scholarly journals Bimodal Behavior in the Zonal Mean Flow of a Baroclinic β-Channel Model

2005 ◽  
Vol 62 (6) ◽  
pp. 1746-1769 ◽  
Author(s):  
S. Kravtsov ◽  
A. W. Robertson ◽  
M. Ghil
Keyword(s):  
Channel Model ◽  
Low Frequency ◽  
Zonal Flow ◽  
Relative Energy ◽  
Empirical Orthogonal Functions ◽  
Stationary Mode ◽  
Nonlinear Interactions ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Synoptic Eddies

Abstract The dynamical origin of midlatitude zonal-jet variability is examined in a thermally forced, quasigeostrophic, two-layer channel model on a β plane. The model’s behavior is studied as a function of the bottom-friction strength. Two distinct zonal-flow states exist at realistic, low, and intermediate values of the bottom drag; these two states are maintained by the eddies and differ mainly in terms of the meridional position of their climatological jets. The system’s low-frequency evolution is characterized by irregular transitions between the two states. For a given branch of model solutions, the leading stationary and propagating empirical orthogonal functions are related to eigenmodes of the model’s dynamical operator, linearized about the climatological state on this branch. Nonlinear interactions between these modes are instrumental in determining their relative energy level. In particular, the stationary modes’ self-interaction is shown to vanish. Thus, these modes do not exchange energy with the mean flow and, consequently, dominate the lowest-frequency behavior in the model. The leading stationary mode resembles the observed annular mode in the Southern Hemisphere. The bimodality is due to nonlinear interactions between nearly equivalent barotropic, stationary, and propagating modes, while the synoptic eddies play a modest role in determining the relative persistence of the two states. The role of synoptic eddies is very substantial only at unrealistically high values of the bottom drag, where they give rise to ultralow frequency variability by modifying the jet in a way that reinforces generation of the eddy field. This type of behavior is related to the presence of a homoclinic orbit in the model’s phase space and is not apparent for more realistic, lower values of the bottom drag.

scholarly journals Multiple Regimes and Low-Frequency Oscillations in the Northern Hemisphere’s Zonal-Mean Flow

2006 ◽  
Vol 63 (3) ◽  
pp. 840-860 ◽  
Author(s):  
S. Kravtsov ◽  
A. W. Robertson ◽  
M. Ghil
Keyword(s):  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Zonal Flow ◽  
Empirical Orthogonal Functions ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Atlantic Sector ◽  
Low Frequency Oscillations ◽  
Multiple Regimes ◽  
Flow States

Abstract This paper studies multiple regimes and low-frequency oscillations in the Northern Hemisphere zonal-mean zonal flow in winter, using 55 yr of daily observational data. The probability density function estimated in the phase space spanned by the two leading empirical orthogonal functions exhibits two distinct, statistically significant maxima. The two regimes associated with these maxima describe persistent zonal-flow states that are characterized by meridional displacements of the midlatitude jet, poleward and equatorward of its time-mean position. The geopotential height anomalies of either regime have a pronounced zonally symmetric component, but largest-amplitude anomalies are located over the Atlantic and Pacific Oceans. High-frequency synoptic transients participate in the maintenance of and transitions between these regimes. Significant oscillatory components with periods of 147 and 72 days are identified by spectral analysis of the zonal-flow time series. These oscillations are described by singular spectrum analysis and the multitaper method. The 147-day oscillation involves zonal-flow anomalies that propagate poleward, while the 72-day oscillation only manifests northward propagation in the Atlantic sector. Both modes mainly describe changes in the midlatitude jet position and intensity. In the horizontal plane though, the two modes exhibit synchronous centers of action located over the Atlantic and Pacific Oceans. The two persistent flow regimes are associated with slow phases of either oscillation.

