Identification and Removal of Non-meteorological Echoes in Dual-polarization Radar Data Based on a Fuzzy Logic Algorithm

A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek.For selected precipitation and non-meteorological events,the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values.The membership functions and weights are then determined by these density functions.Finally,the nonmeteorological echoes are identified by combining the membership functions and weights.The performance is qualitatively evaluated by long-term rain accumulation.The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection（POD）,false alarm rate（FAR）,and clutter–signal ratio（CSR）.In addition,the issues in using filtered dual-polarization data are alleviated.

Recent Progress in Dual-Polarization Radar Research and Applications in China

Dual-polarization(dual-pol)radar can measure additional parameters that provide more microphysical information of precipitation systems than those provided by conventional Doppler radar.The dual-pol parameters have been successfully utilized to investigate precipitation microphysics and improve radar quantitative precipitation estimation(QPE).The recent progress in dual-pol radar research and applications in China is summarized in four aspects.Firstly,the characteristics of several representative dual-pol radars are reviewed.Various approaches have been developed for radar data quality control,including calibration,attenuation correction,calculation of specific differential phase shift,and identification and removal of non-meteorological echoes.Using dual-pol radar measurements,the microphysical characteristics derived from raindrop size distribution retrieval,hydrometeor classification,and QPE is better understood in China.The limited number of studies in China that have sought to use dual-pol radar data to validate the microphysical parameterization and initialization of numerical models and assimilate dual-pol data into numerical models are summarized.The challenges of applying dual-pol data in numerical models and emerging technologies that may make significant impacts on the field of radar meteorology are discussed.

Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars(DP-PAWRs)and an S-band dual-polarization Doppler weather radar(CINRAD/SA-D),the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed.After location matching,the observations of DP-PAWR and CINRAD/SA-D were compared in terms of reflectivity(Z_(H)),radial velocity(V),differential reflectivity(Z_(DR)),and specific differential phase(K_(DP)).The results showed that:(1)DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SAD;the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction.(2)DP-PAWR’s Z_(H)and V structures are acceptable,while its sensitivity is worse than that of CINRAD/SA-D.The Z H suffers from attenuation and the Z_(H)area distribution is distorted around strong rainfall regions.(3)DP-PAWR’s Z_(DR)is close to a normal distribution but slightly smaller than that of CINRAD/SA-D.The K_(DP)products of DP-PAWR have much higher sensitivity,showing a better indication of precipitation.(4)DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line,as well as the merging of the cell with the squall line,which cannot be observed by CINRAD/SA-D.With its fast volume scan feature and dual-polarization detection capability,DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.

Experimental Research of Dual-Polarization Passive Radar Based on DTTB Signal

The passive radar is a hot research topic. A multi-channel wideband passive radar experimental system is designed and the digital television terrestrial broadcasting (DTTB) signal is chosen to carry out the target detection experiment of civil aviation aircraft. The polarization and spatial filtering methods are used to solve the strong direct path interference suppression problems brought by the receiving system location;combined with the characteristics of DTTB signal, the block length selection interval in the block batch processing method for range-Doppler images calculation is given;the clutter suppression performance is compared through the experimental data receiving from different bistatic polarization channels, the conclusion is different from the monostatic radar and it can guide the passive radar experiment.

Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction

After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.

Deep convolutional neural network for meteorology target detection in airborne weather radar images

Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.

Evaluating the Algorithm for Correction of the Bright Band Effects in QPEs with S-, C-and X-Band Dual-Polarized Radars

The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of signifi- cant overestimation in quantitative precipitation estimation （QPE） based on the Z-R （reflectivity factor-rain rate） relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity （VPR） correction. In this study, we applied bright-band correction algorithms to evaluate three different bands （S-, C- and X-band） of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algo- rithms using average VPR （AVPR） alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient （AVPR＋CC）, the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gange observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE （root-mean-square error）, RMAE （relative mean absolute error） and RMB （relative mean bias） of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR＋CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR＋CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.

