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The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards (STORM973) project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region (BMR) during the warm season from 2014 to 2018. The aim of the project was to understand how dynamical, microphysical and electrical processes interact in severe thunderstorms in the BMR, and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts. The platforms used in the field campaign included the Beijing Lightning Network (BLNET, consisting of 16 stations), 2 X-band dual linear polarimetric Doppler radars, and 4 laser raindrop spectrometers. The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region. Although diverse thunderstorm types were documented, it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area, influenced by the terrain and environmental conditions. The flash density maximums were found in eastern Changping District, central and eastern Shunyi District, and the central urban area of Beijing, suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing. In addition, the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions. The super (5% of the total), strong (35%), and weak (60%) thunderstorms contributed about 37%, 56%, and 7% to the total flashes in the BMR, respectively. Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms, the lightning flash rate can be used as an indicator of severe weather events, such as hail and short-duration heavy rainfall. Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale, through adjusting or correcting the thermodynamic and microphysical parameters of the model.

A three-dimensional variational (3DVAR) lidar data assimilation method is developed based on the Community Radiative Transfer Model (CRTM) and Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. A 3DVAR data assimilation (DA) system using lidar extinction coefficient observation data is established, and variables from the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) mechanism of the WRF-Chem model are employed. Hourly lidar extinction coefficient data from 12:00 to 18:00 UTC on March 13, 2018 at four stations in Beijing are assimilated into the initial field of the WRF-Chem model; subsequently, a 24 h PM2.5 concentration forecast is made. Results indicate that assimilating lidar data can effectively improve the subsequent forecast. PM2.5 forecasts without using lidar DA are remarkably underestimated, particularly during heavy haze periods; in contrast, forecasts of PM2.5 concentrations with lidar DA are closer to observations, the model low bias is evidently reduced, and the vertical distribution of the PM2.5 concentration in Beijing is distinctly improved from the surface to 1200 m. Of the five aerosol species, improvements of NO3− are the most significant. The correlation coefficient between PM2.5 concentration forecasts with lidar DA and observations at 12 stations in Beijing is increased by 0.45, and the corresponding average RMSE is decreased by 25 μg·m−3, which respectively compared to those without DA.

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.

The performances of Beijing Lightning Network (BLNET) operated in Beijing-Tianjin-Hebei urban cluster area have been evaluated in terms of detection efficiency and relative location accuracy. A self-reference method has been used to show the detection efficiency of BLNET, for which fast antenna waveforms have been manually examined. Based on the fast antenna verification, the average detection efficiency of BLNET is 97.4% for intracloud (IC) flashes, 73.9% for cloud-to-ground (CG) flashes and 93.2% for the total flashes. Result suggests the CG detection of regional dense network is highly precise when the thunderstorm passes over the network; however it changes day to day when the thunderstorms are outside the network. Further, the CG stroke data from three different lightning location networks across Beijing are compared. The relative detection efficiency of World Wide Lightning Location Network (WWLLN) and Chinese Meteorology Administration - Lightning Detection Network (CMA-LDN, also known as ADTD) are approximately 12.4% (16.8%) and 36.5% (49.4%), respectively, comparing with fast antenna (BLNET). The location of BLNET is in middle, while WWLLN and CMA-LDN average locations are southeast and northwest, respectively. Finally, the IC pulses and CG return stroke pulses have been compared with the S-band Doppler radar. This type of study is useful to know the approximate situation in a region and improve the performance of lightning location networks in the absence of ground truth. Two lightning flashes occurred on tower in the coverage of BLNET show that the horizontal location error was 52.9 m and 250 m, respectively.

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.

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.

