scholarly journals The Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0

2016 ◽  
Vol 9 (8) ◽  
pp. 2793-2808 ◽  
Author(s):  
Lesley De Cruz ◽  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Arbitrary Order ◽  
Low Frequency ◽  
Spectral Expansion ◽  
Truncation Level ◽  
Reduced Order ◽  
New Model ◽  
Low Frequency Variability ◽  
Model Dynamics ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. This paper describes a reduced-order quasi-geostrophic coupled ocean–atmosphere model that allows for an arbitrary number of atmospheric and oceanic modes to be retained in the spectral decomposition. The modularity of this new model allows one to easily modify the model physics. Using this new model, coined the "Modular Arbitrary-Order Ocean-Atmosphere Model" (MAOOAM), we analyse the dependence of the model dynamics on the truncation level of the spectral expansion, and unveil spurious behaviour that may exist at low resolution by a comparison with the higher-resolution configurations. In particular, we assess the robustness of the coupled low-frequency variability when the number of modes is increased. An "optimal" configuration is proposed for which the ocean resolution is sufficiently high, while the total number of modes is small enough to allow for a tractable and extensive analysis of the dynamics.

scholarly journals A Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0

2016 ◽  
Author(s):  
Lesley De Cruz ◽  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Arbitrary Order ◽  
Low Frequency ◽  
Spectral Expansion ◽  
Truncation Level ◽  
Reduced Order ◽  
New Model ◽  
Low Frequency Variability ◽  
Model Dynamics ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. This paper describes a reduced-order quasi-geostrophic coupled ocean-atmosphere model that allows for an arbitrary number of atmospheric and oceanic modes to be retained in the spectral decomposition. The modularity of this new model allows one to easily modify the model physics. Using this new model, coined "Modular Arbitrary-Order Ocean-Atmosphere Model" (MAOOAM), we analyse the dependence of the model dynamics on the truncation level of the spectral expansion, and unveil spurious behaviour that may exist at low resolution by a comparison with the higher resolution versions. In particular, we assess the robustness of the coupled low-frequency variability when the number of modes is increased. An "optimal" version is proposed for which the ocean resolution is sufficiently high while the total number of modes is small enough to allow for a tractable and extensive analysis of the dynamics.

scholarly journals Comparison of stochastic parameterizations in the framework of a coupled ocean-atmosphere model

2018 ◽  
Author(s):  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Probability Distributions ◽  
Low Frequency ◽  
Markov Operator ◽  
Model Errors ◽  
Low Frequency Variability ◽  
Ocean Atmosphere ◽  
Physically Based ◽  
Intermediate Order ◽  
Atmosphere Model ◽  
The Impact

Abstract. A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of MAOOAM, a coupled ocean-atmosphere model of intermediate complexity. Two physically-based parameterizations are investigated, the first one based on the singular perturbation of Markov operator, also known as homogenization. The second one is a recently proposed parameterization based on the Ruelle's response theory. The two parameterization are implemented in a rigorous way, assuming however that the unresolved scale relevant statistics are Gaussian. They are extensively tested for a low-order version known to exhibit low-frequency variability, and some preliminary results are obtained for an intermediate-order version. Several different configurations of the resolved-unresolved scale separations are then considered. Both parameterizations show remarkable performances in correcting the impact of model errors, being even able to change the modality of the probability distributions. Their respective limitations are also discussed.

Nonlinearly induced low-frequency variability in a midlatitude coupled ocean-atmosphere model of intermediate complexity

2002 ◽  
Vol 19 (3-4) ◽  
pp. 303-320 ◽  
Author(s):  
E. van der Avoird ◽  
Dijkstra H. ◽  
Nauw J. ◽  
Schuurmans C.
Keyword(s):  
Low Frequency ◽  
Intermediate Complexity ◽  
Low Frequency Variability ◽  
Ocean Atmosphere ◽  
Atmosphere Model

scholarly journals Low-frequency variability and heat transport in a low-order nonlinear coupled ocean–atmosphere model

2015 ◽  
Vol 309 ◽  
pp. 71-85 ◽  
Author(s):  
Stéphane Vannitsem ◽  
Jonathan Demaeyer ◽  
Lesley De Cruz ◽  
Michael Ghil
Keyword(s):  
Heat Transport ◽  
Low Frequency ◽  
Low Frequency Variability ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
Low Order

scholarly journals Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model

2018 ◽  
Vol 25 (3) ◽  
pp. 605-631 ◽  
Author(s):  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Probability Distributions ◽  
Low Frequency ◽  
Model Errors ◽  
Low Frequency Variability ◽  
Ocean Atmosphere ◽  
Physically Based ◽  
Intermediate Order ◽  
Atmosphere Model ◽  
The Impact ◽  
New Framework

