Predicting the Future of the Earth With Artificial Intelligence

 
Published: 25 October 2021

AI offers additional possibilities, greater accuracy for climate models

The original release appeared on the Argonne National Laboratory website.

AI4ESP is multi-lab initiative working with the Earth and Environmental Systems Science Division (EESSD) of the Office of Biological and Environmental Research (BER) to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence across field, lab, modeling, and analysis activities.
AI4ESP is multi-lab initiative working with the Earth and Environmental Systems Science Division (EESSD) of the Office of Biological and Environmental Research (BER) to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence across field, lab, modeling, and analysis activities.

Computer simulations that scientists use to understand the evolution of the Earth’s climate offer a wealth of information to public officials and corporations planning for the future. However, climate models—no matter how complex or computationally intensive—do contain some degree of uncertainty. Addressing this uncertainty is proving increasingly important as decision makers are asking more complex questions and looking to smaller scales.

To improve climate simulations, scientists are looking to the potential of artificial intelligence (AI). AI has offered profound insights in fields from materials science to manufacturing, and climate researchers are excited to explore how AI can be used to revolutionize how the earth system, and especially its water cycle, can be simulated in order to dramatically improve our understanding and representation of the real world. In particular, AI offers the potential to dramatically increase the accuracy of predictions down to the scales of interest to scientists, and even stakeholders focused on designing, financing, and deploying equitable climate solutions to America’s most disadvantaged communities.

Motivated by this opportunity, the U.S. Department of Energy (DOE) is launching a comprehensive workshop: Artificial Intelligence for Earth System Predictability (AI4ESP). After the collection of more than 150 white papers from the scientific community, AI4ESP is kicking into high gear by hosting a workshop beginning October 25. The workshop will include 17 sessions over a six-week period designed to create a new scientific community that marries climate research with artificial intelligence, applied math, and supercomputing.

“Earth system predictability refers to the intersection of climate with hydrology, ecology, infrastructure, and human activities,” said Nicki Hickmon, an Argonne scientist, the DOE Atmospheric Radiation Measurement (ARM) user facility’s associate director for operations, and the lead for the AI4ESP workshop.

By linking researchers in earth system predictability and computer sciences, AI4ESP seeks to create a paradigm shift in simulating the earth system. AI4ESP seeks to inspire a new generation of AI algorithms specifically aimed at earth system predictability.

According to Hickmon, continuous improvements will enhance the ability of current simulations to provide deeper insights into community-scale issues and those involving extreme weather, potentially allowing stakeholders a better grasp of the uncertainties that surround such events.

“AI for climate is still in its infancy,” said Hickmon. ​“However, it is still essential that we explore the potential of AI to see how it can better inform our models and prepare us for the future.”

Click here to see the agenda and register for the workshop. The public is welcome to attend any of the open sessions. Some components of the workshop are invitation-only in order to gather the required materials for the workshop report.

The workshop is sponsored by DOE’s Biological and Environmental Research program and Office of Advanced Scientific Computing Research.

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This work was supported by the U.S. Department of Energy’s Office of Science, through the Biological and Environmental Research program as part of the Atmospheric System Research program.