| GRAPES_Meso背景误差特征及应用 |
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| 引用本文： | 庄照荣,王瑞春,王金成,龚建东.GRAPES_Meso背景误差特征及应用[J].应用气象学报,2019,30(3):316-331. |
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| 作者姓名： | 庄照荣 王瑞春 王金成 龚建东 |
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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： | 国家重点研究发展计划（2018YFC1507502，2017YFC1502001） |
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| 摘 要： | 基于2015年6月—2016年5月GRAPES_Meso有限区域中尺度数值预报模式产品，采用美国国家气象中心（NMC）方法和高斯函数拟合方案统计中国区域的背景误差和水平相关尺度随纬度、高度和季节的变化特征。结果表明:控制变量的背景误差与水平相关尺度不仅随高度和纬度有明显变化，其中非平衡Exner气压和比湿具有明显的局地性和季节变化特征。非平衡Exner气压的背景误差在青藏高原地区较大，且冬季最大，夏季最小。比湿背景误差在低纬度热带季风区较大，且夏季最大，冬季最小。非平衡Exner气压和比湿的水平相关尺度在冬季最大，夏季最小。同时文中采用随高度变化的水平相关尺度替换GRAPES-3DVar中单一尺度参数，1个月的分析和模式预报试验表明，6 h的位势高度预报在对流层有明显改进；风场分析及其12 h内的预报在平流层改进明显；对24 h不同量级降水的预报有显著正贡献，也显著改善24 h内的小雨、中雨和大雨的空报现象，明显改善12~24 h特大暴雨的漏报现象。
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| 关 键 词： | 背景误差 水平相关尺度 NMC方法 三维变分 GRAPES_Meso |
| 收稿时间： | 2018/12/18 0:00:00 |
| 修稿时间： | 2019/2/11 0:00:00 |
Characteristics and Application of Background Errors in GRAPES_Meso |
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| Zhuang Zhaorong,Wang Ruichun,Wang Jincheng and Gong Jiandong.Characteristics and Application of Background Errors in GRAPES_Meso[J].Quarterly Journal of Applied Meteorology,2019,30(3):316-331. |
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| Authors: | Zhuang Zhaorong Wang Ruichun Wang Jincheng and Gong Jiandong |
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| Affiliation: | 1.National Meteorological Center, Beijing 1000812.Numerical Weather Prediction Center of CMA, Beijing 100081 |
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| Abstract: | The statistic structure of background covariance is studied by NMC method of USA based on GRAPES regional model forecast data spanning one year from June 2015 to May 2016. The horizontal correlation length scale is estimated with Gauss function linear fitting method. Characteristics of background error and horizontal correlation length scale with the latitude, height and season are investigated. Results show that background error and horizontal correlation characteristic scale obviously change with height and latitude, and the unbalanced non-dimensional pressure and humidity are closely related to the season. Background errors of four control variables are nonhomogeneous, among which background errors of stream function and unbalanced velocity potential mainly change with latitude and height, background errors of unbalanced non-dimensional pressure and humidity show local and seasonal characteristics. The biggest background errors of the unbalanced non-dimensional pressure occur in the Tibetan Plateau, and they are larger in winter while smaller in summer. The biggest background errors of humidity happen in low latitude of tropical monsoon region, and they are larger in summer while smaller in winter. The horizontal correlation length scales of four control variables with Gauss function fitting are reasonable except that correlation coefficients of the unbalanced non-dimensional pressure are overestimated in close distance and underestimated in far distance. Horizontal correlation length scales of steam, unbalanced velocity potential and humidity obviously change with height are largest in tropopause. The length scale of unbalanced non-dimensional pressure obviously changes with latitude and is larger in low latitude of middle tropospheric. The horizontal correlation length scale of the unbalanced non-dimensional pressure and humidity both are larger in winter and smaller in summer. The horizontal correlation length scales changing with height are used in GRAPES-3DVar system instead of single parameter, and then the analysis and forecast experiment results of one month indicate that, qualities of 6-hour geopotential height forecast in troposphere are improved. Analysis and 12-hour forecast of wind in stratosphere are greatly improved; all levels of 24-hour accumulated precipitation forecast are obviously improved; the false prediction of 24-hour accumulated precipitation of light rain, moderate rain and heavy rain are improved; 12-24-hour accumulated precipitation of extra torrential rain in control test fails to be reported, but the experiment with changing horizontal correlation length scales improves forecasts of positions and values for extra torrential rain. |
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| Keywords: | background error horizontal correlation length scale NMC method of USA 3DVar GRAPES_Meso |
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