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Abstract Phased array weather radar (PAWR) for hazardous weather phenomena observation has attracted considerable attention. In this paper, a PAWR simulator for volume scan mode modeling is designed and the volume scan model has been used to evaluate the one-dimensional (1D) PAWR beam pattern characteristics and the effect of scanning mode. Firstly, the three-dimensional weather field has been generated by interpolating spectral moment parameters from next-generation weather radar data (NEXRAD), including reflectivity factor, radial velocity and spectral width. Secondly, based on the parameters of radar system and volume scanning modeling, the relationship between phased array beam characteristics and volume scanning mode is established, which can fully simulate the scanning process of phased array radar at different elevation cuts. Finally, according to the concept of 'scattering center', the time series of each range bin during volume scanning is reconstructed. The performance of the PAWR simulator has been evaluated under typical weather scenario, such as tornadoes and the results indicated the effectiveness and superiority over traditional Doppler weather radar. Simulation examples are provided to illustrate the flexibility and practicability of the PAWR simulator, and the factors affecting its PAWR detection performance are evaluated. The research results represent that reducing the number of linear array elements and increasing the array angle will further exacerbate the degradation of data quality.

The quality of weather radar affects the reliability and effectiveness of monitoring severe convective weather. Therefore, rigorous calibration and validation are the foundation for the quantitative application of weather radar. Among the available methods, radial velocity validation is of great significance for reducing the false alarm rate in the identification of tornadoes and thunderstorms. Based on the traditional method that utilizes internal and external instrument radar velocity measurements, we propose a weather radar radial velocity validation method that uses RTK UAV to simulate external targets. In addition, according to the characteristics of the UAV application scenarios, we introduce the evaluation parameter of optimal absolute accuracy to supplement the original parametric system. The experimental results show that the evaluation parameter of optimal absolute accuracy can effectively reduce the interference caused by the systematic deviation of the UAV due to the internal and external environment, which can affect the validation results. When the UAV velocity is not greater than 10 m/s, the optimal absolute accuracy of the radial velocity validation is less than 0.05 m/s, which is essentially consistent with the external instruments’ measurement results. This method can be effectively applied to the procedural handling of weather radar radial velocity validation. It is significant for ensuring the accuracy and quality of weather radar radial velocity measurements and improving the effectiveness of radar velocity data applications.

To better calibrate the aerosol lidar network constructed by the China Meteorological Administration, and ensure the data quality observed by the network, the Meteorological Observation Center (China Meteorological Administration) and the University of Naples (Italy) jointly developed a “high quality 532 nm Raman aerosol lidar” (REAL lidar) in 2018. The ability to detect Raman–Mie scattering signals was improved through signal detection in a large dynamic range. This study compared the REAL lidar with the reference lidar (European ACTRIS aerosol lidar network) considering three wavelengths and eight channels. The results show that both the original signals and data products of the two radars exhibited good consistency. In the calibration application of China’s domestic lidar network, after REAL calibration, the relative average and standard deviations of the backscattering coefficient of the in-station lidar decreased from 55.4% to 7.9% and from 64% to 9.9%, respectively. The effect was significant, which indicates that REAL is an aerosol lidar with a high-performance index. The results satisfy the demand for calibration of the aerosol lidar network, and the REAL was successfully applied to the calibration of the aerosol lidar network.

Aerosol optical properties retrieved using polarization Raman lidar observations play an increasingly vital role in meteorology and environmental protection. The quality of the data products directly affects the impact of relevant scientific applications. However, the quality of aerosol optical properties retrieved from polarization Raman lidar signals is difficult to assess. Various factors, such as hardware system performance, retrieval algorithm, and meteorological conditions at the observation site, influence data quality. In this study, we propose a method that allows for assessing the reliability of aerosol optical properties derived from polarization Raman lidar observations. We analyze the factors that affect the reliability of retrieved aerosol optical properties. We use scoring methods combined with a weight-assignment scheme to evaluate the quality of the retrieved aerosol optical properties. The scores and weights of each factor are arranged based on our analysis of a simulation study and the characteristics of each factor. We developed an automatic retrieval algorithm that allows for deriving homogeneous aerosol optical data sets. We also assess with this method the quality of retrieved aerosol optical properties obtained with different polarization Raman lidars under different measurement scenarios. Our results show that the proposed quality assurance method can distinguish the reliability of the retrieved aerosol optical properties.

