Impact of the Assimilation Frequency of Radar Data with the ARPS 3DVar and Cloud Analysis System on Forecasts of a Squall Line in Southern China

Assimilation configurations have significant impacts on analysis results and subsequent forecasts. A squall line system that occurred on 23 April 2007 over southern China was used to investigate the impacts of the data assimilation frequency of radar data on analyses and forecasts. A three-dimensional variational system was used to assimilate radial velocity data,and a cloud analysis system was used for reflectivity assimilation with a 2-h assimilation window covering the initial stage of the squall line. Two operators of radar reflectivity for cloud analyses corresponding to single-and double-moment schemes were used. In this study, we examined the sensitivity of assimilation frequency using 10-, 20-, 30-, and 60-min assimilation intervals. The results showed that analysis fields were not consistent with model dynamics and microphysics in general;thus, model states, including dynamic and microphysical variables, required approximately 20 min to reach a new balance after data assimilation in all experiments. Moreover, a 20-min data assimilation interval generally produced better forecasts for both single-and double-moment schemes in terms of equitable threat and bias scores. We conclude that a higher data assimilation frequency can produce a more intense cold pool and rear inflow jets but does not necessarily lead to a better forecast.

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

A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 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 refiectivity 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.

Retrieving Microphysical Properties and Air Motion of Cirrus Clouds Based on the Doppler Moments Method Using Cloud Radar

Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and the mean air vertical motion. Unlike strong precipitation, the motion of particles in cirrus clouds is quite close to the air motion around them. In this study, a method of Doppler moments was developed and used to retrieve cirrus cloud microphysical properties such as the mean air vertical velocity, mass-weighted diameter, effective particle size, and ice content. Ice content values were retrieved using both the Doppler spectrum method and classic Z-IWC （radar reflectivity-ice water content） relationships; however, the former is a more reasonable method.

A 35-GHz Polarimetric Doppler Radar and Its Application for Observing Clouds Associated with Typhoon Nuri

Millimeter-wavelength radar has proved to be an effective instrument for cloud observation and research. In this study, 8-mm-wavelength cloud radar （MMCR） with Doppler and polarization capabilities was used to investigate cloud dynamics in China for the first time. Its design, system specifications, calibration, and application in measuring clouds associated with typhoon are discussed in this article. The cloud radar measurements of radar reflectivity （Z）, Doppler velocity （Vr）, velocity spectrum width （Sw） and the depolar-ization ratio （LDR） at vertical incidence were used to analyze the microphysical and dynamic processes of the cloud system and precipitation associated with Typhoon Nuri, which occurred in southern China in August 2008. The results show the reflectivity observed using MMCR to be consistent with the echo height and the melting-layer location data obtained by the nearby China S-band new-generation weather radar （SA）, but the Ka-band MMCR provided more detailed structural information about clouds and weak precipitation data than did the SA radar. The variation of radar reflectivity and LDR in vertical structure reveals the transformation of particle phase from ice to water. The vertical velocity and velocity spectrum width of MMCR observations indicate an updraft and strong turbulence in the stratiform cloud layer. MMCR provides a valuable new technology for meteorological research in China.

Rainfall Microphysical Properties of Landfalling Typhoon Yagi(201814)Based on the Observations of Micro Rain Radar and Cloud Radar in Shandong,China

The development and evolution of precipitation microphysical parameters and the vertical structure characteristics associated with Typhoon Yagi(201814)are analyzed in the city of Jinan,Shandong Province based primarily on the observations of a micro rain radar(MRR),a cloud radar,and a disdrometer.The precipitation process is further subdivided into four types:convective,stratiform,mixed,and light precipitation according to the ground disdrometer data,which is in agreement with the vertical profile of the radar reflectivity detected by the MRR.Vertical winds may be the main source of MRR retrieval error during convective precipitation.Convective precipitation has the shortest duration but makes the largest contribution to the cumulative precipitation.Collision-coalescence is the main microphysical process of stratiform precipitation and light precipitation below the bright band observed by the MRR.It is worth noting that as Typhoon Yagi(201814)transformed into an extratropical cyclone,its raindrop size distributions no longer had the characteristics of maritime precipitation,but become more typical of the characteristic of continental precipitation,which represents a very different raindrop size distribution from that which is normally observed in a landfalling typhoon.

