| 温湿统计平衡约束关系对GRAPES全球湿度分析的作用 |
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| 引用本文： | 龚建东,王瑞春,郝民.温湿统计平衡约束关系对GRAPES全球湿度分析的作用[J].气象学报,2016,74(3):380-396. |
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| 作者姓名： | 龚建东 王瑞春 郝民 |
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| 作者单位： | 1.国家气象中心, 北京, 100081 |
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| 基金项目： | 国家公益性行业(气象)科研专项项目(GYHY201506003)。 |
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| 摘 要： | 为改进GRAPES全球三维变分同化系统(GRAPES-3DVar)的湿度分析,借鉴Hólm等(2002)的思想,在背景误差协方差结构中引入湿度与温度的统计平衡约束关系。通过扣除湿度变化中与温度有关的平衡部分获取非平衡拟相对湿度,并引入非线性对称变换对其做标准化处理,将处理后的变量作为新的湿度控制变量。统计结果表明,温湿统计平衡约束主要出现在中高纬度对流层中层相对湿度大于80%的区域,与大尺度抬升凝结加热有关;新的湿度控制变量能满足无偏、高斯分布特征。单点理想观测试验结果表明,新的湿度分析具备了流依赖特征,并能有效地抑制负水汽与超饱和水汽的出现。同化循环与预报试验结果表明,新方案给出的湿度分析的偏差和均方根误差均有所减小。而针对降水预报的检验结果表明,引入新方案后的0.1-10 mm降水预报,在ETS评分没有显著降低的情况下,BIAS评分更靠近1,降水空报有所减缓。然而60-84 h的25 mm以上的降水漏报现象更为明显,表明湿度同化分析方案还有改进空间。通过引入温湿统计平衡约束关系,完善了GRAPES-3DVar分析框架,为全球湿度分析的持续改进奠定了坚实基础。
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| 关 键 词： | 变分资料同化 背景误差协方差 温湿平衡约束 拟相对湿度 |
| 收稿时间： | 2015/11/13 0:00:00 |
| 修稿时间： | 2016/3/29 0:00:00 |
The impact of a balance constraint between temperature and humidity on the global humidity analysis in GRAPES |
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| GONG Jiandong,WANG Ruichun and HAO Min.The impact of a balance constraint between temperature and humidity on the global humidity analysis in GRAPES[J].Acta Meteorologica Sinica,2016,74(3):380-396. |
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| Authors: | GONG Jiandong WANG Ruichun and HAO Min |
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| Institution: | 1.National Meteorological Center, CMA, Beijing 100081 China2.Numerical Weather Prediction Center of CMA, Beijing 100081 China |
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| Abstract: | In order to improve the humidity analysis in GRAPES global three dimensional variational data assimilation system (GRAPES-3DVar), a statistical balance constraint between temperature and humidity has been introduced into the formulation of background error covariance based on the previous work by Hólm et al. (2002).By deducting the balanced part associated with temperature and using a nonlinear normalization method, the normalized unbalanced pseudo-relative humidity is used as the new humidity control variable. Statistical results show that the coupling between temperature and humidity is related to large scale upwelling and condensation and mainly appears in areas where the environmental relative humidity is larger than 80%. Such areas are often found in the middle troposphere over mid-and high-latitudes. The results also show that the new humidity control variable is nearly unbiased with a Gaussian distribution pattern of error characteristics. Experiments of single pseudo-observation show that the analysis is flow-dependent and the problem of negative moisture and super-saturation is less severe by using the new humidity analysis scheme. Results of cycle analysis and forecast experiments indicate that the bias and root mean square error of the humidity analysis both decrease. The precipitation verification results show that, for the 0.1-10 mm precipitation forecast at 24 hour interval, the Equitable threat score (ETS) changes little, but the bias score (BIAS) is much closer to 1 and the false alarm rate decreases. However, the miss rate for heavy rainfall (> 25 mm) in the 60-84 hour forecast has increased, which means the humidity analysis needs further improvement in the future. This study improves GRAPES 3DVAR by introducing the statistical balance constraint between temperature and humidity into the system, which has laid a solid foundation for continuous improvements of the global humidity analysis in the future. |
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| Keywords: | Variational data assimilation Background error covariance Balance constraint between temperature and humidity Pseudo-relative humidity |
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