| 雷达热动力反演资料的高分辨率同化模拟试验 |
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| 引用本文： | 张亦洲,苗世光,陈明轩.雷达热动力反演资料的高分辨率同化模拟试验[J].气象学报,2017,75(1):165-177. |
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| 作者姓名： | 张亦洲 苗世光 陈明轩 |
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| 作者单位： | 中国气象局北京城市气象研究所, 北京, 100089 |
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| 基金项目： | 北京市气象局科技项目（BMBKJ201403005）；北京市科技计划课题（Z151100002115045）；国家自然科学基金项目（41175015）；国家国际科技合作专项项目（2015DFA20870）。 |
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| 摘 要： | 目前，北京地区的天气预报系统对局地对流性定量降水预报能力较弱，远不能满足人们生产、生活和防灾、减灾工作的需要。针对北京地区对提高0-12 h短时临近天气，尤其是夏季局地对流性降水预报能力的需求，基于中国气象局北京城市气象研究所变分多普勒雷达分析系统（VDRAS）的雷达热动力反演资料，建立了WRF模式初始化模块，采用四维资料同化（FDDA）方法，将VDRAS系统高时空分辨率三维热动力结构分析场资料同化到WRF模式中，实现了北京地区VDRAS分析场资料在WRF中尺度模式系统中的应用。通过降水个例的高分辨率同化模拟试验分析了雷达热动力反演资料同化对模式预报结果的影响。研究结果表明:雷达热动力反演资料的同化能够提高模式系统对近地面温、湿、风大气要素和降水过程的模拟能力，改善2 m比湿、降水落区、降水量级、降水时间的预报效果，减少降水漏报的现象。温度和比湿的同化比风的同化对模拟降水结果的改善更重要。虽然研究表明雷达热动力反演资料在WRF模式中的同化能够明显改善模式对选取降水个例的模拟效果，但其对模式尤其是数值业务模式系统预报效果的影响需要进一步更全面、更系统的检验，为业务化应用奠定更坚实的基础。
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| 关 键 词： | 变分多普勒雷达分析系统 WRF模式 四维资料同化(FDDA)方法 降水 |
| 收稿时间： | 2016/3/22 0:00:00 |
| 修稿时间： | 2016/8/31 0:00:00 |
Numerical experiments on assimilation of high-resolution radar thermodynamic data |
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| ZHANG Yizhou,MIAO Shiguang and CHEN Mingxuan.Numerical experiments on assimilation of high-resolution radar thermodynamic data[J].Acta Meteorologica Sinica,2017,75(1):165-177. |
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| Authors: | ZHANG Yizhou MIAO Shiguang and CHEN Mingxuan |
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| Institution: | Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China |
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| Abstract: | The accuracy of weather forecast in Beijing is still far from satisfying the demands of people''s routine life and disaster prevention and reduction, especially the quantitative forecast for local convective rainfall. To address the demands for improved 0-12 h short-term weather forecast in Beijing, especially the forecast of local convective rainfall in the summer, an initialization module that can be used in the Weather Research and Forecasting (WRF) model is developed based on Variational Doppler Radar Analysis System (VDRAS) in Institute of Urban Meteorology (IUM), China Meteorological Administration, Beijing. The radar data, which contain high temporal and spatial resolution three-dimensional thermodynamic characteristics, are assimilated into WRF model through the Four-Dimensional Data Assimilation (FDDA) method. Impacts of radar thermodynamic data on WRF model results are analyzed based on numerical simulation experiments of several rainfall cases. The results show that assimilation of the high-resolution radar thermodynamic data into WRF model can improve the simulation of the rainfall cases. The accuracies of simulated 2 m humidity, location, period and intensity of the rainfall are improved. The missing rates in the rainfall simulation also decrease with the application of data assimilation. Further analysis indicates that the assimilation of temperature and humidity is more important than the assimilation of wind for the improvement of the model results. Although the present study have shown that the assimilation of radar thermodynamic data into the WRF model can significantly improve the model results for the selected rainfall cases, more comprehensive and systematic investigation is needed to further study the effects of data assimilation in operational numerical model systems. |
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| Keywords: | VDRAS WRF model FDDA method Rainfall |
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