A three-dimensional variational (3DVAR) lidar data assimilation method is developed based on the Community Radiative Transfer Model (CRTM) and Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. A 3DVAR data assimilation (DA) system using lidar extinction coefficient observation data is established, and variables from the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) mechanism of the WRF-Chem model are employed. Hourly lidar extinction coefficient data from 12:00 to 18:00 UTC on March 13, 2018 at four stations in Beijing are assimilated into the initial field of the WRF-Chem model; subsequently, a 24 h PM

Beijing Lightning Network (BLNET), a regional multi-frequency-band lightning detection and location network, has been developed for both research and operational purposes. The network consisted of 15 stations in 2014, covering an area of about 100 km × 85 km in Beijing area. In this paper, we present the configuration of the network and the detailed description on the sensors for the first time. The Chan algorithm and Levenberg–Marquardt method are adopted jointly in the lightning location algorithm. The Monte Carlo simulation reveals that the horizontal and the vertical location errors within BLNET coverage are less than 300 m and 600 m, respectively. The comparison of total lightning location results with the corresponding radar reflectivity for a thunderstorm case indicates that BLNET has a good capability to track thunderstorms in the Beijing area. Besides, we examine the electric field waveforms of the preliminary breakdown process (PBP) of 111 − CG flashes, 92 + CG flashes, 22 normal-polarity IC flashes and 22 inverted-polarity IC flashes. Statistics on the time interval between the largest PBP pulse and the corresponding first RS pulse for CG flash ( PB–RS interval), the ratio of the largest PBP pulse to the corresponding first RS pulse for CG flash ( PB / RS ratio), the pulse width for individual pulse in the PBP train ( T w ) and the time interval between successive pulses in the PBP train ( T i ) are presented. The 3D location result shows that the PBP of a − CG flash initiates at an altitude of ~ 6 km and propagates downward to ~ 3 km with a vertical speed of 5.9 × 10 5 m/s. The initial 10 ms of an IC flash is found to start at ~ 7.2 km and develop upward to ~ 10 km. The vertical propagation speed is estimated to be 4.8 × 10 5 m/s during the first 6 ms. A PBP with relatively clear branched 3D structure is presented and discussed in the end of the paper. The average 3D propagation speed of two branches is estimated to be 2.1 × 10 6 m/s and 2.6 × 10 6 m/s, respectively.

Two intense quasi-linear mesoscale convective systems (QLMCSs) in northern China were simulated using the WRF (Weather Research and Forecasting) model and the 3D-Var (three-dimensional variational) analysis system of the ARPS (Advanced Regional Prediction System) model. A new method in which the lightning density is calculated using both the precipitation and non-precipitation ice mass was developed to reveal the relationship between the lightning activities and QLMCS structures. Results indicate that, compared with calculating the results using two previous methods, the lightning density calculated using the new method presented in this study is in better accordance with observations. Based on the calculated lightning densities using the new method, it was found that most lightning activity was initiated on the right side and at the front of the QLMCSs, where the surface wind field converged intensely. The CAPE was much stronger ahead of the southeastward progressing QLMCS than to the back it, and their lightning events mainly occurred in regions with a large gradient of CAPE. Comparisons between lightning and non-lightning regions indicated that lightning regions featured more intense ascending motion than non-lightning regions; the vertical ranges of maximum reflectivity between lightning and non-lightning regions were very different; and the ice mixing ratio featured no significant differences between the lightning and non-lightning regions.

Using 1 km satellite remote sensing observations, this paper examines the clouds, aerosols, water vapor and surface skin temperature over Beijing to understand the possible urban system contributions to the extreme rainfall event on 21 July 2012 (i.e., 721 event). Remote sensing measurements, with the advantage of high spatial resolution and coverage, reveal three key urban-related mechanisms: (a) the urban heat island effect (UHI) resulted in strong surface convection and high level cloud cover over Beijing, (b) urban aerosol amount peaked before the rainfall, which “seeded” the clouds and invigorated precipitation, and (c) urban tall buildings provided additional lift for the air mass and provided heat at the underlying boundary to keep the rainfall system alive for a long duration precipitation (&gt, 10 hours). With the existing rainfall system moving from the northwest and abundant water vapor was transported from the southeast into Beijing, the urban canyon-lifting, aerosol, and UHI effects all enhanced this extreme rainfall event. This work proves that urban system is responsible, at least partly, for urban rainfall extremes and thus should be considered for urban extreme rainfall prediction in the future.

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.