Seminar: “Climate Models Are Good; Can AI Make Them Better?”

Christopher Bretherton, professor emeritus of the atmospheric science and applied mathematics departments at the University of Washington, will present “Climate Models Are Good; Can AI Make Them Better?” This seminar is open to the public.

Climate and earth system models are our most sophisticated scientific tools for understanding and predicting climate change. However, these models make a range of predictions about the sensitivity of temperature and regional precipitation to increases in greenhouse gases, leading some to doubt their credibility. This talk will review the science behind why some aspects of climate model predictions are intrinsically more robust than others. Bretherton will also introduce a new generation of computer models that add local detail to reduce the uncertainties of current climate models but whose large computational expense may prohibit routine use. Lastly, he will discuss how researchers can use machine learning to affordably translate the simulations of new-generation computer models to better inform location-specific decision-making as societies try to adapt to climate change in the upcoming decades.

This event is part of the Highlight Seminar Series organized by the Andlinger Center for Energy and the Environment (ACEE) and co-sponsored by the High Meadows Environmental Institute (HMEI).

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Seminar: “Climate Models Are Good; Can AI Make Them Better?”

Event Date

Thu, Nov 10, 2022 ・ 12:30 PM - 1:30 PM

Location

Maeder Hall- Andlinger Center for Energy and the Environment

Earth in space view

Christopher Bretherton, professor emeritus of the atmospheric science and applied mathematics departments at the University of Washington, will present “Climate Models Are Good; Can AI Make Them Better?” This seminar is open to the public.

Climate and earth system models are our most sophisticated scientific tools for understanding and predicting climate change. However, these models make a range of predictions about the sensitivity of temperature and regional precipitation to increases in greenhouse gases, leading some to doubt their credibility. This talk will review the science behind why some aspects of climate model predictions are intrinsically more robust than others. Bretherton will also introduce a new generation of computer models that add local detail to reduce the uncertainties of current climate models but whose large computational expense may prohibit routine use. Lastly, he will discuss how researchers can use machine learning to affordably translate the simulations of new-generation computer models to better inform location-specific decision-making as societies try to adapt to climate change in the upcoming decades.

This event is part of the Highlight Seminar Series organized by the Andlinger Center for Energy and the Environment (ACEE) and co-sponsored by the High Meadows Environmental Institute (HMEI).