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doi:  10.12013/qxyjzyj2017030
江西区域多元变量背景误差协方差特征分析

The Analysis of Multivariate Background Error Covariance in Jiangxi Province
摘要点击 48  全文点击 27  投稿时间:2017-04-07  修订日期:2017-08-24
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基金:  基金项目:2017年江西省气象局青年人才培养项目“背景误差协方差平衡约束在江西省暴雨预报中的适用性研究”
中文关键词:  WRF模式,资料同化,背景误差协方差,江西
英文关键词:  The Weather Research and Forecasting model  data assimilation  background error covariances  Jiangxi province
           
作者中文名作者英文名单位
夏雪Xia Xue江西省气象灾害防御技术中心
林嘉妮Lin Jiani德安县气象局
高雅隽Gao Yajun江西省气象灾害防御技术中心
孟德明Meng Deming南京信息工程大学 气象灾害预报预警与评估协同创新中心
引用:夏雪,林嘉妮,高雅隽,孟德明.2017,江西区域多元变量背景误差协方差特征分析[J].气象与减灾研究,40(3):193-199
中文摘要:
      江西省暴雨灾害频繁发生,改善同化系统性能是提高数值天气预报水平的有效手段,构建合理的背景误差协方差是做好资料同化的关键工作。基于WRF模式的江西区域一个月控制预报为样本,计算得到多元变量相关的背景误差协方差,分析其平衡约束特征、特征值、特征向量以及特征长度尺度。结果表明,江西区域模式层中的低层和高层风场辐合、辐散分量的作用更大,各个变量对水汽场的贡献也集中在低层和高层,其中温度场起主导作用;在模式层中的高层温度场的模拟效果偏差,各个变量的垂直相关性较大;相较于风场,温度场和水汽场在水平方向影响范围小,具有较强的局地性。
Abstract:
      Heavy rainstorms occurred frequently in Jiangxi province. Ameliorated performance in the assimilation system was an effective way to improve the numerical weather prediction (NWP). A reasonable background error covariance (BE)modeling was significant to obtain a good data assimilation result. The multivariate background error covariance (MBE) was calculated based on the one-month forecast in Jiangxi province,and the major parameters of BE, such as correlation coefficients, eigen-values, eigen-vectors and eigen-length scales were compared and analyzed. Results indicated that the convergence and divergence of wind field played a more important role at bottom and top of the model,where each variable made a significant contribution to the water vapor field,especially the temperature field. In addition, the temperature field simulation at the top of model was not satisfactory and the vertical correlation among each variable was relatively strong. The influence of temperature and water vapor field was smaller than that of wind field in the horizontal lengthscales, which presented strong local features.
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