Rapid-Scan and Polarimetric Phased-Array Radar Observations of a Tornado in the Pearl River Estuary

The strong destructive winds during tornadoes can greatly threaten human life and destroy property.The increasing availability of visual and remote observations,especially by Doppler weather radars,is of great value in understanding tornado formation and issuing warnings to the public.In this study,we present the first documented tornado over water detected by a state-of-the-art dual-polarization phased-array radar(dual-PAR)in China.In contrast to new-generation weather radars,the dual-PAR shows great advantages in tornado detection for its high spatial resolution,reliable polarimetric variables,and rapid-scan strategy.The polarimetric signature of copolar cross-correlation coefficient with anomalously low magnitude appears to be effective for verifying a tornado and thus is helpful for issuing tornado warnings.The Guangdong Meteorological Service has been developing an experimental X-band dual-PAR network in the Pearl River Delta with the goal of deploying at least 40 advanced dual-PARs and other dual-polarization weather radars before 2035.This network is the first quasi-operational X-band dual-PAR network with unprecedented high coverage in the globe.With such high-performance close-range PARs,efficient operational nowcasting and warning services for small-scale,rapidly evolving,and damaging weather(e.g.,tornadoes,localized heavy rainfall,microbursts,and hail)can be expected.

Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.

Radar-based Characteristics and Formation Environment of Supercells in the Landfalling Typhoon Mujigae in 2015

This study presents the radar-based characteristics and formation environment of supercells spawned by the tornadic landfalling Typhoon Mujigae(2015)in October 2015.More than 100 supercells were identified within a 24-hour period around the time of the typhoon’s landfall,of which three were tornadic with a rotational intensity clearly stronger than those of non-tornadic supercells.The identified supercells were concentrated within a relatively small area in the northeast quadrant beyond 140 km from the typhoon center.These supercells were found more likely to form over flat topography and were difficult to maintain in mountainous regions.During the study period,more supercells formed offshore than onshore.The mesocyclones of the identified supercells were characterized by a small diameter generally less than 5 km and a shallow depth generally less than 4 km above ground level.An environmental analysis revealed that the northeast quadrant had the most favorable conditions for the genesis of supercell in this typhoon case.The nondimensional supercell composite parameter(SCP)and entraining-SCP(E-SCP)were effective in separating supercell from non-supercell environment.Even though the atmosphere in the typhoon’s northeast quadrant was characterized by an E-SCP/SCP value supportive of supercell organization,orography was an impeditive factor for the supercell development.These findings support the use of traditional parameters obtained from midlatitude supercells to assess the supercell potential in a tropical cyclone envelope.

Broadband printed antennas and dual-polarized microstrip and waveguide slot antenna arrays

In order to meet the urgent needs in wireless communications, microwave image synthetic aperture radars （SAR）, and electronic warfare systems, this dissertation studies several types of broadband dual-polarized planar antenna elements and arrays, and proposes a few of novel designs with experimental verification. The main accomplishments reported in the dissertation are as follows.

基于SRTM数据的天气雷达净空环境评估研究

针对天气雷达的选址受净空环境直接影响的问题,提出基于SRTM数据的天气雷达净空环境评估研究。采用航天飞机雷达地形测绘使命高程数据,对天气雷达净空环境进行评估,并进行方位矫正和距离矫正。测试结果表明,基于航天飞机雷达地形测绘使命数据的天气雷达净空环境评估方法的方位分辨率为0.25°,测距大于260千米;与实地勘测结果之间的误差最小,具有较好的一致性;方位角的变化幅度较小,误差小。表明研究提出的方法在天气雷达净空环境评估中具有较好的应用效果,对气象检测技术的发展有一定促进作用。

