何静. 2019. 雷达反射率三维拼图观测在北方区域数值模式预报系统中的同化应用研究[J]. 气象学报, (0):-, doi:10.11676/qxxb2019.005
雷达反射率三维拼图观测在北方区域数值模式预报系统中的同化应用研究
The Study of Radar Three-Dimension Reflectivity Mosaic Assimilation in Regional Forecasting Model of North China
投稿时间:2018-02-13  修订日期:2018-04-27
DOI:10.11676/qxxb2019.005
中文关键词:  雷达拼图资料同化,区域数值预报系统,降水预报
英文关键词:Radar 3D mosaic reflectivity, 3DVAR, Regional forecasting model, Precipitation forecasting
基金项目:省自然科学基金
作者单位E-mail
何静 中国气象局北京城市气象研究所 jhe@ium.cn 
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中文摘要:
      以业务应用为目标,开展雷达反射率三维拼图观测在北方区域数值模式预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测,重点关注其对降水、湿度、温度及风的预报性能影响。首先,基于2017年8月份雷达拼图观测批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报性能等方面有明显的改善作用。其次,选择在业务中预报难度较高的强降水个例开展分析研究,分析表明:1)同化雷达拼图观测有效提高模式降水预报性能,临近降水发生的循环起报时次预报效果更好;2)对于短时间多次强降水过程发生的模式预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水物质或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水物质分布、热力场等进行调整,提高模式降水预报性能。
英文摘要:
      The radar three-dimension(3D) mosaic reflectivity covering North China region is assimilated in the regional numerical weather forecasting system RMAPS-ST via an indirect radar reflectivity assimilation method of WRF-3DVAR to improve model forecasting skill, which mainly focuses on its influence on precipitation, specific humidity, temperature, wind forecasting. Firstly, experiments with and without radar mosaic reflectivity assimilation are performed from 1 Aug to 31 Aug 2017, and quantitative verification is done based the batch experiments and the results show that radar mosaic reflectivity assimilation improve the forecasting skill of precipitation, specific humidity, temperature largely but increases the forecasting error of wind. Secondly, how radar mosaic reflectivity assimilation improving the forecasting skill of RMAPS-ST is displayed based on a heavy rainfall case, which shows: 1) precipitation forecasting skill is improved largely and the cycle which is closer to the beginning of rainfall has higher forecasting skill by assimilating radar mosaic; 2) water vapor, energy and thermal condition which are exhausted and weakened by the previous rainfall can be supplied and re-organized to trigger the next rainfall by assimilating radar mosaic reflectivity in cycle way, which plays important role in the situation of multiple rainfalls occurring during short time. Finally, two schemes of the WRF-3DVAR indirect radar reflectivity assimilation method are tested, which shows that retrieved hydrometeor assimilation scheme and derived water vapor assimilation scheme can both improve precipitation forecasting, but the later one plays more important role, and using two schemes together can make reasonable adjustments for the rainwater, snow water, water vapor and thermal condition, which are the key to improve precipitation forecasting.
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