阵列天气雷达设计与初步实现
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摘要
阵列天气雷达是分布式、高度协同的相控阵天气雷达。阵列天气雷达至少包括3个相控阵收发子阵(简称收发子阵),通过增加收发子阵而扩大探测区域。每3个相邻的收发子阵一组协同扫描,保证3个相邻收发子阵在同一个空间点的数据时差小于2 s,从而保证径向速度合成正确的流场。采用相控阵多波束扫描技术,4个发射波束和64个接收波束覆盖0°～90°仰角,机械扫描覆盖360°方位,整个体扫时间为12 s,为多普勒天气雷达整个体扫时间的1/30。阵列天气雷达通过金属球进行了强度、波束宽度、方位、仰角的定标。阵列天气雷达在长沙机场布设试验,成功获取了精细的风场和回波强度数据,可为更精细、更完整揭示小尺度天气系统变化规律提供新工具。
With the development of phased array technology and networked radars, focusing on the requirement of small-scale weather fine detection,the array weather radar(AWR) is developed, which is a distributed and highly collaborative radar. The traditional Doppler weather radar can obtain radial velocity of cloud or precipitation targets. However, single radial velocity of a spatial point cannot reflect the movement information of precipitation and atmosphere. A multi-radar network can obtain a plurality of radial velocity values using a collaborative detection method, but disadvantages are that the time difference of the same single spatial point obtained by multiple radars is high, leading to composition error of the velocity or invalid observation.The AWR comprises at least three phased array transmit-receive subarrays(subarrays for short), and the detection region of the AWR can be enlarged by increasing the number of subarrays. The AWR employs a multi-beam phase array scanning technology, which has 4 transmission beams and 64 receiving beams covering an elevation angle between 0° and 90°. And meanwhile, a 360° azimuth is covered by mechanical scanning. One volume scanning time of the AWR is 12s which are several tenths of the traditional Doppler weather radar. Each three adjacent subarrays work as a group, which performs collaborative scanning to ensure data time differences at the same spatial point from three adjacent subarrays are less than 2s, and then correct flow fields can be synthesized by using radial velocity of the subarrays. This is a big progress in acquiring thermodynamic information and dynamic information of precipitation targets.One AWR consisting of three subarrays has been deployed at Changsha Airport and has acquired three-dimensional velocity and intensity(reflectivity factor) data, and more fine information of small-scale weather systems may be obtained by using data. There are still a lot of problems to be solved and a lot of works to be done in the field of the AWR technology and application.
With the development of phased array technology and networked radars, focusing on the requirement of small-scale weather fine detection,the array weather radar(AWR) is developed, which is a distributed and highly collaborative radar. The traditional Doppler weather radar can obtain radial velocity of cloud or precipitation targets. However, single radial velocity of a spatial point cannot reflect the movement information of precipitation and atmosphere. A multi-radar network can obtain a plurality of radial velocity values using a collaborative detection method, but disadvantages are that the time difference of the same single spatial point obtained by multiple radars is high, leading to composition error of the velocity or invalid observation.The AWR comprises at least three phased array transmit-receive subarrays(subarrays for short), and the detection region of the AWR can be enlarged by increasing the number of subarrays. The AWR employs a multi-beam phase array scanning technology, which has 4 transmission beams and 64 receiving beams covering an elevation angle between 0° and 90°. And meanwhile, a 360° azimuth is covered by mechanical scanning. One volume scanning time of the AWR is 12s which are several tenths of the traditional Doppler weather radar. Each three adjacent subarrays work as a group, which performs collaborative scanning to ensure data time differences at the same spatial point from three adjacent subarrays are less than 2s, and then correct flow fields can be synthesized by using radial velocity of the subarrays. This is a big progress in acquiring thermodynamic information and dynamic information of precipitation targets.One AWR consisting of three subarrays has been deployed at Changsha Airport and has acquired three-dimensional velocity and intensity(reflectivity factor) data, and more fine information of small-scale weather systems may be obtained by using data. There are still a lot of problems to be solved and a lot of works to be done in the field of the AWR technology and application.
引文
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[18]吴翀,刘黎平,汪旭东,等.相控阵雷达扫描方式对回波强度测量的影响.应用气象学报,2014,25(4):406-414.
[19]杨金红,高玉春,程明虎,等.相控阵天气雷达波束特性.应用气象学报,2009,20(1):119-123.
[20]郑永光,周康辉,盛杰,等.强对流天气监测预报预警技术进展.应用气象学报,2015,26(6):641-657.
[21]黄先香,俞小鼎,炎利军,等.广东两次台风龙卷的环境背景和雷达回波对比.应用气象学报,2018,29(1):70-83.
