Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Van Roekel, Luke"'
Autor:
Sun, Yixuan, Cucuzzella, Elizabeth, Brus, Steven, Narayanan, Sri Hari Krishna, Nadiga, Balasubramanya, Van Roekel, Luke, Hückelheim, Jan, Madireddy, Sandeep, Heimbach, Patrick
Numerical models of the ocean and ice sheets are crucial for understanding and simulating the impact of greenhouse gases on the global climate. Oceanic processes affect phenomena such as hurricanes, extreme precipitation, and droughts. Ocean models r
Externí odkaz:
http://arxiv.org/abs/2404.09950
Autor:
Sun, Yixuan, Sowunmi, Ololade, Egele, Romain, Narayanan, Sri Hari Krishna, Van Roekel, Luke, Balaprakash, Prasanna
Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage the advanced search algorithms for multiobjective optimization in DeepHyper, a scalable hyperparameter optimization so
Externí odkaz:
http://arxiv.org/abs/2404.05768
Autor:
Sun, Yixuan, Cucuzzella, Elizabeth, Brus, Steven, Narayanan, Sri Hari Krishna, Nadiga, Balu, Van Roekel, Luke, Hückelheim, Jan, Madireddy, Sandeep
Modeling is crucial to understanding the effect of greenhouse gases, warming, and ice sheet melting on the ocean. At the same time, ocean processes affect phenomena such as hurricanes and droughts. Parameters in the models that cannot be physically m
Externí odkaz:
http://arxiv.org/abs/2311.08421
Autor:
Garanaik, Amrapalli, Pereira, Filipe, Smith, Katherine, Robey, Rachel, Li, Qing, Pearson, Brodie, Van Roekel, Luke
While various parameterizations of vertical turbulent fluxes at different levels of complexity have been proposed, each has its own limitations. For example, simple first-order closure schemes such as the K-Profile Parameterization (KPP) lack energet
Externí odkaz:
http://arxiv.org/abs/2212.08776
Critical point tracking is a core topic in scientific visualization for understanding the dynamic behavior of time-varying vector field data. The topological notion of robustness has been introduced recently to quantify the structural stability of cr
Externí odkaz:
http://arxiv.org/abs/2209.11708
Autor:
Shi, Neng, Xu, Jiayi, Wurster, Skylar W., Guo, Hanqi, Woodring, Jonathan, Van Roekel, Luke P., Shen, Han-Wei
We propose GNN-Surrogate, a graph neural network-based surrogate model to explore the parameter space of ocean climate simulations. Parameter space exploration is important for domain scientists to understand the influence of input parameters (e.g.,
Externí odkaz:
http://arxiv.org/abs/2202.08956
Autor:
Ikuyajolu, Olawale James1,2,3 (AUTHOR) olawale@lanl.gov, Van Roekel, Luke3 (AUTHOR), Brus, Steven R.4 (AUTHOR), Thomas, Erin E.3 (AUTHOR), Deng, Yi2 (AUTHOR), Benedict, James J.3 (AUTHOR)
Publikováno v:
Journal of Climate. May2024, Vol. 37 Issue 10, p3011-3036. 26p.
Akademický článek
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Autor:
Van Roekel, Luke P, Adcroft, Alistair J., Danabasoglu, Gokhan, Griffies, Stephen M., Kauffman, Brian, Large, William, Levy, Michael, Reichl, Brandon, Ringler, Todd, Schmidt, Martin
We evaluate the Community ocean Vertical Mixing (CVMix) project version of the K-profile parameterization (KPP). For this purpose, one-dimensional KPP simulations are compared across a suite of oceanographically relevant regimes against large eddy si
Externí odkaz:
http://arxiv.org/abs/1710.02558
Autor:
Orbe, Clara, Van Roekel, Luke, Adames, Ángel F., Dezfuli, Amin, Fasullo, John, Gleckler, Peter J., Lee, Jiwoo, Li, Wei, Nazarenko, Larissa, Schmidt, Gavin A., Sperber, Kenneth R., Zhao, Ming
Publikováno v:
Journal of Climate, 2020 Sep 01. 33(17), 7591-7617.
Externí odkaz:
https://www.jstor.org/stable/26938034