The Relationship between Statistically Linear and Nonlinear Feedbacks and Zonal-Mean Flow Variability in an Idealized Climate Model

2009 ◽  
Vol 66 (2) ◽  
pp. 353-372 ◽  
Author(s):  
Sergey Kravtsov ◽  
John E. Ten Hoeve ◽  
Steven B. Feldstein ◽  
Sukyoung Lee ◽  
Seok-Woo Son
Keyword(s):  
Phase Space ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Zonal Flow ◽  
Empirical Orthogonal Functions ◽  
Nonlinear Flow ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Flow Variability

Abstract Simulations using an idealized, atmospheric general circulation model (GCM) subjected to various thermal forcings are analyzed via a combination of probability density function (PDF) estimation and spectral analysis techniques. Seven different GCM runs are examined, each model run being characterized by different values in the strength of the tropical heating and high-latitude cooling. For each model run, it is shown that a linear stochastic model constructed in the phase space of the ten leading empirical orthogonal functions (EOFs) of the zonal-mean zonal flow provides an excellent statistical approximation to the simulated zonal flow variability, which includes zonal index fluctuations, and quasi-oscillatory, poleward, zonal-mean flow anomaly propagation. Statistically significant deviations from the above linear stochastic null hypothesis arise in the form of a few anomalously persistent, or statistically nonlinear, flow patterns, which occupy particular regions of the model’s phase space. Some of these nonlinear regimes occur during certain phases of the poleward propagation; however, such an association is, in general, weak. This indicates that the regimes and oscillations in the model may be governed by distinct dynamical mechanisms.

scholarly journals Multilevel Regression Modeling of Nonlinear Processes: Derivation and Applications to Climatic Variability

2005 ◽  
Vol 18 (21) ◽  
pp. 4404-4424 ◽  
Author(s):  
S. Kravtsov ◽  
D. Kondrashov ◽  
M. Ghil
Keyword(s):  
Nonlinear Dynamics ◽  
Polynomial Regression ◽  
Climatic Variability ◽  
Low Frequency ◽  
Inverse Model ◽  
Empirical Orthogonal Functions ◽  
Multilevel Regression ◽  
Coherent Noise ◽  
Orthogonal Functions ◽  
Constant Matrix

Abstract Predictive models are constructed to best describe an observed field’s statistics within a given class of nonlinear dynamics driven by a spatially coherent noise that is white in time. For linear dynamics, such inverse stochastic models are obtained by multiple linear regression (MLR). Nonlinear dynamics, when more appropriate, is accommodated by applying multiple polynomial regression (MPR) instead; the resulting model uses polynomial predictors, but the dependence on the regression parameters is linear in both MPR and MLR. The basic concepts are illustrated using the Lorenz convection model, the classical double-well problem, and a three-well problem in two space dimensions. Given a data sample that is long enough, MPR successfully reconstructs the model coefficients in the former two cases, while the resulting inverse model captures the three-regime structure of the system’s probability density function (PDF) in the latter case. A novel multilevel generalization of the classic regression procedure is introduced next. In this generalization, the residual stochastic forcing at a given level is subsequently modeled as a function of variables at this level and all the preceding ones. The number of levels is determined so that the lag-0 covariance of the residual forcing converges to a constant matrix, while its lag-1 covariance vanishes. This method has been applied to the output of a three-layer, quasigeostrophic model and to the analysis of Northern Hemisphere wintertime geopotential height anomalies. In both cases, the inverse model simulations reproduce well the multiregime structure of the PDF constructed in the subspace spanned by the dataset’s leading empirical orthogonal functions, as well as the detailed spectrum of the dataset’s temporal evolution. These encouraging results are interpreted in terms of the modeled low-frequency flow’s feedback on the statistics of the subgrid-scale processes.

