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    A Mental Models Study of Hurricane Forecast and Warning Production, Communication, and Decision-Making 

    Source: Weather, Climate, and Society:;2015:;volume( 008 ):;issue: 002:;page 111
    Author(s): Bostrom, Ann; Morss, Rebecca E.; Lazo, Jeffrey K.; Demuth, Julie L.; Lazrus, Heather; Hudson, Rebecca
    Publisher: American Meteorological Society
    Abstract: he study reported here explores how to enhance the public value of hurricane forecast and warning information by examining the entire warning process. A mental models research approach is applied to address three risk ...
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    Identifying and Categorizing Bias in AI/ML for Earth Sciences 

    Source: Bulletin of the American Meteorological Society:;2024:;volume( 105 ):;issue: 003:;page E567
    Author(s): McGovern, Amy; Bostrom, Ann; McGraw, Marie; Chase, Randy J.; Gagne, David John; Ebert-Uphoff, Imme; Musgrave, Kate D.; Schumacher, Andrea
    Publisher: American Meteorological Society
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    Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School 

    Source: Bulletin of the American Meteorological Society:;2023:;volume( 104 ):;issue: 006:;page E1222
    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
    Publisher: American Meteorological Society
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    Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness 

    Source: Weather and Forecasting:;2024:;volume( 039 ):;issue: 008:;page 1219
    Author(s): Cains, Mariana G.; Wirz, Christopher D.; Demuth, Julie L.; Bostrom, Ann; Gagne, David John; McGovern, Amy; Sobash, Ryan A.; Madlambayan, Deianna
    Publisher: American Meteorological Society
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