气象科技2024,Vol.52Issue(2) :195-204.DOI:10.19517/j.1671-6345.20230093

基于大数据云平台的天山气象APP设计与应用

Design and Effect of Tianshan Meteorological App Based on Big Data Cloud Platform

陶淘 侯俊 张晨亮 屈莘 杨挺
气象科技2024,Vol.52Issue(2) :195-204.DOI:10.19517/j.1671-6345.20230093

基于大数据云平台的天山气象APP设计与应用

Design and Effect of Tianshan Meteorological App Based on Big Data Cloud Platform

陶淘 1侯俊 1张晨亮 2屈莘 3杨挺1
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作者信息

  • 1. 新疆维吾尔自治区气象信息中心,乌鲁木齐 830002
  • 2. 新疆维吾尔自治区气象技术装备保障中心,乌鲁木齐 830002
  • 3. 民航新疆空中交通管理局,乌鲁木齐 830011
  • 折叠

摘要

为提升大数据云平台与移动互联网的耦合气象服务质量,满足气象防灾减灾移动可视化需求,推进新疆气象信息化事业高质量发展,亟需开发一款专业气象服务APP.该APP在"云+端"业务模式下充分利用气象业务现有数字化成果,采取多源存储、接口调用、控制反转和数据交互技术,对全疆天气自动站的地面观测、格点实况融合、雷达回波、灾害预警等气象资料进行加工处理和移动展示.天山气象APP可按用户需求提供疆内基于实时位置的天气实况、精细化预报、预警详情、雷达拼图、实况要素产品和统计值要素产品,同时继承大数据云平台服务接口高额承载能力,实现毫秒级响应,在全疆天气自动站应急保障与气象防灾减灾服务中应用成效显著.

Abstract

The current service recipients of the Xinjiang Meteorological Big Data Cloud Platform are mostly based on numerical forecasting models and multi-source fusion analysis of meteorological intranet business systems.The integration with the mobile internet is not high,and most of the frontline observation data are directly extracted and processed without being visually displayed through media.The basic stations also lack the means to access the operational status of automatic stations and local refined forecasting and warning on mobile devices.Therefore,to enhance the quality of meteorological services and meet the mobile visualisation needs for meteorological disaster prevention and reduction,as well as to improve the monitoring and warning capabilities of small and medium-scale weather disasters at the basic level in Xinjiang,there is urgency to develop a professional meteorological service APP.The Tian Shan Weather APP breaks through the heterogeneous barriers between the Xinjiang meteorological intranet and the mobile internet at the network level,fully utilises the existing digital achievements of meteorological business in the"cloud+end"business model.It processes and displays meteorological data such as ground observations from automatic weather stations,grid-based actual conditions,radar echoes,and disaster warnings.The key technologies are as follows:using multi-source data processing and storage technology to process and reprocess raw data and standardised storage products;using service interfaces that inherit the technical characteristics of the large-scale data cloud platform and achieve millisecond-level data calls;using the SSM development framework based on inversion of control to separate APP transaction management from main business logic;using a data interaction mode based on the Restful architecture style for cross-platform development.At present,the Tian Shan Weather APP can provide real-time weather conditions,refined forecasts,warning details,and radar mosaics based on the user's location in Xinjiang according to the user's needs.It can also customise the calculation and analysis products of ground actual condition elements and statistical value elements for meteorological research purposes.Through simulated testing of the data cloud platform service interface and the original CIMISS system interface,it is found that under 100 concurrent accesses,the data cloud platform interface is 5.7 times faster than the original CIMISS interface,and under 200 concurrent accesses,it is 5.3 times faster.This shows that the APP inherits the high carrying capacity of the data cloud platform service interface.The APP is being widely promoted and used by meteorological departments at the provincial,municipal,and county levels,as well as in related industries such as civil aviation and the air force in Xinjiang.It has been widely recognized and has achieved significant results in the emergency support of weather automatic stations and meteorological disaster prevention and reduction services throughout Xinjiang.

关键词

大数据云平台/加工处理/移动展示/服务接口/气象防灾减灾

Key words

big data cloud platform/process/display/service interface/meteorological disaster prevention and reduction services

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基金项目

新疆维吾尔自治区创新环境(人才、基地)建设专项(2022287713)

出版年

2024
气象科技
中国气象科学研究院 北京市气象局 中国气象局大气探测技术中心 国家卫星气象中心 国家气象信息中心

气象科技

CSTPCD
影响因子:1.154
ISSN:1671-6345
参考文献量18
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