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