Artificial Intelligence for Earth System Predictability (AI4ESP) (2021 Workshop Report)

Technical Report · Thu Sep 01 00:00:00 EDT 2022

DOI:https://doi.org/10.2172/1888810· OSTI ID:1888810

Hickmon, Nicki L. ^[1]; Varadharajan, Charuleka ^[2]; Hoffman, Forrest M. ^[3]; Wainwright, Haruko M. ^[4]; Collis, Scott ^[1]

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1. Argonne National Lab. (ANL), Argonne, IL (United States)
2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
4. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

In October 2021, the U.S. Department of Energy (DOE) welcomed participants to the Artificial Intelligence for Earth System Predictability (AI4ESP) Workshop, hosted by the Office of Biological and Environmental Research (BER)—Advanced Scientific Computing Research (ASCR). The workshop is part of BER-ASCR’s ambition to more radically and aggressively advance prediction capabilities in the climate, Earth, and environmental sciences through the use of modern data analytics and artificial intelligence (AI). Advances in these capabilities are needed to improve predictions of climate change and extreme events that provide actionable information for planning and building resilience to their impacts.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1888810
• Report Number(s): ANL-22/54; 177828
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
97 MATHEMATICS AND COMPUTING