Meteorology Open Application Platform (MOAP3.0) -- the Application and Implementation of Brand-new Intelligent Analysis Meteorological Platform

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;The implementation of Intellectualized&amp;amp;#160;Analysis Meteorological Platform is&amp;amp;#160;based&amp;amp;#160;on the Meteorology Open Application Platform (MOAP3.0),which developed by the National Meteorological Centre of China Meteorological Administration. This visualization&amp;amp;#160;analysis network platform integrates the main&amp;amp;#160;characteristics of statistical analysis, intelligent interaction, and rendering&amp;amp;#160;method and uses decoupling development mode. Its Web-Server deployed on distributed cloud framework in&amp;amp;#160;a&amp;amp;#160;distributed&amp;amp;#160;environment, which can support real-time analysis, interactive&amp;amp;#160;analysis and visualization analysis of massive meteorological data. The data are including national&amp;amp;#160;meteorological&amp;amp;#160;observation&amp;amp;#160;data, national guidance forecast data (0.05&amp;amp;#176; x 0.05&amp;amp;#176;), the area of forecast, MICAPS data, etc. It has been put into operation since December 2019. According to the results of continual&amp;amp;#160;tests,&amp;amp;#160;it&amp;amp;#160;indicates&amp;amp;#160;that&amp;amp;#160;the&amp;amp;#160;entire&amp;amp;#160;system&amp;amp;#160;is quite stable,&amp;amp;#160;reliable, with second-grade responding&amp;amp;#160;time in data&amp;amp;#160;transmission. The whole system adopts the design of &amp;quot;one key linkage&amp;quot; and &amp;quot; drilling-down analysis&amp;amp;#160;of a&amp;amp;#160;temporal&amp;amp;#160;and&amp;amp;#160;spatial&amp;amp;#160;context step by step &amp;quot; , finalizes three main home pages of &amp;quot;disaster analysis&amp;quot;, &amp;quot;meteorological big data for living analysis&amp;quot; and &amp;quot;station&amp;amp;#8217;s climate background analysis&amp;quot;, involves in 36 standard&amp;amp;#160;interfaces ,and sets up 21 independent functional modules. In the spatial dimension, the cascading of six spatial levels of meteorological data is followed&amp;amp;#160;by observing&amp;amp;#160;data, grid data, urban, river basins, regional meteorological centers and national meteorological centers. In the time dimension, the linkage analysis of minute, hour, daily, ten-day periods, monthly value, and annual value completes the full time chain. Theoretically, the integration analysis of history- reality- forecast in China is realized basing on the whole station climate background and a relatively well-developed analysis system of meteorological spatial-temporal data mining. To be specific, the basic meteorological algorithms including in the background of the system are regional average value, precipitation days of different magnitude, historical extremes of single meteorological element, spatial interpolation, fall area analysis, etc. The web-visualization functions contain the online rendering of weather map, spatial-temporal integration display of multiple meteorological elements, color scale classification and filtering, etc. At the same time, in order to solve the problems of dense site in daily&amp;amp;#160;operation, the strategies of site thinning and hierarchical rendering are used to optimize. In&amp;amp;#160;conclusion, the whole system takes the standardized tile-type electronic map in China as the carrier, displays and interacts the massive meteorological data of various dimensions and types, and finally carries out a complete real-time sequence analysis product, which will be playing an important role in the practical application of forecasting and early warning system of Chinese meteorological fields.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;