Design and Implementation of Intelligent Grid Forecasting Platform Based on MICAPS4

With the rapid development of modern weather prediction in China, large amounts of high-resolution data are widely used. An efficient and convenient platform for data displaying, analyzing and forecasting is urgently needed. In response to the requirement of business, an intelligent grid forecasting platform is designed and implemented based on MICAPS4 (Meteorological Information Comprehensive Analysis Processing System Version 4), which is used by the provincial meteorological departments to produce and distribute meteorological grid forecasting products. The application background, requirement analysis, framework design and main functions implementation are discussed in details. In addition, some key technologies involved in the platform realization are also described.The MVVM (model-view-viewmodel) design mode is adopted in the platform to separate the business logic from the view. And the coupling degree between modules is reduced by dividing each sub-function module, which has good scalability. The supporting data environment of the platform mainly includes meteorological service network/Internet, CIMISS (China Integrated Meteorological Information Service System), as well as other local data sources. The display and analysis program of high-resolution grid forecast data is realized, which includes 17 weather elements such as precipitation, temperature, wind, relative humidity, cloud cover and disastrous weather. And several intelligent forecasting tools based on contours, grids and key points are developed, which integrates objective forecast methods such as the precipitation time consistency algorithm and the correction of timing temperature using 24 h high and low temperature extreme value. Some element consistency algorithms are developed, such as precipitation, temperature, humidity and so on, which helps forecasters to improve work efficiency and ensure consistency among products. A graphical configuration management interface is provided, which facilitates user localization application.Since July 2016, the platform has been put into operation in most of the provincial meteorological departments in China, which provides an important support for the national intelligent grid forecasting business. Ever since, the platform is further improved by adding new functions and fixing bugs based on user feedbacks.In the future, intelligent multi-source objective prediction products recommending module will be developed, which is based on machine learning, inspection and evaluation and other technical methods. An intelligent collaborative engine of elements will be designed and realized in order to achieve more diverse forecast products. And some of the classic objective methods in weather forecasting will be integrated into the platform. On this basis, the visual modeling tool will be developed, which provides a graphical modeling approach to model forecasting experience, so that experience and intelligent methods of forecasters can achieve a better combination.