714CD多普勒天气雷达和711测雨雷达探测雹云的对比分析

利用７１４ＣＤ多普勒天气雷达和７１１天气雷达对１９９５年８月２６日一次较强单体雹云的对比观测资料,分析了南疆北部渭干河灌区单体雹云的结构及发展演变特点,比较并分析了两部雷达观测结果的异同及其产生原因。结果表明：７１４ＣＤ多普勒天气雷达与７１１雷达相比具有探测能力强、探测精度高的优势,而且在探测雹云的结构方面,与７１１雷达的探测结果基本一致,可以引用７１１雷达长期以来对雹云的研究结果。     

新一代天气雷达及其遥感新技术应用研究

围绕气象业务需求和雷达气象的国际前沿，新一代天气雷达建设及雷达新技术以在灾害性天气监测和预测中的应用为主要目标，开展了新一代天气雷达资料质量控制、风场反演、三维数字组网等工作。双多普勒雷达和双多基地多普勒雷达在暴雨和对流系统三维探测、反演、中尺度动力和热力结构分析中发挥了重要作用。与业务单位和雷达生产厂家开展了广泛的合作，在暴雨和新疆对流过程风场中尺度结构分析等方面形成了有创新性的科研成果。在新一代天气雷达应用方面形成了有业务应用前景的成果。     

多普勒天气雷达资料在沙尘天气监测中的应用

利用3830型多普勒天气雷达回波资料及常规气象资料对2002年3月20日发生在我国西部一直延伸至黑龙江省的沙尘、浮尘天气过程，分析其多普勒天气雷达回波，并用PPI和RHI上探测沙尘的特征、高度、厚度、浓度、移动特点、速度场分布以及垂直风速分布特点等。为多普勒天气雷达监测沙尘提供可靠依据。     

多普勒天气雷达资料在沙尘天气监测中的应用

利用3830型多普勒天气雷达回波资料以及常规气象资料，研究了2002年3月20日发生在从我国西部一直延伸至黑龙江省的沙尘暴、浮尘天气过程。初步分析了沙尘暴在PPI(平面位置显示器)和RHI(距离高度显示器)上的特征，如沙尘暴的高度、厚度、浓度、移动特点、速度场分布以及垂直风速分布等特点。为多普勒天气雷达监测沙尘暴天气提供依据。     

新一代C波段脉冲多普勒天气雷达——3830天气雷达简介

3830天气雷达是由信息产业部电子第38研究所研制并生产,是我省即将投入业务运行的新一代C波段全相干脉冲多普勒天气雷达。本文主要介绍了它的工作过程以及与713天气雷达相比3830雷达先进的技术特点,最后列举了3830雷达几种主要的气象产品,以供对新一代天气雷达感兴趣的人们参考     

中尺度气旋强风暴的单部多普勒雷达特征分析

利用北京多普勒雷达资料并结合其他资料分析了１９９１年７月１１日发生在北京以南的强风暴天气。分析表明，这次强风暴天气与多普勒天气雷达观测到的中尺度气旋相联系。文中对中尺度气旋的特征进行了分析，对主要参数（核半径、横切速度以及涡度和散度值）进行了计算，并与美国多普勒雷达观测的一些结果进行了比较     

新一代天气雷达

阐述了双偏振多普勒雷达的理论基础，以ＣＳＵ－ＣＨＩＬＬ Ｓ波段双偏振及多普勒天气雷达为例，介绍了双偏振多普勒雷达的系统结构和工作原理，并以雷达测量的数据处理和分析实例说明了双偏振多普勒雷达在气象学中的应用。     

新一代多普勒天气雷达产品及应用

黑龙江省引进的新型雷达是华东电子工程研究所最新研制的新一代大型C波段全相参脉冲多普勒天气雷达(简称3830天气雷达)。它与常规天气雷达相比，在探测手段上上了一个新台阶。它可以探测到常规天气雷达所不能探测到的云雾、弱降水等天气目标；但不能提供直接的要素预报，即使是有一部分预报产品，也还是需要在应用中不断订正。要真正发挥它的作用，还需广大预报员在分析应用中不断积累经验和开发研究。     

新一代天气雷达与常规天气雷达性能浅析

对我省新一代天气雷达和常规天气雷达的技术指标，发射接收体制及探测性能的差异等进行了分析，在实际业务应用中具有一定参考价值。     

多普勒天气雷达及其应用

简单介绍了多普勒天气雷达探测原理及测速能力,并介绍了多普勒天气雷达速度资料的应用。     

Calibration of radar reflectivity measurements from the KMA operational radar network

