Xiaoguang (Richard) Xu
Assistant Professor · Non-Tenure Track
About
My research integrates advanced satellite remote sensing, Earth system modeling, and machine learning, with a focus on atmospheric aerosol and cloud, to address critical challenges in climate change, air quality, and environmental health. I specialize in the fusion of hyper-spectral and polarimetric data (e.g., from NASA PACE, TEMPO satellites) to characterizeatmospheric aerosols and their impacts on urban and coastal environments. My work spans in the areas of: (1) developing next-generation radiative transfer models (UNL-VRTM) and physics-informed machine learning algorithms for efficient satellite data retrieval; (2) utilizing data assimilation to constrain aerosol sources and their climate forcing; and (3) applying these tools to interdisciplinary studies linking atmospheric composition to public health and climate resilience.Research interests
Chemistry transport modeling; radiative transfer; satellite remote sensing of aerosolsTeaching interests
Climate modeling; Physical meteorology; atmospheric physics and chemistry; Remote SensingEducation
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Ph D, Earth and Atmospheric Science
— University of Nebraska-Lincoln (2015) Retrieval of Aerosol Microphysical Properties from AERONET Photopolarimetric Measurements
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MS, Meteorology
— Lanzhou University (2008) Study on Predictability of the T63L16 Climate Model
- BS — Lanzhou University (2005)