Deep Learning for Subgrid‐Scale Turbulence Modeling in Large‐Eddy Simulations of the Convective Atmospheric Boundary Layer
Abstract In large‐eddy simulations, subgrid‐scale (SGS) processes are parameterized as a function of filtered grid‐scale variables. First‐order, algebraic SGS models are based on the eddy‐viscosity assumption, which does not always hold for turbulence. Here we apply supervised deep neural networks (...
Gorde:
| Egile Nagusiak: | , , , , , , , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
American Geophysical Union (AGU)
2022-05-01
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| Saila: | Journal of Advances in Modeling Earth Systems |
| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1029/2021MS002847 |
| Etiketak: |
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