Supercooled liquid water (SLW) in mixed-phase clouds significantly influences precipitation efficiency and aviation safety. However, a comprehensive understanding of its vertical structure has been hampered by a lack of sustained, vertically resolved observations over the North China Plain. This study presents the first systematic analysis of SLW vertical distribution and microphysics in this region, utilizing a year-long dataset (2022) from synergistic ground-based instruments in Beijing. Our retrieval approach integrates Ka-band cloud radar, microwave radiometer, ceilometer, and radiosonde data, combining fuzzy-logic phase classification with a liquid water content inversion constrained by column liquid water path. Key findings reveal a distinct bimodal seasonality: SLW primarily occurs at mid-to-upper levels (4–7.5 km) during spring and summer, driven by convective lofting, while winter SLW is confined to lower altitudes (1–2 km) under stable atmospheric conditions. The temperature-dependent occurrence probability of SLW clouds has an annual maximum at −12 °C. The diurnal variation in SLW in summer shows peaks in the afternoon and at night, corresponding to convective cloud activity. Spring, autumn, and winter do not exhibit strong diurnal variations. Retrieved microphysical properties, including liquid water content and droplet effective radius, are consistent with in situ aircraft measurements, validating our methodology. This analysis provides a critical observational benchmark and offers actionable insights for improving cloud microphysics parameterizations in models and optimizing weather modification strategies, such as seeding altitude and timing, in this water-stressed region.

Riming and aggregation are critical ice-phase microphysical processes in winter clouds, but their overlapping signatures and dynamic transitions pose challenges for conventional single-frequency radar detection. We introduce a novel gradient-based identification method using ground-based triple-frequency dual-polarization radar observations. By analyzing vertical gradients of triple-frequency radar variables, rather than their absolute values, we discern these microphysical processes through physically based thresholds that reflect particle growth regimes. This approach captures subtle spatiotemporal variations in riming and aggregation that conventional threshold methods would miss, particularly in resolving layered riming-aggregation transitions. The dynamic gradient-based method demonstrates enhanced physical consistency and adaptability near process boundaries, thereby improving the tracking of ice-particle evolution. These advances provide a pathway to refine microphysical parameterizations and enhance high-resolution snowfall forecasting.

The line-of-sight multiple-input multiple-output (LOS-MIMO) has emerged as a potential solution for increasing spectral efficiency in dense urban microwave links, given limited spectrum resources. Phase variation and power attenuation may introduce uncertainty to the channel estimation, affecting channel capacity and the performance of interference cancellation by zero-forcing receivers. This article investigates the impact of this uncertainty in the presence of rain. Commercial backhaul links (CMLs) in cellular networks are not only essential for data transmission but have also proven useful for rainfall monitoring. They are now emerging as a new opportunistic integrated sensing and communication (OISAC) application for weather sensing. This article also studies the use of LOS-MIMO backhaul technology for rain rate estimation. The availability of multiple data streams allows the number of rain estimation values to increase linearly with the minimum number of transmit and receive antennas in the MIMO link, Additionally, the potential for LOS-MIMO microwave links to retrieve parameters related to rain drop size distribution based on measurement data is also explored. This new backhaul solution shows great potential to be used for near-ground environmental monitoring and weather prediction studies, particularly with the advent of the big data era.