A systematic procedure for calibrating system gain bias (so-called “calibration error”) of radar reflectivity measurements from the Korea Meteorological Administration (KMA) operational radar network is presented. First, the RJNI radar located at Jindo Island is calibrated by comparing with radar reflectivities simulated theoretically by a scattering algorithm using drop spectra collected by a disdrometer from June 19 to 29, 2009. Once the RJNI radar is calibrated, the reflectivity measurements from nearby radars are compared with the RJNI radar reflectivities to determine existing gain biases of nearby radars. This radar-radar calibration procedure was repeated with the other radars within the network. For isolating a system gain bias, echoes affected by partial beam blockage due to ground clutter and by attenuation due to precipitation were removed. The system gain biases of the RJNI and RPSN radars were ?3 and ?4.2 dB, respectively, during the experimental period. The RBRI and RDNH radars revealed relatively large biases, above ?8 dB. The other radars (RKSN, RGSN, RSSP, RKWK, RGDK, RIIA, and RMYN) revealed biases from ?6 to ?7 dB. Thus, the reflectivity measurements from all of the KMA radars were severely biased. New R-Z relations of R = 3.350 × 10^?2Z^0.624 (Z = 231.1R ^1.6) for stratiform and R=1.546 × 10^?2 Z ^0.714 (Z = 342.4R ^1.4) for convective precipitations were derived using disdrometer data. Using these R-Z relations, the radar-derived total rainfall amounts from the reflectivity measurements without calibration produced significant underestimations, compared to gauge measurements at about 80 sites, with a normalized bias of about ?56%. On the other hand, after calibrating the above system biases, the radar-derived rainfall amounts corresponded well with the gauge measurements, with a normalized bias of about ?3%. In conclusions, the radar reflectivity measurements from the KMA radar network are severely biased and the procedure presented in this study can be used to resolve the system gain biases.     

Comparison of the observation capability of an X-band phased-array radar with an X-band Doppler radar and S-band operational radar

An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.     

成都新一代天气雷达资料整编程序开发

作者利用Visual Basic 6.0作为编程工具开发的程序,对成都站新一代天气雷达资料进行整编,既能满足国家局对雷达资料共享的部分要求,又有利于日常资料的保存和使用.使用该程序可以提高资料整编效率,给雷达资料的保存带来了方便.     

TRMM星载测雨雷达和地基雷达反射率因子数据的三维融合

TRMM卫星上的测雨雷达(TRMMPR)探测资料分布均匀且具有很高的垂直分辨率,但灵敏度较低;地基雷达(GR)水平分辨率较高且具有较高的灵敏度,但其垂直分辨率低。通过将TRMM PR与GR反射率因子数据的三维数据融合,得到了更优的反射率因子图像。测雨雷达与地基雷达三维数据融合主要分为以下几步:测雨雷达与地基雷达数据预处理——如去杂波、衰减校正;测雨雷达与地基雷达时空匹配;选取和应用合适的三维图像融合算法;对融合后的图像进行效果评估。试验结果表明:融合后的图像不仅增大了信息量,更好地检测弱降水,还提高了空间三维(3D)分辨率,能更好地反映降水区域细节,且使得数据总体上具有更高的完整性和可靠性。此外,还将基于雷达资料估测的降水数据与地面雨量计数据进行对比,估计反射率因子数据融合在降水测量上的有效性。      

成都新一代天气雷达资料整编程序开发

作者利用Visual Basic 6.0作为编程工具开发的程序,对成都站新一代天气雷达资料进行整编,既能满足国家局对雷达资料共享的部分要求,又有利于日常资料的保存和使用。使用该程序可以提高资料整编效率,给雷达资料的保存带来了方便。     

多普勒雷达与L波段雷达垂直风廓线对比分析北大核心

利用2012-2017年阜阳多普勒雷达与L波段雷达测风数据进行对比分析,统计两者的相关性和测量误差,进一步了解多普勒雷达风廓线产品的准确性和可信度。结果表明:两者测风结果一致性较好,风向和风速相关系数分别为0.97和0.94,标准差分别为19.5°和2.65 m·s^(-1)。多普勒雷达风速总体上在同一高度比L波段雷达风速偏小,两者风速相对偏差平均为24.48%;风速标准差随高度增高呈增大趋势,在降水期间对比差值小于非降水;风向标准差在7 km以下呈递减趋势,8 km以上有小幅增加趋势;风速相关系数随高度增加呈增大趋势,除低空偏低以外,其他高度相关系数均较高。     