面向艇载气象雷达的稀疏相控阵优化设计

台风是一种持续性的热带气旋,常带来狂风、暴雨等灾害天气。平均每年约有七次台风登陆我国,对我国人口密集的东南沿海和部分内陆地区带来严重影响。气象雷达具有对台风等灾害天气的探测和预警能力,但现有的气象雷达多为地基相控阵雷达,距离远且分辨率低,对台风内部结构观测不清,导致在台风强度和路径的预测上存在着较大的不确定性。为降低台风灾害带来的损失,北京航空航天大学承担的国家自然科学基金重大科研仪器研制项目(简称“大仪器”项目)提出由临近空间飞艇搭载气象雷达对台风进行追踪抵近探测,提供台风内部结构长时、精细的观测数据。不同于地基雷达,临近空间飞艇独特的平台限制约束了气象雷达的重量、功耗、尺寸等成本参数,而实现台风探测的高性能亟须大孔径阵列。因此,艇载台风探测雷达的技术难点在于:如何用最低的成本实现最高的性能。在“大仪器”项目的资助下,本文提出一种稀疏相控阵气象雷达,可以在降低系统成本的同时实现高分辨率探测。本文的主要贡献总结如下:首先,对单天线气象回波的时间序列进行模拟仿真,扩展至多天线相控阵气象雷达的回波数据模拟,并通过多普勒分析验证其准确性;然后,考虑稀疏化均匀间隔的相控阵列,通过减少阵元数降低硬件成本的同时,保持高分辨率的波束扫描与接收;最后,联合优化阵列构型和权重系数,权重系数满足恒模约束以最大化雷达发射功效,从而进一步压低副瓣电平来改善气象雷达的抗干扰性能。仿真和实验结果表明,相控阵雷达能够实现准确高效的气象探测,稀疏阵的引入使系统在维持高分辨率的同时降低了硬件成本。具体地,在相同阵元数的条件下,稀疏阵在对气象回波反射率、多普勒频率及谱宽的估计上,都展现明显优于均匀阵的效果。

基于FMCW毫米波雷达的测距值气象改正模型的建立

FMCW毫米波雷达具有低功耗、低成本、全天时全天候、精度高等优点,选择其作为监测设备,可以很大程度上满足监测需求,同时其操作便捷,携带方便。但是有研究表明,FMCW毫米波雷达在进行长时序观测时,雷达测距值会随着空气中的气象因素(温度、湿度、气压等)的改变而发生变化,导致测量精度降低。基于此,本文针对气象因素对毫米波雷达测距精度的影响而展开研究,提出基于调制载波折射率公式构建毫米波雷达的气象改正模型,改正后雷达测距值随时间的波动程度相较于改正前明显降低,测距值的标准差较改正之前降低了30%左右,与温度和湿度的相关系数均降低了50%及以下。结果表明,该模型在一定程度上削弱了气象因素对毫米波雷达测距值的影响,但是削弱效果有限,模型还有待优化。

基于RC-LSTM的雷达回波外推方法

雷达回波外推是降水临近预报的重要手段,所用的方法分为数值预报与数据驱动预报。前者依托数学与物理模型,后者依托深度学习技术总结历史规律。尽管深度学习在气象预报中研究活跃,但实际应用仍面临挑战,尤其是精度问题。因此设计了一种雷达回波外推系统,应用所提出的残参卷积长短期记忆(RC-LSTM)模型,在使用规划采样的同时,为每一层堆叠的ConvLSTM单元添加了残差连接,使得模型在更深的同时保留原有小模型的学习能力,保证网络最大限度降低空间维度的历史信息损耗,从而提高长时效雷达回波外推的精度。

