Papers
11
Total Citations
253
H-Index
8
About
Lili Qie is a prominent atmospheric scientist specializing in aerosol remote sensing, satellite-based retrieval methods, and aerosol optical property characterization. Her research has made substantial contributions to advancing our ability to monitor and quantify atmospheric aerosols from space, with a particular focus on East Asia — a region critically affected by air pollution and climate-relevant particulate matter. Qie's most influential work includes developing a Dark Target algorithm for Himawari-8/AHI aerosol retrieval (62 citations), enabling high-temporal-resolution monitoring of aerosol dynamics from geostationary orbit. She has also pioneered methods for retrieving aerosol fine-mode fraction (FMF) using multiangle polarimetric data from PARASOL (43 citations), and advanced our understanding of aerosol complex refractive indices for both fine and coarse particle modes simultaneously through AERONET data (47 citations). Her methodological innovations span empirical orthogonal functions, optimal estimation frameworks, and grouped residual error sorting approaches for satellite aerosol retrieval. More recently, Qie has embraced machine learning, applying capsule network models to polarimetric satellite data, signaling her commitment to next-generation retrieval techniques. With over 250 cumulative citations, her body of work significantly enhances the scientific community's capacity to characterize aerosol properties critical for climate modeling and air quality assessment.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10