任意时段累年气候数据统计流程优化及应用

Flow Optimization of Any Period Climatic Data Statistics for Successive Years and Its Application

任意时段累年气候数据的统计是气象部门一项常规实时(准实时)业务,需要相应业务系统的支撑。为了提高该系列数据的统计检索效率,本文对获取该数据的统计流程进行了优化,提出了优化后的原始数据逻辑分解流程,并以关系型数据库Oracle为例,利用广东省86个国家气象观测站近65年,及2313个区域自动气象站近10年逐日气象数据,进行了任意时段累年气候数据统计流程优化前后效率的对比。结果显示:基于优化前的流程,随着任意时段日期跨度的增长,数据统计效率逐步降低;而基于优化后的流程,无论任意时段起止日期的跨度大小,数据统计均可以保持很高的效率。本文将优化后的统计流程应用于广东省农业气象业务系统(AGROS)对应的功能模块,对提高系统效率、优化用户体验起到了很大作用,并进一步推动了该系统在广东全省的推广应用。对于全国各省区乃至国家级气象部门业务系统相关模块的开发也有参考价值。

Any period climatic data statistics for successive years is a common real/quasi-real time operational task in meteorological service,which should be supported by the corresponding operational system.In order to improve the efficiency,we optimize the statistic flow and propose a logic decomposition process of the original data in this paper.Taking the relational database Oracle as an example,based on the 65-year daily data of 86 national weather stations and the 10-year daily data of 2313 regional weather stations,the optimized flow is tested.The results show that,based on the flow before the optimization,the query efficiency decreases with the increasing period span.Conversely,based on the flow after the optimization,the query efficiency maintains a high level,regardless of the span of the period.The optimized flow is applied in the AGRo-meteorology Operation System of Guangdong Province（AGROS）and plays an important role in improving the system efficiency and optimizing the user experiences.Eventually,the popularization and application of the system in Guangdong Province are further promoted.The optimization flow proposed in this paper has important reference value in the related operational system development in other provinces and national meteorological services.