Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Mooers, Griffin"'
Autor:
Kochkov, Dmitrii, Yuval, Janni, Langmore, Ian, Norgaard, Peter, Smith, Jamie, Mooers, Griffin, Klöwer, Milan, Lottes, James, Rasp, Stephan, Düben, Peter, Hatfield, Sam, Battaglia, Peter, Sanchez-Gonzalez, Alvaro, Willson, Matthew, Brenner, Michael P., Hoyer, Stephan
General circulation models (GCMs) are the foundation of weather and climate prediction. GCMs are physics-based simulators which combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes such as cloud for
Externí odkaz:
http://arxiv.org/abs/2311.07222
Despite the importance of quantifying how the spatial patterns of extreme precipitation will change with warming, we lack tools to objectively analyze the storm-scale outputs of modern climate models. To address this gap, we develop an unsupervised m
Externí odkaz:
http://arxiv.org/abs/2211.01613
Autor:
Mooers, Griffin, Pritchard, Mike, Beucler, Tom, Srivastava, Prakhar, Mangipudi, Harshini, Peng, Liran, Gentine, Pierre, Mandt, Stephan
Global Storm-Resolving Models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult to quantify objective differences in how GSRMs resolve complex atmosph
Externí odkaz:
http://arxiv.org/abs/2208.11843
Understanding the details of small-scale convection and storm formation is crucial to accurately represent the larger-scale planetary dynamics. Presently, atmospheric scientists run high-resolution, storm-resolving simulations to capture these kilome
Externí odkaz:
http://arxiv.org/abs/2112.01221
Autor:
Mooers, Griffin, Pritchard, Mike, Beucler, Tom, Ott, Jordan, Yacalis, Galen, Baldi, Pierre, Gentine, Pierre
We explore the potential of feed-forward deep neural networks (DNNs) for emulating cloud superparameterization in realistic geography, using offline fits to data from the Super Parameterized Community Atmospheric Model. To identify the network archit
Externí odkaz:
http://arxiv.org/abs/2010.12996
While cloud-resolving models can explicitly simulate the details of small-scale storm formation and morphology, these details are often ignored by climate models for lack of computational resources. Here, we explore the potential of generative modeli
Externí odkaz:
http://arxiv.org/abs/2007.01444
Autor:
Mooers, Griffin1 (AUTHOR) gmooers96@gmail.com, Pritchard, Mike1 (AUTHOR), Beucler, Tom2 (AUTHOR), Srivastava, Prakhar3 (AUTHOR), Mangipudi, Harshini3 (AUTHOR), Peng, Liran1 (AUTHOR), Gentine, Pierre4 (AUTHOR), Mandt, Stephan3 (AUTHOR)
Publikováno v:
Scientific Reports. 12/15/2023, Vol. 13 Issue 1, p1-15. 15p.
Akademický článek
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Publikováno v:
Journal of Applied Meteorology and Climatology, 2020 Mar 01. 59(3), 551-565.
Externí odkaz:
https://www.jstor.org/stable/26935921
Autor:
Mooers, Griffin1,2 (AUTHOR) gmooers96@gmail.com, Pritchard, Michael1 (AUTHOR), Beucler, Tom1 (AUTHOR), Ott, Jordan1,2 (AUTHOR), Yacalis, Galen3 (AUTHOR), Baldi, Pierre2 (AUTHOR), Gentine, Pierre4 (AUTHOR)
Publikováno v:
Journal of Advances in Modeling Earth Systems. May2021, Vol. 13 Issue 5, p1-26. 26p.