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The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant 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 algorithms 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-gauge 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.

For to know the performance of dual linear polarization SC radar and its consistency with CINRAD-SA detection data, the echo reflectance data of two kinds of radar are compared and analyzed. Using reflectivity data of two radars at the same time in the same rainfall event, two radar data were interpolated into a 3d grid at the same height to compare their intersecting areas by using the method of region lattice point comparison. Study on the scatter characteristics and probability distribution of two radar reflectivity values in intersecting regions. The results show that echo reflectivity characteristics of the perpendicular bisector in two radars have good consistency, but the echo data value detected by dual linear polarization SC radar is larger than that of SA radar; Under 25 dB, the detection value of dual-line polarization SC radar is greater than that of SA radar; The echo reflectivity data of SC radar are less discrete. The rainfall calculated by using the Z-R relation, R(KDP) and R(ZH, ZDR) method of the dual-line polarization SC radar is all higher than the observed values of the ground rain gauge, and the difference between the observed values of the rainfall calculated by the R(KDP) method and the rain gauge is relatively small. In order to improve the effect of quantitative precipitation estimation, further quality control of polarization parameters and echo data is needed.

Doppler Weather Radar (DWR) observations of a severe hailstorm were assimilated in the Weather Research and Forecasting (WRF) model, the three dimensional variational (3D-Var) assimilation is the more common approach. The hailstorm occurred in Bayannur, Inner Mongolia, China, during August 9-10, 2019. The processes of formation, development, and dissipation of the hail-cloud were analyzed, simulated, and discussed in this study. The simulation and assimilation results were verified against X-band dual-linear polarization radar observations. The Morrison and Milbrandt parameterization scheme is applied to simulate synoptic process. In this paper, comparative experiments are set to analysis the impact with and without assimilation of doppler weather radar data on hail simulation:1) control experiment (CTL): without data assimilation; 2) assimilate reflectivity and radial velocity together. The result shows that the Morrison and Milbrandt parameterization scheme can simulate the hail weather process well; at the time when hail occurred, there were strong vertical wind shear, small precipitation amount, low freezing layer, the potential temperature decreases with the height, and the radar echo intensity was around 60dBZ. The hail simulation is improved significantly after assimilation of doppler radar reflectivity and radial velocity

—This paper uses Haikou ’s dual linearly polarized SA bond radar (Z9898) and Dongfang’s SA band new generation Doppler weather radar (Z9072) to compare and analyze a precipitation process that occurred in Hainan Province on July 2, 2019, and carefully compared the relationship between the reflectivity factors of the two radars to study the detection ability of dual polarization radars. Considering the consistency of radar observations, this study selected the reflectivity factors near the mid-perpendicular line of the two radars for comparison, and used the bilinear interpolation method to interpolate the radar reflectivity volume scan data in the spherical coordinate system to the grid under coordinate system to obtain the CAPPI (Constant Altitude Plan Position Indicator), and compare the reflectivity factors of the same height, and then draw and analyze a scatter plot of the reflectivity factors. At the same time, two The probability distribution of the reflectance factors of the two radars in the selected area is compared, and the mean, standard deviation and correlation coefficient of the observation data of the two radars in the area are counted. Finally, the rainfall estimation is performed according to the Z-R relationship. Experiments show that for areas of the same distance from two radars, the observation data of dual-linear polarization radar is significantly larger than that of CINRAD-SA radar; and through statistical analysis, the average value of dual-polarization radar is 7.7 dBZ greater than CINRAD-SA and the standard deviation is 0.32 lower, indicating dual-linear polarization radar performance is better than the CINRAD-SA radar; finally, the rainfall calculation result of the dual linear polarization radar is greater than that of the CINRAD-SA radar.

In this study, the Weather Research and Forecasting (WRF) model is used to simulate a severe convective process in Hainan, China on September 16, 2019. For the purpose of improving precipitation simulation and forecast, the WRF model’s three-dimensional Variational (3DVAR) assimilation system is used to assimilate CINRAD/SA Weather radar data. The assimilation results and precipitation forecast are compared and analyzed in order to study the influence of weather radar data assimilation on precipitation prediction. Four experiments of assimilation are carried out: 1) Control experiment: no assimilation of any data; 2) Only radar reflectivity data is assimilated; 3) Assimilating the radar radial velocity data; 4) Simultaneously assimilating the radar reflectivity and radial velocity data. The results show that the assimilation of the reflectivity data from the weather radar can effectively adjust the spatial distribution and magnitude of water vapor and temperature field in the background field. Assimilating the radar radial velocity data mainly improves the wind field of initial field. The assimilation of reflectivity can better adjust the precipitation forecast compared with the assimilation of radial velocity. Assimilating both reflectivity and radial velocity at the same time shows the best positive effect on precipitation forecast.

