Research

Remote Sensing

Satellite remote sensing offers the most practical way to observe the global atmosphere. I develop novel spectral, spatial, and temporal algorithms using satellite data to advance the detection and retrieval of aerosol, air pollutants, and cloud properties.

Publication: Chang et al. (2025), Chang et al. (2021), Chang & Christopher (2016)

Aerosol-Cloud-Radiation Interactions

Atmospheric aerosols present a major influence on the climate system and remain a significant atmospheric component to predicting changes to the Earth climate system. I combine measurements and Earth system models to understand how aerosols interact with clouds and how they impact climate. I also work with modelers to diagnose the cause of model biases in order to address deficiencies in model processes.

Publication: Chang et al. (2025), Chang et al. (2023)

Radiative Transfer Modeling

Modeling the transport of electromagnetic waves in the atmosphere is needed to quantify the Earth's energy budget. I use radiative transfer models to simulate how aerosols and clouds affect narrowband and broadband irrandiance/radiance from the top of the atmosphere down to the Earth's surface.

Publication: Chang et al. (2025), Chang et al. (2017)

Precipitation

Precipitation distributions and rates serve as one of the key climate change indicators. I use global satellite precipitation data to study rainfall climatology associated with storm systems and how they are related to various meteorological parameters.

Publication: Chang et al. (2014)

Air Quality and Atmospheric Chemistry

Air pollution satellites enable large-scale studies of pollutants such as trace gases. Here is an article that my student, Justina Arena, wrote under my supervision in NSF's Research Experiences for Undergraduates (REU) summer program. We compared regional particulate matter and trace gas distributions before, during, and after the COVID-19 lockdown.

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