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About

Shantikumar S. Ningombam is a leading atmospheric scientist whose research focuses on aerosol optical properties, radiative forcing, and long-term atmospheric monitoring, particularly over the Indian subcontinent. His major contributions include establishing a 23-year (1995–2018) climatology of aerosol optical depth using ground-based AERONET and SKYNET measurements from aged-background sites, a foundational dataset that has garnered 76 citations. He has also advanced the understanding of how active fire events in the Indo-Gangetic Plains alter aerosol optical and physical properties, with implications for regional climate forcing (28 citations). Notably, Ningombam has pioneered the application of machine learning—specifically spectral clustering algorithms—to classify aerosol types, a novel approach that has already attracted 15 citations. His work on classifying MODIS fire emission data using aerosol absorption Ångström exponents from AERONET further demonstrates his innovative use of satellite and ground-based data integration. Additionally, he has contributed to astronomical site characterization by analyzing atmospheric opacity and water vapor trends at the Indian Astronomical Observatory in Hanle. With a growing citation impact and a focus on both fundamental aerosol science and practical applications in climate and astronomy, Ningombam’s research is essential for understanding aerosol dynamics in South Asia.