Yanli Qiao
Papers
2
Total Citations
15
H-Index
2
About
Yanli Qiao is a leading researcher in atmospheric aerosol remote sensing, specializing in the retrieval of aerosol fine-mode fraction (FMF)—a critical parameter for understanding anthropogenic pollution and climate forcing. Her major contributions center on advancing inversion algorithms to extract FMF from both ground-based and satellite observations. In her most-cited work (2019, 11 citations), Qiao introduced an optimal estimation (OE) framework that retrieves FMF from single-viewing, multi-spectral sky light measurements, significantly improving accuracy over traditional methods. Earlier, she developed a novel technique to enhance MODIS satellite retrievals of FMF over ocean (2011, 4 citations), addressing key limitations in lookup-table-based approaches by refining top-of-atmosphere reflectance calculations. These innovations have direct implications for air quality monitoring, climate modeling, and aerosol radiative effect studies. Qiao’s work bridges the gap between theoretical retrieval theory and practical satellite applications, offering robust tools for global aerosol characterization. Her research continues to influence the development of next-generation aerosol algorithms, making her a notable figure in Earth observation science.
Research Focus
Key Achievements
Top Papers
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