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A headshot of Elizabeth Barne, black-and-white and in front of a brick wall

Viewing Anthropogenic Change Through an AI Lens?

The seminar flyer of Elizabeth Barnes, all information is on the webpage

Prof. Elizabeth Barnes

Dept. of Atmospheric Science

Colorado State University

Monday January 31, 2022, 2 PM ET

 

Abstract:

Humans are vastly modifying the earth system, with identifiable impacts across the land surface, ocean and atmosphere. Here, we will explore three example applications of how explainable AI (XAI) techniques can help us visualize and quantify these changes over time. First, we will demonstrate how we can utilize XAI methods to quantify the footprint of human activity across the global land surface in near-real time. Second, we will demonstrate the utility of XAI for extracting forced climate patterns through time amidst a sea of climate noise and model disagreement. Third, we will show how XAI can help us better understand and predict temporal variations in decadal warming trends. All three parts of this talk serve as examples of how viewing our climate through an AI lens has the power to uncover new insights into anthropogenic change – allowing scientists to ask “why?” but now with the power of machine learning.

 

Biosketch:

Dr. Elizabeth (Libby) Barnes is an associate professor of Atmospheric Science at Colorado State University. She joined the CSU faculty in 2013 after obtaining dual B.S. degrees (Honors) in Physics and Mathematics from the University of Minnesota, obtaining her Ph.D. in Atmospheric Science from the University of Washington, and spending a year as a NOAA Climate & Global Change Fellow at the Lamont-Doherty Earth Observatory. Professor Barnes’ research is largely focused on climate variability and change and the data analysis tools used to understand it. Topics of interest include earth system predictability, jet-stream dynamics, Arctic-midlatitude connections, subseasonal-to-decadal (S2D) prediction, and data science methods for earth system research (e.g. machine learning, causal discovery). She teaches graduate courses on fundamental atmospheric dynamics and data science and statistical analysis methods. Professor Barnes is involved in a number of research community activities. In addition to being a member of the National Academies’s Committee on Earth Science and Applications from Space, a funded member of the NSF AI Institute for Research on Trustworthy AI in Weather, Climate and Coastal Oceanography (AI2ES), and on the Steering Committee of the CSU Data Science Research Institute, she recently finished being the lead of the NOAA MAPP S2S Prediction Task Force (2016-2020).

Dr. Barnes received the AGU Macelwane Medal and became a Fellow of the AGU in 2021, received the AGU Turco Lectureship for 2020, AMS Clarence Leroy Meisinger Award for 2020, and was awarded an NSF CAREER grant in 2018. She received the George T. Abell Outstanding Early-Career Faculty Award in 2016 and was recognized for her teaching and mentoring by being awarded an Honorable Mention for the CSU Graduate Advising and Mentorship Award in 2017 and being named the Outstanding Professor of the Year Award in 2016 by the graduate students of the Department of Atmospheric Science. In 2014 she was the recipient of an AGU James R. Holton Junior Scientist Award.

 

Webinar:

Webinar: https://go.umd.edu/barneswebinar

Event site: https://go.umd.edu/barnes

Webinar number: 2621 990 3014
Webinar password: essic

To join the audio conference only:

+1-202-860-2110 United States Toll (Washington D.C.)
+1-646-992-2010 United States Toll (New York City)

Global call-in numbers

 

For IT assistance:
Cazzy Medley: cazzy@umd.edu

Resources:

Seminar schedule & archive: https://go.umd.edu/essicseminar

Seminar Google calendar: https://go.umd.edu/essicseminarcalendar

Seminar recordings on Youtube: https://www.youtube.com/user/ESSICUMD

Date

Jan 31 2022

Time

2:00 pm - 3:00 pm
Category

Organizer

John Xun Yang
Email
jxyang@umd.edu