doi:  10.3878/j.issn.1006-9895.1608.15288
雷达资料同化在局地强对流预报中的应用

Application of Radar Data Assimilation in Local Severe Convective Weather Forecast
摘要点击 350  全文点击 272  投稿时间:2015-10-18  
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基金:  国家科技支撑计划课题2015BAH50F01,中国气象局公益性行业专项GYHY201406006,国家测绘地理信息公益性行业科研专项201512026,江西省气象局面上项目“省际雷达资料质量控制和三维组网技术应用研究”,江西省科技支撑计划重大项目20152ACG70002
中文关键词:  雷达资料同化  ARPS模式  强对流  数值模拟
英文关键词:  Radar data assimilation  ARPS (Advanced Regional Prediction System)  Severe convection  Numerical simulation
              
作者中文名作者英文名单位
薛谌彬XUE Chenbin江西省气象台, 南昌 330096
陈娴CHEN Xian江西省基础地理信息中心, 南昌 330029;流域生态与地理环境监测国家测绘地理信息局重点实验室, 南昌 330029
吴俞WU Yu海南省气象台, 海口 570203
徐星生XU Xingsheng江西省气象台, 南昌 330096
高勇GAO Yong中国人民解放军 95994 部队, 甘肃省酒泉市 735006
引用:薛谌彬,陈娴,吴俞,徐星生,高勇.2017.雷达资料同化在局地强对流预报中的应用[J].大气科学,41(4):673-690,doi:10.3878/j.issn.1006-9895.1608.15288.
Citation:XUE Chenbin,CHEN Xian,WU Yu,XU Xingsheng,GAO Yong.2017.Application of Radar Data Assimilation in Local Severe Convective Weather Forecast[J].Chinese Journal of Atmospheric Sciences (in Chinese),41(4):673-690,doi:10.3878/j.issn.1006-9895.1608.15288.
中文摘要:
      采用ARPS模式的资料分析系统ADAS同化多普勒雷达径向速度和反射率因子资料,分析两者对初始场的改进作用,并应用于WRF中尺度模式中对2012年8月21日江西省一次局地强对流过程进行了模拟试验。分析结果表明:(1)ADAS同化系统能够利用雷达径向速度和反射率因子资料有效增加初始场中的中小尺度风场信息和云、水物质含量,并通过湿绝热或非绝热初始化对温度场、湿度场和风场进行调整,使初始场在动力和热力上达到平衡。(2)同化径向速度后对改善模式初始场的动力场有重要贡献,而对大气水凝物和降水的预报影响较小;同化反射率因子的主要作用是调整初始场中的水凝物场和热力场,有效缩短了模式的“ spin-up”时间,明显改进了定量降水预报;同时同化雷达径向速度和反射率因子后,初始场中快速调整出了中小尺度风场水平辐合、垂直运动以及合理的温、湿分布,对3小时内雨带形状、降水落区及定量降水的预报与实况更接近。(3)模拟试验表明,同时同化径向速度和反射率因子能成功模拟出本次对流单体风暴的中β尺度三维空间分布结构及其演变过程,中低层切变线的辐合抬升强迫作用是对流单体风暴组织、发展和维持的主要动力机制之一,对流凝结潜热加热在对流单体风暴的发生发展中发挥了重要作用。因此,雷达资料同化对提高临近数值天气预报的准确率以及对强对流天气系统的模拟能力具有重要意义。
Abstract:
      The Advanced Regional Prediction System (ARPS) along with its Data Analysis System (ADAS) were used to analyze the improvement of the initial field by assimilating radar radial velocity and reflectivity data. A local severe convective event that occurred on 21 August 2012 in Jiangxi Province was then simulated and studied by using the adjusted initial field in the Weather Research and Forecasting (WRF) model. The main results are as follows. (1) Both the mesoscale wind fields and cloud, moisture contents of the initial field were improved by assimilation of radar radial velocity and reflectivity data. The diabatic initialization of ADAS could adjust the temperature, moisture and wind fields to balance the dynamic and thermodynamic process of the initial field. (2) Assimilation of radar radial velocity made an important contribution to the improvement of the initial dynamic field, but it had little effect on atmospheric hydrometeors and precipitation forecast. Assimilation of radar reflectivity played a role mainly in adjusting the initial hydrometeors and thermal fields, which efficiently mitigated the spin-up time of the model and significantly improved the quantitative rainfall forecast. Assimilation of both radar radial velocity and reflectivity could result in a rapid development of the mesoscale horizontal wind convergence and vertical motion, adjusted temperature and moisture distributions reasonably in the initial field, and improved quantitative precipitation forecast, especially for 3-hour forecast. (3) The results of simulation show that the three dimensional structure of the convective storm and its evolution have been successfully simulated by assimilating radar radial velocity and reflectivity. The convergence and uplift force of the shear line at the middle and lower levels is one of the major dynamic mechanisms for the organization, development and maintenance of the convective storm. The convective condensation and associated latent heat release played an important role in the development of the convective storm. Therefore, radar data assimilation is of great importance to improve the accuracy of the numerical weather prediction and the model ability for the simulation of severe convective weather.
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