Cloud Classification and Distribution of Cloud Types in Beijing Using Ka-Band Radar Data

A cloud clustering and classification algorithm is developed for a ground-based Ka-band radar system in the vertically pointing mode. Cloud profiles are grouped based on the combination of a time–height clustering method and the k-means clustering method. The cloud classification algorithm, developed using a fuzzy logic method, uses nine physical parameters to classify clouds into nine types: cirrostratus, cirrocumulus, altocumulus, altostratus, stratus, stratocumulus, nimbostratus,cumulus or cumulonimbus. The performance of the clustering and classification algorithm is presented by comparison with all-sky images taken from January to June 2014. Overall, 92% of the cloud profiles are clustered successfully and the agreement in classification between the radar system and the all-sky imager is 87%. The distribution of cloud types in Beijing from January 2014 to December 2017 is studied based on the clustering and classification algorithm. The statistics show that cirrostratus clouds have the highest occurrence frequency(24%) among the nine cloud types. High-level clouds have the maximum occurrence frequency and low-level clouds the minimum occurrence frequency.

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 sinmltaneous 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 refiectivity 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.

Assessment of FY-4A and Himawari-8 Cloud Top Height Retrieval through Comparison with Ground-Based Millimeter Radar at Sites in Tibet and Beijing

The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-based millimeter radar at two sites: Yangbajing, Tibet, China (YBJ), and the Institute of Atmospheric Physics (IAP), Beijing, China. The comparison shows that Himawari-8 missed more CTHs at night than FY-4A, especially at YBJ. It is found that the CTH difference (CTHD;radar CTH minus satellite CTH) for FY-4A and Himawari-8 is 0.06 ± 1.90 km and −0.02 ± 2.40 km at YBJ respectively, and that is 0.93 ± 2.24 km and 0.99 ± 2.37 km at IAP respectively. The discrepancy between the satellites and radar at IAP is larger than that at YBJ. Both satellites show better performance for mid-level and low-level clouds than for high-level clouds at the two sites. The retrievals from FY-4A agree well with those from Himawari-8, with a mean difference of 0.08 km at YBJ and 0.06 km at IAP. It is found that the CTHD decreases as the cloud depth increases at both sites. However, the CTHD has no obvious dependence on cloud layers and fractions. Investigations show that aerosol concentration has little impact on the CTHD. For high and thin clouds, the CTHD increases gradually with the increase of the surface temperature, which might be a key factor causing the regional discrepancy between IAP and YBJ.

A Ka-band Solid-state Transmitter Cloud Radar and Data Merging Algorithm for Its Measurements

This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar（i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3） is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month＇s continuous measurements during summertime at Naqu on the Tibetan Plateau,we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes＇ data to the merged data were estimated.The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of -35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However,large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes.The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar(MMCR)provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds.Therefore,MMCR has been widely applied in cloud observations.However,due to the influence of non-meteorological factors such as insects,the cloud observations are often contaminated by non-meteorological echoes in the clear air,known as clear-air echoes.It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background.The characteristics of clear-air echoes are studied here by combining data from four devices:an MMCR,a laser-ceilometer,an L-band radiosonde,and an all-sky camera.In addition,a new algorithm,which includes feature extraction,feature selection,and classification,is proposed to achieve the automatic identification of clear-air echoes.The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions.The recognition accuracy can reach up to 95.86%for the simple cases when cloud echoes and clear-air echoes are separate,and 88.38%for the complicated cases when low cloud echoes and clear-air echoes are mixed.

Spectral dispersion of cloud droplet size distributions and radar threshold reflectivity for drizzle

From first principles, we find that the radar threshold reflectivity between nonprecipitating clouds and precipitating clouds is strongly related to not only the cloud droplet number concentration but also the spectral dispersion of cloud droplet size distributions. The further investigation indicates that the threshold value is an increasing function of spectral dispersion and cloud droplet number concentration. These results may improve our understanding of the cloud-precipitation interaction and the aerosol indirect effect.

Verification and Correction of Cloud Base and Top Height Retrievals from Ka–band Cloud Radar in Boseong,Korea

In this study,cloud base height（CBH） and cloud top height（CTH） observed by the Ka-band（33.44 GHz） cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013（September-November） were verified and corrected.For comparative verification,CBH and CTH were obtained using a ceilometer（CL51） and the Communication,Ocean and Meteorological Satellite（COMS）.During rainfall,the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops,and this difference increased with rainfall intensity.During dry periods,however,the CBH and CTH observed by the cloud radar,ceilometer,and COMS were similar.Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS.In cases of rainfall or missing cloud radar data,the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data.These corrected cloud data were used to classify cloud types,which revealed that low clouds occurred most frequently.

