Analysis on Three-dimensional Structure and Echo Characteristic Quantity of a Supercell Storm

[Objective] The research aimed to study three-dimensional structure and echo characteristic quantity of a supercell storm in central Gansu on May 30,2005.[Method] By monitoring data of Lanzhou CINRAD/CC Doppler radar,the three-dimensional structure characteristics of a rare supercell storm which happened in central Gansu on May 30,2005 were analyzed.We tried to reveal three-dimensional structure and echo characteristic index of supercell storm in the northeast of Qinghai-Tibet Plateau,and find reason of rare heavy hail appearance.[Result] The large-scale strong storm was formed by the common effect of Mongolia cold vortex,low-level jet and ground cold front.When the development of main echo was mature,on reflectivity factor map,it presented obvious inverted 'V' shaped structure in left front of low-level storm,typical hooked and 'person'-type echo characteristics in the right rear.The bounded weak echo zone(vault) in low level corresponded with strong echo overhanging body in high level.It surpassed 60 dBz in the strong reflectivity factor zone.It presented one weak meso-cyclone on corresponding radial velocity map.The jumped increase characteristic of VIL could be as one of indices for judging that hail started to grow.Almost all storms(VILD ≥4.0 g/m3) had more obvious indication significance than VIL for judging heavy hail(diameter ≥20 mm).[Conclusion] The research provided reference for nowcasting of strong convection weather and artificial hail suppression.

Diurnal Variation Characteristics of Precipitation in the Shiyang River Basin of Northwest China in Summer

Based on the hourly precipitation data from 32 regional meteorological stations and 5 automatic meteorological stations in summer (from June to August) over the Shiyanghe River basin from 2009 to 2013, we analyzed the diurnal variation characteristics of precipitation over the Shiyanghe River basin, by using four precipitation indices (hourly precipitation, hourly precipitation frequency, hourly precipitation intensity, and different duration precipitation). The results show that the spatial distribution of hourly precipitation, hourly precipitation frequency in summer declines from upstream to downstream over the Shiyanghe River basin because of geographical position, altitude, latitude and weather systems, and the spatial distribution of hourly intensity is complex. The precipitation, the precipitation frequency and the precipitation intensity over the Shiyanghe River basin present a diurnal pattern of double-peak distribution, with the peak periods at 01:00-09:00 and 14:00-23:00, strong precipitation present single-peak with the peak period at 14:00-23:00. Total precipitations and precipitation frequencies of 1 - 3 h short-time rainfall are more than long time rainfall continued more than 10 h over the Shiyanghe River Basin. The short-time rainfall continuing within 1 - 6 h often occurs from afternoon to evening, the long time rainfall continuing more than 6 h often occurs from evening to early morning or late afternoon to evening.

Classified Early Warning and Forecast of Severe Convective Weather Based on LightGBM Algorithm

Severe convective weather can lead to a variety of disasters, but they are still difficult to be pre-warned and forecasted in the meteorological operation. This study generates a model based on the light gradient boosting machine (LightGBM) algorithm using C-band radar echo products and ground observations, to identify and classify three major types of severe convective weather (i.e., hail, short-term heavy rain (STHR), convective gust (CG)). The model evaluations show the LightGBM model performs well in the training set (2011-2017) and the testing set (2018) with the overall false identification ratio (FIR) of only 4.9% and 7.0%, respectively. Furthermore, the average probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR) for the three types of severe convective weather in two sample sets are over 85%, 65% and lower than 30%, respectively. The LightGBM model and the storm cell identification and tracking (SCIT) product are then used to forecast the severe convective weather 15 - 60 minutes in advance. The average POD, CSI and FAR for the forecasts of the three types of severe convective weather are 57.4%, 54.7% and 38.4%, respectively, which are significantly higher than those of the manual work. Among the three types of severe convective weather, the STHR has the highest POD and CSI and the lowest FAR, while the skill scores for the hail and CG are similar. Therefore, the LightGBM model constructed in this paper is able to identify, classify and forecast the three major types of severe convective weather automatically with relatively high accuracy, and has a broad application prospect in the future automatic meteorological operation.

