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Organizational Modes and Environmental Conditions of the Severe Convective Weathers Produced by the Mesoscale Convective Systems in South China
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作者 张元春 鲁蓉 +1 位作者 孙建华 杨新林 《Journal of Tropical Meteorology》 SCIE 2023年第1期26-38,共13页
Composite radar reflectivity data during April-September 2011-2015 are used to investigate and classify storms in south China(18-27°N;105-120°E). The storms appear most frequently in May. They are either lin... Composite radar reflectivity data during April-September 2011-2015 are used to investigate and classify storms in south China(18-27°N;105-120°E). The storms appear most frequently in May. They are either linear;cellular or nonlinear systems, taking up 29.45%, 24.51% and 46.04%, respectively, in terms of morphology. Linear systems are subdivided into six morphologies: trailing stratiform precipitation(TS), bow echoes(BE), leading stratiform precipitation(LS), embedded line(EL), no stratiform precipitation(NS) and parallel stratiform precipitation(PS). The TS and NS modes have the highest frequencies but there are only small samples of LS(0.61%) and PS(0.79%) modes.Severe convective wind(≥17m s-1at surface level) accounts for the highest percentage(35%) of severe convective weather events produced by cellular systems including individual cells(IC) and clusters of cells(CC). Short-duration heavy rainfall(≥50 mm h-1) and severe convective wind are the most common severe weather associated with TS and BE modes. Comparison of environmental physical parameters shows that cellular convection systems tend to occur in the environment with favorable thermal condition, substantial unstable energy and low precipitable water from the surface to300 hPa(PWAT). However, the environmental conditions favoring the initiation of linear systems feature strong vertical wind shear, high PWAT, and intense convective inhibition. The environmental parameters favoring the initiation of nonlinear systems are between those of the other two types of morphology. 展开更多
关键词 storms composite reflectivity MORPHOLOGY severe convective weather environmental physical parameter
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Hazard Analysis of Severe Convective Weather in Guangdong Province, China
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作者 庞古乾 何健 +3 位作者 刘畅 张柳红 刘运策 刘蔚琴 《Journal of Tropical Meteorology》 SCIE 2021年第2期169-176,共8页
In the present study,a hazard model of severe convective weather was constructed on the basis of meteorological observational data obtained in Guangdong Province between 2003 and 2015.In the analysis,quality control w... In the present study,a hazard model of severe convective weather was constructed on the basis of meteorological observational data obtained in Guangdong Province between 2003 and 2015.In the analysis,quality control was first conducted on the severe convective weather data,and the kriging method was then used to interpolate each hazard-formative factor.The weights of which were determined by applying the coefficient of variation method.The results were used to establish the hazard-formative factor model of severe convective weather.The cities showing the greatest hazards for severe convective weather in Guangdong Province include Yangjiang,Dongguan,Foshan,Huizhou,Jiangmen,and Qingyuan. 展开更多
关键词 severe convective weather quality control WEIGHT hazard-formative factor HAZARD
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Analysis on a Severe Convective Weather Process of Guangxi in 2018
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作者 Juan WANG Chao YIN Xianghong LI 《Meteorological and Environmental Research》 CAS 2020年第3期7-11,共5页
Based on conventional meteorological observation data and Doppler radar data,the occurrence and development mechanism of mixed severe convective weather and evolution of convective storm in Guangxi on March 4,2018 wer... Based on conventional meteorological observation data and Doppler radar data,the occurrence and development mechanism of mixed severe convective weather and evolution of convective storm in Guangxi on March 4,2018 were analyzed. The results showed that the dry line was the main trigger mechanism of this severe convective weather. Instable convection stratification of cold advection at middle layer and warm advection at low layer and abundant water vapor from low-level jet provided favorable stratification and water vapor conditions for the occurrence and development of severe convection. Cold trough at middle layer,low pressure and strong vertical wind shear at middle and lower layers may be main factors for the development and maintenance of strong storm system. Squall line developed along ground convergence line,and there was bow echo on reflectivity factor chart. Moving velocity of convective system was quick,and there was gale core and velocity ambiguity on velocity map. 展开更多
关键词 Short-term heavy rainfall Thunderstorm gale HAIL severe convective weather
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Classified Early Warning and Forecast of Severe Convective Weather Based on LightGBM Algorithm
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作者 Xinwei Liu Haixia Duan +2 位作者 Wubin Huang Runxia Guo Bolong Duan 《Atmospheric and Climate Sciences》 2021年第2期284-301,共18页
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 boos... 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 (</span><i><span style="font-family:Verdana;">i.e.</span></i><span style="font-family:Verdana;">, 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. 展开更多
关键词 severe Convective weather Machine Learning LightGBM Early Warning and Forecast
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Problems and Opportunities for Biometeorological Assessment of Conditions in Cold Season
