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.     

深圳S波段与X波段双偏振雷达在定量降水估计中的应用

双偏振多普勒天气雷达的一个重要应用是进行定量降水估计（QPE）,它可以获得反射率（Z_H）、差分反射率（Z_DR）和差传播相移率（K_dp）这些与降水粒子有关的信息,常用的双偏振雷达降水估计方法有基于Z_H的R（Z_H）、基于Z_H和Z_DR的R（Z_H,Z_DR）、基于K_dp的R（K_dp）和基于K_dp与Z_DR的R（K_dp,Z_DR）这4种。文中利用深圳市S波段和X波段双偏振多普勒雷达探测资料,结合高精度地形数据和雨滴谱仪观测数据,设计了基于双偏振量的定量降水估计方法:首先利用地形数据和雷达地理信息,分析了雷达的遮挡状况,形成了这两部雷达的复合平面扫描仰角信息;随后利用雨滴谱仪观测资料,使用T矩阵方法统计得到了深圳地区的上述4种降水反演方法的参数;最后设计了混合降水反演方法,基于双偏振信号（即K_dp和Z_DR）的强弱,使用不同的降水反演方法进行定量降水估计。基于12个降水个例,利用各反演方法产生的定量降水估计结果与雨量计观测资料比较。结果表明,混合降水反演方法在降水反演的准确度和稳定性上均优于任何一种单一定量降水估计反演方法。基于文中介绍的定量降水估计方法,使用深圳S波段和X波段雷达产生了定量降水估计产品,并与深圳目前业务定量降水估计产品进行对比评估。结果表明,使用本方法产生的定量降水估计产品在准确度和稳定性上要优于目前的业务产品。此外,X波段雷达的定量降水估计产品性能要略高于S波段雷达的定量降水估计产品,这说明高时、空分辨率的X波段雷达可以提高定量降水估计精度。但由于雷达扫描平面内双偏振雷达对融化层和冰区的偏振量观测与降水的关系尚未明确,因此,本方法仅适用于雷达扫描平面内液态降水区。      

基于TRMM/PR的长江下游地基雷达一致性订正

我国有近200部地基多普勒天气雷达,已经积累了近20年的观测数据,这些数据对雷达气候学研究非常重要。但由于不同雷达的标定误差不同,雷达之间存在观测值不一致性的现象（与美国的地基雷达类似）,有的反射率因子差异超过了3 dB。这种不一致影响了多雷达联合降水估计的精度和雷达组网临近预报的效果。为此,采用筛选比较法对地基雷达与TRMM/PR（Tropical Rainfall Measuring Mission/Precipitation Radar）进行空间匹配和异常数据剔除,以TRMM/PR为参照计算并订正地基雷达偏差。对2013年5—9月长江下游7部S波段雷达数据订正后,结果表明:订正后7部雷达之间的平均反射率因子差异从1.8 dB降至0.5 dB,任意两部雷达之间的差异均小于1.0 dB,多雷达的观测一致性和空间连续性有明显改善。与传统的几何匹配法比较,筛选比较法订正结果相对稳定,不存在过量订正的问题。     

Comparison of Precipitation Observations from a Prototype Space-based Cloud Radar and Ground-based Radars

A prototype space-based cloud radar has been developed and was installed on an airplane to observe a precipitation system over Tianjin,China in July 2010.Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype.A cross-comparison algorithm between different wavelengths,spatial resolutions and platform radars is presented.The reflectivity biases,correlation coefficients and standard deviations between the radars are analyzed.The equivalent reflectivity bias between the S-and Ka-band radars were simulated with a given raindrop size distribution.The results indicated that reflectivity bias between the S-and Ka-band radars due to scattering properties was less than 5 dB,and for weak precipitation the bias was negligible.The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity,but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter.The measured reflectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar(SA radar),and 13.7 dB stronger than that by the ground-based cloud radar.The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar.This study could provide a method for the quantitative examination of the observation ability for space-based radars.     

