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热带风压场平衡特征及其对GRAPES系统中同化预报的影响研究Ⅱ:动力与统计混合平衡约束方案的应用 被引量:10

Tropical Balance Characteristics between Mass and Wind Fields and Their Impact on Analyses and Forecasts in GRAPES System. Part Ⅱ: Application of Linear Balance Equation–Regression Hybrid Constraint Scheme
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摘要 研究I的结果表明:线性平衡方程(LBE)在热带地区不适用,而进一步改进方向是削弱LBE在该区域的约束程度。本文以此为基础,在GRAPES(global/regional assimilation and prediction system)全球变分同化系统中引入动力与统计混合平衡约束方案。新方案在逐层求解LBE的基础上增加垂直方向的线性回归,回归系数随纬度和高度变化。针对背景误差协方差的分析表明,新方案可以更好的保证独立分析变量间预报误差不相关的基本要求,并大幅度减小热带地区平衡气压预报误差方差的量值和占总方差的比例。单点试验结果表明,与LBE方案相比,新方案对中、高纬影响很小,但在热带地区成功实现了风、压场分析的解耦,两者分析更为独立。并且,虽未考虑具体波动模态,但新方案给出的风、压场协相关结构与研究I的理论分析结果相近。一个月的同化循环与预报结果表明,引入新方案后,赤道外地区的同化预报效果为中性偏正,而热带地区风场的同化预报效果显著提高,LBE方案中平流层低层的风场同化预报异常被基本消除。 The results of Part I of this study show that the imposition of the Linear Balance Equation(LBE) in the tropics is not correct and additional steps should be taken to decouple the analysis of mass and wind fields. Based on the results in Part I, this paper developed a LBE-regression hybrid balance constraint in GRAPES(global/regional assimilation and prediction system) global variational data assimilation system. In the new scheme, after the calculation of LBE on each level, a vertical regression whose coefficients could vary at different latitudes and model levels was introduced. By analyzing and comparing the implied background error covariance of different schemes, the authors found that the new scheme could efficiently reduce the unreasonable correlations of control variables. Additionally, the forecast error variance of the balanced pressure and its ratio to the whole pressure were also both dramatically reduced in the tropics. Results of the single-observation experiments indicated that, the new scheme had little impacts on the mid- and high-latitude compared to the LBE scheme, but it did successfully decouple the mass/wind analyses in the tropics. Although equatorial wave modes were not explicitly considered in the new scheme, the structure of covariance was consist with the theory analysis results based on those modes in Part I. The results of cycle analysis and forecast experiments in one month showed that, the new scheme could bring slightly positive results in the extratropics and significantly improve the wind analysis and forecast accuracy in the tropics, the abnormally large tropical wind errors in the LBE scheme were dramatically suppressed.
出处 《大气科学》 CSCD 北大核心 2015年第6期1225-1236,共12页 Chinese Journal of Atmospheric Sciences
基金 公益性行业科研专项GYHY201106008 中国气象局数值预报(GRAPES)发展专项 江苏省普通高校研究生科研创新计划项目CXZZ13_0497
关键词 变分资料同化 平衡约束 线性平衡方程 线性回归 GRAPES(global/regional ASSIMILATION and prediction system) Variational data assimilation, Balance constraint, Linear balance equation, Linear regression, GRAPES
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  • 1Bannister R N. 2008. A review of forecast error covariance statistics in atmospheric variational data assimilation, lI: Modelling the forecast error covariance statistics [J]. Quart. J. Roy. Meteor. Soc., 134 (637): 1971- 1996.
  • 2Barker D M, Huang W, Guo Y R, et al. 2004. A three-dimensional variational data assimilation system for MM5: Implementation and initial results [J]. Mon. Wea. Rev., 132 (4): 897-914.
  • 3Berre L. 2000. Estimation of synoptic and mesoscale forecast error covariances in a limited-area model [J]. Mon. Wea. Rev., 128 (3): 644-667.
  • 4Chen Y D, Rizvi S R H, Huang X Y, et al. 2013. Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions [J]. Meteor. Atmos. Phys., 121 (1-2): 79-98.
  • 5Daley R. 1991. Atmospheric Data Analysis [M]. Cambridge: Cambridge University Press, 457pp.
  • 6Daley R. 1993. Atmospheric data assimilation on the equatorial beta plane [J]. Atmos.-Ocean, 31 (4): 421-450.
  • 7Daley R. 1996. Generation of global multivariate error covariances by singular-value decomposition of the linear balance equation [J]. Mort. Wea. Rev., 124 (11): 2574-2587.
  • 8Derber J, Bouttier F. 1999. A reformulation of the background error covariance in the ECMWF global data assimilation system [J]. Tellus, 51A (2): 195-221.
  • 9Fisher M. 2003. Background error covariance modeling [C]// ECMWF seminar on recent developments in data assimilation for atmosphere and ocean, 8-12 September 2003, Reading: ECMWF, 45-63.
  • 10Holton J R. 1992. An Introduction to Dynamic Meteorology [M]. 3rd ed. New York: Academic Press, 507pp.

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