报告时间: 2026年11月06日 14:00-15:00
报告地点：北辰楼312会议室
主 持 人：刘 超 教授
报告题目: Earth Intelligence from Space: Satellite Remote Sensing in the Age of AI
专家简介： Dr. Jonathan H. Jiang is an atmospheric and space scientist whose research spans satellite remote sensing, climate dynamics, clouds, aerosols, water vapor, radiation, climate-model evaluation, and planetary habitability. He has had a long scientific career at NASA’s Jet Propulsion Laboratory, California Institute of Technology, where his work has contributed to major Earth-observing missions and satellite-based studies of the climate system. His research has used observations from missions such as Aura MLS, A-Train, CloudSat/CALIPSO, CERES, DSCOVR and other satellite systems to understand cloud–aerosol–radiation interactions, upper-tropospheric and lower-stratospheric water vapor, and climate-model biases. Dr. Jiang has authored or co-authored hundreds of scientific publications and has received major recognitions including NASA achievement medals and election as a Fellow of the American Meteorological Society.
报告摘要：Satellite remote sensing has evolved from spaceborne imaging into a quantitative observing system for the coupled Earth system. This seminar traces that evolution from spectral physics, radiative transfer and physical retrievals to today’s multi-sensor observations of clouds, aerosols, water vapor, radiation, ocean, land and ice. Using examples from Aura MLS, A-Train, CERES, CloudSat/CALIPSO, CMIP model diagnosis, and new missions such as PACE, EarthCARE and NISAR, I will show how satellites reveal climate processes and expose model uncertainties. Looking forward, I argue that the next breakthrough will come from physics-aware AI: combining forward models, uncertainty quantification, satellite simulators and machine learning to build trusted Earth-system intelligence. This hybrid approach can accelerate retrievals, fuse observations, constrain climate feedbacks, evaluate models and support climate digital twins for a rapidly changing planet.
欢迎广大师生踊跃参加！
江苏省精密协同导航定位与智能应用工程研究中心
自然资源部遥感导航一体化应用工程技术创新中心
天都-南信大深空探测联合实验室
遥感与测绘工程学院
2026年11月2日
