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NWS partners’ preferences, perceptions, and uses of probabilistic winter forecast information: results of a Central Region-wide survey

CITE Title : NWS partners’ preferences, perceptions, and uses of probabilistic winter forecast information: results of a Central Region-wide survey Personal Author(s) : Rogers, Peter J.;Serr, Kelly;Deitsch, Kevin;Schumacher, Philip N.;Demuth, Julie L.;Prestley, Robert;Wirz, Christopher D.; Corporate Authors(s) : United States. National Weather Service. Central Region.;National Center for Atmospheric Research (U.S.); Published Date : 2023 DOI : https://doi.org/10.25923/5n5j-0x24 Rogers, Peter J. et al. (2023). NWS partners’ preferences, perceptions, and uses of probabilistic winter forecast information: results of a Central Region-wide survey. https://doi.org/10.25923/5n5j-0x24 Rogers, Peter J. et al. "NWS partners’ preferences, perceptions, and uses of probabilistic winter forecast information: results of a Central Region-wide survey" (2023), https://doi.org/10.25923/5n5j-0x24 Rogers, Peter J. et al. "NWS partners’ preferences, perceptions, and uses of probabilistic winter forecast information: results of a Central Region-wide survey" , 2023, https://doi.org/10.25923/5n5j-0x24 Export RIS Citation Information.

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Rogers, Peter J. ;

Serr, Kelly

2023

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This report summarizes results from a survey of National Weather Service (NWS) partners about their perspectives on probabilistic forecast information...
Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School

CITE Title : Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School Personal Author(s) : McGovern, Amy;Gagne, David John;Wirz, Christopher D.;Ebert-Uphoff, Imme;Bostrom, Ann;Rao, Yuhan;Schumacher, Andrea;Flora, Montgomery;Chase, Randy;Mamalakis, Antonios;McGraw, Marie;Lagerquist, Ryan;Redmon, Robert J.;Peterson, Taysia; Published Date : 2023 Source : Bulletin of the American Meteorological Society (2023) DOI : https://doi.org/10.1175/BAMS-D-22-0225.1 Journal Title : Bulletin of the American Meteorological Society McGovern, Amy et al. (2023). Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School. https://doi.org/10.1175/BAMS-D-22-0225.1 McGovern, Amy et al. "Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School" (2023), https://doi.org/10.1175/BAMS-D-22-0225.1 McGovern, Amy et al. "Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School" , 2023, https://doi.org/10.1175/BAMS-D-22-0225.1 Export RIS Citation Information.

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McGovern, Amy ;

Gagne, David John

2023 | Bulletin of the American Meteorological Society (2023)

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Many of our generation’s most pressing environmental science problems are wicked problems, which means they cannot be cleanly isolated and solved wi...
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.

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McGovern, Amy

;

Ebert‐Uphoff, Imme

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

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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.

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Bostrom, Ann

;

Demuth, Julie L.

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

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Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for tr...
National Weather Service (NWS) Forecasters’ Perceptions of AI/ML and Its Use in Operational Forecasting

CITE Title : National Weather Service (NWS) Forecasters’ Perceptions of AI/ML and Its Use in Operational Forecasting Personal Author(s) : Wirz, Christopher D.;Demuth, Julie L.;Cains, Mariana G.;White, Miranda;Radford, Jacob;Bostrom, Ann; Published Date : 2024 Source : Bulletin of the American Meteorological Society, 105(11), E2194-E2215 DOI : https://doi.org/10.1175/bams-d-24-0044.1 Journal Title : Bulletin of the American Meteorological Society Wirz, Christopher D. et al. (2024). National Weather Service (NWS) Forecasters’ Perceptions of AI/ML and Its Use in Operational Forecasting. 105(11). https://doi.org/10.1175/bams-d-24-0044.1 Wirz, Christopher D. et al. "National Weather Service (NWS) Forecasters’ Perceptions of AI/ML and Its Use in Operational Forecasting" 105, no. 11 (2024), https://doi.org/10.1175/bams-d-24-0044.1 Wirz, Christopher D. et al. "National Weather Service (NWS) Forecasters’ Perceptions of AI/ML and Its Use in Operational Forecasting" vol. 105, no. 11, 2024, https://doi.org/10.1175/bams-d-24-0044.1 Export RIS Citation Information.

:

Wirz, Christopher D.

;

Demuth, Julie L.

2024 | Bulletin of the American Meteorological Society, 105(11), E2194-E2215

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Artificial intelligence and machine learning (AI/ML) have attracted a great deal of attention from the atmospheric science community. The explosion of...
Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

CITE Title : Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods Personal Author(s) : Wirz, Christopher D.;Sutter, Carly;Demuth, Julie L.;Mayer, Kirsten J.;Chapman, William E.;Cains, Mariana Goodall;Radford, Jacob;Przybylo, Vanessa;Evans, Aaron;Martin, Thomas;Gaudet, Lauriana C.;Sulia, Kara;Bostrom, Ann;Gagne, David John;Bassill, Nick;Schumacher, Andrea;Thorncroft, Christopher; Published Date : 2024 Source : Earth and Space Science, 11(7) DOI : https://doi.org/10.1029/2023ea003364 Journal Title : Earth and Space Science Wirz, Christopher D. et al. (2024). Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods. 11(7). https://doi.org/10.1029/2023ea003364 Wirz, Christopher D. et al. "Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods" 11, no. 7 (2024), https://doi.org/10.1029/2023ea003364 Wirz, Christopher D. et al. "Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods" vol. 11, no. 7, 2024, https://doi.org/10.1029/2023ea003364 Export RIS Citation Information.

:

Wirz, Christopher D.

;

Sutter, Carly

2024 | Earth and Space Science, 11(7)

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Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge ...
Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness

CITE Title : Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness Personal Author(s) : Cains, Mariana G.;Wirz, Christopher D.;Demuth, Julie L.;Bostrom, Ann;Gagne, David John;McGovern, Amy;Sobash, Ryan A.;Madlambayan, Deianna; Published Date : 2024 Source : Weather and Forecasting, 39(8), 1219-1241 DOI : https://doi.org/10.1175/WAF-D-23-0180.1 Journal Title : Weather and Forecasting Cains, Mariana G. et al. (2024). Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness. 39(8). https://doi.org/10.1175/WAF-D-23-0180.1 Cains, Mariana G. et al. "Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness" 39, no. 8 (2024), https://doi.org/10.1175/WAF-D-23-0180.1 Cains, Mariana G. et al. "Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness" vol. 39, no. 8, 2024, https://doi.org/10.1175/WAF-D-23-0180.1 Export RIS Citation Information.

:

Cains, Mariana G.

;

Wirz, Christopher D.

2024 | Weather and Forecasting, 39(8), 1219-1241

:

As artificial intelligence (AI) methods are increasingly used to develop new guidance intended for operational use by forecasters, it is critical to e...