GPM/DPR雷达与CINRAD雷达降水探测对比

通过对比星载DPR雷达与地基CINRAD雷达的降雨测量值,评估星地雷达联合应用的潜力。为了提高对比的准确性,在尽可能高的时空分辨率下,以几何匹配与格点匹配相结合的方式,提取星地雷达降水样本数据。2015年6月30日降水过程的对比分析结果表明:泰州、常州CINRAD雷达反射率因子在两站中分剖面的平均值偏差0.94 dB,地基雷达之间有很好的一致性;在DPR雷达与常州、泰州CINRAD雷达同时覆盖的降雨区域,星地之间雷达反射率因子的平均值偏差分别为-1.2 dB和-1.6 dB,显示星地雷达也有较好的一致性;现有DPR雷达陆上衰减订正算法在缩小星地雷达偏差方面起到一定作用,平均订正量0.4 dB,只要回波覆盖充分,匹配样本的高度以及其到地基雷达的距离对对比结果没有明显影响,而衰减订正和匹配样本区回波覆盖率是影响星地雷达对比结果的重要因素。     

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.     

The operational weather radar of Fossalon di Grado (Gorizia, Italy): accuracy of reflectivity and differential reflectivity measurements

Summary The error structure of radar measurements should be accurately known in order to provide reliable estimates for a number of quantitative meteorological applications, from rainfall rate estimation to cloud microphysics. The aim of this paper is to give a detailed characterization of Z _H and Z _DR measurements obtained by the weather radar of Fossalon di Grado (Gorizia, Italy). Vertical-looking observations are used to determine the system bias on differential reflectivity and to estimate the measurement error on both Z _H and Z _DR in the rain medium. It is estimated that no bias is affecting Z _DR and the accuracy of Z _H and Z _DR is 0.8 and 0.1 dB, respectively. A similar evaluation is done in the rain medium at larger ranges with the antenna pointing at low elevation angles. The long time stability of the absolute reflectivity calibration is also established by radar-rain gage inter-comparison over almost 200 hours of precipitation data collected during nearly two years. Received June 21, 2001 Revised November 13, 2001     

Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar)

Quantifying snowfall intensity especially under arctic conditions is a challenge because wind and snow drift deteriorate estimates obtained from both ground-based gauges and disdrometers. Ground-based remote sensing with active instruments might be a solution because they can measure well above drifting snow and do not suffer from flow distortions by the instrument. Clear disadvantages are, however, the dependency of e.g. radar returns on snow habit which might lead to similar large uncertainties. Moreover, high sensitivity radars are still far too costly to operate in a network and under harsh conditions. In this paper we compare returns from a low-cost, low-power vertically pointing FM-CW radar (Micro Rain Radar, MRR) operating at 24.1?GHz with returns from a 35.5?GHz cloud radar (MIRA36) for dry snowfall during a 6-month observation period at an Alpine station (Environmental Research Station Schneefernerhaus, UFS) at 2,650?m height above sea level. The goal was to quantify the potential and limitations of the MRR in relation to what is achievable by a cloud radar. The operational MRR procedures to derive standard radar variables like effective reflectivity factor (Z _e) or the mean Doppler velocity (W) had to be modified for snowfall since the MRR was originally designed for rain observations. Since the radar returns from snowfall are weaker than from comparable rainfall, the behavior of the MRR close to its detection threshold has been analyzed and a method is proposed to quantify the noise level of the MRR based on clear sky observations. By converting the resulting MRR-Z _e into 35.5?GHz equivalent Z _e values, a remaining difference below 1?dBz with slightly higher values close to the noise threshold could be obtained. Due to the much higher sensitivity of MIRA36, the transition of the MRR from the true signal to noise can be observed, which agrees well with the independent clear sky noise estimate. The mean Doppler velocity differences between both radars are below 0.3?ms^?1. The distribution of Z _e values from MIRA36 are finally used to estimate the uncertainty of retrieved snowfall and snow accumulation with the MRR. At UFS low snowfall rates missed by the MRR are negligible when comparing snow accumulation, which were mainly caused by intensities between 0.1 and 0.8 mm?h^?1. The MRR overestimates the total snow accumulation by about 7%. This error is much smaller than the error caused by uncertain Z _e?Csnowfall rate relations, which would affect the MIRA36 estimated to a similar degree.     

