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Earth's terrestrial biosphere currently absorbs one-third of anthropogenic CO2 emissions, thereby mitigating impacts of climate change. Earth System Models project that land will continue to act as a carbon sink, but the strength of this sink is subject to significant uncertainties. Reducing these uncertainties is essential for scientific purposes and supports global climate change policies. The rapid advancement of machine learning, coupled with accelerating computational speed and increasing global earth observations, creates new opportunities for advancing earth system modeling. Our group's research supports the evaluation and development of the Canadian Earth System Model.
Queen's School of Computing • Kingston, ON, Canada
Teaching and conducting research in Climate Modeling, Earth System Modeling, and Machine Learning.
Department of Computing offers research-based, project-based, and course-based patterns.