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 ◽  
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.

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 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 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.

scholarly journals Mechanisms for low-frequency variability of summer Arctic sea ice extent

2015 ◽  
Vol 112 (15) ◽  
pp. 4570-4575 ◽  
Author(s):  
Rong Zhang
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
Low Frequency ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Low Frequency Variability ◽  
Sea Ice Decline ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Satellite observations reveal a substantial decline in September Arctic sea ice extent since 1979, which has played a leading role in the observed recent Arctic surface warming and has often been attributed, in large part, to the increase in greenhouse gases. However, the most rapid decline occurred during the recent global warming hiatus period. Previous studies are often focused on a single mechanism for changes and variations of summer Arctic sea ice extent, and many are based on short observational records. The key players for summer Arctic sea ice extent variability at multidecadal/centennial time scales and their contributions to the observed summer Arctic sea ice decline are not well understood. Here a multiple regression model is developed for the first time, to the author’s knowledge, to provide a framework to quantify the contributions of three key predictors (Atlantic/Pacific heat transport into the Arctic, and Arctic Dipole) to the internal low-frequency variability of Summer Arctic sea ice extent, using a 3,600-y-long control climate model simulation. The results suggest that changes in these key predictors could have contributed substantially to the observed summer Arctic sea ice decline. If the ocean heat transport into the Arctic were to weaken in the near future due to internal variability, there might be a hiatus in the decline of September Arctic sea ice. The modeling results also suggest that at multidecadal/centennial time scales, variations in the atmosphere heat transport across the Arctic Circle are forced by anticorrelated variations in the Atlantic heat transport into the Arctic.

scholarly journals Low-Frequency Variability, Coherence Resonance, and Phase Selection in a Low-Order Model of the Wind-Driven Ocean Circulation

2011 ◽  
Vol 41 (9) ◽  
pp. 1585-1604 ◽  
Author(s):  
Stefano Pierini
Keyword(s):  
Ocean Circulation ◽  
Kuroshio Extension ◽  
Global Bifurcation ◽  
Low Frequency ◽  
Galerkin Projection ◽  
Coherence Resonance ◽  
Primitive Equation ◽  
Phase Selection ◽  
Low Frequency Variability ◽  
Low Order

Abstract In this paper, a low-order spectral quasigeostrophic (QG) model of the wind-driven ocean circulation is derived and used to analyze the low-order character of the intrinsic low-frequency variability of the midlatitude double-gyre ocean circulation and of the related coherence resonance and phase selection phenomena. The model includes an exponential in the basis functions that allows for westward intensification, retains only four modes in the Galerkin projection, is defined in a rectangular domain, and is forced by deterministic and stochastic winds, thus extending previous low-order QG ocean models. The solution under steady forcing is first obtained, and the results are also analyzed in terms of dynamical systems theory. A homoclinic bifurcation (with the wind amplitude chosen as the control parameter) leads to intrinsic decadal relaxation oscillations (ROs) similar in several respects to those obtained with primitive equation models. The system is then forced with an additional red noise wind, and, in a parameter range preceding the global bifurcation, a coherence resonance scenario very similar to the one found with a primitive equation model of the Kuroshio Extension is obtained: this suggests that such a phenomenon is of low-order character. To study the RO excitation mechanism, a method denoted as phase selection is proposed. The system is forced with additional fictitious periodic winds that produce an emergence of ROs yielding strong phase dependence with the periodic forcing. The subsequent analysis reveals the character of the wind forcing that is most likely to excite a RO. All the results are discussed within the general framework of climate dynamics.

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