Abstract. The interior of the Tibetan Plateau exerts a first-order influence on the Asian monsoon and regional climate, yet vertically resolved aerosol observations there are scarce, and no openly archived, multi-year, ground-based profile record has existed for this exceptionally clean high-altitude environment. We present such a dataset from a six-channel elastic/Raman/depolarisation lidar (355, 387, 408, 532, 607, 1064 nm) at Yangbajing (30.10° N, 90.52° E, 4284 m a.s.l.), covering September 2021 to December 2024: 437 quality-controlled nighttime profiles on a 75 m grid (157 levels, 0.30 to 12 km a.g.l.) and 279 daytime column-AOD retrievals. The independent products are the nitrogen-Raman extinction at 355 and 532 nm and the Raman-derived lidar ratio. The aerosol backscatter at 355 and 532 nm is retrieved by the elastic (Fernald) inversion with an assumed lidar ratio of 50 sr, and the 1064 nm backscatter is a non-independent colour-ratio transfer. Volume and particle depolarisation ratios (532 nm), water vapour mixing ratio (408/387 nm; radiosonde-calibrated C = 90.4 g kg-1, ~17 % uncertainty), Ångström exponents and column aerosol optical depth (AOD) complete the product set, and a scattering-ratio cloud screen supplemented by a particle-depolarisation ice test separates mineral dust from ice. The site is among the cleanest continental settings sampled by lidar: the nighttime detection-night median column AOD at 532 nm is 0.053 (n = 269) and the daytime detection median is 0.078 (n = 208). The Raman-derived site-mean lidar ratio is 51.6 sr (IQR 41 to 80 sr, n = 85), consistent in the median with the assumed 50 sr and with the CALIPSO clean-continental value, but it varies by a factor of two from night to night. This assumption, not photon noise (median relative σ ~1.7 % for the 532 nm extinction, rising to a 90th percentile of ~24 % in the weak-signal upper troposphere), dominates the column-AOD uncertainty (+60 %/-18 %), for which per-profile S = 41 and 80 sr bounds are provided. Daytime AOD tracks AERONET Nam Co (~85 km) in rank order (Pearson r = 0.61, Spearman ρ = 0.72, both p < 0.001, n = 41). To our knowledge this is the first openly archived, multi-year, ground-based multi-wavelength aerosol profile dataset from the clean interior Tibetan Plateau, a region pivotal for the Asian monsoon and the Third Pole cryosphere where high surface albedo and complex terrain defeat passive retrievals and leave spaceborne lidar the de facto reference. It supplies the vertically resolved ground truth needed to evaluate and correct spaceborne-lidar aerosol detection and typing, to benchmark next-generation missions such as EarthCARE over bright, high terrain, and to constrain reanalysis, model, and aerosol radiative studies of dust transport and monsoon aerosol over the Third Pole.

Escalating global climate change has intensified the urgent demand for high-precision, real-time rainfall monitoring. While rainfall retrieval based on commercial microwave links (CMLs) currently faces key challenges, such as data scarcity and insufficient model generalization. The integration of core sixth-generation (6G) technologies within the Internet of Things (IoT) framework presents promising solutions. These emerging technologies offer inherent advantages, including wide coverage, low cost, easy deployment, and strong real-time capability. Building upon these strengths, it has significantly enhanced CMLs rainfall retrieval performance by integrating 6G's terahertz communication and ultralow latency transmission, IoT-enabled edge intelligence, integrated sensing and communication (ISAC), and artificial intelligence (AI) for data processing and real-time analysis, the performance of CML-based rainfall retrieval has been significantly enhanced. This provides a viable technical pathway for achieving subkilometer accuracy meteorological monitoring and building multidimensional sensing systems for smart cities. The main works of this article are as follows: 1) a comprehensive review of recent advances in CML-based rainfall retrieval, covering both model-driven and data-driven retrieval technical routes from fundamental principles; 2) designing and conducting a rainfall retrieval experiment using a long-short-term memory (LSTM) model based on real-world E-band CMLs measurements from Nanjing, China, which robustly verifies the high-precision retrieval potential of data-driven approaches in complex urban propagation environments; and 3) an in-depth analysis of emerging challenges, such as high-frequency data fusion, faced by CMLs rainfall retrieval technology in scenarios deeply integrated with 6th-generation IoT scenarios, along with discussion of potential technical solutions.

Accurate cloud detection over the Tibetan Plateau (TP) is crucial for understanding regional weather patterns and global climate dynamics. Yet, it remains challenging due to harsh environmental conditions and sparse observations. While ground-based infrared radiometers offer a promising solution through downwelling infrared brightness temperature (IRBT) measurements, existing algorithms require supplementary meteorological data often unavailable in remote TP regions. This study presents a novel cloud detection algorithm that operates solely on IRBT data from a single ground-based infrared radiometer, addressing the critical need for autonomous cloud monitoring in resource-limited environments. The algorithm integrates spectral and temporal analysis approaches: the spectral test identifies cloud presence by comparing observed IRBT against statistically derived clear-sky diurnal cycles, and the temporal test detects clouds through IRBT variability analysis using sliding standard deviation calculations. A key innovation includes a normalization procedure that effectively mitigates dust contamination effects – a persistent challenge in the arid TP environment that can introduce extremely large errors. Validation against 13 months of radiosonde data demonstrates robust performance with agreement rates exceeding 70 % in most months, with particularly effective performance during the wet season. This work provides a practical and cost-effective solution for autonomous cloud monitoring over the TP, with potential for application in other regions with limited observational data.

