Professor Sundar A. Christopher’s research focuses on using satellite, airborne, and ground-based observations together with numerical models to better understand aerosols, clouds, and air quality. Over more than three decades, his work has advanced how we observe particulate matter (PM₂.₅), biomass burning smoke, dust, and mixed aerosol systems, and how these particles influence radiation, clouds, climate, and human health.
A major theme of his research is the development and application of satellite-based methods to estimate surface air quality, particularly PM₂.₅, at regional to global scales. His group has combined data from platforms such as MODIS, MISR, OMI, GOES, PlanetScope, and MERRA-2 reanalyses with machine learning and statistical models to produce hourly to daily PM₂.₅ estimates and long-term datasets for cities and regions around the world. Recent work has examined unusual biomass burning seasons (e.g., stubble burning in northern India) and the air quality impacts of large wildfire events in Canada and the western United States.
Professor Christopher has also contributed extensively to understanding the direct radiative effects of aerosols and their interactions with clouds. His publications include global and regional assessments of aerosol radiative forcing over land and ocean, observational analyses of absorbing aerosols above clouds, and studies of aerosol–cloud–precipitation interactions in regions such as the Southeast Atlantic, Amazonia, Southeast Asia, and the Arabian Sea. These efforts have informed climate model evaluation and improved satellite-based radiative flux estimates.
Field and campaign-based science is another cornerstone of his work. He has played key roles in multi-platform studies such as SCAR-B, PRIDE, DABEX, GERBILS, ADRIEX, and 7SEAS, integrating aircraft, ground, and satellite measurements to characterize the vertical structure and optical properties of dust and smoke, evaluate model forecasts, and improve retrieval algorithms. His research group also collaborates with operational agencies to incorporate satellite products into air quality systems such as AirNow and to prepare the community for next-generation geostationary missions.
Current Focal Areas 1) Satellite-based estimation of surface PM₂.₅ using machine learning and reanalysis products 2) Air quality impacts of wildfires and biomass burning (North America, South Asia, and beyond) 3) Radiative effects of absorbing aerosols above clouds and their role in regional climate 4) Aerosol–cloud interactions and diurnal cycles of low clouds in aerosol-rich environments5)
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