Atmospheric constituents feature a large vertical gradient in concentration, especially at the first few hundred meters over the earth’s surface. Atmospheric lidar usually cannot cover this range due to the incomplete overlap effect or the limited dynamic range of detectors. This drawback is well known as the blind zone effect, which hinders the application of atmospheric lidars in many aspects. In this work, a method based on an optical fiber bundle was proposed to mitigate the blind zone effect. An optical fiber head with several stages, installed at the focal plane of the telescope, is used to receive backscatter light from different range levels. The design of the optical fiber head is analyzed with the ray-tracing technique. The optical fiber installed at the highest stage of the fiber head can collect far-range light like a small aperture, and all the other optical fibers are bundled into a near-range detection channel to receive backscatter light from the first few hundred meters. This special design can avoid the near-range light loss in conventional lidar systems, usually equipped with a small aperture. Different optical attenuations are then applied to near-range and far-range channels to suppress the overall signal dynamic range. This light-receiving method was applied in a 1030 nm elastic lidar, in which a fiber bundle with a three-stage fiber head was fabricated and installed. A test experiment was performed to verify this approach. A good agreement between simulations and in-system results was found. Based on this design, the blind zone of the lidar system is less than 50 m, and the detectable range can be over 10 km along the lidar’s line of sight with a single telescope receiver. This approach brings a new way of designing atmospheric lidar with a low blind zone and can strengthen our ability to monitor urban pollution and promote land-atmosphere interaction research.

This research investigates Southwest Vortex (SWV) events in China’s Sichuan Basin using Fengyun-4A (FY-4A) and Global Precipitation Mission (GPM) observations. We selected representative cloud systems and precipitation cases, divided into developing, mature, and dissipating stages. Detailed analysis revealed critical characteristics of precipitation cloud systems at each stage. Our findings reveal that (1) during the SWV’s developing and mature stages, a high concentration of water particles and ice crystals stimulates precipitation. In contrast, the dissipating stage is marked by fewer mixed-phase and ice particles, reducing precipitation area and intensity. (2) Near-surface precipitation in all stages is predominantly liquid, with a bright band of around 5.5 km. At the same time, stratiform precipitation is dominant in each life stage. Stratiform precipitation remains dominant throughout the life stages of the SWV, with localized convective activity evident in the developing and mature stages. (3) Mature stage particles, characterized by a configuration of 1.0–1.2 mm Dm and 31–35 dBNW (dBNW = 10log10NW), contribute significantly to near-surface precipitation. The Cloud Top Height (CTH) serves as an indicator of convective intensity and assists in characterizing raindrop concentration. These findings considerably enhance routine observations, advance our understanding of SWV events, and propose a novel approach for conducting refined observational experiments.

Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM10 is the main pollutant and the ratio of PM2.5/PM10 is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.

During the Beijing Winter Olympics, three sets of aerosol lidar in different regions were used to conduct continuous observations to study the optical properties and vertical distribution characteristics of atmospheric aerosol. Based on the lidar data and sun photometer data, the accurate lidar ratio was determined to improve the inversion accuracy of the aerosol backscattering coefficient. The influence of meteorological conditions such as temperature, relative humidity, wind speed, and wind direction on the optical properties of aerosol were analyzed, and the type of aerosol was classified by the depolarization ratio of aerosol particles and CALIPSO data. Furthermore, the backward trajectory analysis, potential source contribution function (PSCF), and concentration weighted trajectories (CWT) were employed to explore the sources and transport mechanisms of pollutants. The analysis found that the extinction coefficient under the atmospheric boundary layer during the Winter Olympics had a spatial distribution pattern of high value in the southeast and low value in the northwest. The occurrence of aerosol pollution events is not only caused by local emissions, but is also related to regional transmission.

In this paper, a dual-polarization weather radar echo signal simulation method is proposed for the evaluation of the performance enhancement of dual-polarization weather radar systems, the optimization of signal processing algorithms and the improvement of scanning strategies. The actual weather radar base data are used in the simulation as the reference weather scene, which avoids using a complex algorithm for weather modeling. Moreover, based on radar weather equations, the radar system parameters are added into the radar echo signal modeling to establish the relationship between the simulated echo signal and radar system. As a result, the final simulated echo signal not only shows both the time and frequency domain characteristics of the weather target, but also includes the effects of the important performance of the dual-polarization weather radar system. In addition, to evaluate the performance of range ambiguity mitigation using phase coding and batch working modes, two different simulation methods for the radar signal are established on the method above; one is for batch working mode with long-PRT (pulse repetition time) and short-PRT transmission and receiving, and the other is for phase-coded mode with phase-coded transmission and phase-uncoded receiving. Under the same weather scene, the observation of these two different methods of range ambiguity mitigation are simulated and compared. Results show that the performance of the phase coding mode for mitigating range ambiguity is better than that of the batch mode. Obviously, the simulation method can be used to directly show the observation of different algorithms for mitigation range ambiguity under the same weather process, and quickly compare and evaluate the algorithm’s performance, which is not possible for real radars.

