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Development and Operation Transformation of GRAPES Global Middle-range Forecast System
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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
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.-
Key words:
- GRAPES_GFS;
- dynamic frame;
- physical process;
- 3DVar
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图 1 年平均北半球位势高度分析场与ERA-Interim
Fig. 1 Annual mean of geopotential height root mean square error analyzed by GRAPES_3DVar against ERA-Interim averaged over the Northern Hemisphere
图 2 1年循环试验中第1，3，7天预报的北半球500 hPa高度场距平相关系数(a)和均方根误差(b)
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
图 3 GRAPES_GFS2.0与T639预报的中国区域各量级降水ETS (a)和Bias (b)技巧评分
Fig. 3 Two-year averaged ETS and Bias scores over mainland China for GRAPES_GFS2.0 and T639
表 1 不同分辨率下批量预报试验1个月平均的距平相关系数
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 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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表 2 2009年7月批量预报试验的统计检验结果
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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表 3 积云对流和边界层的改进物理方案
Table 3 The improvement of cumulus convection and boundary layer scheme
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表 4 两年循环预报试验结果在北半球和东亚区的距平相关系数
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 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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[1] Bauer P, Thorpe A, Brunet G.The quiet revolution of numerical weather prediction.Nature, 2015, 525:47-55. doi: 10.1038/nature14956 [2] Met Office Science Strategy:2016-2021.London:UKMO, 2015. [3] 陈德辉, 沈学顺.新一代数值预报系统GRAPES研究进展.应用气象学报, 2006, 17(6):773-777. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=200606125&flag=1 [4] 陈德辉, 杨学胜, 张红亮, 等.多尺度非静力通用模式框架的设计策略.应用气象学报, 2003, 14(4):452-461. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20030456&flag=1 [5] 薛纪善, 陈德辉.数值预报系统GRAPES的科学设计与应用.北京:科学出版社, 2008. [6] Zhang R H, Shen X S.On the development of the GRAPES-A new generation of the National operational NWP system in China.Chin Sci Bull, 2008, 53(22):3429-3432. http://www.cnki.com.cn/Article/CJFDTOTAL-JXTW200822002.htm [7] 胡江林, 沈学顺, 张红亮, 等.GRAPES模式动力框架的长期积分特征.应用气象学报, 2007, 18(3):276-284. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070349&flag=1 [8] 伍湘君, 金之雁, 黄丽萍, 等.GRAPES模式软件框架与实现.应用气象学报, 2005, 16(4):539-546. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20050468&flag=1 [9] Temperton C, Hortal M, Simmons A.A two-time-level semi-Lagrangian global spectral model.Q J R Meteorol Soc, 2001, 127:111-127. doi: 10.1002/(ISSN)1477-870X [10] Gospodinov I, Spiridonov V, Geleyn J.Second-order accuracy of two-time-level semi-Lagrangian schemes.Q J R Meteorol Soc, 2001, 127:1017-1033. doi: 10.1002/(ISSN)1477-870X [11] McDonald A.The Origin of Noise in Semi-Lagrangian Integrations//Seminar Proceedings on Numerical Methods in Atmospheric Models.1991, 2:308-334. [12] Hortal M.The development and testing of a new two-time-level semi-Lagrangian scheme (SETTLS) in the ECMWF forecast model.Q J R Meteorol Soc, 2002, 128:1671-1687. doi: 10.1002/(ISSN)1477-870X [13] Klemp J B, Dudhia J, Hassiotis A D.An upper gravity-wave absorbing layer for NWP applications.Mon Wea Rev, 2008, 136:3987-4004. doi: 10.1175/2008MWR2596.1 [14] Wood N, Staniforth A, White A, et al.An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations.Q J R Meteorol Soc, 2015, 140:1505-1520. http://adsabs.harvard.edu/abs/2014QJRMS.140.1505W [15] Mlawer E J, Taubman S J, Brown P D, et al.Radiative transfer for inhomogeneous atmospheres:RRTM, a validated correlated-k model for the longwave.J Geophys Res, 1997, 102:16663-16682. doi: 10.1029/97JD00237 [16] Clough S A, Shephard M W, Mlawer E J, et al.Atmospheric radiative transfer modeling:A summary of the AER codes.J Quant Spectrosc Radiat Transfer, 2005, 91:233-244. doi: 10.1016/j.jqsrt.2004.05.058 [17] Iacono M J, Delamere J S, Mlawer E J, et al.Radiative forcing by long-lived greenhouse gases:Calculations with the AER radiative transfer models.J Geophys Res, 2008, 113:1395-1400. https://www.researchgate.net/publication/238030140_Radiative_Forcing_by_Long-Lived_Greenhouse_Gases_Calculations_with_the_AER_Radiative_Transfer_Models [18] Dai Y, Zeng X, Dickinson R E, et al.The Common Land Model (CLM).Amer Meter Soc, 2003, 84:1013-1023. doi: 10.1175/BAMS-84-8-1013 [19] Palmer T, Shutts G J, Swinbank R. Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parameterization.Q J R Meteorol Soc, 1986, 112:1001-1039. doi: 10.1002/(ISSN)1477-870X [20] McFarlane N A.The effects of orographically excited gravity waves on the general circulation of the lower stratosphere and troposphere.J Atmos Sci, 1987, 44:1775-1800. doi: 10.1175/1520-0469(1987)044<1775:TEOOEG>2.0.CO;2 [21] Lott F, Miller M.A new sub-grid scale orographic drag parameterization:Its formulation and testing.Q J R Meteorol Soc, 1997, 123:101-127. doi: 10.1002/(ISSN)1477-870X [22] 苏勇, 沈学顺, 张倩, 等.应用样条插值提高GRAPES模式物理过程反馈精度.应用气象学报, 2014, 25(2):202-211. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20140210&flag=1 [23] Jakob C, Siebesma A P.A new subcloud model for mass-flux convection schemes-Influence on triggering, updraught properties and model climate.Mon Wea Rev, 2003, 131:2765-2778. doi: 10.1175/1520-0493(2003)131<2765:ANSMFM>2.0.CO;2 [24] Bechtold P, Kohler M, Jung T, et al.Advances in simulating atmospheric variability with the ECMWF model:From synoptic to decadal time-scales.Q J R Meteorol Soc, 134, 634:1337-1351. [25] Han J, Pan H L.Revision of convection and vertical diffusion schemes in the NCEP Global Forecast System.Wea Forecasting, 2011, 26:520-533. doi: 10.1175/WAF-D-10-05038.1 [26] Han J, Pan H L.Sensitivity of hurricane intensity forecast to convective momentum transport parameterization.Mon Wea Rev, 2006, 134:664-674. doi: 10.1175/MWR3090.1 [27] Grant A.Cloud-base fluxes in the cumulus-capped boundary layer. Q J R Meteorol Soc, 2001, 127:407-421. doi: 10.1002/(ISSN)1477-870X [28] Siebesma A P, Bretherton C S, Brown A, et al.A large eddy simulation intercomparison study of shallow cumulus convection.J Atmos Sci, 2003, 60:1201-1219. doi: 10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2 [29] 刘艳, 薛纪善, 张林, 等.GRAPES全球三维变分同化系统的检验与诊断.应用气象学报, 2016, 27(1):1-15. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20160101&flag=1 -
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