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Implementation and Development Plan of MICAPS4
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摘要: 以精细化预报为标志的现代天气预报业务对高时空分辨率气象数据的应用提出了更高的需求，而传统的预报分析制作系统MICAPS3（Meteorological Information Comprehensive Analysis and Processing System Version 3）无法满足符合大数据特征的实时预报相关的数据应用。同时，模式预报和集合预报应用已在各专业预报领域中发挥越来越重要的作用，网格预报产品正在涵盖全部的预报业务流程，而MICAPS3无法提供便捷高效的支撑。为解决上述问题，国家气象中心启动了MICAPS4建设，一方面建立了基于大数据的气象实时预报应用技术体系，解决了气象大数据处理、存储、分析和显示效率的关键技术难题；另一方面搭建了多个满足不同复杂预报业务需求的专业化版本。MICAPS4将信息化技术与预报技术、预报业务流程紧密结合，解决了现代化预报方法的平台化集成应用与精细化预报制作的关键技术难题，基于MICAPS4基础框架的多个专业版在中央气象台和部分省级气象台进行业务化应用推广。基于CIMISS（China Integrated Meteorological Information Sharing System）-MICAPS4的海量数据存储环境，极大减轻了系统部署和本地化工作量，显著提升了数据解析及数据存储访问效率。
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关键词:
- 预报业务平台;
- MICAPS4;
- 精细化预报业务;
- CIMISS-MICAPS4海量数据存储
Abstract: Marked by refined weather forecasts, modern weather forecasting demands for higher spatial and temporal resolution of weather data applications. However, the existing forecast analysis system-MICAPS3 (Meteorological Information Comprehensive Analysis and Processing System Version 3) cannot meet needs of using real-time meteorological data with big data characteristics. Besides, MICAPS3 cannot provide sufficient support for numerical weather prediction model, ensemble prediction model and grid forecasting product, which are playing increasingly important role in the professional forecasting fields. Therefore, China National Meteorological Center launches development of MICAPS4, aiming to build an advanced, efficient, intelligent, convenient and open modern weather service forecast platform.Firstly, established a real-time forecasting system based on big data technology to solve the key technical problems of data processing, storage, analysis and display efficiency. Secondly, set up several specialized platforms to meet needs of different complex forecasting business. MICAPS4 combines information technology with forecasting technology and forecasting business processes to solve the key technical problems of the platform integration of modern forecasting methods and the production of refined forecast, many of specialized platforms based on MICAPS4 basic framework have promoted the application of business in China National Meteorological Center and many provinces. CIMISS (China Integrated Meteorological Information Sharing System)-MICAPS4 massive data storage environment has greatly reduced the workload of system deployment and localization, improved data analysis and data storage access efficiency significantly. Besides the utilization of the big data technology, MICAPS4 client is also upgraded in underlying rendering engine using parallel computing framework, and it can display high resolution data in high efficiency including the stream animation as a result. MICAPS4 client follows the OGC (open geospatial consortium) standards, to achieve the standard of geographic information and the intervention of WMTS (Web map tile service). The client of MICAPS4 allows users to customize data display style conveniently and support the forecast product rapid manufacturing. Flat design interface is adopted and users can switch between black theme and white theme quickly, to reduce visual fatigue and support the forecast product rapid manufacturing.MICAPS4 is a modern full-purpose forecaster work station system for processing and displaying meteorological data. The multi-window technology and specialized applications make MICAPS the ideal tool not only for operational weather forecasting, but also for other applications where meteorological information plays a vital role. -
图 6 MICAPS4客户端时间垂直剖面
Fig. 6 Time sequential-space vertical cross-section on MICAPS4 client
图 7 2017年4月15—17日过程降水分析
Fig. 7 Precipitation during 15-17 Apr 2017 analysed by MICAPS4
