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In this paper, we analyzed the precipitation data from 2016 to 2017 obtained by the new-generation weather radar and 256 ground automatic rainfall stations in Leshan and applied the dynamic grading Z-I relationship method of the quantitative precipitation estimation of Leshan area, while the method was based on constant altitude plan position indicator (CAPPI) products. The results show the dynamic grading Z-I relationship method is better than the fixed Z-I relationship method of estimation of heavy rain intensity (above 40 mm/h) and the overall estimation effect in the rain intensity and hourly cumulative rainfall. But there still exists an underestimation of heavy precipitation.

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.

Observed data of each sampling height from P-band troposphere type □ wind profiler in Sichuan Yanyuan station(2466m ASL) and Qianwei station(486m ASL) in March 2018 is taken to study the temporal and spatial characteristics as well as the differences of wind shear from troposphere wind profiler at different altitudes. The values of horizontal wind speed and wind direction obtained by wind profiler are used to calculate the wind shear index at different time and different altitudes based on the power-law formula. By calculating vector difference and fitting the index on account of least square method, the vertical wind shear characteristics over the two stations are analyzed and compared with the products measured by wind profiler. The results show that the algorithm of wind shear index based on the power-law formula can preferable to reflect the wind shear characteristics of the wind field. The wind shear index tends to decrease with the increase of altitude because of the influence of the underlying surface on the wind speed. In addition, wind shear index also shows a trend of smaller in daytime, larger at night, smaller in plain area and larger in hilly area.

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.

Based on the HEC-GeoHMS module, this paper extracts the river network information of the Heihe River Basin effectively by using the Digital Elevation Model (DEM) obtained free of charge. By the steps of filling the sinks, determining the flow direction, flowing accumulation and streaming definition, we get the river network density corresponding to the thresholds of different confluence accumulations in the basin. By fitting the curve of the relationship between the threshold of sink flow and the density of the river network, we conclude that the most suitable threshold for the accumulation of the Basin is 42.3km2. In addition, the river network density decreases with the increase of the confluence accumulation threshold. But when the confluence accumulation threshold increases to a certain value, the change of the river network density becomes stable. According to the value of which the density tends to be stable, the river network information in the Heihe River Basin can be extracted effectively, which provides basic data for the establishment of the hydrological model in the region.

A historical severe rainfall case in the metropolitan area of Beijing was studied using a C-band dual-polarization radar system. The QPE results from the evaluation was then validated using 5-min resolution gauge observation from an operational national weather station where is in the severe rainfall area. Results show that the rainfall estimation is more consistent with the surface rain gauge observation compared with the S-band single polarization observation and the algorithm of R(KDP): Brandes (2002) is the best for this case.

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.

With the successful implementation of distributed collaborative adaptive sensing (DCAS) paradigm in CASA project, weather radar network has shown great advantages over conventional stand-alone weather radar, especially in urban environment. In order to better understand the initiation, development and cloud microphysics of thunderstorm in rainy season near the plateau area, this paper attempts to design a radar network near Chengdu Metropolitan area in western Sichuan Basin, China. This radar network, as a core part of the mesoscale meteorological observation system for Sichuan Basin, is an ideal research platform to investigate the local precipitation microphysics. It can also serve as a semi-operational network for local weather monitoring and emergency management.

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.