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作者 Elena S.Andreeva Sergey S.Andreev 《Journal of Atmospheric Science Research》 2023年第4期77-85,共9页
The article is devoted to a discussion of the possibilities of biometeorological assessment of the severity of weather conditions during the cold season.The relevance of the study is ensured not only by the fact that ... The article is devoted to a discussion of the possibilities of biometeorological assessment of the severity of weather conditions during the cold season.The relevance of the study is ensured not only by the fact that residents of a number of states,whose total number is more than 27 million people,live in these extreme climatic conditions,but also by the need to improve biometeorological approaches to assessing the impact of these conditions on the body and health of the population.This study examined biometeorological characteristics that illustrate a measure of cold stress.These include the Siple wind-chill index;Bodman winter severity index;Arnoldi weather hardness coefficient;Mountain wind chill index;weather hardness coefficient according to I.M.Osokin.The results of a comparison of winter severity assessments based on the values of the calculated Siple and Bodman indices made it possible to establish that the Bodman index is more acceptable when assessing mildly severe winters.The most adequate for assessing the“severity”of the cold period against the background of a decrease in air temperature and an increase in wind speed is the Siple index.The need to provide the countries of the world with high-quality hydrometeorological and biometeorological forecast information is justified and relevant.In this regard,these studies are very promising. 展开更多
关键词 Biometeorological indices severe weather Cold period of the year “rigidity”of weather conditions Cold stress Biometeorological assessment
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A Brief Discussion on the High-impact Cold-season Tornado Outbreak During 10-11 December 2021 in the United States
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作者 李彩玲 白兰强 +5 位作者 俞小鼎 谭浩波 黄先香 炎利军 李兆明 张泽宇 《Journal of Tropical Meteorology》 SCIE 2022年第2期252-260,共9页
An outbreak of powerful tornadoes tore through multiple states in the central and southern United States from 10 to 11 December 2021.It is claimed the deadliest tornado outbreak that has taken place on December days.T... An outbreak of powerful tornadoes tore through multiple states in the central and southern United States from 10 to 11 December 2021.It is claimed the deadliest tornado outbreak that has taken place on December days.The National Oceanic and Atmospheric Administration had confirmed 66 tornadoes as of 21 December,producing at least 90 fatalities.Most tornadoes occurred at night and thus they were difficult to be visually located,which directly increases the risk for local residents.Two violent nighttime tornadoes were rated category 4 on the enhanced Fujita scale(EF4).Although a high death toll was caused during this event,the operational service actually presented an excellent performance.This tornado outbreak has aroused extensive discussion from both the public and the research community in China.This paper presents a brief discussion on the formation environment and warning services of the tornado outbreak.Recall the deadliest violent tornado in the past 45 years in China,the radar-based tornadic vortex signatures at the locations with EF4 damages show a comparable strength with those in the current cases.Some views on the tornado warning issuance and receiving and damage surveys in China are also presented. 展开更多
关键词 TORNADO tornado outbreak severe weather cold season warning service
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Progress in Severe Convective Weather Forecasting in China since the 1950s 被引量:3
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作者 Xiaoling ZHANG Jianhua SUN +5 位作者 Yongguang ZHENG Yuanchun ZHANG Ruoyun MA Xinlin YANG Kanghui ZHOU Xuqing HAN 《Journal of Meteorological Research》 SCIE CSCD 2020年第4期699-719,共21页
Located in the Asian monsoon region, China frequently experiences severe convective weather(SCW), such as short-duration heavy rainfall(SDHR), thunderstorm high winds, hails, and occasional tornadoes. Progress in SCW ... Located in the Asian monsoon region, China frequently experiences severe convective weather(SCW), such as short-duration heavy rainfall(SDHR), thunderstorm high winds, hails, and occasional tornadoes. Progress in SCW forecasting in China is closely related to the construction and development of meteorological observation networks,especially weather radar and meteorological satellite networks. In the late 1950 s, some county-level meteorological bureaus began to conduct empirical hail forecasting based on observations of clouds and surface meteorological variables. It took over half a century to develop a modern comprehensive operational monitoring and warning system for SCW forecast nationwide since the setup of the first weather radar in 1959. The operational SCW forecasting, including real-time monitoring, warnings valid for tens of minutes, watches valid for several hours, and outlooks covering lead times of up to three days, was established in 2009. Operational monitoring and forecasting of thunderstorms,SDHR, thunderstorm high winds, and hails have been carried out. The performance of operational SCW forecasting will be continually improved in the future with the development of convection-resolving numerical models(CRNMs), the upgrade of weather radar networks, the launch of new-generation meteorological satellites, better understanding of meso-γ and microscale SCW systems, and further application of artificial intelligence technology and CRNM predictions. 展开更多
关键词 severe convective weather(SCW) forecasting RADAR meteorological satellite artificial intelligence convection-resolving numerical model(CRNM)
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