NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)

Amy McGovern; Ann Bostrom; Phillip Davis; Julie L. Demuth; Imme Ebert-Uphoff; Ruoying He; Jason Hickey; David John Gagne; Nathan Snook; Jebb Q. Stewart; Christopher Thorncroft; Philippe Tissot; John K. Williams

doi:10.1175/BAMS-D-21-0020.1

NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)

Amy McGovern, Ann Bostrom, Phillip Davis, Julie L. Demuth, Imme Ebert-Uphoff, Ruoying He, Jason Hickey, David John Gagne, Nathan Snook, Jebb Q. Stewart, Christopher Thorncroft, Philippe Tissot, John K. Williams

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute was funded in 2020 as part of a new initiative from the NSF to advance foundational AI research across a wide variety of domains. To date AI2ES is the only NSF AI institute focusing on environmental science applications. Our institute focuses on developing trustworthy AI methods for weather, climate, and coastal hazards. The AI methods will revolutionize our understanding and prediction of high-impact atmospheric and ocean science phenomena and will be utilized by diverse, professional user groups to reduce risks to society. In addition, we are creating novel educational paths, including a new degree program at a community college serving underrepresented minorities, to improve workforce diversity for both AI and environmental science.

Original language	English
Pages (from-to)	E1658-E1668
Journal	Bulletin of the American Meteorological Society
Volume	103
Issue number	7
DOIs	https://doi.org/10.1175/BAMS-D-21-0020.1
State	Published - Jul 2022
Externally published	Yes

Keywords

Artificial intelligence
Atmosphere
Data science
Education
Ocean
Social Science

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10.1175/BAMS-D-21-0020.1

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McGovern, A., Bostrom, A., Davis, P., Demuth, J. L., Ebert-Uphoff, I., He, R., Hickey, J., Gagne, D. J., Snook, N., Stewart, J. Q., Thorncroft, C., Tissot, P., & Williams, J. K. (2022). NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). Bulletin of the American Meteorological Society, 103(7), E1658-E1668. https://doi.org/10.1175/BAMS-D-21-0020.1

@article{7611e8ef3be64ce2b2edf7272e429d78,

title = "NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)",

abstract = "We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute was funded in 2020 as part of a new initiative from the NSF to advance foundational AI research across a wide variety of domains. To date AI2ES is the only NSF AI institute focusing on environmental science applications. Our institute focuses on developing trustworthy AI methods for weather, climate, and coastal hazards. The AI methods will revolutionize our understanding and prediction of high-impact atmospheric and ocean science phenomena and will be utilized by diverse, professional user groups to reduce risks to society. In addition, we are creating novel educational paths, including a new degree program at a community college serving underrepresented minorities, to improve workforce diversity for both AI and environmental science.",

keywords = "Artificial intelligence, Atmosphere, Data science, Education, Ocean, Social Science",

author = "Amy McGovern and Ann Bostrom and Phillip Davis and Demuth, \{Julie L.\} and Imme Ebert-Uphoff and Ruoying He and Jason Hickey and Gagne, \{David John\} and Nathan Snook and Stewart, \{Jebb Q.\} and Christopher Thorncroft and Philippe Tissot and Williams, \{John K.\}",

note = "Publisher Copyright: {\textcopyright} 2022 American Meteorological Society.",

year = "2022",

month = jul,

doi = "10.1175/BAMS-D-21-0020.1",

language = "English",

volume = "103",

pages = "E1658--E1668",

journal = "Bulletin of the American Meteorological Society",

issn = "0003-0007",

publisher = "American Meteorological Society",

number = "7",

}

McGovern, A, Bostrom, A, Davis, P, Demuth, JL, Ebert-Uphoff, I, He, R, Hickey, J, Gagne, DJ, Snook, N, Stewart, JQ, Thorncroft, C, Tissot, P & Williams, JK 2022, 'NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)', Bulletin of the American Meteorological Society, vol. 103, no. 7, pp. E1658-E1668. https://doi.org/10.1175/BAMS-D-21-0020.1

TY - JOUR

T1 - NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)

AU - McGovern, Amy

AU - Bostrom, Ann

AU - Davis, Phillip

AU - Demuth, Julie L.

AU - Ebert-Uphoff, Imme

AU - He, Ruoying

AU - Hickey, Jason

AU - Gagne, David John

AU - Snook, Nathan

AU - Stewart, Jebb Q.

AU - Thorncroft, Christopher

AU - Tissot, Philippe

AU - Williams, John K.

PY - 2022/7

Y1 - 2022/7

N2 - We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute was funded in 2020 as part of a new initiative from the NSF to advance foundational AI research across a wide variety of domains. To date AI2ES is the only NSF AI institute focusing on environmental science applications. Our institute focuses on developing trustworthy AI methods for weather, climate, and coastal hazards. The AI methods will revolutionize our understanding and prediction of high-impact atmospheric and ocean science phenomena and will be utilized by diverse, professional user groups to reduce risks to society. In addition, we are creating novel educational paths, including a new degree program at a community college serving underrepresented minorities, to improve workforce diversity for both AI and environmental science.

AB - We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute was funded in 2020 as part of a new initiative from the NSF to advance foundational AI research across a wide variety of domains. To date AI2ES is the only NSF AI institute focusing on environmental science applications. Our institute focuses on developing trustworthy AI methods for weather, climate, and coastal hazards. The AI methods will revolutionize our understanding and prediction of high-impact atmospheric and ocean science phenomena and will be utilized by diverse, professional user groups to reduce risks to society. In addition, we are creating novel educational paths, including a new degree program at a community college serving underrepresented minorities, to improve workforce diversity for both AI and environmental science.

KW - Artificial intelligence

KW - Atmosphere

KW - Data science

KW - Education

KW - Ocean

KW - Social Science

UR - https://www.scopus.com/pages/publications/85134891326

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DO - 10.1175/BAMS-D-21-0020.1

M3 - Article

AN - SCOPUS:85134891326

SN - 0003-0007

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JO - Bulletin of the American Meteorological Society

JF - Bulletin of the American Meteorological Society

IS - 7

ER -

NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)

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