Commercial microwave links (CMLs) are used to transmit information between base station towers in cellular networks. Opportunistic remote sensing of rainfall, using the signal level measurements from CMLs, has proven to be highly accurate in rain rate estimation. As traditional CML link has single antenna and polarization setup, its capability of retrieving other precipitation parameters is limited. The latest microwave technology line-of-sight multiple-input multiple-output (LoS MIMO) are equipped with multiple transmitters and receivers to increase capacity. In a 2x2 LOS-MIMO system, each of the two antennas employs a different polarization. In this study, we investigate the potential of using LOS-MIMO microwave link to retrieve parameters related to rain drop size distribution based on measurement data.

Cloud vertical structure (CVS) strongly affects atmospheric circulation and radiative transfer. Yet, long-term, ground-based observations are scarce over the Tibetan Plateau (TP) despite its vital role in global climate. This study utilizes ground-based lidar and Ka-band cloud profiling radar (KaCR) measurements at Yangbajain (YBJ), TP, from October 2021 to September 2022 to characterize cloud properties. A satisfactorily performing novel anomaly detection algorithm (LevelShiftAD) is proposed for lidar and KaCR profiles to identify cloud boundaries. Cloud base heights (CBH) retrieved from KaCR and lidar observations show good consistency, with a correlation coefficient of 0.78 and a mean difference of -0.06 km. Cloud top heights (CTH) derived from KaCR match the FengYun-4A and Himawari-8 products well. Thus, KaCR measurements serve as the primary dataset for investigating CVSs over the TP. Different diurnal cycles occur in summer and winter. The diurnal cycle is characterized by a pronounced increase in cloud occurrence frequency in the afternoon with an early-morning decrease in winter, while cloud amounts remain high all day, with scattered nocturnal increases in summer. Summer features more frequent clouds with larger geometrical thicknesses, a higher multi-layer ratio, and greater inter-cloud spacing. Around 26% of the cloud bases occur below 0.5 km. Winter exhibits a bimodal distribution of cloud base heights with peaks at 0-0.5 km and 2-2.5 km. Single-layer and geometrically thin clouds prevail at YBJ. This study enriches long-term measurements of CVSs over the TP, and the robust anomaly detection method helps quantify cloud macro-physical properties via synergistic lidar and radar observations.

Raindrop size distribution (DSD) plays a crucial role in enhancing the accuracy of radar quantitative precipitation estimates in the Tibetan Plateau (TP). However, there is a notable scarcity of long-term, high-resolution observations in this region. To address this issue, long-term observations from a two-dimensional video disdrometer (2DVD) were leveraged to refine the radar and satellite-based algorithms for quantifying precipitation in the hinterland of the TP. It was observed that weak precipitation (R<1, mm h−1) accounts for 86

An investigation is undertaken to explore a sudden quasi-linear precipitation and gale event that transpired in the afternoon of 30 May 2024 over Beijing. It was situated at the southwestern periphery of a double-center low-vortex system, where a moisture-rich belt efficiently channeled abundant warm, humid air northward from the south. The interplay between dynamical lifting, convergent airflow-induced uplift, and the amplifying effects of the northern mountainous terrain’s topography creates favorable conditions that support the development and persistence of quasi-linear convective precipitation, accompanied by gale-force winds at the surface. The study also analyzes the impacts of five microphysics schemes (Lin, WSM6, Goddard, Morrison, and WDM6) employed in a weather research and forecasting (WRF) numerical model, with which the simulated rainfall and radar reflectivity are compared against ground-based rain gauge network and weather radar observations, respectively. Simulations with the five microphysics schemes demonstrate commendable skills in replicating the macroscopic quasi-linear pattern of the event. Among the schemes assessed, the WSM6 scheme exhibits its superior agreement with radar observations. The Morrison scheme demonstrates superior performance in predicting cumulative rainfall. Nevertheless, five microphysics schemes exhibit limitations in predicting the rainfall amount, the rainfall duration, and the rainfall area, with a discernible lag of approximately 30 min in predicting precipitation onset, indicating a tendency to forecast peak rainfall events slightly posterior to their true occurrence. Furthermore, substantial disparities emerge in the simulation of the vertical distribution of hydrometeors, underscoring the intricacies of microphysical processes.