X波段一维扫描有源相控阵天气雷达测试定标方法

该文根据有源相控阵天气雷达的体制特点,参考多普勒天气雷达测试定标方法,提出了一维扫描有源相控阵天气雷达的测试和定标方法,将测试重点放在天馈系统、T/R组件、脉冲压缩、动态范围的测试和定标上,以解决不同观测模式、不同波位的天线增益等参数变化引起的回波强度测量误差问题。测试结果表明:天馈系统在不同观测模式下的天线参数随仰角的变化情况、波束指向的准确度、T/R组件的动态范围等均符合设计要求,回波强度和径向速度定标精度较高。雷达经过测试和定标后,于2014年5—8月分别在安徽定远和四川甘孜进行外场试验,并与附近多普勒天气雷达 (SA) 和C波段双线偏振雷达观测数据进行对比,结果表明:回波强度误差在合理范围内,精细测量、警戒搜索、快速观测3种模式观测的强回波的水平和垂直位置、结构和系统误差均比较一致,数据可靠。     

Statistics of the <Emphasis Type="Italic">Z</Emphasis>–<Emphasis Type="Italic">R</Emphasis> Relationship for Strong Convective Weather over the Yangtze–Huaihe River Basin and Its Application to Radar Reflectivity Data Assimilation for a Heavy Rain Event

The relationship between the radar reflectivity factor (Z) and the rainfall rate (R) is recalculated based on radar observations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze–Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z–R relationship is combined with an empirical q_r–R relationship to obtain a new Z–q_r relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational (3DVar) data assimilation system of the Weather Research and Forecasting (WRF) model to improve the analysis and prediction of severe convective weather over the Yangtze–Huaihe River basin. The performance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z–R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected reflectivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better performance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original reflectivity operator. This suggests that the new statistical Z–R relationship is more suitable for predicting severe convective weather over the Yangtze–Huaihe River basin than the Z–R relationships currently in use.     

微降水雷达测量精度分析

利用数值模拟的方法,讨论了利用微降水雷达MRR(Micro Rain Radar)雷达功率谱密度反演降水参数时,MIE散射(米散射)效应、垂直气流(包括上升气流、下沉气流)对数浓度N、雷达反射率Z、雨强I、液态含水量LWC等参数的影响。MIE散射主要影响直径为1.20~4.00 mm的粒子,MIE散射效应影响的N、Z、I、LWC偏差的平均值分别为2.74 m-3 mm-1、1.47 d BZ、0.0061 mm h~(-1)、0.0004 g m-3。下沉气流使反演液滴直径偏大,上升气流使得反演的液滴直径偏小,下沉气流的影响更大,尤其是对低层影响大于高层。例如,在300 m高度上,当液滴直径为2.67 mm时,下沉气流为2.00 m s-1时,理论上反演的直径为8.07 mm,超出了MRR探测的阈值,其相对误差值能接近200%。下沉气流使得反射率谱向大粒子方向平移,且谱型展宽;上升气流则相反。将MRR资料与同步观测的THIES雨滴谱仪数据进行比对,分析MRR资料的可靠性。选取2015年4月1日01~12时(协调世界时)山东济南的一次降水过程,将MRR在300 m高度上反演的雷达反射率因子、雨强、数浓度、中值体积直径与雨滴谱仪资料进行对比。结果表明:两种仪器探测的Z、I、N、中值体积直径D0在时间序列上都有较好的吻合度,变化趋势和幅度相近,Z、I、D0的平均偏差分别为1.19 d BZ、0.34 mm h~(-1)、0.36 mm。MRR反演的I值偏大,而粒子直径偏小,分析了产生偏差的主要原因,除了探测系统偏差、分析方法本身存在的偏差外,上升气流导致的偏差不容忽视。这些结果初步验证了微降水雷达观测的功率谱密度及其反演方法的可靠性。     

Experimental results on rainfall estimation in complex terrain with a mobile X-band polarimetric weather radar

