Weather Research and Forecasting Innovation Act (

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

Narrow Results:

2024 2
2023 1
2022 2
2021 1
2017 1

Journal Article 7

1 - 7 of 7 Results

Refine Results

Refine Results:

Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences

CITE Title : Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences Personal Author(s) : Boukabara, Sid-Ahmed;Krasnopolsky, Vladimir;Penny, Stephen G.;Stewart, Jebb Q.;McGovern, Amy;Hall, David;Ten Hoeve, John E.;Hickey, Jason;Allen Huang, Hung-Lung;Williams, John K.;Ide, Kayo;Tissot, Philippe;Haupt, Sue Ellen;Casey, Kenneth S.;Oza, Nikunj;Geer, Alan J.;Maddy, Eric S.;Hoffman, Ross N.; Published Date : 2021 Source : Bulletin of the American Meteorological Society, 102(5) DOI : https://doi.org/10.1175/BAMS-D-20-0031.1 Journal Title : Bulletin of the American Meteorological Society Boukabara, Sid-Ahmed et al. (2021). Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences. 102(5). https://doi.org/10.1175/BAMS-D-20-0031.1 Boukabara, Sid-Ahmed et al. "Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences" 102, no. 5 (2021), https://doi.org/10.1175/BAMS-D-20-0031.1 Boukabara, Sid-Ahmed et al. "Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences" vol. 102, no. 5, 2021, https://doi.org/10.1175/BAMS-D-20-0031.1 Export RIS Citation Information.

:

Boukabara, Sid-Ahmed ;

Krasnopolsky, Vladimir

2021 | Bulletin of the American Meteorological Society, 102(5)

:

Promising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of c...
The History and Practice of AI in the Environmental Sciences

CITE Title : The History and Practice of AI in the Environmental Sciences Personal Author(s) : Haupt, Sue Ellen;Gagne, David John;Hsieh, William W.;Krasnopolsky, Vladimir;McGovern, Amy;Marzban, Caren;Moninger, William;Lakshmanan, Valliappa;Tissot, Philippe;Williams, John K.; Published Date : 2022 Source : Bulletin of the American Meteorological Society, 103(5), E1351-E1370 DOI : https://doi.org/10.1175/bams-d-20-0234.1 Journal Title : Bulletin of the American Meteorological Society Haupt, Sue Ellen et al. (2022). The History and Practice of AI in the Environmental Sciences. 103(5). https://doi.org/10.1175/bams-d-20-0234.1 Haupt, Sue Ellen et al. "The History and Practice of AI in the Environmental Sciences" 103, no. 5 (2022), https://doi.org/10.1175/bams-d-20-0234.1 Haupt, Sue Ellen et al. "The History and Practice of AI in the Environmental Sciences" vol. 103, no. 5, 2022, https://doi.org/10.1175/bams-d-20-0234.1 Export RIS Citation Information.

:

Haupt, Sue Ellen ;

Gagne, David John

2022 | Bulletin of the American Meteorological Society, 103(5), E1351-E1370

:

Artificial intelligence (AI) and machine learning (ML) have become important tools for environmental scientists and engineers, both in research and in...
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather

CITE Title : Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather Personal Author(s) : McGovern, Amy;Elmore, Kimberly L.;Gagne, David John;Haupt, Sue Ellen;Karstens, Christopher D.;Lagerquist, Ryan;Smith, Travis;Williams, John K.; Published Date : 2017 Source : Bulletin of the American Meteorological Society, 98(10), 2073-2090 DOI : https://doi.org/10.1175/BAMS-D-16-0123.1 Journal Title : Bulletin of the American Meteorological Society McGovern, Amy et al. (2017). Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather. 98(10). https://doi.org/10.1175/BAMS-D-16-0123.1 McGovern, Amy et al. "Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather" 98, no. 10 (2017), https://doi.org/10.1175/BAMS-D-16-0123.1 McGovern, Amy et al. "Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather" vol. 98, no. 10, 2017, https://doi.org/10.1175/BAMS-D-16-0123.1 Export RIS Citation Information.

:

McGovern, Amy ;

Elmore, Kimberly L.

2017 | Bulletin of the American Meteorological Society, 98(10), 2073-2090

:

High-impact weather events, such as severe thunderstorms, tornadoes, and hurricanes, cause significant disruptions to infrastructure, property loss, a...
NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)

CITE Title : NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) Personal Author(s) : McGovern, Amy;Bostrom, Ann;Davis, Phillip;Demuth, Julie L.;Ebert-Uphoff, Imme;He, Ruoying;Hickey, Jason;Gagne II, David John;Snook, Nathan;Stewart, Jebb Q.;Thorncroft, Christopher;Tissot, Philippe;Williams, John K.; Published Date : 2022 Source : Bulletin of the American Meteorological Society, 103(7), E1658-E1668 DOI : https://doi.org/10.1175/bams-d-21-0020.1 Journal Title : Bulletin of the American Meteorological Society McGovern, Amy et al. (2022). NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). 103(7). https://doi.org/10.1175/bams-d-21-0020.1 McGovern, Amy et al. "NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)" 103, no. 7 (2022), https://doi.org/10.1175/bams-d-21-0020.1 McGovern, Amy et al. "NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)" vol. 103, no. 7, 2022, https://doi.org/10.1175/bams-d-21-0020.1 Export RIS Citation Information.

