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Design and Implementation of Meteorological Disaster Risk Management System
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摘要: 为满足我国气象灾害风险管理业务体系建立和发展的需求，有效支撑防灾减灾决策服务，设计并建设了气象灾害风险管理系统。该系统包括大数据应用、模型算法、在线分析与产品制作、综合运维等分系统，面向暴雨、台风、干旱、高温、低温等主要气象灾害，覆盖气象灾害风险管理业务的主要环节，实现灾害监测识别、影响评估、风险评估、风险预估和风险区划等功能。系统探索应用时空匹配的大数据融合、Web-GIS、空间数据分布式存储、微服务和多租户等技术。目前，系统可实现实时发布灾情监测、灾害事件识别、影响评估、风险评估、风险预估、风险区划等多类业务产品。在国家级气象业务部门的应用显示，该系统具有良好的业务能力与发展前景，有助于推进客观化、定量化、精细化气象灾害风险管理业务发展，提升防灾减灾决策服务能力。Abstract: China is one of the countries with the most serious meteorological disasters in the world. Reducing disaster losses and mitigating disaster risks is important for improving social governance and enhancing people's welfare, and it is also the fundamental goal of meteorological services. As a non-engineering measure for disaster prevention and mitigation, Meteorological Disaster Risk Management System (MDRMS) provides users with reference for decision making and is one of the most effective tools for mitigating meteorological disaster risks. In order to effectively reduce the risk of meteorological disasters and meet the urgent needs of service, China National Climate Center has designed and built MDRMS. MDRMS provides decision-makers and other stakeholders with professional services with four sub-systems:Big data application sub-system, model algorithm sub-system, online analysis sub-system, and comprehensive operation sub-system.From the view of application and function, MDRMS realizes the functions of disaster monitoring and identification, disaster impact assessment, risk assessment, risk prediction, risk zoning, and disaster information services for major meteorological disasters such as rainstorm, typhoon, drought, high temperature and low temperature. A series of products are also established.From the view of design and construction, the key technologies adopted are generic and the operation is intuitive and friendly. The system is built with key technologies such as big data fusion based on spatial-temporal matching, Web-GIS, distributed spatial data storage, micro service, and multi-tenant. The application of new technologies significantly improves the access efficiency and application capability of the system to multi-source, heterogeneous and massive data related to meteorology disaster risk management and enhances the user experience.From the view of deployment and openness, MDRMS has better integration, openness and scalability. It is deployed in China Meteorological Administration, ensuring access, personalized configuration, and service customization for internal users at four levels:National, provincial, municipal, and county levels, as well as access for external users at some product levels.The implementation of MDRMS shows that it has good operational capability and development prospect, which promotes the objective development of meteorological disaster risk management operation and enhances disaster prevention and mitigation decision-making service capability. In the future, the system will be improved following the principle of intensification, integration, and objectification. It will be integrated with the meteorological big data cloud platform in terms of data environment, product interfaces and algorithm functions, and provincial versions and mobile versions will be vigorously developed, focusing on creating an application ecosystem for MDRMS, providing richer and more practical meteorological disaster risk management products for users at all levels, and further playing an important role of information technology in meteorological disaster risk management.
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图 3 2021年1月低温灾害事件直接经济损失分布
Fig. 3 Direct economic losses from low temperature disaster events in Jan 2021
图 4 2020年6月27日—7月12日暴雨事件的累积降水量分布
Fig. 4 Total precipitation in rainstorm event from 27 Jun to 12 Jul in 2020
图 5 2021年3月24日—4月19日气象干旱面积逐日变化(a)和2021年4月4日气象干旱分布(b)
Fig. 5 Daily variation of meteorological drought area from 24 Mar to 19 Apr in 2021(a) and distribution of meteorological drought on 4 Apr 2021(b)
图 6 1961—2021年全国单次区域性高温事件的最大影响气象站数历年变化
Fig. 6 Maximum number of meteorological stations affected by single regional high temperature event over China from 1961 to 2021
图 7 2020年9月2日起报的台风美莎克(2009)未来24 h风险预估分布
Fig. 7 Risk prediction of Typhoon Maysak(2009) in 24 h forecasted on 2 Sep 2020
图 8 我国东部地区城市内涝风险区划
Fig. 8 Risk zoning of waterlogging risk of county-level cities in the eastern China
表 1 数据类别表
Table 1 Data types
数据类别 主要数据和产品集 致灾因子 站点观测、数值模式、台风路径和登陆信息等 承灾体 人口、社会经济、兴趣点等 孕灾环境 地形、土地利用、植被类型、河流分布、城市排水管网密度、城市绿地率等 灾害影响 灾情直报、省级灾情、县级灾情、重大灾害事件等 灾害事件 暴雨事件、干旱事件、低温事件、高温事件、台风等 风险评估 暴雨风险评估、干旱风险评估、低温风险评估、高温风险评估、台风风险评估、城市内涝风险评估等 风险预估 暴雨风险预估、干旱风险预估、低温风险预估、高温风险预估、台风风险预估等 风险区划 暴雨风险区划、干旱风险区划、低温风险区划、高温风险区划、台风风险区划等 风险普查 隐患点、预警点、致灾阈值、脆弱性曲线、中小河流洪水风险区划、山洪风险区划、城市内涝风险区划、风暴潮风险区划等 行业评估 农业、交通、环境、水资源等 评估指标 灾体量指数、气候指数、台风能量指数等 行业信息 农业、环境、水文水利等 基础信息 行政区划、气象站、水文站、水库、水资源分区、中小河流流域分区、山洪沟分区等 
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