计算机科学与探索2026，Vol.20Issue(4)：905-922,18.DOI:10.3778/j.issn.1673-9418.2508007
气象多模态数据融合方法研究综述
Review of Research on Multimodal Data Fusion Methods in Meteorology
摘要
Abstract
Advancements in multi-source observation technologies have ushered in the era of multimodal meteorological data.However,single-modal data is inherently limited in its ability to characterize the complex and dynamic atmospheric system,failing to meet the demand for more precise predictions.Consequently,integrating multimodal data to leverage complementary information and enhance performance has become a key research frontier in meteorology.This paper addresses the core challenge of effectively integrating meteorological data from different modalities by providing a systematic review of multimodal data fusion methods.First,this paper traces the evolution of multimodal fusion techniques,with a particular focus on deep learning-based strategies.It elaborates on the core concepts,architectural features,and advantages of mainstream models,such as encoder-decoder architectures,attention mechanisms,graph neural networks,and generative adversarial networks in the context of multimodal data fusion.Then,this paper comprehensively analyzes the current applications of this technology.Drawing on a systematic compilation of publicly available multimodal meteorological data-sets,this paper reviews the technology's application in key tasks,including precipitation nowcasting and predicting the paths and intensities of typhoons and tropical cyclones.It summarizes the research progress and effectiveness of different fusion methods in these scenarios.Furthermore,this paper analyzes the key challenges currently facing multimodal fusion in meteo-rology.Finally,based on the identified challenges,it outlines future research directions for the field.关键词
气象学/多模态/数据融合/深度学习Key words
meteorology/multimodal/data fusion/deep learning分类
信息技术与安全科学引用本文复制引用
吴若飞,方巍,蒋鸿儒,鲍艳松..气象多模态数据融合方法研究综述[J].计算机科学与探索,2026,20(4):905-922,18.基金项目
广西重点研发计划(桂科AB25069126) （桂科AB25069126）
国家自然科学基金面上项目(42475149) （42475149）
中国气象局流域强降水重点开放实验室开放研究基金(2023BHR-Y14) （2023BHR-Y14）
灾害天气国家重点实验室开放课题(2024LASW-B19).This work was supported by the Key Technologies Research and Development Program of Guangxi(AB25069126),the National Natu-ral Science Foundation of China(42475149),the Open Fund of China Meteorological Administration Basin Heavy Rainfall Key Labo-ratory(2023BHR-Y14),and the Open Grants of the State Key Laboratory of Severe Weather(2024LASW-B19). （2024LASW-B19）