[22]陈元昭,俞小鼎,陈训来,等.2015年5月华南一次龙卷过程观测分析.应用气象学报,2016,27(3):334-341.
[23]毕宝贵,代刊,王毅,等.定量降水预报技术进展.应用气象学报,2016,27(5):534-549.
[24]杨洪平,张沛源,程明虎,等.多普勒天气雷达组网拼图有效数据区域分析.应用气象学报,2009,20(1):47-55.
[2] Junyent F, Chandrasekar V, McLaughlin D, et al. The CASA integrated project 1 networked radar system. J Atmos Oceanic Technol,2010,27(1):61-78.
[3] McLaughlin D J, Chandrasekar V K, Droegemeier K,et al. Distributed Collaborative Adaptive Sensing(DC AS)for Improved Detection, Understanding, and Prediction of Atmospheric Hazards. Ninth Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface. American Meteorological Society,2005.
[4] Philips B,Pepyne D,Westbrook D,et al. Integrating end user needs into system design and operation:The center for collaborative adaptive sensing of the atmosphere(CASA). Chemistry&Biodiversity,2007,1(11):1829-1841.
[5]陈洪滨,李兆明,段树,等.天气雷达网络的进展.遥感技术与应用,2012,27(4):4487-495.
[6] Nitin B,Chandrasekar V,Junyent F. Signal processing system for the CASA integrated project I radars. J Atmos Oceanic Technol,2010,27(9):1440-1460.
[7] Brotzge J A,Zink M,Preston M,et al. CASA's First Test Bed:Integrated Project 1(IP1). 32nd Conference on Radar Meteorology,American Meteorological Society,2005.
[8] Chandrasekar V, McLaughlin D,Brotzge J, et al. Distributed Collaborative Adaptive Radar Network:Preliminary Results from the CASA IPI Testbed. IEEE Radar Conference,2008.
[9] Brotzge J,Droegemeier K, McLaughlin D. Collaborative adaptive sensing of the atmosphere(CASA):A new radar system for improving analysis and forecasting of surface weather conditions. Transportation Research Record,2006,1948:145-151.
[10]李思腾,陈洪滨,马舒庆,等.网络化天气雷达协同自适应观测技术的实现.气象科技,2016,44(4):517-527.
[11] William E B.Torok G,Weber M,et al. Progress of Multifunction Phased Array Radar(MPAR)Program. 25th Conference on International Interactive Information and Processing Systems(IUPS)for Meteorology,Oceanography,and Hydrology,2009.
[12] Wu T,Takayanagi Y,Yoshida S,et al. Spatial relationship between lightning narrow bipolar events and parent thunderstorms as revealed by phased array radar. Geophys Res Lett,2013,40(3):618-623.
[13] Adachi T,Kusunoki K,Yoshida S,et al. IIigh-speed volumetric observation of a wet microburst using X-Band phased array weather radar in Japan. Mon Wea Rev, 2016, 144(10):3749-3765.
[14] Adachi T,Kusunoki K,Yoshida S,et al. Rapid volumetric growth of misocyclone and vault-like structure in horizontal shear observed by phased array weather radar. Sola,2016,12:314-319.
[15] Yoshida S, Adachi T,Kusunoki K,et al. Relationship between thunderstorm electrification and storm kinetics revealed by phased array weather radar. J Geophys Res, 2017, 122(7):3821-3836.
[16]张培昌,王振会.大气微博遥感基础.北京:气象出版社,1995.
[17]刘黎平,吴翀,汪旭东,等.X波段一维扫描有源相控阵天气雷达测试定标方法.应用气象学报,2015,26(2):129-140.
[18]吴翀,刘黎平,汪旭东,等.相控阵雷达扫描方式对回波强度测量的影响.应用气象学报,2014,25(4):406-414.
[19]杨金红,高玉春,程明虎,等.相控阵天气雷达波束特性.应用气象学报,2009,20(1):119-123.
[20]郑永光,周康辉,盛杰,等.强对流天气监测预报预警技术进展.应用气象学报,2015,26(6):641-657.
[21]黄先香,俞小鼎,炎利军,等.广东两次台风龙卷的环境背景和雷达回波对比.应用气象学报,2018,29(1):70-83.
[22]陈元昭,俞小鼎,陈训来,等.2015年5月华南一次龙卷过程观测分析.应用气象学报,2016,27(3):334-341.
[23]毕宝贵,代刊,王毅,等.定量降水预报技术进展.应用气象学报,2016,27(5):534-549.
[24]杨洪平,张沛源,程明虎,等.多普勒天气雷达组网拼图有效数据区域分析.应用气象学报,2009,20(1):47-55.