数据与计算发展前沿2026，Vol.8Issue(1)：168-182,15.DOI:10.11871/jfdc.issn.2096-742X.2026.01.014
基于工作流的陆地生态系统碳循环实时同化预测系统
The Real-Time Assimilation and Prediction System for Terrestrial Ecosystem Carbon Cycling Based on Workflow
摘要
Abstract
[Objective]The feedback effects of terrestrial ecosystem carbon cycling on climate change are central to global change research.Currently,there is a lack of real-time,efficient,and automated carbon source-sink assessment and prediction systems,making it difficult to quickly and accurately quantify the carbon sink size,stability,and sustainability.This limitation affects the formulation of carbon sequestration strategies and the implementation of carbon neutrality initiatives.[Methods]This study develops a real-time assimilation and prediction system for ter-restrial ecosystem carbon cycling,comprising multiple core modules such as data collection,transmission,analy-sis,workflow management,scheduling,prediction,and visualization.By integrating deep learning-based meteoro-logical models,carbon cycle process models,data assimilation algorithms,and ecological iterative prediction methods,the system continuously assimilates real-time station observation data to enable short-term carbon sink predictions,which serves as a paradigm for transitioning from observation to prediction in field station research.[Results]Since its deployment in February 2023,the system has successfully integrated with four stations,includ-ing Dinghushan,Qianyanzhou,and Huitong,accumulating over 110,000 data records to date.[Conclusion]The system significantly improves the timeliness and efficiency of carbon cycle prediction,providing reliable data support and observable real-time retrieval services for ecological research and environmental management deci-sion-making.关键词
气候变化/碳循环/同化预测/深度学习/生态系统/数据同化/短期预测Key words
climate change/carbon cycle/assimilation prediction/deep learning/ecosystem/data assimilation/short-term prediction引用本文复制引用
万萌,王珏,高超,何洪林,任小丽,聂宁明,曹荣强,王宗国,李凯,王晓光,王彦棡..基于工作流的陆地生态系统碳循环实时同化预测系统[J].数据与计算发展前沿,2026,8(1):168-182,15.基金项目
国家重点研发计划"标准化生态台站监测数据产品体系构建与系统开发"(2021YFF0703902) （2021YFF0703902）