:

McGovern, Amy ;

Bostrom, Ann

2022 | Bulletin of the American Meteorological Society, 103(7), E1658-E1668

:

We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). ...
AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography

CITE Title : AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography Personal Author(s) : McGovern, Amy;Ebert‐Uphoff, Imme;Barnes, Elizabeth A.;Bostrom, Ann;Cains, Mariana G.;Davis, Phillip;Demuth, Julie L.;Diochnos, Dimitrios I.;Fagg, Andrew H.;Tissot, Philippe;Williams, John K.;Wirz, Christopher D.; Published Date : 2024 Source : AI Magazine, 45(1), 105-110 DOI : https://doi.org/10.1002/aaai.12160 Journal Title : AI Magazine McGovern, Amy et al. (2024). AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography. 45(1). https://doi.org/10.1002/aaai.12160 McGovern, Amy et al. "AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography" 45, no. 1 (2024), https://doi.org/10.1002/aaai.12160 McGovern, Amy et al. "AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography" vol. 45, no. 1, 2024, https://doi.org/10.1002/aaai.12160 Export RIS Citation Information.

:

McGovern, Amy

;

Ebert‐Uphoff, Imme

2024 | AI Magazine, 45(1), 105-110

:

The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) focuses on creating trustworthy AI for a var...
Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences

CITE Title : Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences Personal Author(s) : Bostrom, Ann;Demuth, Julie L.;Wirz, Christopher D.;Cains, Mariana G.;Schumacher, Andrea;Madlambayan, Deianna;Bansal, Akansha Singh;Bearth, Angela;Chase, Randy;Crosman, Katherine M.;Ebert‐Uphoff, Imme;Gagne, David John;Guikema, Seth;Hoffman, Robert;Johnson, Branden B.;Kumler‐Bonfanti, Christina;Lee, John D.;Lowe, Anna;McGovern, Amy;Przybylo, Vanessa;Radford, Jacob T.;Roth, Emilie;Sutter, Carly;Tissot, Philippe;Roebber, Paul;Stewart, Jebb Q.;White, Miranda;Williams, John K.; Published Date : 2023 Source : Risk Analysis, 44(6), 1498-1513 DOI : https://doi.org/10.1111/risa.14245 Journal Title : Risk Analysis Bostrom, Ann et al. (2023). Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences. 44(6). https://doi.org/10.1111/risa.14245 Bostrom, Ann et al. "Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences" 44, no. 6 (2023), https://doi.org/10.1111/risa.14245 Bostrom, Ann et al. "Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences" vol. 44, no. 6, 2023, https://doi.org/10.1111/risa.14245 Export RIS Citation Information.

:

Bostrom, Ann

;

Demuth, Julie L.

2023 | Risk Analysis, 44(6), 1498-1513

:

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for tr...
Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations, and the Warn-on-Forecast System

CITE Title : Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations, and the Warn-on-Forecast System Personal Author(s) : Schmidt, Tobias G.;McGovern, Amy;Allen, John T.;Potvin, Corey K.;Chase, Randy J.;Wiley, Chad M.;McGovern-Fagg, William R.;Flora, Montgomery L.;Homeyer, Cameron R.;Williams, John K.; Published Date : 2024 Source : Artificial Intelligence for the Earth Systems (2024) DOI : https://doi.org/10.1175/aies-d-24-0026.1 Journal Title : Artificial Intelligence for the Earth Systems Schmidt, Tobias G. et al. (2024). Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations, and the Warn-on-Forecast System. https://doi.org/10.1175/aies-d-24-0026.1 Schmidt, Tobias G. et al. "Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations, and the Warn-on-Forecast System" (2024), https://doi.org/10.1175/aies-d-24-0026.1 Schmidt, Tobias G. et al. "Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations, and the Warn-on-Forecast System" , 2024, https://doi.org/10.1175/aies-d-24-0026.1 Export RIS Citation Information.

:

Schmidt, Tobias G. ;

McGovern, Amy

2024 | Artificial Intelligence for the Earth Systems (2024)

:

Hailstorms cause billions of dollars in damage across the United States each year. Part of this cost could be reduced by increasing warning lead times...