Microphysical characteristics of precipitating cumulus cloud based on airborne Ka-band cloud radar and droplet measurements

在积云中,大多数云粒子的直径在7到10微米之间,而在层云中,大多数云粒子的直径不超过2微米.云滴有效半径与云中行星边界层(PBL)及PBL上层的气溶胶数浓度(Na)呈负相关.在1500米以上的高液态水含量区域,云滴浓度(Nc)变化不大,Na含量降低.高雷达反射率对应于大的FCDP云粒子浓度和小的气溶胶粒子浓度.积云中的强上升气流增加了云滴的峰值半径和数浓度,拓宽了云滴谱;较低的空气温度有利于粒子的凝结增长,并产生较大的液滴.

The Characteristics of the Cold Front Cloud in Doppler Radar Reflectivity Factor

[Objective] The aim was to summarize the characteristics of refelectivity factors of Doppler radar of the cold front cloud system. [Method] Judging from the characteristics of reflectivity factors, by dint of the new generation weather radar in Harbin from 2002 to 2007, the features of the reflectivity factors of the cold front cloud system were summarized. [Result] The cloud formed by the cold front was in banded form in general. However, there was void in the cloud and its intensity was uneven. Most fast moving cold front was long and narrow banded echo and basically the radial velocity turned from northwest wind to southwest. With the changes of month, the feature of the reflective rate also changed. In winter, the cold front cloud was in layer form. The feature of the reflectivity factors was weak and in large area. However, the structure was loose and there was space in the echo. Among them, there were several strong echoes. Strong convection cell echo formed in the two sides of the cold front, and it moved with the entire cloud belt. When the dry cold front moved, regional strong convective current formed, mainly by convective cloud and small echo area. Generally, the changes of the wind direction can not be expounded from the radial velocity. However, the intensity of the convection cell was distinct, 'three-body scattering', 'side lobe echo', and 'weak echo', as well as features of super convection cell. [Conclusion] The study provided positive role for the application of Doppler radar in the surveillance of weather in Heilongjiang Province.

基于激光雷达扫描的料仓原料储料量测量方法

为提高仓内原料储料量测量自动化和智能化水平,设计了一种基于二维激光雷达扫描的储料量测量装置与系统。本系统采用RPLIDARS1型二维激光雷达扫描获取不同储料量物料的原始点云数据,通过坐标变换、重叠点提取、滤波、分割等方法对原始点云进行预处理,采用贪婪投影三角化算法将预处理后的点云进行三维重建,获得仓内原料的三维模型,结合物料三维模型和物料的容重获得仓内原料的储料量,从而实现储料量的自动测量。以玉米为试验对象,测量小型储料塔内玉米储料量并对玉米不同储料量进行扫描测量,验证模型的准确性,结果显示:测量结果的平均绝对误差为8.05kg,平均相对误差为1.52%。研究结果表明,基于二维激光雷达扫描的储料量测量方法是可行的,具有较好的稳定性和测量精度,能够满足实际生产需求。

复杂多方向威胁下的导弹预警雷达优化部署方法

针对现有导弹预警雷达部署相对独立、协同困难,难以满足大规模对抗场景的现状,从远程预警雷达、跟踪识别雷达、机动式预警雷达不同的任务特点出发,建立应对复杂多方向威胁的多型导弹预警雷达优化部署模型,在满足最优覆盖、协同交接、目标识别等任务约束下,解决雷达协同部署问题。针对所提模型设计了一种基于云自适应的分区优化离散粒子群(CPBPSO)算法,通过设计分区编码策略缩减算法求解空间、加入云自适应变异算子提高算法全局寻优和局部跳出能力,使算法更适用于导弹预警雷达部署问题的处理。实例验证了所提模型在求解单方向、多方向威胁场景部署问题的可行性,对比分析了CPBPSO算法的有效性,基本满足导弹预警雷达最优化协同部署的需求。