Meteorological radars, as remote sensing instruments, play a vital role in observing clouds and precipitation. However, due to the complexity of hydrometeors in shape, density, diameter, orientation, and particle size distributions, accurate quantification of the inner microphysical characteristics of a cloud/precipitation system is challenging for a single-frequency radar. Recently, the advancement in scattering theory of hydrometeors, computer science, and hardware manufacturing (such as millimeter-wave devices) has stimulated the application of multi-frequency radars, bringing novel observations for an improved understanding of cloud and precipitation microphysics. Over the past few years, the multi-frequency vertical detection techniques have evolved from the new retrieval methods being enlightened by scattering theory to a new stage of the crucial microphysical processes being revealed by field observations. In this paper, from the perspectives of liquid and frozen hydrometeor microphysics, we introduce the key techniques used for dual- and triple-frequency radar retrieval techniques based on the scattering and attenuation of hydrometeors. Meanwhile, enlightened by the scattering of hydrometeors, we propose that the multi-frequency radar detecting techniques are developing from the classical W/Ka/X wavelengths to a "triple-frequency plus" stage, involving radars with shorter wavelengths and/or longer wavelengths. With spaceborne radars being developed from single-frequency to dual-frequency radars, the improvement of ground-based multi-frequency radars is expected to provide crucial support to future spaceborne multi-frequency radar missions.

For triple-frequency radar, the attenuation attributed to atmospheric gases and stratiform clouds is diverse due to different snowfall microphysical properties, particularly in regions far from the radar. When using triple-frequency ground-based radar measurements, evaluating the attenuation of the three radars at different heights is common to derive attenuation-corrected effective reflectivity. Therefore, this study proposes a novel quality-controlled approach to identify radar attenuation due to gases and stratiform clouds that can be neglected due to varying snowfall microphysical properties and assess attenuation along the radar observation path. The key issue lies in the lack of information about vertical hydrometeor and cloud distribution. Therefore, European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data are employed. The Self-Similar-Rayleigh-Gans Approximation (SSRGA) for the nonspherical scattering model in the Passive and Active Microwave TRAnsfer model 2 (PAMTRA2) is compared and analyzed against other scattering models to obtain the optimal triple-frequency radar attenuation correction strategies for stratiform cloud meteorological conditions with varying snowfall microphysical properties. This methodology paves the way for understanding differential attenuation attributed to gas and stratiform clouds with snowfall microphysical properties. Simultaneously, the bin-by-bin approximation method is used to perform the attenuation correction. The two-way attenuation correction increased up to 4.71 dB for heights above 6 km, remaining minimal for regions with heights below 6 km. These values, attributable to gases and stratiform clouds’ two-way attenuation, are nonnegligible, especially at distances far from the W-band radar at heights above 6 km. Both values are relatively small for the X- and Ka-band radars and can be neglected for the varying snowfall microphysical properties. The attenuation correction of triple-frequency radar reflectivity is validated using the cross-calibration and dual-frequency reflectivity ratios. The results show that the method is valid and feasible.