济南边界层风廓线雷达与L波段雷达探空测风资料对比研究

采用统计、相关分析等方法,对2014年济南站边界层风廓线雷达观测资料和L波段雷达探空资料进行了长期时空变化规律的对比,进而研究了地面无降雨、有降雨时段两者的风向、风速数据的相关关系及差值。结果得出全年有降雨、无降雨时段两者的风向、风速总体一致性较好,相关性较高,并具有较好可比性和互补性的结论,对了解固定式边界层风廓线雷达探测的准确性,改进观测资料质量控制方法等具有很好的参考价值。     

Relationship between cloud characteristics and radar reflectivity based on aircraft and cloud radar co-observations

Cloud properties were investigated based on aircraft and cloud radar co-observation conducted at Yitong, Jilin, Northeast China. The aircraft provided in situ measurements of cloud droplet size distribution, while the millimeter-wavelength cloud radar vertically scanned the same cloud that the aircraft penetrated. The reflectivity factor calculated from aircraft measurements was compared in detail with simultaneous radar observations. The results showed that the two reflectivities were comparable in warm clouds, but in ice cloud there were more differences, which were probably associated with the occurrence of liquid water. The acceptable agreement between reflectivities obtained in water cloud confirmed that it is feasible to derive cloud properties by using aircraft data, and hence for cloud radar to remotely sense cloud properties. Based on the dataset collected in warm clouds, the threshold of reflectivity to diagnose drizzle and cloud particles was studied by analyses of the probability distribution function of reflectivity from cloud particles and drizzle drops. The relationship between reflectivity factor (Z) and cloud liquid water content (LWC) was also derived from data on both cloud particles and drizzle. In comparison with cloud droplets, the relationship for drizzle was blurred by many scatter points and thus was less evident. However, these scatters could be partly removed by filtering out the drop size distribution with a large ratio of reflectivity and large extinction coefficient but small effective radius. Empirical relationships of Z-LWC for both cloud particles and drizzle could then be derived.     

秦皇岛地区雨滴谱仪和雷达探测的反射率因子差异分析研究

利用布设在秦皇岛市抚宁地区的OTT Parsivel激光雨滴谱仪和卢龙地区S波段天气雷达,对2017—2019年4—9月共23次降水过程进行了观测,并分析了基于雨滴谱参数(滴谱粒子数N(D)和粒子直径大小D₀)计算的雷达反射率因子Z_D和雷达探测的雷达反射率因子Z_R的差异Z_C。结果表明,N(D)主要集中在130～530个范围内,Z_C标准差随着N(D)的增大而逐渐减少;D₀主要集中在0.8～1.6 mm范围内,Z_C标准值在D₀<1.2 mm范围内随着D₀的增大而逐渐减少,D₀在1.2～1.6 mm范围内趋于稳定;Z_D主要集中在15～40 dBZ范围内,Z_C标准差在15～35 dBZ范围内随着Z_D值增大而减小。     

Forecasting weather radar propagation conditions

Summary The increasing use of weather radar quantitative precipitation estimates, particularly in automatic applications such as operational hydrometeorological modelling or assimilation in numerical weather prediction (NWP) models, has promoted the development of quality control procedures on radar data. Anomalous propagation (AP) of the radar beam due to deviation from the standard refractivity vertical profile, is one of the factors that may affect seriously the quality of radar observations because of the increase in quantity and intensity of non-precipitating clutter echoes and consequent contamination of the estimated rainfall field. Another undesired effect of AP is the change in the expected radar echo height, which may be relevant when correcting for beam blockage in radar rainfall estimation in complex terrain. The aim of this paper is to study the use of NWP mesoscale forecasts to predict and monitor AP events. A nested 15-km grid resolution version of the MASS model has been used to retrieve refractivity profiles in the coastal area of Barcelona, near a weather radar and a radiosonde station. Using the refractivity profiles two different magnitudes were computed: the vertical refractivity profile of the lowest 1000 m layer and a ducting index which describes the existence and intensity of the most super-refractive layer contained in the lowest 3-km layer. A comparison between model forecasts and radiosonde diagnostics during a six-month period showed that the model tended to underestimate the degree of super-refraction, with a bias of 4 km⁻¹ and RMSE of 11 km⁻¹ in the 1-km vertical refractivity gradient. Further analysis of the data showed that a combination of previous observations and forecasts allowed to produce modified forecasts improving the original direct model output, decreasing substantially the bias, reducing the RMSE by 20% and improving the skill by 40%, beating also radiosonde observations persistence.