地球与行星物理论评（中英文）2026，Vol.57Issue(1)：118-125,8.DOI:10.19975/j.dqyxx.2025-015
基于CNN-LSTM的临近空间温度预报研究
Research on temperature forecasting in near space based on CNN-LSTM algorithm
摘要
Abstract
Near space refers to the complex transition region between the Earth's atmosphere and space,with its height between 20-100 km,including the stratosphere,the mesosphere and the lower thermosphere which are important components of the Earth's atmospheric system.The near space is affected not only by small-scale disturb-ances in the troposphere but also by planetary waves in the middle and upper atmosphere.There are also atmo-spheric dynamic processes in the region and physical and chemical interactions between layers of the atmosphere,which make the study of near space difficult.Scholars at home and abroad have done a lot of research on the ap-plication of machine learning and deep learning algorithms in the field of space physics,and achieved good results.However,due to the complexity and variability of atmospheric environment,there is little research on using deep learning algorithm to forecast environmental temperature in near space.The study of temperature forecasting in near space is of great scientific significance for understanding atmospheric dynamics,cross-layer coupling and ana-lyzing atmospheric fluctuations.In this paper,CNN-LSTM algorithm is used to forecast temperature in near space based on MERRA-2 datasets.The CNN part can effectively extract spatial features and the LSTM part can capture temporal dependencies.Its output window is 7 days,and the relative error is controlled within 2%compared with the original data.On this basis,we do some research on the sensitivity of the algorithm in season,altitude and lati-tude.The results show that in summer and autumn of the Northern Hemisphere,the forecast results are better,and the accuracy of the forecast model is more reliable at low latitudes.关键词
临近空间/温度预报/机器学习/深度学习Key words
near space/temperature forecasting/machine learning/deep learning分类
天文与地球科学引用本文复制引用
何汉圳,谷升阳,秦雨松,刘宇轩..基于CNN-LSTM的临近空间温度预报研究[J].地球与行星物理论评（中英文）,2026,57(1):118-125,8.基金项目
国家自然科学基金资助项目(42374195,42404168) （42374195,42404168）
博士后创新人才支持计划(BX20230273)Supported by the National Natural Science Foundation of China(Grant Nos.42374195,42404168),and the Postdoctoral Innovation Talent Support Program(Grant No.BX20230273) （BX20230273）