In this work the capability of reliable rainfall measurements with small weather radars in complex terrain for flood forecasting purposes is examined. Rain measurements were carried out during winter–spring 2007 with a mobile X-band dual-polarization radar in the northwestern mountainous part of the island of Crete in Greece. In this area a 2D-video disdrometer and a network of raingauges was installed for radar calibration and evaluation of rainfall measurements, respectively. The complex terrain of the experimental site may significantly reduce the performance of rain measurements due to ground clutter and partial or total beam blockage. A beam blockage algorithm using high resolution terrain data was applied in order to find areas with significant terrain effects and estimate correction of the radar measurements. Rain attenuation correction was based on modern sophisticated algorithms using differential phase measurements. The accuracy of rainfall estimation from standard or polarimetric algorithms at plan position indicator (PPI) scans was examined for high-temporal resolution (1 min) rainfall rates and accumulated rainfall values for winter and spring time rain events. For high elevation measurements, which were required in order to avoid terrain effects in large areas of interest, a correction for the vertical-profile-of-reflectivity (VPR) was also applied to the radar data. An average VPR model used in the corresponding correction of reflectivity was constructed based on range–height indicator (RHI) scans. It was concluded that quantitative high resolution X-band radar observations of rainfall in complex terrain is possible after careful application of all the above processing steps.     

雨滴谱仪与风廓线雷达反射率对比试验

针对风廓线雷达估算的反射率数据需要进行验证。开展雨滴谱仪与风廓线雷达反射率对比试验,通过两种不同探测设备观测数据的对比,以验证风廓线反射率数据的可靠性和可用性。结果表明:确定了以风廓线低模360~1440 m采样体积内的反射率与3 min雨滴谱反射率数据对比方法能最大程度的减少时空差异;在雨滴谱仪反射率小于40 dBz时,对应的风廓线雷达反射率数据是可靠和可用的;同时由于风廓线雷达有限的动态范围造成反射率低估的现象,使得风廓线雷达反射率在大气垂直结构以及微物理特性等方面应用受到一定的局限性。     

Quantitative detection of mass concentration of sand-dust storms via wind-profiling radar and analysis of <Emphasis Type="Italic">Z</Emphasis>-<Emphasis Type="Italic">M</Emphasis> relationship

With the aim to achieve quantitative monitoring of sand-dust storms in real time, wind-profiling radar is applied to monitor and study the process of four sand-dust storms in the Tazhong area of the Taklimakan Desert. Through evaluation and analysis of the spatial-temporal distribution of reflectivity factor, it is found that reflectivity factor ranges from 2 to 18 dBz under sand-dust storm weather. Using echo power spectrum of radar vertical beams, sand-dust particle spectrum and sand-dust mass concentration at the altitude of 600 ～ 1500 m are retrieved. This study shows that sand-dust mass concentration reaches 700?μg/m³ under blowing sand weather, 2000?μg/m³ under sand-dust storm weather, and 400?μg/m³ under floating dust weather. The following equations are established to represent the relationship between the reflectivity factor and sand-dust mass concentration: Z?=?20713.5?M ^0.995 under floating dust weather, Z?=?22988.3?M ^1.006 under blowing sand weather, and Z?=?24584.2?M ^1.013 under sand-dust storm weather. The retrieval results from this paper are almost consistent with previous monitoring results achieved by former researchers; thus, it is implied that wind-profiling radar can be used as a new reference device to quantitatively monitor sand-dust storms.     

Improvement of radar quantitative precipitation estimation based on real-time adjustments to <Emphasis Type="Italic">Z-R</Emphasis> relationships and inverse distance weighting correction schemes

The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations.In this study,a real-time adjustment to the radar reflectivity-rainfall rates(Z-R) relationship scheme and the gauge-corrected,radar-based,estimation scheme with inverse distance weighting interpolation was developed.Based on the characteristics of the two schemes,the two-step correction technique of radar quantitative precipitation estimation is proposed.To minimize the errors between radar quantitative precipitation estimations and rain gauge observations,a real-time adjustment to the Z-R relationship scheme is used to remove systematic bias on the time-domain.The gauge-corrected,radar-based,estimation scheme is then used to eliminate non-uniform errors in space.Based on radar data and rain gauge observations near the Huaihe River,the two-step correction technique was evaluated using two heavy-precipitation events.The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.     

