Zobrazeno 1 - 4
of 4
pro vyhledávání: '"David John Gagne II"'
Autor:
Christopher D. Wirz, Carly Sutter, Julie L. Demuth, Kirsten J. Mayer, William E. Chapman, Mariana Goodall Cains, Jacob Radford, Vanessa Przybylo, Aaron Evans, Thomas Martin, Lauriana C. Gaudet, Kara Sulia, Ann Bostrom, David John Gagne II, Nick Bassill, Andrea Schumacher, Christopher Thorncroft
Publikováno v:
Earth and Space Science, Vol 11, Iss 7, Pp n/a-n/a (2024)
Abstract Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they i
Externí odkaz:
https://doaj.org/article/e829cabd53eb47d19b26de2fe0d6faa8
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 3, Pp n/a-n/a (2020)
Abstract Stochastic parameterizations account for uncertainty in the representation of unresolved subgrid processes by sampling from the distribution of possible subgrid forcings. Some existing stochastic parameterizations utilize data‐driven appro
Externí odkaz:
https://doaj.org/article/4b5d235976db471c90734b5f35c84ca0
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
Publikováno v:
Monthly Weather Review.
An ensemble precipitation forecast post-processing method is proposed by hybridizing the Analog Ensemble (AnEn), Minimum Divergence Schaake Shuffle (MDSS), and Convolutional Neural Network (CNN) methods. This AnEn-CNN hybrid takes the ensemble mean o