The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies.

Aerosol lidar network can play an important role on revealing structural characteristics of atmospheric boundary layer, urban heat island effect, spatial distribution of aerosols, especially monitoring atmospheric pollution in a megacity. To fulfill the need of monitoring and numerical forecast of atmospheric pollution, an aerosol lidar network is proposed by China Meteorological Administration, which serves as an important part of "MegaCity Experiment on Integrated Meteorological Observation in China" (MEMO). To ensure high standard of data quality and traceability of measurement error, an inter-comparison campaign, dedicated for quality assessment of lidar systems from different institutes and manufacturers, was designed and performed at Beijing Southern Suburb Observatory in September 2021. Six Mie-Rayleigh lidar systems at 1064 nm were involved in this campaign. The strategies for lidar self-evaluations and inter-comparisons were predefined. A lidar system at 1064 nm, which was developed by Atmospheric Remote Sensing group at Wuhan University, was selected as the reference lidar system after passing all self-evaluations quality checks in a strict way. The reference lidar system serves as the corner stone for evaluating the performance of other lidar systems. After using the self-test of Rayleigh fit and signal-to-noise evaluation for each individual lidar system to fast check the data quality, the range-corrected signal and backscatter coefficient obtained from all the lidar systems were inter-compared with a reference lidar system. In the end, the lidar systems were quality assured, of which the standard deviation of range-corrected signal can be controlled within 5% at 500-2000m while 10% at 2000-5000m. For the derived aerosol backscatter coefficients, standard deviations can be controlled within 10% at 500-2000m and 2000-5000 m. The quality assurance strategy lays down a solid basis for atmospheric lidar at near-infrared wavelength and will be applied in Chinese lidar network development. [ABSTRACT FROM AUTHOR]

Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as vertical wind field measurement. In order to verify the accuracy of the Doppler wind lidar, the major domestic Doppler wind lidar manufacturers were organized to compare the Minute-level average wind speed and direction data measured by the lidars to which measured by meteorological gradient tower and L band Sounding radar in Shenzhen and Zhangjiakou, respectively. The result of comparison with the wind cup on the meteorological gradient tower is in good agreement, the correlation coefficient of wind speed is close to or higher than 90%, and the maximum standard deviation of the wind direction is about 7 ° except the inflection point. When the L-band sounding radar is used as a reference for the lidar equipment which joint the comparison. The system difference and standard deviation of daily wind speed and direction vary greatly, and the reliability is poor. At the same time, it was founded that compared with the 1-minute average data, when the 10-minute average data were used for comparison, the system deviation and standard deviation were reduced. That mean the results were more stable and reliable. The comparison results show that the technical indicators of several domestic lidar equipment are equivalent to windcube indicators made by Vaisala and complying with the World Meteorological Organization's requirements for the Coherent Doppler Lidar indicator for near-term weather forecasts. It shows the lidars are reliable to obtain wind speed and direction parameters at different altitudes in real time. [ABSTRACT FROM AUTHOR]

A denoising method of all-fiber pulsed coherent Doppler LIDAR (CDL) is investigated. The goal is to enhance the signal-to-noise ratio (SNR) in the weak signal regime. Based on differential detection theory, the total noise expression of CDL with a dual-balanced detector is introduced and analyzed. The conclusion is drawn that the total noise can be acquired under the local oscillator laser exposure conditions by reasonable simplification. Using the actual measured data, the ratio of the standard deviation to the mean value of the total noise in each range gate is obtained and is up to approximately 11%. In order to suppress the jitter of the noise, an effective noise modeling by the trend of each range gate is developed. The feasibility of this method is verified by a long set of measured data. The spatial and temporal distribution of wind speed is illustrated with 400 pulses accumulation. Compared to the noise modeling of the tail, the detection range of wind speed using the proposed method can be improved by 35.3%. [ABSTRACT FROM AUTHOR]