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投稿时间:2023-07-05 修订日期:2024-03-04
投稿时间:2023-07-05 修订日期:2024-03-04
中文摘要: 以2017年6月16日发生在广东省的一次中尺度对流过程为例,利用WRF模式对中尺度对流系统进行模拟,分析了联合同化闪电和地面常规观测资料较单独同化其中一种资料的改进作用。闪电资料通过WRF-FDDA系统以15 min作为一个闪电累积窗口被连续同化入模式中,地面常规观测资料通过WRFDA-3DVAR系统以1 h间隔循环同化入模式中。结果显示,相比于只同化地面常规观测资料,联合同化试验中闪电资料的引入提高了背景场中上升气流、冷池和阵风锋的准确度;相比于只同化闪电观测资料,地面常规观测资料的引入减小了更大范围的温度、水汽、风场的背景场误差,抑制了部分地区的虚假对流,即两种资料的联合同化整体上提高了对流系统的模拟准确度。预报技巧评分结果显示,联合同化对同化期和预报期的评分也有一定程度的提高。
Abstract:A mesoscale convective progress occurred in Guangdong Province on 16 June 2017, and the system was simulated by WRF model. This article analyzes the impact of the combined assimilation of the lightning and conventional surface observation data on the simulation of mesoscale convective system compared with the single assimilation of one kind of data. The lightning data were continuously assimilated into the model through the WRF-FDDA system with a lightning accumulation window of 15 min, while the conventional observation data were assimilated into the model by the WRFDA-3DVAR system with one hour interval. The results show that the introduction of lightning data in the joint assimilation experiment has improved the accuracy of updrafts, cold pools, and gust fronts in the background fields relative to the assimilation of conventional surface observations only. The introduction of conventional surface observations has reduced the background field errors in temperature, water vapor, and wind fields over a larger area, suppressed the spurious convection in some areas, and overall improved the simulation accuracy of the convective system. The results of prediction skill score show that the combined assimilation of the two kinds of data can also improve the prediction skill score of the assimilation period and the forecast period to some extent.
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基金项目:国家自然科学基金气象联合基金项目(U2342222)、国家自然科学基金项目(42230604)共同资助
引用文本:
师雨豪,王昊亮,刘玉宝,2024.联合同化闪电资料和地面常规观测资料对强对流天气预报的影响[J].气象,50(10):1231-1242.
SHI Yuhao,WANG Haoliang,LIU Yubao,2024.Impact of Combined Assimilation of Lightning and Conventional Surface Observations on the Forecast of Severe Convective Weather[J].Meteor Mon,50(10):1231-1242.
师雨豪,王昊亮,刘玉宝,2024.联合同化闪电资料和地面常规观测资料对强对流天气预报的影响[J].气象,50(10):1231-1242.
SHI Yuhao,WANG Haoliang,LIU Yubao,2024.Impact of Combined Assimilation of Lightning and Conventional Surface Observations on the Forecast of Severe Convective Weather[J].Meteor Mon,50(10):1231-1242.