The Introduction and Application of Severe Weather Monitoring Analysis Nowcasting Forecasting Warning Platform

The Severe Weather Monitoring Analysis Nowcasting Forecasting Warning Platform, which core database from 13 Doppler radars  distributed in the northwestern region of China, automatic rain gauge, satellite images, important weather message, TITAN, the high-resolution numerical forecast products of T639, the Wind Profiler data, and so on. The platform combined with geographic information system(GIS) can monitoring, analyze and alarm  severe convective weather and geological disasters automatically. At the same time, it display the monitoring, early warning, short-term forecast and Nowcasting data by the clear and concise graph.

The platform integrates forecast、early warning and monitoring of strong convective weather as an organic whole. It is a integrated application platform with intensive and refinement highly. Radar monitoring and fine near TITAN forecast to village, short-term forecast precision to town; The platform can take advantage of sounding data on 08h to calculate the sounding data that within 100 kilometers from near the county (district) on 14h, which make up the lack of time and space distribution of sounding data.

There were 73 times strong convective weather process  in Gansu  from 2011-2016,the platform provided a reliable support for meteorological offices and stations that strong convective forecasting warning products provides, reduced the major property loss and casualties. Such as,"7.25" tianshui catastrophic mudslide disaster in 2013, with the help of monitoring alarm and forecast results of short-term、 nowcasting, early warning products and fine service for the local government in fighting and transfer population (5000 people) provided a reliable reference. In a large hail weather in June 13,2016 , depending on the platform near the short-term forecast, we had issue warning signal early and organizate to carry out the artificial hail suppression work in time, relied to minimized the losses of hail disaster.