CINRAD／CD型雷达体扫时自动抬升仰角不稳定典型故障分析及处理

对遵义雷达运行9a来12次元故障报警情况下,体扫自动抬升仰角不稳定典型故障进行归纳总结,认为：造成体扫不稳定的原因一方面是雷达体扫数据量少于扫描方位360。的80％或者相邻的两度无数据时,终端不发抬升仰角命令。另一方面是雷达俯仰控制到位精度不能满足要求,使发送了仰角命令而不能动作。造成仰角指令未发送主要有3个方面：①监控机与终端之间通信不畅导致方位角码变换不连续或数据采集量不够;②监控机与采集机之间的24针传输命令电缆故障;③方位角码变换单元故障导致角码变化不连续。造成俯仰控制精度不够主要有6个方面：①驱动误差电压出现异常;②俯仰伺服放大器的静态特性和动态特性发生变化;③俯仰伺服放大器板子上有元器件出现损坏;④俯仰的速度反馈出现故障;⑤汇流环出现故障;⑥天线反射体回差较大。     

CINRAD/CD雷达伺服系统频发故障判断与处理总结

通过对2018年贵州新一代天气雷达故障进行统计分析,CINRAD/CD雷达伺服系统故障占了总故障的37%,且部分伺服系统故障在排除时耗时较长。由于伺服系统故障多种多样,掌握伺服系统信号流程是解决故障的根本方法。因此该文先介绍了CINRAD/CD雷达伺服系统原理及信号流程;然后根据伺服系统信号流程给出伺服系统频发故障的分析、判断及处理过程;最后要求台站人员做好常规维护和定标,可避免一些松动、断线等软性故障,有效提高CINRAD/CD雷达伺服系统故障处理效率及业务可用性。     

CINRAD/SA数字交流伺服系统调试和维修方法

总结了CINRAD/SA雷达交流变频数字伺服系统技术特点和交流变频数字伺服系统的主通道信号流程、监控信号流程、变频器信号流程,根据监测信息、报警信息、关键点参数,从位置环、速度环、加速度环3个方面探讨了CINRAD/SA雷达交流变频数字伺服系统故障诊断方法,以及天线不受控制、天线运转不正常、跳码或角码和天线实际位置不一致故障诊断方法.列举了两个典型故障个例,即：由于伺服速度反馈信号不正常,导致天线方位电机过热报警,方位无法完成无超调控制且方位到位精度差和过冲;由于方位和俯仰跳码,导致雷达动态错误报警,天线失控到高仰角死区.总结了这两个典型故障个例的理论分析和处理步骤.提出了交流变频数字伺服系统维修方面的一些建议,为新一代天气雷达技术支持和保障提供借鉴.     

CINRAD/SA雷达伺服电机连续故障诊断分析

CINRAD/SA天气雷达投入业务运行以来,在天线伺服系统方面出现了很多次故障,而直流方位电机是天线伺服系统的主要组成部分也是发生故障较多的部件之一。2014年福建长乐CINRAD/SA天气雷达在重大天气保障过程中,连续发生方位电机卡死造成雷达停机和测速机性能降低引起天线转速不稳造成雷达产品异常的故障;根据天线控制信号流程,通过运行雷达RDASOT测试程序、测量直流方位电机阻值、测量测速机反馈电压等方法,分析其故障的成因,对雷达伺服直流电机故障分析及解决方法有重要的指导作用。     

CINRAD雷达产品“缺角”现象分析及处理

基于CINRAD/SA雷达图像产品出现"缺角"的现象,分析信号流程并通过BDAVC5软件观察天线运动轨迹,发现激磁电压过低导致旋转变压器有时辨识不出来正弦波信号,引起方位跳码,使得天线在未完成本仰角扫描的情况下就提前跳转到下一仰角进行扫描,从而造成了仰角剩余方位角度上的数据缺测。详细阐述了激磁电压过低而导致数据缺测的原因,指出此类故障多数发生在伺服系统,提出利用BDAVC5软件分析天线运行轨迹在伺服故障定位方面能起到很好的辅助作用。     

CINRAD/SA雷达天线锥摆故障诊断分析

天线锥摆现象是雷达天线伺服系统较为常见的故障,天线长期锥摆,会降低天线的控制精度,磨损天线伺服系统的机械结构,严重时还会导致雷达强制停机。为解决滨州CINRAD/SA雷达天线追摆故障,根据天线伺服系统的工作原理、天线位置控制策略和天线各信号流程,逐一排查可能存在的故障点,最终发现俯仰电机速度反馈信号异常,造成天线锥摆。详细描述了故障的发现、诊断、排查、处理过程,通过对此次故障分析处理,为雷达技术保障提供经验。     

