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| 同化X波段雷达数据对风暴尺度天气系统模拟的试验研究 | |
| 其他题名 | An Experimental Research on X-band Radar Data Assimilation in Storm-scale Weather System Simulation |
| 吴忠元 | |
| 出版年 | 2012 |
| 学位类型 | 硕士 |
| 导师 | 楚荣忠 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | X波段（3.2cm）双线偏振多普勒天气雷达雷达资料具有高时空分辨率的特征，如被充分利用将有利于改善高分辨率数值模式中的中小尺度信息。\n 集合卡尔曼滤波（EnKF）是美国大气研究中心（NCAR）资料同化平台（DART）最新资料同化系统。EnKF是利用集合样本预报场与观测资料来求取最佳的分析场，同时更新背景场误差。EnKF资料同系统已经成功应用于风暴尺度天气系统的预报中。\n 在不考虑模式偏差的前提下，本文先利用DART中的EnKF方案对模拟的X波段雷达资料进行同化试验，考察了EnKF方案同化模拟X波段雷达资料对改善数值模式初始场的能力。随后对2007年7月22日发生在我国西北地区甘肃平凉的一次典型风暴过程进行了同化试验，在同化过程中采用了NCEP再分析资料和中国科学院寒区与旱区环境与工程研究所自主研发的车载X波段双线偏振多普勒天气雷达资料，研究了EnKF同化实际雷达观测资料对于改善实际风暴尺度天气过程中数值模式初始场的能力。结论如下：\n （1）雷达数据的预处理和质量控制（包括去除孤立点，稀疏化）可以去除噪声和减少资料间的相关性，有利于同化的实施。\n （2）EnKF同化模拟雷达资料的理想试验的结果表明，同化模拟雷达资料后，EnKF能够根据模拟的雷达观测资料提供的信息调整预报模式的分析变量场，同化后的扰动位温、风场和水汽的配置较为合理，更有利于风暴的发展，且随着观测信息的融入，除对于预报模式分析变量中的垂直速度、扰动气压和云冰混合比的改善效果不明显外，对于其它的9个分析诊断变量的改善较为明显。多次同化后EnKF的分析结果在总体上更加接近于真实场。\n （3）对X波段雷达资料进行EnKF同化试验的结果表明，仅同化雷达反射率后，EnKF分析的雷达反射率与雷达观测的反射率较接近。在雷达反射率的基础上同时同化雷达径向风数据后，EnKF分析的雷达反射率与雷达观测的反射率更为接近。同时发现同化雷达径向风后，数值模式中风场的合理调整是EnKF分析的雷达反射率改善的主要原因。 |
| 英文摘要 | The X-band ( 3.2cm ) data of dual polarization Doppler weather radar have high spatial and temporal resolution. We can employ it to extract more precise meso-microscale information in numerical model.\n The ensemble Kalman filter is the newly data assimilation research system (DART) provided by the united states space research center（ncar）data assimilation platform. In this system, the assemble sample of forecast and the observation information is used to get the best of the analysis. And the EnKF system have been successfully applied in the storm-scale weather forecast.\n Based on WRF model and ensemble Kalman filter scheme provided by DART Platform, a perfect assimilation experiment was carried out using simulated X-band radar data，to checkout the ability of EnKF method in the X-band radar data assimilation. Then a storm-scale weather process at Pingliang city of Gansu province in the northwest area of China during July 24, 2007 is assimilated as a real case. In this case, we employed NCEP reanalysis data in combined with the data obtained from the on-board X-band polarization doppler weather radar developed by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The impact of radial velocity assimilation on the storm-scale weather process model is studied on the basis of single radar reflectivity assimilation. The following conclusions can be drawn from the present study.\n Firstly, The pre-processing and quality control of radar data (including removal of outliers and sparsifying ) can reduce noise and the correlation between the observation data，thus paving the way for subsequent data assimilation.\n Secondly, the perfect experiment results demonstrate that the EnKF can adjust the variable field of the forecast model from the simulation of radar observation data. Configuration of the perturbation potential temperature, wind field , and water vapor become more reasonable after assimilation and it help improve accuracy of the storm simulation .With fusion of observed data, we achieve a significant improvement for nine diagnose parameter in the weather forecast model except vertical speed, except air pressure and cloud ice mixing ratio. The result is closed to the true value of atmosphere after several assimilation cycles.\n Thirdly, X-band radar data assimilation results show that radar reflectivity obtained from EnKF is close to observation reflectivity after reflectivity assimilation alone. Best results are obtained when radial velocity and reflectivity data were assimilated simultaneously. The performance improvement is mainly attributed to reasonable adjustment of wind field in the weather forecast model. |
| 中文关键词 | X波段 ; 风暴尺度 ; 集合卡尔曼滤波 ; 数值预报 |
| 英文关键词 | storm scale assimilation of radar observation ensemble Kalman filter numerical forecast |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 大气物理学与大气环境 |
| 来源机构 | 中国科学院西北生态环境资源研究院 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287037 |
| 推荐引用方式 GB/T 7714 | 吴忠元. 同化X波段雷达数据对风暴尺度天气系统模拟的试验研究[D]. 中国科学院大学,2012. |
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