摘要:本文针对2016年6月山西、山东地区一次强对流活动，通过GRAPES（Global/Regional Assimilation andPrediction Enhanced System）云分析系统融合了多普勒雷达反射率三维组网拼图资料和ADTD（Active DirectoryTopology Diagrammer）闪电定位资料，对模式初始场的云水、云冰等云微物理变量进行了调整和分析，并对这次强对流过程设计了3组数值试验。结果表明：（1）云分析系统在加入雷达反射率资料以后，能在模式初始场中较准确的计算模式的初始水物质；（2）闪电定位资料转换成的替代雷达反射率对原有的雷达反射率有一定的补充作用，使模式的初始场与真实状况更接近；（3）从模式降水的角度看，在加入雷达资料以后，GRAPES云分析可以显著提高6小时以内降水的模拟效果，而闪电定位资料的加入，对中雨以上量级的降水模拟有进一步的改进作用。
关键词:云分析/
雷达反射率/
闪电定位
Abstract:In this study, we analyze a strong convective activity occurred in Shanxi Province and Shandong Province in June 2016. Combined with Doppler weather radar three-dimensional mosaic reflectivity data and ADTD(Active Directory Topology Diagrammer) lightning location data, cloud microphysical variables (such as cloud water, cloud ice, etc.) in the initial field can be adjusted and analyzed by the Cloud Analysis System in GRAPES (Global/Regional Assimilation and Prediction Enhanced System). Based on this strong convective activity, three sets of experiments are designed. The results indicate that:(1) The cloud analysis system in GRAPES can more accurately analyze cloud microphysical variables in the initial field when the radar reflectivity data is used. (2) The lightning location data can complement radar reflectivity data, making the initial field closer to the real state of atmosphere. (3) From the perspective of precipitation, 6-h forecast of precipitation is improved when the radar reflectivity data is applied. For moderate and heavier rain, the application of lightning data can further improve the simulation.
Key words:Cloud analysis/
Radar reflectivity/
Lightning location
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