Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Amy McGovern"'
Autor:
Amy McGovern, Julie Demuth, Ann Bostrom, Christopher D. Wirz, Philippe E. Tissot, Mariana G. Cains, Kate D. Musgrave
Publikováno v:
npj Natural Hazards, Vol 1, Iss 1, Pp 1-6 (2024)
Abstract Artificial Intelligence applications are rapidly expanding across weather, climate, and natural hazards. AI can be used to assist with forecasting weather and climate risks, including forecasting both the chance that a hazard will occur and
Externí odkaz:
https://doaj.org/article/99c1ee6c4ae84764bba11786db116a00
Publikováno v:
Environmental Data Science, Vol 1 (2022)
Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods across all aspects of environmental sciences, it is imperative that we initiate a discussion about the ethical and responsible use of AI. In fact, much can be lea
Externí odkaz:
https://doaj.org/article/5cd6fa24aaca46afbab6c73cf1796649
Publikováno v:
Artificial Intelligence for the Earth Systems. :1-56
We present and evaluate a deep learning first-guess front identification system that identifies cold, warm, stationary, and occluded fronts. Frontal boundaries play a key role in the daily weather around the world. Human-drawn fronts provided by the
Autor:
Amy McGovern, Randy J. Chase, Montgomery Flora, David J. Gagne, Ryan Lagerquist, Corey K. Potvin, Nathan Snook, Eric Loken
Publikováno v:
Artificial Intelligence for the Earth Systems. :1-61
We present an overviewof recentwork on using artificial intelligence/machine learning techniques for forecasting convective weather and its associated hazards, including tornadoes, hail, wind, and lightning. These high-impact phenomena globally cause
Autor:
Jerald A. Brotzge, Don Berchoff, DaNa L. Carlis, Frederick H. Carr, Rachel Hogan Carr, Jordan J. Gerth, Brian D. Gross, Thomas M. Hamill, Sue Ellen Haupt, Neil Jacobs, Amy McGovern, David J. Stensrud, Gary Szatkowski, Istvan Szunyogh, Xuguang Wang
Publikováno v:
Bulletin of the American Meteorological Society. 104:E698-E705
Autor:
Amy McGovern, Ann Bostrom, Phillip Davis, Julie L. Demuth, Imme Ebert-Uphoff, Ruoying He, Jason Hickey, David John Gagne II, Nathan Snook, Jebb Q. Stewart, Christopher Thorncroft, Philippe Tissot, John K. Williams
Publikováno v:
Bulletin of the American Meteorological Society. 103:E1658-E1668
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 foundationa
Autor:
Amy McGovern, David John Gagne, Christopher D. Wirz, Imme Ebert-Uphoff, Ann Bostrom, Yuhan Rao, Andrea Schumacher, Montgomery Flora, Randy Chase, Antonios Mamalakis, Marie McGraw, Ryan Lagerquist, Robert J. Redmon, Taysia Peterson
Publikováno v:
Bulletin of the American Meteorological Society.
Many of our generation’s most pressing environmental science problems are wicked problems, which means they cannot be cleanly isolated and solved with a single ‘correct’ answer (e.g., Rittel 1973; Wirz 2021). The NSF AI Institute for Research o
Autor:
Shelley Stall, Guido Cervone, Caroline Coward, Joel Cutcher-Gershenfeld, Thomas J Donaldson, Chris Erdmann, R. Brooks Hanson, Jeanne Holm, John Leslie King, Laura Lyon, Delia Pembrey MacNamara, Amy McGovern, Ryan McGranaghan, Ayris A. Narock, Micaela S. Parker, Ge Peng, Yuhan \\'Douglas\\' Rao, Erin Ryan, Brian Sedora, Shashi Shekhar, Kristina Vrouwenvelder, Lance A. Waller, Christopher D. Wirz, AGU AI/ML Ethics Workshop Participants
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::971a2d3a6d0b2aa6c7f227ce4516fc89
https://doi.org/10.22541/essoar.168132856.66485758/v1
https://doi.org/10.22541/essoar.168132856.66485758/v1
Publikováno v:
Weather and Forecasting. 37:871-899
Recent research has shown that random forests (RFs) can create skillful probabilistic severe weather hazard forecasts from numerical weather prediction (NWP) ensemble data. However, it remains unclear how RFs use NWP data and how predictors should be
Autor:
Sue Ellen Haupt, David John Gagne, William W. Hsieh, Vladimir Krasnopolsky, Amy McGovern, Caren Marzban, William Moninger, Valliappa Lakshmanan, Philippe Tissot, John K. Williams
Publikováno v:
Bulletin of the American Meteorological Society. 103:E1351-E1370
Artificial intelligence (AI) and machine learning (ML) have become important tools for environmental scientists and engineers, both in research and in applications. Although these methods have become quite popular in recent years, they are not new. T