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Completed TRL 3 (started at 2, targeting 3)
Current and future greenhouse gas emissions will have a profound impact on the future state of our climate. As such, quantifying their emissions is critically important for both projecting future climate and assessing the impact of environmental policy. Many of the human-caused greenhouse gas emissions come from point sources. Observing and quantifying these sources necessitates densely spaced measurements. In response to this, there has been a proliferation of dense observing systems (e.g., geostationary satellites) that allow us to study these sources. However, it becomes computationally intractable to relate the observations back to the sources for these dense observing systems. This project aims to develop a computationally efficient emulator of a full-physics model, allowing us to fully utilize the measurements from these dense observing systems. The combination of these of dense observing systems and our high-fidelity emulator will allow us to study greenhouse gas point sources that are critically important for future climate.
Due to the proliferation of dense observing systems such as geostationary satellites, this project will advance the tools needed to interpret dense observations related to surface sensitivity. These advancements will allow researchers to address evolving scientific questions about emissions from point sources, which is critically important for future climate.
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