底最大容许质量通量^[23] ②引入有组织的卷入^[24] ③考虑由于积云对流引起的气压梯度力变化而带来的动量输送^[25-26]
浅对流	①湍流扩散型的方案改为质量通量型 ②云底质量通量计算改为地表浮力通量的函数^[27] ③夹卷率计算改为Siebesma (2003)方案^[28]
边界层	①考虑层积云顶由于辐射冷却引起的湍流混合 ②对于夜间稳定边界层，将基于近地层稳定度函数的扩散计算改为局地扩散方案

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Table 4 Anomaly correlation coefficeient in the Northern Hemisphere and east Asian for two-year cycle forecast

积分时间/h	北半球500 hPa			东亚500 hPa
积分时间/h	T639	GRAPES_GFS 1.0	GRAPES_GFS 2.0	T639	GRAPES_GFS 1.0	GRAPES_GFS 2.0
0	1	1	1	1	1	1
24	0.99	0.98	0.99	0.99	0.98	0.99
48	0.97	0.95	0.97	0.96	0.94	0.97
72	0.93	0.90	0.94	0.93	0.89	0.94
96	0.88	0.84	0.89	0.86	0.82	0.88
120	0.80	0.74	0.81	0.80	0.72	0.82
144	0.70	0.64	0.72	0.71	0.62	0.73
168	0.59	0.54	0.62	0.60	0.51	0.63

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