偏振雷达探测小椭球粒子群LDR的雷达气象方程

双线偏振雷达探测小椭球粒子群时,雷达单发双收或交替发射。在粒子旋转轴呈某一取向时,要获得定义为RLD_(vh)或RLD_(hv)这个物理量,必须先建立Z_(vh)及Z_(hv)的雷达气象方程,并需重新定义相应的雷达反射率因子。本文推导出了能反演Z_(vh)及Z_(hv)的雷达气象方程,并模拟了具有Gamma谱分布的扁椭球粒子群在空间均匀取向时的LDR的变化情况。     

X波段双线偏振雷达回波强度衰减和地物回波识别订正

与常规雷达相比,双线偏振天气雷达在降水系统的准确探测、资料质量的提高等方面具有明显的优势,但X波段双线偏振雷达资料受衰减和地物的影响较大,需要进行必要的衰减和地物订正。本文以2010年7月中国气象局在广东阳江开展的遥感数据比对试验得到数据为例,用ZH和ZDR结合的方法对ZH进行衰减订正,用ZH和ZDR的方差识别地物回波,并利用反射率因子垂直廓线订正受地物影响的底层回波。将订正后的ZH与S波段雷达探测的ZH相比较,将订正后的ZH与KDP的散点图和拟合的KDP与ZH曲线关系对比验证。结果表明经过订正的ZH与S波段雷达探测的ZH一致性较好,与拟合曲线也更为吻合,说明方法能有效提高雷达资料的质量。     

雨滴谱垂直演变特征的微雨雷达观测研究

雨滴谱的垂直变化特征对于认识降水过程、改进模式和雷达定量估计降水等具有重要意义。利用2016年6月1日-9月30日雨量筒、微雨雷达（micro rain radar,简称MRR）和PARSIVEL雨滴谱仪连续4个月的观测数据,在对比3种仪器观测结果的基础上,研究了层状云降水不同降水强度下微物理特征量和雨滴谱垂直演变特征。结果表明:MRR与PARSIVEL雨滴谱仪观测降水强度相关性较好,且两种仪器观测的雨滴谱在中等粒子段（0.5~2.5 mm）表现出较好的一致性,而对于小粒子段（雨滴直径小于0.5 mm）PARSIVEL雨滴谱仪观测的数浓度明显低于MRR。对于弱降水（降水强度R ≤ 0.2 mm·h-1）,液水含量和降水强度随高度降低减小,雨滴在下落过程中蒸发明显。对于较强降水（R>2 mm·h-1）,随高度降低,雷达反射率因子增大,小滴数浓度减小的同时大滴数浓度增加明显,雨滴下落过程碰并作用明显。所有高度直径不超过0.5 mm的小滴对数浓度贡献均为最大。高层雨滴直径不小于1 mm的小粒子对降水强度的贡献可达50%,小粒子对降水强度贡献随高度降低减小。     

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。     

双偏振相控阵雷达与业务雷达的定量对比及观测精度研究

相控阵天气雷达突破了全机械驱动天线天气雷达的时空分辨率瓶颈,能够提供更加快速、精细的观测资料。但阵列天线存在性能参数随扫描角偏离法向而恶化的情况,使相控阵雷达定量测量存在困难。本文针对中国华南地区最新布网的双偏振相控阵天气雷达,通过与当地S波段业务雷达在相同区域内的定量对比,评估了反射率因子差分反射率因子的误差量级及其随扫描角、观测时间的变化趋势。研究结果表明,相控阵雷达反射率因子的误差不大、约0.82 dB,而差分反射率因子的误差则高达1.04 dB,并且不同仰角、不同时刻之间也存在一定的波动。为此本文提出了基于S波段雷达实时数据的订正方案,能够较好地解决双偏振相控阵天气雷达的定标问题,为相控阵雷达的业务应用提供了保障。