CASUS Institute Seminar, Dr. Yunha Lee, Visiting Faculty, CASUS

Atmospheric models have been developed to resolve a target-spatiotemporal resolution (e.g., global vs. meso-scale). However, with recent advances in computing, models have been redesigned to bridge multi-scale phenomena and account for more complex systems. For example, global general circulation models became earth system models and grid sizes decreased from a few hundred kilometers to a few kilometers. Such substantial improvements make the modeling system become more advanced over time, but does the model prediction capability improve as well?

In this talk, Yunha will present her research efforts in achieving higher-accuracy models with a focus on air quality (esp. aerosols) applications in support of science-based public policy. She will present the following work in greater detail: (1) development and evaluation of the NASA GISS ModelE2-TOMAS, (2) decadal evaluation of a regional air quality forecasting system, and (3) ongoing machine learning-based surrogate modeling for air quality predictions. Yunha will conclude by sharing what she has learned from her research journey as well as what the future potential research directions are.

Due to a CASUS-related time conflict, the seminar had to be re-scheduled from 28 October 2021. Our apologies to all participants and especially to the speaker.