Abstract. A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of the Modular Arbitrary-Order Ocean-Atmosphere Model (MAOOAM), a coupled ocean–atmosphere model of intermediate complexity. Two physically based parameterizations are investigated – the first one based on the singular perturbation of Markov operators, also known as homogenization. The second one is a recently proposed parameterization based on Ruelle's response theory. The two parameterizations are implemented in a rigorous way, assuming however that the unresolved-scale relevant statistics are Gaussian. They are extensively tested for a low-order version known to exhibit low-frequency variability (LFV), and some preliminary results are obtained for an intermediate-order version. Several different configurations of the resolved–unresolved-scale separations are then considered. Both parameterizations show remarkable performances in correcting the impact of model errors, being even able to change the modality of the probability distributions. Their respective limitations are also discussed.

qgs: A flexible Python framework of reduced-order multiscale climate models

2021 ◽  
Author(s):  
Lesley De Cruz ◽  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Open Source Software ◽  
Climate Models ◽  
Low Frequency ◽  
Atmospheric Dynamics ◽  
The Other ◽  
Research Use ◽  
Good Representation ◽  
Atmospheric Variability ◽  
Reduced Order ◽  
Low Frequency Variability

<p>In atmospheric and climate sciences, research and development is often first conducted with a simple idealized system like the Lorenz-<em>N</em> models (<em>N ∈</em> {63, 84, 96}) which are toy models of atmospheric variability. On the other hand, reduced-order spectral quasi-geostrophic models of the atmosphere with a sufficient number of modes offer a good representation of the dry atmospheric dynamics. They allow one to identify typical features of the atmospheric circulation, such as blocked and zonal circulation regimes, and low-frequency variability. However, these models are less often considered in literature, despite their demonstration of more realistic behavior.</p><p><strong>qgs</strong> (Demaeyer et al., 2020) aims to popularize these systems by providing a fast and easy-to-use Python framework for researchers and teachers to integrate this kind of model. The documentation makes it clear and efficient to handle the model, by explaining the equations and parameters and linking these to the code. </p><p>The choice to use Python was specifically made to facilitate its use in Jupyter Notebooks and with the multiple recent machine learning libraries that are available in this language.</p><p>In this talk, we will present the modeling capabilities of <strong>qgs</strong> and show its usage in a varieties of didactical and research use cases.</p><p><strong>Reference</strong></p><p>Demaeyer, J., De Cruz, L., & Vannitsem, S. (2020). qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software, 5(56), 2597, https://doi.org/10.21105/joss.02597 .</p>

Low-frequency variability of storms in the northern Black Sea and associated processes in the ocean–atmosphere system

2013 ◽  
Vol 14 (5) ◽  
pp. 1861-1871 ◽  
Author(s):  
A. Polonsky ◽  
V. Evstigneev ◽  
V. Naumova ◽  
E. Voskresenskaya
Keyword(s):  
Black Sea ◽  
Low Frequency ◽  
Atmosphere System ◽  
Low Frequency Variability ◽  
Ocean Atmosphere

scholarly journals Climate Regime Variability for Past and Present Time Slices Simulated by the Fast Ocean Atmosphere Model

2009 ◽  
Vol 22 (1) ◽  
pp. 58-70 ◽  
Author(s):  
Dörthe Handorf ◽  
Klaus Dethloff ◽  
Andrew G. Marshall ◽  
Amanda Lynch
Keyword(s):  
Climate Model ◽  
Low Frequency ◽  
Empirical Orthogonal Functions ◽  
Climate Regime ◽  
Orthogonal Functions ◽  
Medium Resolution ◽  
Ocean Atmosphere ◽  
Dimensional State Space ◽  
Atmosphere Model ◽  
Low Dimensional

Abstract This paper presents an analysis of Northern Hemisphere climate regime variability for three different time slices, simulated by the Fast Ocean Atmosphere Model (FOAM). The three time slices are composed of present-day conditions, the mid-Holocene, and the Last Glacial Maximum (LGM). Climate regimes have been determined by analyzing the structure of a spherical probability density function in a low-dimensional state space spanned by the three leading empirical orthogonal functions. This study confirms the ability of the FOAM medium-resolution climate model to reproduce low-frequency climate variability in the form of regime-like behavior. Three to four regimes have been detected for each time slice. Compared with present-day conditions, new climate regimes appeared for the LGM. For the mid-Holocene, which had slightly different boundary conditions and external forcings than the present-day simulation, the frequency of occurrence of the regimes was altered while only slight changes were found in the structure of some regimes.

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