Articles | Volume 23, issue 6
https://doi.org/10.5194/npg-23-435-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-23-435-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Nov 2016
Research article |
| 28 Nov 2016
Parameterization of stochastic multiscale triads
Jeroen Wouters
CORRESPONDING AUTHOR
School of Mathematics and Statistics, The University of Sydney, Sydney, Australia
Klimacampus, Meteorologisches Institut, University of Hamburg, Hamburg, Germany
Stamen Iankov Dolaptchiev
Institut für Atmosphäre und Umwelt, Goethe-Universität Frankfurt, Frankfurt am Main, Germany
Valerio Lucarini
Klimacampus, Meteorologisches Institut, University of Hamburg, Hamburg, Germany
Department of Mathematics and Statistics, University of Reading, Reading, UK
Walker Institute for Climate System Research, University of Reading, Reading, UK
Ulrich Achatz
Institut für Atmosphäre und Umwelt, Goethe-Universität Frankfurt, Frankfurt am Main, Germany
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Cited
16 citations as recorded by crossref.
- A proof of concept for scale‐adaptive parametrizations: the case of the Lorenz '96 model G. Vissio & V. Lucarini https://doi.org/10.1002/qj.3184
- On some aspects of the response to stochastic and deterministic forcings M. Santos Gutiérrez & V. Lucarini https://doi.org/10.1088/1751-8121/ac90fd
- Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model J. Demaeyer & S. Vannitsem https://doi.org/10.5194/npg-25-605-2018
- Evaluating a stochastic parametrization for a fast–slow system using the Wasserstein distance G. Vissio & V. Lucarini https://doi.org/10.5194/npg-25-413-2018
- Reduced-order models for coupled dynamical systems: Data-driven methods and the Koopman operator M. Santos Gutiérrez et al. https://doi.org/10.1063/5.0039496
- Response formulae forn-point correlations in statistical mechanical systems and application to a problem of coarse graining V. Lucarini & J. Wouters https://doi.org/10.1088/1751-8121/aa812c
- Multiplicative Non‐Gaussian Model Error Estimation in Data Assimilation S. Pathiraja & P. van Leeuwen https://doi.org/10.1029/2021MS002564
- Stochastic subgrid‐scale parametrization for one‐dimensional shallow‐water dynamics using stochastic mode reduction M. Zacharuk et al. https://doi.org/10.1002/qj.3396
- Climate Dependence in Empirical Parameters of Subgrid-Scale Parameterizations using the Fluctuation–Dissipation Theorem M. Pieroth et al. https://doi.org/10.1175/JAS-D-18-0022.1
- Stochastic and deterministic kinetic energy backscatter parameterizations for simulation of the two-dimensional turbulence P. Perezhogin et al. https://doi.org/10.1515/rnam-2019-0017
- Opinion: Optimizing climate models with process knowledge, resolution, and artificial intelligence T. Schneider et al. https://doi.org/10.5194/acp-24-7041-2024
- Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations T. Schneider et al. https://doi.org/10.1002/2017GL076101
- Derivation of delay equation climate models using the Mori-Zwanzig formalism S. Falkena et al. https://doi.org/10.1098/rspa.2019.0075
- Edgeworth expansions for slow–fast systems with finite time-scale separation J. Wouters & G. Gottwald https://doi.org/10.1098/rspa.2018.0358
- Subgrid-scale parametrization of unresolved scales in forced Burgers equation using generative adversarial networks (GAN) J. Alcala & I. Timofeyev https://doi.org/10.1007/s00162-021-00581-z
- An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection Z. Tan et al. https://doi.org/10.1002/2017MS001162
16 citations as recorded by crossref.
- A proof of concept for scale‐adaptive parametrizations: the case of the Lorenz '96 model G. Vissio & V. Lucarini https://doi.org/10.1002/qj.3184
- On some aspects of the response to stochastic and deterministic forcings M. Santos Gutiérrez & V. Lucarini https://doi.org/10.1088/1751-8121/ac90fd
- Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model J. Demaeyer & S. Vannitsem https://doi.org/10.5194/npg-25-605-2018
- Evaluating a stochastic parametrization for a fast–slow system using the Wasserstein distance G. Vissio & V. Lucarini https://doi.org/10.5194/npg-25-413-2018
- Reduced-order models for coupled dynamical systems: Data-driven methods and the Koopman operator M. Santos Gutiérrez et al. https://doi.org/10.1063/5.0039496
- Response formulae forn-point correlations in statistical mechanical systems and application to a problem of coarse graining V. Lucarini & J. Wouters https://doi.org/10.1088/1751-8121/aa812c
- Multiplicative Non‐Gaussian Model Error Estimation in Data Assimilation S. Pathiraja & P. van Leeuwen https://doi.org/10.1029/2021MS002564
- Stochastic subgrid‐scale parametrization for one‐dimensional shallow‐water dynamics using stochastic mode reduction M. Zacharuk et al. https://doi.org/10.1002/qj.3396
- Climate Dependence in Empirical Parameters of Subgrid-Scale Parameterizations using the Fluctuation–Dissipation Theorem M. Pieroth et al. https://doi.org/10.1175/JAS-D-18-0022.1
- Stochastic and deterministic kinetic energy backscatter parameterizations for simulation of the two-dimensional turbulence P. Perezhogin et al. https://doi.org/10.1515/rnam-2019-0017
- Opinion: Optimizing climate models with process knowledge, resolution, and artificial intelligence T. Schneider et al. https://doi.org/10.5194/acp-24-7041-2024
- Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations T. Schneider et al. https://doi.org/10.1002/2017GL076101
- Derivation of delay equation climate models using the Mori-Zwanzig formalism S. Falkena et al. https://doi.org/10.1098/rspa.2019.0075
- Edgeworth expansions for slow–fast systems with finite time-scale separation J. Wouters & G. Gottwald https://doi.org/10.1098/rspa.2018.0358
- Subgrid-scale parametrization of unresolved scales in forced Burgers equation using generative adversarial networks (GAN) J. Alcala & I. Timofeyev https://doi.org/10.1007/s00162-021-00581-z
- An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection Z. Tan et al. https://doi.org/10.1002/2017MS001162
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