In this study, empirical A H -K DP and A DP -K DP relationship-based and self-consistent methods were used to correct the attenuation of reflectivity (z h ) and differential reflectivity (Z DR ) acquired from C- and X-bands dualpolarization radars, and the Z h of S-band Doppler radar was used to evaluate the results. The results indicated that, for Xband dual-polarization radar, the attenuation of Z h and Z DR could be corrected by two methods for heavy and moderate rain, and the distribution of Z h -Z DR scatters were closer to the theoretical relationship after self-consistent correction than that after empirical A H -K DP and A DP -K DP relationship-based correction. For light rain, similar results were obtained for two methods. For C-band dual-polarization radar, the degree of attenuation was less than X-band dual-polarization radar for the same intensity of rainfall, and the attenuation was need to be considered in heavy and moderate rain. For heavy rain, the distribution of Z h -Z DR scatters were closer to the theoretical relationship after empirical A H -K DP and A DP -K DP relationship based correction than that after self-consistent correction. For moderate rain, similar results were obtained for two methods. The corrected reflectivity of C-band dual-polarization radar was closer to that of S-band Doppler radar, however, for X-band dual-polarization radar, it was 5.10 dB larger than that of Sband Doppler radar in heavy rain, 4.64 dB in moderate rain, and 3.34 dB in light rain. It was consistent with the scattering simulation results of other scholars.

Windshear is a generic term referring to any rapidly changing wind currents and it’s a hazardous weather condition that can be the reason of airplane crashes. It can be caused by microbursts, a type of weather phenomenon which are local, short-lived downdrafts that radiate outward as they rush toward the ground. In this paper, an automatic microburst detection algorithm (AMDA)[1] is used to locate the windshear area, using 21 cases observed by dual-polarization radar of NEXRAD to verify the practicability and effectiveness of this algorithm. The result shows that the probability of detection based on AMDA is higher than 90%. Furthermore, referring to the wind-shear rating standard (1967) from ICAO (International Civil Aviation Organization) and WMO (World Meteorological Organization), a windshear rating method for ground-based radar is presented.

The reflectivity observation was analyzed to study the reliability of three-dimensional gridding algorithm during a precipitation process in Hainan on July 2, 2019, which acquired from CINRAD/SA weather radars located in Haikou and Dongfang. In this study, according to the nearest neighbor method in radial and the vertical linear interpolation method in azimuth, the volume-scanned reflectivity data of radar at Haikou in the spherical coordinate were interpolated into the longitude and latitude grids in the cartesian coordinate. The three-dimensional gridding reflectivity was verified by comparing its structural characteristics with the original volume-scanned reflectivity. The statistical errors between the three-dimensional gridding reflectivity and the volumescanned reflectivity observed from radar at Dongfang during the same period of time and in the common detection area were analyzed. The results show that the three-dimensional gridding reflectivity has a good continuity in space, and also retains the structural features of the original volume-scanned reflectivity data, and it is in good spatial consistency with the reflectivity observed from the weather radar in Dongfang city.

The polarization radar precipitation particle classification algorithm based on fuzzy logic is widely concerned and applied because of its stability and ease of use. However, due to the characteristics of the algorithm itself, the data quality of the input parameters (radar polarimetric variables: ZH, ZDR, KDP and ρHV) of the algorithm has a great impact on the classification results, which can be quantitatively evaluated through simulation experiment to analyze the sensitivity of precipitation particle fuzzy logic classification algorithm to the deviation of input variables. In this paper, we assume the measurement data of radar polarimetric variables as the true value, then introduced bias of ± 3 dBZ (in an interval 0.25 dBZ) for ZH, ± 1 dB (in an interval 0.25 dB) for ZDR, $\pm 1.25^{\circ} / \mathrm{km}$ (in an interval $0.25^{\circ} / \mathrm{km}$) for KDP, and -0.1 (in an interval 0.01) for ρHV respectively. By studying a case of typical stratiform cloud precipitation, the sensitivity of the precipitation particle classification results to the deviation of polarimetric variables has been analyzed using the method of the control variable test in a quantitative way, which can be evaluated by the percentage of identified precipitation particle distribution. The results show that, for ZH and KDP, the proportional distribution change of the output type of the algorithm is not obvious, however, for ZDR, distribution in the classification of the liquid precipitation particles has relatively obvious change. As for ρHV, the classification algorithm is very sensitive to the change of the deviation of ρHV.

