数据与计算发展前沿2026，Vol.8Issue(2)：3-14,12.DOI:10.11871/jfdc.issn.2096-742X.2026.02.001
冰冻圈"大数据+AI+模型"耦合研究范式探索
Exploration of An Integrated"Big Data+AI+Modeling"Research Paradigm for Cryosphere Studies
摘要
Abstract
[Objective]As a vital component of Earth's system,the cryosphere profoundly impacts global climate,hydrolog-ical cycles,and ecological security through multi-element nonlinear interactions,cross-sphere couplings,and long disaster chains.Traditional physical models exhibit limitations in characterizing multi-scale cryospheric changes,failing to meet practical needs for large-scale monitoring,rapid evolution analysis,and hazard early-warning.[Methods]This paper proposes a"Big Data+AI+Model"research paradigm for cryospheric studies and develops the Global Cryosphere research Engine(GCE)to support this framework.The GCE forms an integrated platform encompassing data management,model construction,AI algorithm application,and task workflow or-chestration,with capabilities for multi-source heterogeneous data fusion,cross-language model collaboration,high-performance computing scheduling,and intelligent analysis.[Conclusions]Based on the GCE platform,model construction approaches such as"embedding AI into physical models","embedding physical models into AI",and"data-driven parameter optimization coupled with AI"have been implemented.Focusing on soil mois-ture simulation experiments over the Tibetan Plateau,a novel multi-element interaction framework integrating"observation data+deep learning(hierarchical LSTM)+physical model(Noah-MP)"was developed.The average correlation between simulated and observed layered soil moisture exceeded 0.8,significantly outperforming the Noah model.The results demonstrate the feasibility of a research paradigm that combines data-driven approach-es,physical model support,and artificial intelligence to effectively characterize cryospheric processes,while also validating the utility of the GCE platform.This framework can provide a supportive environment for new re-search paradigms in ecological environments and cryospheric disasters,promoting intelligent cryospheric re-search with cross-regional multi-element interactions.关键词
冰冻圈/大数据/人工智能/模型/冰冻圈研究引擎GCEKey words
cryosphere/big data/AI/model/GCE(Global Cryosphere research Engine)引用本文复制引用
张耀南,刘景琦,康建芳,南卓铜,田文彪,敏玉芳,赵书萍,王保得..冰冻圈"大数据+AI+模型"耦合研究范式探索[J].数据与计算发展前沿,2026,8(2):3-14,12.基金项目
国家重点研发计划(2022YFF0711704) （2022YFF0711704）
2022年度新疆交通运输行业科技项目(2022-ZD-006) （2022-ZD-006）
新疆交投2021年揭榜挂帅科技项目(ZKXFWCG2022060004) （ZKXFWCG2022060004）
新疆交通设计院公司科研基金(KY2022041101) （KY2022041101）
新疆维吾尔自治区科技支疆项目(2024E02030) （2024E02030）