CINRAD/SA雷达闪码故障分析和排查方法

天线伺服系统是CINRAD/SA天气雷达的重要组成部分,大部分组件长期处于机械运转中,且线路复杂,是雷达系统中故障率较高的部分,其中,闪码故障发生概率较大。本文对2007—2013年全国CINRAD/SA雷达站收集的68个闪码故障案例进行统计分析,结果表明,电机、旋转变压器、汇流环、轴角编码盒、光纤链路、数字控制单元等环节均有可能导致闪码。结合CINRAD/SA雷达伺服系统天线角码信号流程和关键点的参数特征,对可能导致雷达闪码故障的所有环节逐个进行分析,归纳总结出CINRAD/SA雷达出现此类故障的排查方法,并从收集的案例中选取5个典型个例展开分析。通过统计样本案例的故障归属,提出轴角闪码时检测部件的先后顺序,为各台站快速排除雷达闪码故障提供了思路,对解决其他天线伺服系统故障也有一定的借鉴意义。     

新一代天气雷达轴角盒故障的分析处理

CINRAD/SA天气雷达在PPI扫描过程中天线来回摆动,导致雷达无规律出现方位扇形范围无回波,雷达不能正常发挥其有效作用。为查找故障原因,从新一代天气雷达伺服系统信号流程入手,结合雷达基数据分析软件,分析雷达天线运行轨迹,通过信号流程中关键点参数的测量和比较,发现问题出现在轴角编码盒方位环节,导致轴角盒串行方位轴角数据输出不连续,造成雷达无规律出现方位扇形范围无回波。通过对此类故障分析思路与处理经验的总结,对台站级雷达技术保障提供借鉴。     

CINRAD/SC天气雷达伺服系统故障分析

分析了临沂新一代天气雷达伺服系统的工作原理,在此基础上对近几年伺服系统出现的故障进行分析,并结合故障实例给出伺服系统的故障排除方法。特别是对2009年全运会期间一次伺服系统故障进行了详细分析并介绍了排除过程,为今后新一代天气雷达的维护维修提供参考。     

CINRAD／SA天气雷达伺服系统特殊故障分析

CINRAD／SA雷达的伺服系统是整个雷达数字控制电路与机械电机联接的关键环节,它的故障造成雷达系统报警不断,俯仰环节的故障将导致系统无法工作。本文在杭州CINRAD／SA天气雷达中,选取了二个伺服系统故障导致系统无法工作的典型例子,对其进行系统分析,揭示它的故障成因,提出改进措施。     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;     

Information for Contributors

正Journal of Meteorological Research is an international academic journal in atmospheric sciences edited and published by Acta Meteorologica Sinica Press,sponsored by the Chinese Meteorological Society.It has been acting as a bridge of academic exchange between Chinese and foreign meteorologists and aiming at introduction of the current advancements in atmospheric sciences in China.The journal columns include Articles.Note and Correspondence,and research letters.Contributions from all over the world are welcome.     

前寒武纪气候演化中的三个重要科学问题

自地球形成至寒武纪将近40亿年（距今46亿～5.4亿年,通常称为前寒武纪）的气候演变是一个具有特殊难度和挑战性的研究领域,同时也是基础和前沿的研究领域。文章选择了前寒武纪气候演化中的三个重要科学问题进行综述：大气演化、两次全球性的冰川期以及暗弱太阳问题。关于大气演化,本文首先描述了大气成分的演化历史,然后简述了影响大气成分演化的三个基本过程：大气逃逸、两次大气氧含量突然增加、碳酸盐-硅酸盐循环及其对气候系统的负反馈作用。两次全球性的冰川期分别发生在古元古代（距今24亿～21亿年）和新元古代（距今8亿～5.8亿年）,文章简述了其成因以及相关的气候模拟结果。暗弱太阳问题是地球历史气候演化的一个经典问题,论文简要地综述了一些最新的研究成果和观点。     

淮河流域水文极值预测模型研究

为探索气候变化影响下水文极值的非平稳性和预测方法,建立了水文极值非平稳广义极值（GEV）分布的统计预测模型。利用1952-2010年淮河上游流域累计面雨量和流量年最大值资料、同期500 hPa环流特征量资料以及17个CMIP5模式对环流特征量的模拟结果,筛选出对水文极值影响显著的年平均北半球极涡强度指数作为GEV分布参数的预测因子。分析了在RCP2.6、RCP4.5和RCP8.5情景下2006-2050年淮河上游流域水文极值对气候变化的响应。结果表明,10年以下与10年以上重现期的水文极值在非平稳过程中呈现前者下降而后者上升的相反变化趋势;多模型预测的集合平均在未来情景中均呈现上升趋势,情景排放量越大增幅越大,重现期越长增幅也越大。与极值的常态相比,极值的极端态更易受气候变化影响。     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.