Maki Kikuchi
Papers
4
Total Citations
442
H-Index
4
About
Maki Kikuchi is a leading figure in satellite-based aerosol remote sensing and data assimilation, whose work has fundamentally improved how we monitor and predict atmospheric particulate matter. Her research centers on developing advanced algorithms to retrieve aerosol properties—such as optical thickness, single-scattering albedo, and Ångström exponent—from multiple satellite sensors, enabling consistent, high-quality observations over both land and ocean. Kikuchi’s most impactful contribution is a common retrieval algorithm for imaging satellite sensors, which has garnered over 206 citations for its automatic channel selection and robust performance. She has also pioneered techniques to leverage geostationary satellites like Himawari-8, achieving hourly aerosol optical thickness estimates with 152 citations, and assimilating these data into models using the four-dimensional local ensemble transform Kalman filter (70 citations). Her work on inverting East Asian dust emission fluxes with an ensemble Kalman smoother (14 citations) showcases her ability to combine satellite observations with chemical transport models to optimize emissions. Kikuchi’s innovations are critical for understanding rapid aerosol evolution, improving air quality forecasts, and supporting climate studies, making her a key contributor to modern atmospheric science.
Research Focus
Key Achievements
Top Papers
- 1Common Retrieval of Aerosol Properties for Imaging Satellite Sensors206 citations · 2018
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