In order to understand of physics process in the hailstorm, a hail event on August 9, 2019 had been analyzed by using the data collected of two X-band dual polarization radars located in Wuyuan County Meteorological Bureau and Ulansuhai Meteorological Observation Station in Bayan Nur, Inner Mongolia Autonomous Region. Hailstorm information recorded by 58 hail pads which were deployed in the experiment region were also used for the validation of the radar observation. The volume scan data of the Wuyuan radar is meshed by three-dimensional coordinates of longitude, latitude and altitude by vertical interpolation. In the common observation area, through comparing and validating the values of the polarization parameters on the crossover line to analyze the vertical structure characteristics of hail cloud. The results showed that the characteristics of hail observation data of the two radars in the same observation area are similar, Combining with two radar data can more completely obtain the hail information. The paper can provide relevant basis for the X-band dual polarization radar to the artificial hail suppression work in the Bayan Nur area.

Dual-polarization Doppler weather radar variables such as differential reflectivity (ZDR), differential propagation phase shift (ΦDP), specific differential phase (KDP), and the co-polar correlation coefficient (ρHV), which are closely related to the characteristic of hydrometeors. The precision of these variables determines the accuracy for quantitative precipitation estimation (QPE) and hydrometeor classification. By analyzing the relationship between the polarimetric radar variables and the signal-to-noise ratio (SNR), it is found that when the SNR decreases to a certain threshold, polarimetric variables become more sensitive to the decrease in the SNR, and the precision of these variables become deteriorated with the decrease of the SNR. This threshold usually is closely related to the radar performance, for the X-band dual-polarization radar used in this paper, the SNR threshold is about 20 dB. The results of this study can provide some reference for radar system performance evaluation and data quality control.

The atmospheric structure constant of refractive index is an important parameter to describe the turbulent characteristics of the atmosphere. Using the ROBS data obtained by the Sichuan Provincial Meteorological Bureau in the Yanyuan, Dayi, Xinjin, Xindu, and Longquanyi districts, the real-time sampling of ROBS data combined with the hourly precipitation data provided by conventional meteorological observation stations was used for statistical analysis. Study the change trend of atmospheric structure constant of refractive index in the precipitation process in different regions. The results show that the convective movement during the precipitation process and the drag effect of the precipitation particles on the surrounding atmosphere, with the occurrence and development of the precipitation process, atmospheric structure constant of refractive index has a significant increasing trend, indicating the significance of precipitation. The vertical velocity and \( C_{n}^{2} \) are consistent with the change of precipitation, which can better reflect the change of precipitation intensity. The \( C_{n}^{2} \) value corresponding to the maximum precipitation time is two to five orders larger than that before and after the occurrence of precipitation.

Weather radar is a traditional remote sensing tool for precipitation observation and analysis. Compared with millimeter wave radar, it is less affected by attenuation, but at the same time, it has lower spatial and temporal resolution normally. Cloud radar has shorter wavelength and can detect basic information of cloud, such as cloud height, thickness and other parameters. It provides a fantastic technique to study fine structure for clouds. But due to the attenuation effect it is rarely used to analyze precipitation. In this paper, A cloud radar and a C-band weather radar nearby are used to analyze two precipitation processes. The Z-I relationship can be obtained by combining ground automatic precipitation observation at the same site of the cloud radar. By a primitive research in this paper, the characteristics of stratiform precipitation was obtained by analyzing the reflectivity vertical profiles, layer mean reflectivity and standard deviation from cloud radar and C-band radar, and it shows that some useful information can be retrieved using cloud radar observation even under precipitation conditions. So with the higher spatial and temporal resolution, more research work will be focused on the fine vertical structure characteristics retrieval from cloud radar observation in the future.

A 35GHz cloud radar was deployed in Chengdu Plain for cloud observation from Sept. 2015 to Mar.2016. After the data is processed, the vertical properties of cloud in these months, such as the distribution of cloud intensity, cloud-top, cloud-bottom and cloud height, will be statically analyzed from the data of radar reflectivity.

This paper will present the performance of Ka-band cloud radar designed by CUIT. Sample observations from this Ka-band solid-state radar for non-precipitation and weak precipitation events during October 2015 and March 2016 will be shown. In addition, the data quality control will be detailed, and the bin-by-bin based attenuation correction methodology using different K-Z relations will be presented.

In this paper, with the analytical method, the problem of unexpected bandwidth occupying is investigated firstly when a narrow-band signal passes through the inertialess nonlinear section of a digital radar receiver. Afterwards, the frequency aliasing that is caused by the digitalization is studied. To solve these two issues, the selection of the sampling frequency is of great importance. In this paper, a maximizing minimum arc-distance strategy is proposed, which is dependent on the frequency range of the signal. The arc-distance method is designed for optimizing the sampling frequency. Furthermore, with this method, the minimum arc distances between the frequency bands of the signal and the interferences can be calculated. The inter-band arc distances are important references for optimizing the transition bandwidth of the filter after the sampling and demodulation process.