图 8 MICAPS4辅助强对流天气过程分析
(a)中气旋路径示意图，(b)自动气象站观测
Fig. 8 Strong convective case analysed by MICAPS4
(a)path diagram of mesocyclone, (b)automatic station observation
图 9 QPF主客观融合订正平台界面
(a)多模式选择界面，(b)模式融合后处理界面
Fig. 9 Platform interface of QPF subjective and objective fusion platform
(a)multi-model selection interface, (b)fusion postprocessing interface
表 1 常用气象预报数据的检索维度
Table 1 Data retrieval dimension of differnet forecast data
数据种类 检索要素 检索维度 确定性模式数据 模式名、物理量、层次、起报时间、预报时效 5 集合预报数据 模式名、成员编号、物理量、层次、起报时间、预报时效 6 地面填图 观测时间、观测方式(人工观测/自动观测) 2 高空填图 观测时间、层次、观测方式 3 卫星数据 卫星型号、通道、投影方式、观测时间 4 雷达数据 雷达名称、仰角、观测时间、产品名称 4 
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[1] 李月安, 曹莉, 高嵩, 等.MICAPS业务平台现状与发展.气象, 2010, 36(7):50-55. doi: 10.7519/j.issn.1000-0526.2010.07.010 [2] 于连庆, 胡争光.MICAPS中天气图交互制作子系统.应用气象学报, 2011, 22(3):375-384. doi: 10.11898/1001-7313.20110315 [3] 高嵩, 代刊, 薛峰.基于MICAPS3.2平台的格点编辑平台设计与开发.气象, 2014, 40(9):1152-1158. doi: 10.7519/j.issn.1000-0526.2014.09.013 [4] 吴林林, 刘黎平, 徐海军, 等.基于MICAPS3核心的人影业务平台设计与开发.气象, 2013, 39(3):383-388. doi: 10.7519/j.issn.1000-0526.2013.03.014 [5] 毕宝贵, 代刊, 王毅, 等.定量降水预报技术进展.应用气象学报, 2016, 27(5):534-549. doi: 10.11898/1001-7313.20160503 [6] 矫梅燕. 促进大数据融合应对信息技术挑战. [2016-11-22]. http://www.cma.gov.cn/2011xwzx/2011xqxxw/2011xqxyw/201611/t20161122_342473.html. [7] 代刊, 曹勇, 钱奇峰, 等.中短期数字化天气预报技术现状及趋势.气象, 2016, 42(12):1445-1455. doi: 10.7519/j.issn.1000-0526.2016.12.002 [8] 聂峰英.大数据资源技术服务协同研究——以气象数据为例.信息化研究, 2016, 42(1):6-11. http://www.cnki.com.cn/Article/CJFDTOTAL-DZGS201601002.htm [9] 朱小祥, 刘震坤, 罗兵, 等.美国AWIPSⅡ系统开发进展及业务应用.气象科技合作动态, 2014(增刊Ⅰ):1-30. http://www.cqvip.com/QK/85781X/2014F06/663951583.html [10] 姚学祥, 高嵩, 季崇萍, 等.中国气象局代表团访问德国气象局总结.气象科技合作动态, 2015(3):1-16. http://www.cqvip.com/QK/85781X/201503/667634360.html [11] 颜长建, 胡文东, 张春梅, 等.基于梯度的500 hPa槽线天气系统自动分析方法.应用气象学报, 2016, 27(6):741-749. doi: 10.11898/1001-7313.20160611 [12] 胡文东, 黄小玉, 赵光平, 等.高空基本影响天气系统定量化自动分析研究.气象, 2008, 34(6):107-111. doi: 10.7519/j.issn.1000-0526.2008.06.016 [13] 胡争光, 郑卫江, 高嵩, 等.气象GIS网络平台关键技术研究与实现.应用气象学报, 2014, 25(3):365-374. doi: 10.11898/1001-7313.20140314 [14] 熊安元, 赵芳, 王颖, 等.全国综合气象信息共享系统的设计与实现.应用气象学报, 2015, 26(4):500-512. doi: 10.11898/1001-7313.20150412 [15] 熊安元, 王伯民, 王颖, 等. 气象资料分类与编码. 中华人民共和国气象行业标准QX/T102-2009. 北京: 气象出版社, 2009. [16] 王遂缠, 吉惠敏, 孙林花.基于MICAPS系统的数字化天气图及常规气象资料检索分析系统.气象科技, 2004, 32(2):120-122. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200402011.htm [17] 宋桂英, 孙永刚, 胡英华, 等.MICAPS3.0的本地化和二次开发.内蒙古气象, 2013(3):25-27. http://www.cnki.com.cn/Article/CJFDTOTAL-NMQX201303011.htm [18] 唐圣钧, 王东海, 杜钧, 等.混合集合预报法在华南暴雨短期预报中的试验.应用气象学报, 2015, 26(6):669-679. doi: 10.11898/1001-7313.20150603 [19] 邓国, 龚建东, 邓莲堂, 等.国家级区域集合预报系统研发和新能检验.应用气象学报, 2010, 21(5):513-523. doi: 10.11898/1001-7313.20100501 [20] 张涵斌, 陈静, 智协飞, 等.GRAPES区域结合预报系统应用研究.气象, 2014, 40(9):1076-1087. doi: 10.7519/j.issn.1000-0526.2014.09.005 [21] 于连庆, 李月安, 高嵩, 等.集合预报产品综合分析显示平台关键技术与实现.应用气象学报, 2015, 26(3):369-377. doi: 10.11898/1001-7313.20150313 [22] 陈静, 陈德辉, 颜宏.集合数值预报发展与研究进展.应用气象学报, 2002, 13(4):497-507. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20020465&flag=1 [23] 黄向东, 王建民, 葛斯函, 等. 一种海量多维文件集合的存储模型//2014年中国数据库学术会议论文集. 2014: 1. [24] Sherif S, Liu A, Batista D M.A survey of large scaled at a management apporoaches in cloud environments.IEEE Communications Surveys Tutorials, 2011, 13(3):311-336. doi: 10.1109/SURV.2011.032211.00087 [25] 李永生, 曾沁, 徐美红, 等.基于Hadoop的数值预报产品服务平台设计与实现.应用气象学报, 2015, 26(1):122-128. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20150113&flag=1 [26] 王若曈, 黄向东, 张博, 等.海量气象数据实时解析与存储系统的设计与实现.计算机工程与科学, 2015, 37(11):2045-2053. doi: 10.3969/j.issn.1007-130X.2015.11.009 [27] 冯新扬, 范颖, 崔凯, 等.利用设计模式改进分层架构.计算机工程与设计, 2007, 28(15):3686-3689. doi: 10.3969/j.issn.1000-7024.2007.15.047 [28] 章国材.气象云建设的研究与思考.气象与环境科学, 2015, 38(4):1-11. http://www.cnki.com.cn/Article/CJFDTOTAL-HNQX201504001.htm -
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