| 基于MICAPS4的智能网格预报平台设计与实现 |
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| 引用本文： | 贺雅楠,高嵩,薛峰,赵声蓉,刘铭,胡皓,魏涛.基于MICAPS4的智能网格预报平台设计与实现[J].应用气象学报,2018,29(1):13-24. |
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| 作者姓名： | 贺雅楠 高嵩 薛峰 赵声蓉 刘铭 胡皓 魏涛 |
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| 作者单位： | 1.国家气象中心, 北京 100081 |
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| 基金项目： | 中国气象局“2015年山洪地质灾害防治气象保障工程建设” |
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| 摘 要： | 随着我国智能网格预报业务的开展，海量高分辨率客观数据需要便捷的分析显示及产品制作平台高效处理。该文基于MICAPS4（Meteorological Information Comprehensive Analysis and Processing System Version 4.0，人机交互气象信息处理和天气预报制作系统）设计并实现智能网格预报平台，采用MVVM（模型-视图-视图模型，model-view-viewmodel）设计模式，实现业务逻辑与视图的分离，通过对各子功能模块的划分，降低模块之间的耦合度，具有良好的可扩展性。平台实现了高分辨率网格预报数据的显示分析和产品输出，开发了基于等值线、网格、关键点等智能化预报制作工具，集成了降水时间拆分、温度极值订正等客观预报方法，开发了降水、温度、相对湿度等要素一致性处理方法，可有效帮助预报员提高工作效率，同时能够确保产品之间的一致性。平台继承MICAPS4的微内核组件服务、高性能渲染引擎和开放式插件扩展管理等优良特性，实现面向智能网格预报的业务编排、智能编辑和算法集成。目前，该平台已经实现业务应用，为全国智能网格预报业务提供重要支撑。
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| 关 键 词： | 智能网格预报 格点编辑 要素一致性 MICAPS4 |
| 收稿时间： | 2017/7/25 0:00:00 |
| 修稿时间： | 2017/12/1 0:00:00 |
Design and Implementation of Intelligent Grid Forecasting Platform Based on MICAPS4 |
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| He Yanan,Gao Song,Xue Feng,Zhao Shengrong,Liu Ming,Hu Hao and Wei Tao.Design and Implementation of Intelligent Grid Forecasting Platform Based on MICAPS4[J].Quarterly Journal of Applied Meteorology,2018,29(1):13-24. |
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| Authors: | He Yanan Gao Song Xue Feng Zhao Shengrong Liu Ming Hu Hao and Wei Tao |
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| Institution: | 1.National Meteorological Center, Beijing 1000812.Fujian Meteorological Observatory, Fuzhou 3500023.Shaanxi Meteorological Observatory, Xi'an 7100144.Guizhou Meteorological Observatory, Guiyang 550002 |
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| Abstract: | 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. |
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| Keywords: | intelligent grid forecast grid editing element consistency MICAPS4 |
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