风廓线雷达资料的应用Ⅰ:质量评估
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1.南京信息工程大学;2.内蒙古通辽市气象局

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Application of Wind Profiler Radar Data I : Quality Assessment
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1.Nanjing University of Information Science Technology;2.Inner Mongolia Tongliao Meteorological Service

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    摘要:

    风廓线雷达是一种新型的测风雷达,能够探测大气水平风的垂直分布,提供高时空分辨率的风场信息,在我国气象业务中发挥着越来越重要的作用。但是,我国风廓线雷达型号众多,资料质量差别较大,为了更好地对风廓线雷达探测资料进行应用,提高数值预报水平,本文利用FNL资料、探空资料对2019年6月~9月位于中国华北地区20个站点共5种型号(CFL-06、GLC-24、TWP8-L、CFL-03、CLC-11-D)的边界层风廓线雷达资料进行了质量评估,结果表明:各型号雷达均具有较强的探测能力,但不同雷达在水平风资料数据获取率以及有效探测高度上差异极大。不区分天气状况时,所有型号雷达均为V风质量优于U风质量。TWP8-L雷达U风测风质量相对最佳,CFL-03雷达紧随其后,GLC-24雷达U风测风质量最差,V风质量则差异不大,U风数据使用前需进行偏差订正以及质量控制。风廓线雷达观测对于降水较为敏感,降水使各型号雷达数据获取率在底层减小,中高层增加,增幅最大达到53%,但探测能力加强并不代表测风质量增加,统计结果表明降水也是造成U风平均误差以及均方根误差较高的重要原因,其中,GLC-24、CLC-11-D雷达对降水最为敏感,降水状态相较于非降水状态均方根误差增幅均达到了5.5m/s以上,降水情况下的U风及V风资料需进行进一步质量控制才可使用。

    Abstract:

    A wind profiler radar is a new type of Doppler wind radar designed to measure the horizontal wind vectors, and are able to provide wind profiles at various elevations with high temporal and spatial resolution. It plays an increasingly important role in China"s Meteorological business. However, the quality of wind profiler radar data varies widely consider-ing the different types of radars deployed in China. To better utilize these data in numerical weather prediction (NWP), this study assesses the data quality from five different types of wind profiler radars (i.e., CFL-06, GLC-24, TWP8-L, CFL-03 and CLC-11-D) at 20 stations in North China from June to September 2019. Results show that each type of profiler has strong detection ability, but different profilers have great differences in data acquisition rate and effective detection height. Without considering the influence of precipitation, the data quality of v-wind is better than that of u-wind for all types of profilers. In all air conditions, the quality of u-wind data from TWP8-L profiler is relatively the best, followed by CFL-03 radar, the quality of u-wind data from GLC-24 radar is the worst. The differences in v-wind data is not noticea-ble, while bias correction and quality control are necessary for u-wind data. The data quality of wind profile radar is quite sensitive to precipitation, which reduces the data acquisition rates at low levels and increases the data acquisition rates at the middle and high levels, with the maximum increase of 53%. The statistical results indicate precipitation is responsible for the large mean errors and root mean square errors (RMSEs) of u wind data. GLC-24 and CLC-11-D profilers are the most sensitive to precipitation. The RMSEs are increased by 5.5 m/s in precipitation regions as compared to non-precipitation regions. The u-wind and v-wind data in precipitation regions requires further quality control procedure.

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历史
  • 收稿日期:2022-05-03
  • 最后修改日期:2022-05-21
  • 录用日期:2022-05-23
  • 在线发布日期: 2022-05-23
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