Articles | Volume 27, issue 2
https://doi.org/10.5194/npg-27-209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-27-209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Apr 2020
Research article |
| 16 Apr 2020
| 16 Apr 2020
Data-driven versus self-similar parameterizations for stochastic advection by Lie transport and location uncertainty
Valentin Resseguier
CORRESPONDING AUTHOR
Lab, SCALIAN DS, Espace Nobel, 2 Allée de Becquerel, 35700 Rennes, France
Wei Pan
Department of Mathematics, Imperial College London, London SW7 2AZ, UK
Baylor Fox-Kemper
Department of Earth, Environmental and Planetary Sciences (DEEPS), Brown University, Providence, RI 02912, USA
Institute at Brown for Environment and Society (IBES), Brown University, Providence, RI 02912, USA
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Cited
17 citations as recorded by crossref.
- Resolving and Parameterising the Ocean Mesoscale in Earth System Models H. Hewitt et al. 10.1007/s40641-020-00164-w
- Comparing two different types of stochastic parametrization in geophysical flow D. Holm et al. 10.1063/5.0238569
- Real-time estimation and prediction of unsteady flows using reduced-order models coupled with few measurements V. Resseguier et al. 10.1016/j.jcp.2022.111631
- Effects of Smooth Divergence-Free Flows on Tracer Gradients and Spectra: Eulerian Prognosis Description V. Resseguier et al. 10.1175/JPO-D-21-0014.1
- Solution properties of the incompressible Euler system with rough path advection D. Crisan et al. 10.1016/j.jfa.2022.109632
- Reduced data-driven turbulence closure for capturing long-term statistics R. Hoekstra et al. 10.1016/j.compfluid.2024.106469
- Data-driven stochastic spectral modeling for coarsening of the two-dimensional Euler equations on the sphere S. Ephrati et al. 10.1063/5.0156942
- Physically constrained covariance inflation from location uncertainty Y. Zhen et al. 10.5194/npg-30-237-2023
- Stochastic Modelling of Small-Scale Perturbation F. Flandoli & U. Pappalettera 10.3390/w12102950
- Quantifying Truncation-Related Uncertainties in Unsteady Fluid Dynamics Reduced Order Models V. Resseguier et al. 10.1137/19M1354819
- Data‐Driven Stochastic Lie Transport Modeling of the 2D Euler Equations S. Ephrati et al. 10.1029/2022MS003268
- Wave propagation in random two-dimensional turbulence: a multiscale approach V. Resseguier et al. 10.1017/jfm.2024.769
- Stochastic Data‐Driven Parameterization of Unresolved Eddy Effects in a Baroclinic Quasi‐Geostrophic Model L. Li et al. 10.1029/2022MS003297
- Bayesian inference for fluid dynamics: A case study for the stochastic rotating shallow water model O. Lang et al. 10.3389/fams.2022.949354
- Spatial Covariance Modeling for Stochastic Subgrid‐Scale Parameterizations Using Dynamic Mode Decomposition F. Gugole & C. Franzke 10.1029/2020MS002115
- New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics V. Resseguier et al. 10.1007/s11831-020-09437-x
- Advances in Observing and Understanding Small-Scale Open Ocean Circulation During the Gulf of Mexico Research Initiative Era E. D'Asaro et al. 10.3389/fmars.2020.00349
14 citations as recorded by crossref.
- Resolving and Parameterising the Ocean Mesoscale in Earth System Models H. Hewitt et al. 10.1007/s40641-020-00164-w
- Comparing two different types of stochastic parametrization in geophysical flow D. Holm et al. 10.1063/5.0238569
- Real-time estimation and prediction of unsteady flows using reduced-order models coupled with few measurements V. Resseguier et al. 10.1016/j.jcp.2022.111631
- Effects of Smooth Divergence-Free Flows on Tracer Gradients and Spectra: Eulerian Prognosis Description V. Resseguier et al. 10.1175/JPO-D-21-0014.1
- Solution properties of the incompressible Euler system with rough path advection D. Crisan et al. 10.1016/j.jfa.2022.109632
- Reduced data-driven turbulence closure for capturing long-term statistics R. Hoekstra et al. 10.1016/j.compfluid.2024.106469
- Data-driven stochastic spectral modeling for coarsening of the two-dimensional Euler equations on the sphere S. Ephrati et al. 10.1063/5.0156942
- Physically constrained covariance inflation from location uncertainty Y. Zhen et al. 10.5194/npg-30-237-2023
- Stochastic Modelling of Small-Scale Perturbation F. Flandoli & U. Pappalettera 10.3390/w12102950
- Quantifying Truncation-Related Uncertainties in Unsteady Fluid Dynamics Reduced Order Models V. Resseguier et al. 10.1137/19M1354819
- Data‐Driven Stochastic Lie Transport Modeling of the 2D Euler Equations S. Ephrati et al. 10.1029/2022MS003268
- Wave propagation in random two-dimensional turbulence: a multiscale approach V. Resseguier et al. 10.1017/jfm.2024.769
- Stochastic Data‐Driven Parameterization of Unresolved Eddy Effects in a Baroclinic Quasi‐Geostrophic Model L. Li et al. 10.1029/2022MS003297
- Bayesian inference for fluid dynamics: A case study for the stochastic rotating shallow water model O. Lang et al. 10.3389/fams.2022.949354
3 citations as recorded by crossref.
- Spatial Covariance Modeling for Stochastic Subgrid‐Scale Parameterizations Using Dynamic Mode Decomposition F. Gugole & C. Franzke 10.1029/2020MS002115
- New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics V. Resseguier et al. 10.1007/s11831-020-09437-x
- Advances in Observing and Understanding Small-Scale Open Ocean Circulation During the Gulf of Mexico Research Initiative Era E. D'Asaro et al. 10.3389/fmars.2020.00349
Latest update: 22 Nov 2024
Short summary
Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
Geophysical flows span a broader range of temporal and spatial scales than can be resolved...
