新疆特色农业智慧气象服务平台设计与应用

Design and Application of Intelligent Meteorological Service Platform for Characteristic Agriculture in Xinjiang

关键词:  农业气象  新疆  气象服务  格点化  智慧平台

Key words:  agrometeorology  Xinjiang  meteorological service  gridding  intelligent platform

摘要:

【目的】新疆作为我国最大的特色林果生产基地，红枣、葡萄、香梨等林果产品在全国市场中占据举足轻重的地位。然而，在全球气候变化的大背景下，极端气象灾害如霜冻、高温和大风发生的频率逐渐升高，给林果业的持续健康发展带来了严峻的挑战。【方法】本研究依托“天擎”气象大数据云平台，构建整合气象大数据、农业生态指标、GIS空间可视化能力的新疆特色农业智慧气象服务平台。平台采用5km×5km精细化格点技术，调用“天擎”内置气象算力，实现精细72小时气象灾害预警，并完成9种主要特色林果生长适宜性分区评价。【结果】2023年库尔勒香梨霜冻灾害案例的数据显示，该平台在高风险地区的预测准确率达到 79%，可精准划定灾害风险区域、指导农户开展防灾作业，充分证明了其在减灾方面的显著作用。【结论】此研究为干旱区特色农业气象服务提供了可推广的技术框架，对提升农业防灾减灾数字化决策能力具有重要的现实意义。

Abstract:

[Purpose]As China''s largest characteristic forest fruit production base, Xinjiang''s forest fruit products such as red dates, grapes, and fragrant pears hold a pivotal position in the national market. However, against the backdrop of global climate change, the frequency of extreme meteorological disasters such as frost, high temperatures, and strong winds is gradually increasing, posing severe challenges to the sustainable and healthy development of the forest fruit industry.[Method]Relying on the "Tianqing" meteorological big data cloud platform, this study constructs an intelligent meteorological service platform integrating meteorological big data, agricultural ecological indicators and GIS spatial visualization functions. Combined with 5km×5km refined grid technology and the built-in computing capacity of Tianqing Platform, the platform realizes 72-hour refined meteorological disaster warning and growth suitability evaluation for nine major forest fruits.[Result]Data from the 2023 Korla fragrant pear frost disaster case shows that the platform''s prediction accuracy rate in high-risk areas reaches 79%, fully demonstrating its significant role in disaster reduction.[Conclusion]This research provides a promotable technical framework for characteristic agricultural meteorological services in arid areas and has important practical significance for improving agricultural disaster prevention and mitigation capabilities.