Precipitation is a critical factor in changing aerosol life cycle, yet its impact on aerosol species with different properties in megacities remains unclear. Here we characterized the changes of PM 2.5 aerosol species during rainfall processes in five summers (2018–2022) in Beijing using highly time‐resolved measurements of aerosol chemical speciation monitor along with precipitation. Average pattern of 233 rainfall processes showed that over 30% decreases in aerosol species before rain start were due to the increased wind speed, and the subsequent decreases were caused by the combined effects of precipitation and winds with an average scavenging of 62%–100% in 1 hr. We also observed very different responses of aerosol species to precipitation depending on intensities, duration and formation mechanisms. During the rainfall processes, aerosol composition showed decreased contributions of organics and sulfate, particularly from late night to morning, while increased contributions of nitrate and chloride due to enhanced gas‐particle partitioning associated with the increase of relative humidity and the decrease of temperature. The scavenging rates of aerosol species significantly increased as the increase of rainfall intensity (>5 mm hr −1 ) and duration (>4 hr). However, the scavenging effect of light rainfall was negligible although the cumulative contribution was ∼50% due to high frequency, and even caused increases in nitrate and chloride. The case analysis of aerosol evolution during weak and heavy rainfall events further illustrated the dual impacts of precipitation on aerosol species through wet scavenging and secondary formation.

介绍了西藏羊八井全大气层观象台最新架设的Ka&W双频毫米波云雷达(以下简称YBJ-DFDR,W波段94 GHz,波长3.2 mm,Ka波段35 GHz,波长8.6 mm)的基本性能,并选择该地区不同类型云的观测数据,对其探测能力开展了分析和对比研究.分析结果显示,该双频云雷达系统具有较高的探测能力,其中W波段雷达和Ka波段雷达在10 km距离处的探测灵敏度分别达为-39.2 dBZ和-33 dBZ.对比研究表明Ka和W波段雷达所测等效反射率因子值因云物理属性不同亦呈现不同的特征.发生降雨时,由于液态雨和云粒子对雷达信号的吸收和散射作用,造成回波信号出现衰减,此时Ka和W波段雷达二者之间的衰减程度明显不同,W波段雷达信号衰减较严重,甚至出现衰减后低于探测灵敏度而无法获得回波的情况(严重时二者之差可达30 dB).而当云中粒子多为冰相时,回波信号的衰减程度显著减弱,W波段雷达相比Ka波段雷达展示出更佳的探测能力,其所测反射率因子值普遍高于Ka波段雷达.研究亦发现Ka波段雷达对于云层边缘区域,如云顶、云底部分,容易出现漏测的情况,从而导致云顶高度的低估和云底高度的高估,其主要原因是这些区域的云粒子较小及数浓度相对较低,回波信号较弱,Ka波段雷达无法探测到.

Abstract. Based on the quality-controlled observational spectral width data of the Beijing Mesosphere–Stratosphere–Troposphere (MST) radar in the altitudinal range of 3–19.8 km from 2012 to 2014, this paper analyzes the relationship between the proportion of negative turbulent kinetic energy (N-TKE) and the horizontal wind speed/horizontal wind vertical shear domain, and gives the distributional characteristics of atmospheric turbulence parameters obtained by using different calculation models. Three calculation models of the spectral width method were used in this study—namely, the H model (Hocking, 1985), N-2D model (Nastrom, 1997) and D-H model (Dehghan and Hocking, 2011). The results showed that the proportion of N-TKE in the H model increases with the horizontal wind speed and/or the vertical shear of horizontal wind speed, up to 80 %. When the horizontal wind speed is greater than 40 m·s−1, the proportion of N-TKE in the H model is greater than 60 %, and thus the H model is not applicable. When the horizontal wind speed is greater than 20 m s−1, the proportion of N-TKE in the N-2D model and D-H model increases with the horizontal wind speed, independent of the vertical shear of the horizontal wind speed, and the maximum values are 2 % and 4 %, respectively. However, it is still necessary to consider the applicability of the N-2D model and D-H model in some weather processes with strong winds. The distributional characteristics with height of the turbulent kinetic energy dissipation rate 𝜀 and the vertical eddy diffusion coefficient Kz derived by the three models are consistent with previous studies. Still, there are differences in the values of turbulence parameters. Also, the range resolution of the radar has little effect on the differences in the range of turbulence parameters' values. The median values of 𝜀 in the H model, N-2D model and D-H model are 10−3.2–10−2.8 m2 s−3, 10−2.8–10−2.4 m2 s−3 and 10−3.0–10−2.5 m2 s−3, respectively. The median values of Kz in these three models are 100.18–100.67 m2 s−1, 100.57–100.90 m2 s−1 and 100.44–100.74 m2 s−1.

