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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.

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

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.

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.

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.

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.

The variation of air temperature measurement errors using two different radiation shields (DTR502B Vaisala, Finland, and HYTFZ01, Huayun Tongda Satcom, China) was studied. Datasets were collected in the field at the Daxing weather station in Beijing from June 2011 to May 2012. Most air temperature values obtained with these two commonly used radiation shields were lower than the reference records obtained with the new Fiber Reinforced Polymers (FRP) Stevenson screen. In most cases, the air temperature errors when using the two devices were smaller on overcast and rainy days than on sunny days; and smaller when using the imported rather than the Chinese shield. The measured errors changed sharply at sunrise and sunset, and reached maxima at noon. Their diurnal variation characteristics were, naturally, related to changes in solar radiation. The relationships between the record errors, global radiation, and wind speed were nonlinear. An improved correction method was proposed based on the approach described by Nakamura and Mahrt (2005) (NM05), in which the impact of the solar zenith angle (SZA) on the temperature error is considered and extreme errors due to changes in SZA can be corrected effectively. Measurement errors were reduced significantly after correction by either method for both shields. The error reduction rate using the improved correction method for the Chinese and imported shields were 3.3% and 40.4% higher than those using the NM05 method, respectively.

The Nested Air Quality Prediction Model System (NAQPMS) was used to investigate the temporal and spatial variations of PM 2.5 over tropospheric central eastern China in January 2013. The impact of regional transport and its implications on pollution prevention and control were also examined. Comparison between simulated and observed PM 2.5 showed NAQPMS was able to reproduce the evolution of PM 2.5 during heavy haze episodes. The results indicated that regional transport of PM 2.5 played an important role in regional haze episodes in the city cluster including Hebei, Beijing and Tianjin (HBT). The cross-city clusters transport outside HBT and transport among cities inside HBT contributed 20%-35% and 26%-35% of PM 2.5 as compared with local emission, in HBT respectively. To meet the Air Quality Standards for Grade Ⅱ, 90%, 90% and 65% of emissions would have to be cut down in Hebei, Tianjin and Beijing, if non-control strategy was taken in the surrounding city clusters of HBT. This implicated that control of emissions in one city cluster is not sufficient to reduce regional haze events, and joint efforts among city clusters are essential. Besides regional transports, two-way feedback between boundary-layer evolution and PM 2.5 also significantly contributed to the formation of heavy hazes, which contributed 30% of monthly average PM 2.5 concentration in HBT.

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.