基于多源观测资料对湖南怀化一次雨雪天气降水相态特征的分析

【目的】为了解湖南怀化雨雪天气降水相态演变特征。【方法】选取ERA5资料、微波辐射计和SA双偏振多普勒雷达等多源观测资料作为基础数据,采用常规统计、环流背景、相关分析等方法,对2022年12月27—28日湖南怀化地区一次雨雪天气的降水相态演变特征进行分析。【结果】(1)中高纬地区在中层槽的引导下冷空气南下,中低纬地区在南支槽的引导下西南气流东移,致使冷空气与暖湿气流交汇,降水相态发生变化。过程前低层切变线南压、低空西南急流发展,低层系统处于暖平流中,且地面温度较高,降水相态为雨。28日20时后冷平流快速发展,地面迅速降温,形成“冷垫”,致使降水相态转为雨夹雪。后期受南下强冷空气影响,导致降水相态转为雪。(2)散度和垂直速度的分布说明,降雪阶段的动力条件来源于低层,降雨时段的动力条件来源于高层。(3)SA双偏振多普勒雷达的偏振量分析结果表明,在较大的水平反射率(20~35 dBz)区域,其差分反射率相对较小(约0.8~1.6 dBz之间),差分位移率也相对较小(约-1.2~0.6之间),相关系数>0.88。微波辐射计反演的0℃线可以作为降雪的重要判据,其液态水含量在降雨时含量较高,水汽浓度在降雪时显著下降,可以准确判断降雪的具体时间。【结论】微波辐射计和双偏振雷达的组合应用可以作为怀化地区对降水相态转换临界预报的重要地基观测设备。

PROPAGATION EFFECTS AND APPLICATION OF PHASE INFORMATION FOR C-BAND DUAL-POLARIZATION RADAR

As a study on exploiting and popularizing the advanced dual-polarization weather radar technique in China,the physical mechanism for the propagation effect of the radar wave is discussed by using the widely adapted extended boundary condition method,and some theoretic results are provided for improving rain measurement accuracy.Furthermore,phase information, another important characteristic quantity of microwave,is considered for tapping the potentialities of the new meteorological radar system.

基于VRT的气象粒子群时域回波仿真研究

随着雷达使用频段提升,降雨、云雾等气象因素对雷达探测的影响逐渐不可忽视。为研究气象粒子群对雷达探测工作产生的影响,文章总结了电磁波在不同类型气象粒子群下的谱分布与衰减特性;再根据粒子谱方程给出气象粒子群的模型信息;最后基于矢量辐射传输方法,提出了一种改进的气象粒子群时域回波快速仿真的方法,包括分区加速、传播路径判断的优化,在大体量粒子群回波建模中的优化效果可达到普通方法的20倍左右。结果表明,雨粒子群对雷达探测工作会造成较大的杂波,其杂波幅值约为发射功率的10-4倍;云粒子群的时域结果存在较强的随机性;雾粒子群时域结果均匀且幅值较低。文章针对不同类型气象粒子群时域回波的仿真结果与分析,对雷达的精准探测研究具有一定参考价值。

基于实测气象参数的InSAR大气校正及其应用研究

针对传统InSAR技术在监测地表形变时受对流层延迟影响的问题,利用地面实测气象参数和NCEP气象再分析资料建立大气校正模型,对生成的鄞州区干涉图进行对流层延迟校正,获取鄞州区2018~2020年高精度地表形变分布。为分析不同大气校正模型对对流层延迟效应的削弱效果,将监测结果与同期实测水准数据作对比。结果发现,地面气象信息模型、NCEP气象再分析资料模型和未加大气校正的InSAR监测结果的均方根误差RMSE分别为2.78 mm、3.86 mm、5.62 mm,表明利用地面气象信息模型校正大气相位误差具有更高的监测精度,能有效削弱对流层延迟对干涉测量结果的影响。

气象小卫星发展的回顾与展望

气象卫星对地观测是大气、空间气象要素观测的重要手段.近年来,气象小卫星发展迅猛,引起对地观测领域的广泛关注.回顾了目前国内外具有重要影响力的气象小卫星星座的设计思路和布局,在已经实现的对降水、云雨粒子和大气温湿度廓线等重要气象要素的探测能力基础上,提出并阐述了未来中国气象小卫星的发展构想.中国将打造具有前沿技术验证能力、科学试验能力、星座协同和即时定制能力的气象小卫星星座,与大平台系列风云气象卫星互联互通,共同作为数字太空系统的天基感知节点,形成大小结合、星地统筹、协同观测、综合应用的气象卫星发展新格局,为气象高质量发展提供新的技术支撑.