Precipitation seesaw phenomenon and its formation mechanism in the eastern and western parts of Northwest China during the flood season

Extending across three major plateaus,namely the Qinghai-Tibetan Plateau,the Inner Mongolia-Xinjiang Plateau and the Loess Plateau,Northwest China has the complex terrain and spatio-temporal climate variations,and is affected by the interactions among different circulation systems,such as the summer monsoon,the westerlies and the plateau monsoon.The understanding of the climate variability,as well as its characteristics and evolution mechanisms in this area has been limited so far.In this paper,the precipitation characteristics and mechanisms in the eastern and western parts of Northwest China during the flood season are compared and analyzed based on the data from 192 national meteorological observational sites in Northwest China in 1961-2016.The results show that,divided by the northern boundary of the East Asian summer monsoon,there are huge differences in the precipitation variation characteristics between the eastern and western parts.The inter-annual variations,interdecadal variations and total trends in the two parts all show a significant seesaw phenomenon.Moreover,it is found that the seesaw phenomenon of precipitation variation is closely related to the opposite variation between the East Asian summer monsoon index(MI)and the westerly circulation index(WI).In addition,the inverse variations on different time scales are only related to the contributions of precipitation at specific grades.Besides,in the two matching patterns of precipitation in the seesaw phenomenon,the middle and high latitudes are occupied by the"high-low-high"wave trains in the precipitation increases in the east of Northwest China(ENWC)and decreases in the west of Northwest China(WNWC)pattern,meaning precipitation increases in ENWC and decreases in WNWC.Whereas the opposite"low-high-low"wave trains at 500 hPa height are observed in the middle and high latitudes in the WH-EA pattern at 500 hPa height,meaning precipitation increases in WNWC and decreases in ENWC.Thus,the atmosphere circulation situation with two wave train types can support both the precipitation seesaw phenomenon and the opposite variation between MI and WI.Moreover,the seesaw phenomenon is shown to be related to the separate or joint effects of the South Asian High,ENSO and the plateau heating on the common but opposite effect on the summer monsoon and the westerlies,in which the South Asian High probably plays a more critical role.This study could deepen the scientific understanding of precipitation mechanisms and improve the weather forecast technology in Northwest China during the flood season.

Statistics of the Z–R Relationship for Strong Convective Weather over the Yangtze–Huaihe River Basin and Its Application to Radar Reflectivity Data Assimilation for a Heavy Rain Event

The relationship between the radar reflectivity factor （Z） and the rainfall rate （R） is recalculated based on radar ob- servations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze-Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z-R relationship is combined with an empirical qr-R relationship to obtain a new Z-qr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational （3DVar） data assimilation system of the Weather Research and Forecasting （WRF） model to im-prove the analysis and prediction of severe convective weather over the Yangtze--Huaihe River basin. The perform- ance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z-R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected refleetivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better per-forrnance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original re-flectivity operator. This suggests that the new statistical Z-R relationship is more suitable for predicting severe con- vective weather over the Yangtze-Huaihe River basin than the Z-R relationships currently in use.

A Case Study on the Rapid Rain-to-Snow Transition in Late Spring 2018 over Northern China:Effects of Return Flows and Topography

Phase changes in the precipitation processes of early winter and late spring in midlatitude regions represent challenges when forecasting the timing and magnitude of snowfall.On 4 April 2018,a heavy snow process occurred in Beijing and northwestern Hebei Province,becoming the most delayed occurrence of heavy spring snow ever recorded over Beijing in the last 30 years.This paper uses observational and numerical simulation data to investigate the causes for the rapid rain-to-snow(RRTS)phase transition during this process.The following results are obtained.(1)Return flows(RFs),an interesting type of easterly wind,including those at 1000,925,and 800 hPa,played an important role in this heavy snow process and presented a characteristic"sandwich"structure.The RFs,complex topography,and snow particles that dominated the clouds,were the three key factors for the RRTS transition.(2)The RRTS transition in the plains was directly related to the RF at 925 hPa,which brought about advective cooling initiated approximately 4-6 h before the onset of precipitation.Then,the RF played a role of diabatic cooling when snow particles began to fall at the onset of precipitation.(3)The RRTS transition in the northern part of the Taihang Mountains was closely related to the relatively high altitude that led to a lower surface temperature owing to the vertical temperature lapse rate.Both immediately before and after the onset of precipitation,the snow particles in clouds entrained the middle-level cold air downward,causing the melting layer(from surface to the 0℃-isotherm level)to become very thin;and thus the snow particles did not have adequate time to melt before falling to the ground.(4)The rapid RRTS over the Yanqing mountainous area in the northwest of Beijing could have involved all the three concurrent mechanisms:the advective cooling of RF,the melting cooling of cloud snow particles,and the high-altitude effect.Compared with that in the plain area with less urbanization the duration of the RRTS in the plain area with significant urbanization was extended by approximately 2 h.