Analysis And Research Of Severe Convective Weather Based On Meteorological Information Network

Severe convective weather forecast is one of difficult points for meteorological support.It is very difficult to well predict the severe convective weather,such as short-time heavy rainfall,thunderstorm,gale and hail.In the precedingflood period in Southern China,severe convective weather and heavy rainfalls often cause serious disasters in Guangdong Province.Therefore,how to improve the support capability of severe convective weather forecast in rainy seasons is the focus of meteorological researchers.Severe convective weather forecast is highly dependent on the information network.It is necessary to build an intensive and efficient,stable and reliable meteorological information network system with reasonable structure and advanced technology,as a cloud computing platform to apply meteorological data.Based on the now available meteorological service system,a fixed and a mobile meteorological information networks are built.By integrating observation system,receiving information system,weather radar,weather forecast and meteorological service system,an intensive and efficient forecast support platform which can receive,transfer and processing data is built.The test results show that the meteorological support information network can well transfer,store and process multi-source meteorological data.By classifying and storing various meteorological data,sharing network data,the multi-source meteorological data,especially the severe convective parameter data are analyzed using artificial intelligence and artificial analysis method.It is shown that the system is reasonable and reliable.It greatly improves the application ability of multi-source meteorological data analysis.By use of the meteorological information network data,the climate characteristics in the precedingflood period in Southern China from 1951 to 2015 were analyzed.The results show that there is a typical characteristic of severe convective weather and more regular precipitation in this period.The severe convective weather is mainly affected by fronts,shear lines(vortices)and troughs(southern branch trough),etc.Severe convective weather is mainly affected by the surface front system from February to May,with the proportion about 87%.By using network multi-source data,the large-scale patterns,sounding maps,instability energy,numerical forecast products,satellite and Doppler radar images are analyzed during the severe convective weather process in Guangdong Province in March 26,2013.The test results show that the meteorological information network is stable and reliable.The system can be used as a meteorological big data cloud computing platform.By statistical analyzing several cases in the precedingflood period in Southern China,and severe convective weather forcast cases in recent years,conceptual models of severe convective weather,namely ‘front type severe convection model' and ‘trough type convection model' are summarized.By use of severe convective parameters and indices,servere convective weather analysis model and forecast model are advanced,and the forecast comparison standard and forecast index of severe convective weather are determined.The above analysis model and forecast model are used to forecast severe convective weather in the flood seasons of 2017.Three typical severe convective weather processes,namely ‘4·21 strong convective thunderstorm and hail',‘5·7·8 short-time heavy rainfall',and ‘6·4 heavy rainfall in Shaoguan' are comparative analyzed.The results test the forecast effects of severe convective weather model and the reliability of comparison standard,providing a reference for the severe convective weather forecast.