| 基于变分技术的天气雷达速度退模糊算法的改进研究 |
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| 引用本文： | 吴彬,魏鸣,李艳芳,郑石,ABRO Mohammad Ilyas.基于变分技术的天气雷达速度退模糊算法的改进研究[J].气象与环境学报,2019,35(3):18-28. |
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| 作者姓名： | 吴彬 魏鸣 李艳芳 郑石 ABRO Mohammad Ilyas |
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| 作者单位： | 湖州市气象局,浙江 湖州313000;南京信息工程大学气象灾害预报预警与评估协同创新中心,江苏 南京210044;南京信息工程大学气象灾害预报预警与评估协同创新中心,江苏 南京,210044;湖州市气象局,浙江 湖州,313000;辽宁省气象装备保障中心,辽宁 沈阳,110166 |
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| 基金项目： | 国家自然科学基金（41675029）、国家重点基础研究发展计划973项目（2013CB430102）、中国气象科学研究院灾害天气国家重点实验室开放课题（2016LASW-B12）、江苏省2018年度普通高校研究生科研创新计划项目（KYCX18_0998）、浙江省气象局预报员专项（2017YBY05）和湖州市公益性技术应用研究（重点）项目（2018GZ27）共同资助。 |
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| 摘 要： | 为有效地识别和提取多普勒天气雷达风场信息,对Gao和Droegemeier提出的基于变分技术的多普勒雷达径向速度数据退模糊方法进行了改进。原方法中将背景风场、方位和径向速度距离梯度信息同时作为约束条件,对Nyquist数进行校正。但是该方法在迭代过程中使用了大量的数值分析和偏微分方程计算,造成径向速度场过度平滑和数据失真。针对这个问题,改进算法在得到径向速度分析场后,结合原始径向速度观测场,通过图像变化检测法,自动识别存在速度模糊的区域及计算需要校正的Nyquist数,对观测场的模糊区域进行校正。利用强对流天气和台风过程的雷达体扫数据验证了改进算法的可行性,并与原始算法及业务应用的WSR-88D算法对比。结果表明:改进算法有效地解决了原始算法中的不足,恢复真实的风场结构和分布特征,改善了退速度模糊的质量,从而得到更为合理的径向速度观测场;并且该算法退模糊效果优于WSR-88D算法,有助于为科研和业务应用服务。
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| 关 键 词： | 变分技术 天气雷达 速度退模糊 图像变化检测法 |
| 收稿时间： | 2018-02-13 |
Research on the improvement of weather radar velocity dealiasing algorithm based on variational technique |
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| WU Bin,WEI Ming,LI Yan-fang,ZHENG Shi,ABRO Mohammad.Research on the improvement of weather radar velocity dealiasing algorithm based on variational technique[J].Journal of Meteorology and Environment,2019,35(3):18-28. |
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| Authors: | WU Bin WEI Ming LI Yan-fang ZHENG Shi ABRO Mohammad |
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| Institution: | 1. Huzhou Meteorological Service, Huzhou 313000, China;2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;3. Liaoning Provincial Meteorological Equipment Support Center, Shenyang 110166, China |
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| Abstract: | In order to effectively identify and extract Doppler weather radar wind field information,the dealiasing method of Doppler radar radial velocity data proposed by Gao and Droegemeier based on the variational technique was improved.In the original method,the information of background wind field,azimuth and radial velocity and distance gradient were simultaneously taken as constraint conditions to calibrate the Nyquist number.However,in the iterative process,a large number of numerical analysis and partial differential equation were used,resulting in the radial velocity excessively smooth and distortion.To solve this problem,based on obtaining the radial velocity analysis field,the improved algorithm combined with the original radial-velocity observation field,automatically identified the area with velocity ambiguity and calculated the Nyquist number to be corrected through the image change detection method,and then corrected the aliasing area of the observation field.The feasibility of the improved algorithm was verified by the radar volume scans data of severe convection weather and a typhoon event.Compared with the original and the operational WSR-88D algorithms,it shows that the improved algorithm can effectively solve the shortcomings of the original algorithm,reproduce the real structure and distribution characteristics of the wind field,improve the quality of velocity dealiasing,and thus obtain a more reasonable radial-velocity observation field.Moreover,the dealiasing effect of this algorithm is better than that of the WSR-88D algorithm,which is helpful for scientific research and operational application. |
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| Keywords: | Variational technique Weather radar Velocity dealiasing Image change detection method |
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