基于WebGIS的实况网格产品应用分析平台及关键技术

实况网格产品是智能网格预报业务重要数据源。为满足气象业务及气象服务对实况网格产品的服务需求,在实时收集和处理各种实况网格产品基础上,采用JavaScript、HTML、CSS等web技术,构建了基于WebGIS的实况网格产品应用分析平台。采用Leaflet、Canvas等技术搭建了基于HTML5的WebGIS框架,实现了各种实况网格产品叠加地理信息统一展示。通过格点与站点观测数据的对比分析,提供产品的实时数据质量评估分析。基于网格格点,实现任意区域、不同要素等级的格点面积及面积比例等定量指标的统计分析。平台自投入业务应用以来,为各级业务应用和精细化气象服务提供了数据支撑。平台基于全国统一的数据环境和参数配置方式,具有很强的应用推广价值。

An WebGIS Based Real Time Application/Analysis Platform of Grid Products and Key Technology

The real time grid products are an important and necessary data sources for intelligent grid forecasting service, as the real time grid products take the dual tasks of forecasting revision and forecasting product inspection. In order to meet the service requirements of meteorological applications and meteorological services for real time grid products, various gird products are collected in real time and standardized, and a WebGIS based real time grid product application analysis platform is established using the Web techniques, such as JavaScript, HTML, CSS, etc. Based on the open source design idea, a framework of WebGIS supported by HTML5 is built by using Leaflet, Canvas and other technologies. All kinds of real time grid products can be displayed on the same geographic information in this platform, and the display region can be conveniently switched among the whole country, provinces and different cities. The station observation data and station information from the CIMISS can be integrated and displayed in this platform, and more than ten thousand stations and over one million grid points can be easily drawn. The real time data quality evaluation and analysis of the products are provided through the comparison and analysis between grid data and observations. Based on the grid points, the statistical analysis results (grid area and area ratio) in any region and different feature levels for any meteorological features are achieved, which are useful information for meteorological decision analysis and early warning forecast service in various disaster weather processes, such as heavy rains, high heat, severe winds, dense fogs, etc. Since the platform is put into application, it has provided great data supports for application and refinement meteorological services of all levels. As based on the national uniform data environment and parameter configuration, the platform has strong application and promotion value.