基于ADS-B数据的一次雷达系统误差配准方法

针对大误差一次雷达测量过程中雷达配准方法的精度提升问题,分析了一次雷达误差分布特性,以广播式自动相关监视系统的航迹数据为真值,提出了基于改进轨迹跟踪滤波的实时雷达配准方法。采用点云配准方法中随机抽样一致性的迭代最近点法,对基于期望增加模型的变结构交互式多模型算法中的偏置函数进行了改进,有效减少了随机误差在配准过程中的影响,并获得最优的偏置参数,以提升大误差一次雷达配准的精度。算例分析结果表明,该方法配准后可使所选一次雷达俯仰角平均绝对误差降低至0.04°,方位角平均绝对误差降低至0.07°,为雷达系统误差配准提供新方法支撑。

人工等离子体云团与无人机群的散射研究

电离层中释放的金属蒸气产生人工等离子体云团,其可显著改变无线电波传播。本文利用几何绕射理论(geometrical theory of diffraction, GTD)和有限元法(finite element method, FEM)相结合的方法,给出了经由天线、人工等离子云团和无人机(unmanned aerial vehicle, UAV)群组成的传播链路中信号强度计算方法。利用30~70 MHz甚高频(very high frequency, VHF)信号研究人工等离子体云团与UAV群的复合散射特性,得出如下结论:接收功率随着信号频率增加呈下降趋势;当机群由N架UAV构成时,阵因子迭加使机群雷达散射截面(radar cross section, RCS)出现一定的起伏,同相迭加时,接收功率可比单个UAV高约20lg N dB;利用人工等离子体云团散射可实现VHF频段用于对米级尺度RCS目标进行超视距探测,有助于解决紧急情况下电离层扰动对高频探测的不利影响。

基于CloudSat和ISCCP资料的中国及周边地区云量分布的对比分析

利用2006年7月至2007年6月的CloudSat 2B-GEOPROF-LIDAR产品资料和国际卫星云气候计划(ISCCP)D2月平均云量数据,统计分析了中国及周边地区午间、凌晨年平均总云量的分布特征,并对两种探测手段得到的年平均总云量及其昼夜变化进行了对比分析。结果表明,ISCCP与CloudSat总云量的分布形势在午间和凌晨均具有较好的一致性,即相对多云与少云中心的位置吻合较好。但是,两种资料得到的总云量在量值上存在一定差异。对于整个研究区域而言,午间ISCCP较CloudSat平均总云量偏低8.9%,凌晨偏低15.1%。除了中国北方少云带和日本岛以北海域等区域ISCCP云量高于CloudSat云量外,其他区域ISCCP云量普遍低于CloudSat云量,且在青藏高原、帕米尔高原、横断山脉、云贵高原以及印度半岛南端和热带部分岛屿等区域尤其显著。进一步对比表明,ISCCP与CloudSat云量差值总体上随CloudSat云量的增大而呈线性变化,在CloudSat少云区ISCCP略有偏高,而在多云区则显著偏低。此外,对云量昼夜变化的对比分析发现,青藏高原地区ISCCP云量昼夜变化量显著大于CloudSat。

“12·14”山东暴雪过程降水相态的多源观测分析

基于毫米波云雷达、降水天气现象仪、风廓线雷达、双偏振雷达、自动气象站等多源观测资料及欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)第五代大气再分析(ECMWF Reanalysis v5,ERA5)资料,对2023年12月14日山东暴雪过程的环流背景和降水粒子微物理参数进行分析,探讨新型观测资料在降水相态监测与预报中的应用。结果表明:(1)此次过程受高空槽、低空西南急流和江淮气旋影响,伴随地面气温下降和中层暖层消退,出现雨、雨夹雪、冰粒和雪等相态。(2)降水天气现象仪探测发现,雪和雨的下落末速度均较小,雪粒子直径超过8 mm,雨粒子直径大多在4 mm以下。(3)毫米波云雷达观测到反射率因子、径向速度、谱宽和垂直液态水含量降低时,雨夹雪转为雪。(4)风廓线雷达显示雨夹雪和冰粒阶段对应强的低空西南急流和最大垂直速度(4~5 m·s^(-1)),转雪时3 km以下垂直速度降低至2 m·s^(-1)左右。(5)相关系数(C c)、差分反射率(Z DR)和水平极化反射率因子(Z h)等双偏振参量可判断融化层亮带,亮带的下降和消失可指示此次过程雨向雪的转换。