气象大数据应用场景与气象服务技术预见研究——面向重庆农业领域

Research on technology foresight of meteorological big data application scenarios and meteorological service technologies:A focus on agriculture in Chongqing

气象大数据在农业领域的应用尚处于模糊前端,优先发展重要应用场景的气象服务关键技术,对推动农业农村现代化具有重要的理论价值和现实意义。本研究基于文献计量和德尔菲法的定性与定量结合的技术预见方法,对“十四五”至2035远景重庆农业领域气象大数据应用场景和基于场景的气象服务技术进行了预见。研究表明:“智慧农业”和“数字乡村”是我国农业领域气象相关大数据研究热点主题。气象大数据的重要应用场景和关键气象服务技术集中于农业产业链的产前和产中环节,农业生产与管理子领域遴选出了最多的5个重要场景和7项关键技术。关键气象服务技术预期实现时间集中在2026—2030年,研发应用风险总体偏大。此外,分析结果表明,“政、产、学、研合作不够”、“数据资源获取和共享不畅”、“研究经费投入不足”、“缺少科研和技术人才”是制约气象大数据在重庆农业领域应用的主要因素。针对这些制约因素,本研究提出了包括促进协同创新、破除“数据壁垒”、提高投入产出效益、培养复合型人才等方面的措施,以推动气象大数据在农业领域的创新发展。

The application of meteorological big data in the agricultural sector is still in its early stages,with priority given to the development of key meteorological service technologies for important application scenarios,which holds significant theoretical value and practical significance for advancing the modernization of agriculture and rural areas.This study utilizes a combined qualitative and quantitative technology foresight approach based on bibliometrics and the Delphi method to anticipate the application scenarios of meteorological big data and the meteorological service technologies based on scenarios in the agricultural sector of Chongqing from the“14th Five-Year Plan”to the 2035 vision.The findings reveal that“smart agriculture”and“digital countryside”are prominent topics in meteorological big data research within China’s agricultural sector.Key application scenarios and meteorological service technologies of meteorological big data are predominantly focused on the pre-production and mid-production stages of the agricultural industry chain,identifying five significant scenarios and seven key technologies within the subfield of agricultural production and management.The anticipated implementation period for key weather service technologies is concentrated between 2026 and 2030,with overall high risks associated with research and development applications.Moreover,the analysis indicates that insufficient cooperation among industry,academia,research,and development,poor access to and sharing of data resources,inadequate investment in research funding,and a shortage of scientific research and technical talents are the primary constraints hindering the application of meteorological big data in Chongqing’s agricultural sector.To address these constraints,this study proposes measures including promoting collaborative innovation,breaking down data barriers,enhancing input-output efficiency,and cultivating composite talents to propel the innovative development of meteorological big data in the agricultural sector.