Last Updated: August 26, 2021
Our research focuses on better understanding the chemical composition of the atmosphere, its perturbation by human activity, and the implications for life on Earth. We use advanced models of atmospheric composition to interpret observations from satellites, aircraft, ground networks, and other platforms. We view our models as part of an integrated observing system to increase fundamental knowledge and address pressing environmental issues.
We have a large number of ongoing projects at any given time, addressing broad research themes and organized in subgroups as described further below. In addition to these research-focused subgroups, we have three other organized subgroups:
- Machine Learning & Data Science (MLDS) subgroup - for discussing MLDS applications to atmospheric chemistry research. Leaders: Daniel Varon, Makoto Kelp, and Drew Pendergrass
- Diversity, Inclusion, and Belonging (DIB) subgroup - for continually improving our practices. Leaders: Eimy Bonilla and Hannah Nesser
- GEOS-Chem Support Team - responsible for development and support of the GEOS-Chem model.