Guangyao Dai
Papers
2
Total Citations
43
H-Index
2
About
Guangyao Dai is an atmospheric scientist whose research focuses on advancing remote sensing techniques for water vapor profiling. His key contributions center on the calibration of Raman lidar systems—a critical tool for measuring atmospheric moisture with high vertical resolution. Dai developed a practical, continuous calibration method that integrates Raman lidar observations with co-located AERONET photometer data and GDAS meteorological information, significantly improving the accuracy and reliability of water vapor mixing ratio profiles. This work, primarily demonstrated using the multiwavelength polarization Raman lidar PollyXT, addresses a longstanding challenge in lidar remote sensing by enabling robust calibration without the need for frequent, costly in-situ measurements. His most cited paper (2018) has garnered 41 citations, reflecting its impact on the lidar and atmospheric science communities. By bridging ground-based photometry and operational meteorological data, Dai’s methodology enhances the utility of Raman lidars for climate studies, weather forecasting, and aerosol-cloud interaction research. His achievements underscore a commitment to practical, data-driven solutions that strengthen the global atmospheric observing network.
Research Focus
Key Achievements
Top Papers
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