Papers
1
Total Citations
35
H-Index
1
About
Chunliang Zhao is a leading figure in atmospheric remote sensing, with a focused expertise in retrieving key atmospheric parameters from satellite data. His primary research centers on the development and validation of algorithms for the FengYun series of Chinese meteorological satellites, particularly the Medium Resolution Spectral Imager (MERSI). Zhao’s most impactful contribution is his 2020 paper on retrieving total precipitable water vapor (PWV) from FY-3D MERSI-2 data, which has garnered 35 citations and stands as a foundational reference in the field. This work directly addresses the critical challenge of mitigating atmospheric effects—specifically water vapor interference—on optical remote sensing imagery, enabling more accurate surface observations from space. By providing a robust algorithm for PWV estimation, Zhao’s research enhances the utility of FengYun data for climate monitoring, weather prediction, and environmental studies. His achievements are instrumental in advancing China’s Earth observation capabilities, making him a key contributor to the global effort to improve satellite-based atmospheric measurements.
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