Accurate snowfall forecasting and quantitative snowfall estimation remain challenging due to the complexity and variability of snow microphysical properties. In this paper, the microphysical characteristics of snowfall in the Yanqing mountainous area of Beijing are investigated by using a Particle Size and Velocity (PARSIVEL) disdrometer. Results show that the high snowfall intensity process has large particle-size distribution (PSD) peak concentration, but the distribution of its spectrum width is much smaller than that of moderate or low snowfall intensity. When the snowfall intensity is high, the corresponding Dm value is smaller and the Nw value is larger. Comparison between the fitted μ−Λ relationship and the relationships of different locations show that there are regional differences. Based on dry snow samples, the Ze−SR relationship fitted in this paper is more consistent with the Ze−SR relationship of dry snow in Nanjing, China. The fitted ρs−Dm relationship of dry snow is close to the relationship in Pyeongchang, Republic of Korea, but the relationship of wet snow shows greatly difference. At last, the paper analyzes the statistics on velocity and diameter distribution of snow particles according to different snowfall intensities.

青藏高原上空云宏观参数的日变化受大尺度环流、当地太阳辐射和地表过程的联合作用,对辐射收支、辐射传输及感热、潜热的分布等有重要影响.由于缺乏持续定量的观测,对各类天气系统云宏观参数日变化特征的了解还十分不足.多波段多大气成分主被动综合探测系统APSOS(Atmospheric Profiling Synthetic Observation System)的Ka波段云雷达是首部在青藏高原实现长期观测云的雷达.本文基于2019年全年APSOS的Ka波段云雷达资料,采用统计和快速傅里叶变换方法研究了西风槽、切变线和低涡三类重要天气系统影响下的有云频率、单层非降水云或者降水云非降水时段的云顶高度、云底高度和云厚日变化的时域和频域特征,得到了统计回归方程.主要结论有:(1)西风槽系统日均有云频率为56.9％,切变线系统为50.8％,低涡系统达73％.(2)尽管西风槽和切变线系统的成因不同,但两类系统云宏观参数的日变化趋势和主要谐波周期相似:日变化趋势基本为单峰单谷型,日出前最低,日落前最高.有云频率表现为日变化和半日变化,单层云云顶高度、云底高度和云厚主要表现为日变化.(3)低涡系统云宏观参数的日变化特征与前两类系统明显不同:日变化趋势表现为多峰多谷型,虽然有云频率和单层云云顶高度、云底高度主要谐波中均以日变化振幅最大,但频谱分布分散,云厚主要变化中振幅最大的是周期为4.8 h的波动.(4)得到了各系统有云频率、单层云云顶高度、云底高度和云厚日变化的统计回归方程.

Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO2), carbon monoxide (CO) and nitrogen dioxide (NO2). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO2 measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration.

本文设计了中国科学院大气物理研究所位于同一观测站内的一部单发双收Ka波段双偏振雷达和一部双发双收X波段双偏振雷达高效结合观测的方法,并首次将Ka和X波段双偏振雷达结合应用在降雪过程的观测中,对2019年2月14日锋面气旋系统在北京地区降雪过程中雪带的形成、发展、消亡过程的宏微观结构进行了分析.结果 表明,雪带的垂直结构符合以往对层状云垂直分层的物理认识,类似但不同于雨带由凝结增长层、丛集层、淞附层、融化层组成的四层结构,雪带只包含由上层"播种"至下层的冰晶形成的凝结增长层、丛集层和淞附层三层.由于各层水平风速不同,雪带的三层结构并非垂直排列.多个雪带不断生成发展维持降雪,直至冰晶凝结生长层变空,云从冰晶凝结生长层分裂为多层云后各自消散.证明了Ka和X波段双偏振雷达结合的必要性和高效性,丰富了对锋面气旋系统雪带的认识,补充了Ka波段和X波段雷达对降雪的观测研究.