Papers
12
Total Citations
317
H-Index
8
About
Youngmin Noh is a leading figure in atmospheric aerosol research, with a focus on the optical properties and classification of aerosols, particularly mineral dust and black carbon. His major contributions center on developing innovative methods to extract detailed aerosol-type information from ground-based remote sensing networks, primarily AERONET. Noh pioneered the use of the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) from AERONET version 3 inversion products to classify aerosol types, a framework that has become a reference in the field, as evidenced by his 2019 paper (94 citations). He further advanced the understanding of dust optical properties by analyzing spectral depolarization and lidar ratios (2018, 88 citations). A key achievement is his development of a technique to retrieve black carbon absorption aerosol optical depth (AAOD) from AERONET data, enabling long-term, global-scale studies of light-absorbing aerosols. His work on separating the absorption components of mixed dust plumes (2019, 43 citations) provides critical insights for climate modeling. With over 300 total citations, Noh’s research directly supports improved aerosol typing in satellite and lidar observations, making his methods essential for studying air quality and climate impacts in East Asia and beyond.
Research Focus
Key Achievements
Top Papers
- 1Aerosol-type classification based on AERONET version 3 inversion products94 citations · 2019
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