《气象前沿资讯》是上海市气象学会服务会员的学术窗口，每季度汇集内部资讯精华。栏目涵盖上海气象科技进展、国际顶刊精选、国际研究动向、权威机构报告四大板块，多维度呈现前沿动态。
即日起，我们将从《气象前沿资讯》2026年第1期（总第4期）开始，通过公众号向大家陆续推送，以轻盈的篇幅助您快速把握技术趋势。2026年第1期将分为5篇，本篇聚焦热带气旋机理、AI气象应用、卫星遥感技术三大方向，重点推介复旦大学、上海台风研究所、华东师范大学在AI模型不确定性量化与 台风低空风场观测数据集研制等领域的最新突破。
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上海气象科技进展（1）
1.中国热带气旋降水空间不均匀性减弱
Dong Huang, Shengyuan Liu, Xin Huang, et al. Decrease in the spatial inhomogeneity of tropical cyclone rainfall in China. Environmental Research Letters (JCR Q1), 2026, 21(2): 024006.
2.从稀疏观测中重建热带气旋的三维结构
Han X, Li X, Niu Z, et al. Physics-guided score-based diffusion for3D reconstruction of tropical cyclones from sparse observations. npj Climate and Atmospheric Science (JCR Q1), 2026 . Doi: 10.1038/s41612-026-01413-9 .
2.从稀疏观测中重建热带气旋的三维结构
Han X, Li X, Niu Z, et al. Physics-guided score-based diffusion for3D reconstruction of tropical cyclones from sparse observations. npj Climate and Atmospheric Science (JCR Q1), 2026 . Doi: 10.1038/s41612-026-01413-9 .
3.机器学习方法重建精细尺度三维风场
Lin, C., Tie, R., Yi, S. et al. Reconstructing fine-scale 3D wind fields with terrain-informed machine learning.Nature Communications (JCR Q1), 2026, 17:3713.
4.基于静止卫星红外云图的台风最大风速半径反演及数据集
Chen, T., Zhuge, X.,Yu, H., et al. Retrieving Tropical Cyclone Radius of Maximum Wind From Geostationary Satellite Infrared Imagery With SAR Observations as Ground Truth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JCR Q1), 2026, 19:11411-11426.
5.基于全国风廓线雷达网，系统“解码”台风低空风场结构
Tang S, Li Y,Yu H.A nationwide radar network reveals typhoon wind profile characteristics in the lower troposphere over China. npj Climate and Atmospheric Science (JCR Q1), 2026. Doi: 10.1038/s41612-026-01404-w.
6.基于U-Net 深度学习的台风诱发降水识别方法
Wan R, Chen C, Bai L, et al.A High-Accuracy U-Net Deep Learning Method for Identifying typhoon-induced precipitation. Artificial Intelligence for the Earth Systems, 2026, e250079 .
7.“大禹”云分析系统：基于静止卫星的高分辨云物理特性集合反演
Xiao Haixia, Zhang Feng, Wang Lingxiao, et al. High-resolution ensemble retrieval of cloud properties for all-day based on geostationary satellite. npj Climate and Atmospheric Science (JCR Q1), 2025, 8: 386.
Li Jingwei, Pan Baoxiang, Zhang Feng, et al. Probabilistic Retrieval of All-Day Overlapping Cloud Microphysical Properties. Advances in Atmospheric Sciences(JCR Q1), 2026, 43(6): 1256-1269.
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