Statistical description of the East Australian Current low-frequency variability from the WOCE PCM3 array

2006 ◽  
Vol 57 (3) ◽  
pp. 273 ◽  
Author(s):  
Mauricio M. Mata ◽  
Susan Wijffels ◽  
John A. Church ◽  
Matthias Tomczak
Keyword(s):  
Ocean Circulation ◽  
World Ocean ◽  
Low Frequency ◽  
General Rule ◽  
Empirical Orthogonal Functions ◽  
East Australian Current ◽  
Orthogonal Functions ◽  
The Pacific ◽  
Strong Surface ◽  
The Impact

The in situ dataset used in the current study consists of the Pacific Current Meter 3 (PCM3) array, which was a significant part of the Australian contribution to the World Ocean Circulation Experiment to study the variability of the East Australian Current (EAC), and was operational between September 1991 and March 1994. Area-preserving spectral analysis has been used to investigate the typical time scales observed by the current meters. As a general rule, the spectra from the top layers of the shallow (1, 2 and 3) and the deep (4, 5 and 6) moorings have a distinct peak in the temporal mesoscale band (periods between 70 and 170 days), with a general redistribution of energy towards the higher-frequencies near the ocean floor. This peak has been linked with eddy variability of the EAC system, which influences the fluctuations of the current main jet. The vertical modes of the velocity profile show that the strong surface-intensified baroclinic signal of the EAC dominated the variability at mooring 4 location. Further offshore the predominant configuration resembles more closely the barotropic mode. Ultimately, spatial empirical orthogonal functions (EOF) analysis point out the impact of the presence/absence of the EAC jet in the array.

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.

scholarly journals Characterizing Midlatitude Jet Variability: Lessons from a Simple GCM

2005 ◽  
Vol 18 (16) ◽  
pp. 3400-3404 ◽  
Author(s):  
John C. Fyfe ◽  
David J. Lorenz
Keyword(s):  
Empirical Orthogonal Functions ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Anomaly Pattern ◽  
Jet Variability ◽  
New Perspective

Abstract Fluctuations in the tropospheric zonal jet are often characterized using anomaly patterns, or empirical orthogonal functions, representing deviations of the zonal-mean flow from climatology. In previous studies the leading anomaly pattern has been interpreted as representing north–south jet movements, while the second anomaly pattern has been interpreted as representing independent fluctuations in jet strength and width. Here it is shown that these leading anomaly patterns are in fact dependent and together represent north–south movements of the jet. Fluctuations in jet strength, which are approximately inversely proportional to jet width, superimpose upon these dominant north–south meanderings. The distinction between the usual anomaly pattern perspective and this new perspective may have important implications in the interpretation of tropospheric zonal jet variability.

scholarly journals Inverse Energy Cascades in an Eddy-Induced NAO-Type Flow: Scale Interaction Mechanism

2015 ◽  
Vol 72 (9) ◽  
pp. 3417-3448 ◽  
Author(s):  
Dehai Luo ◽  
Linhao Zhong ◽  
Christian L. E. Franzke
Keyword(s):  
Large Scale ◽  
Interaction Mechanism ◽  
Zonal Flow ◽  
Scale Model ◽  
Synoptic Scale ◽  
Mean Flow ◽  
The North ◽  
Synoptic Eddies ◽  
Stretching Deformation ◽  
The North Atlantic Oscillation

Abstract In this paper, based on a new wave–eddy interaction framework, the interaction mechanism between the North Atlantic Oscillation (NAO) and synoptic-scale eddies is revealed by using the analytical solutions of a two-scale model as a description of the inverse energy cascade from nonuniform synoptic-scale eddies to the large-scale NAO flow. It is found that the spatial shape of the eddy-induced large-scale streamfunction tendency prior to the NAO onset determines the direction of eddy energy transfer, as well as the phase and growth of the NAO. However, the feedback of the intensified NAO anomaly on synoptic eddies can affect significantly the asymmetry of the NAO between negative (NAO−) and positive (NAO+) phases in amplitude and persistence through the presence or absence of the eddy straining related to cyclonic wave breaking (CWB). For the NAO+, the stretching deformation role of the NAO+ field seems dominant in the eddy variation. Because the eddy energy generation rate (EGR) weakens and tends to be negative in the downstream side of the NAO+ region, the synoptic eddies lose their energy to the NAO+-type zonal flow, thus leading to the weakening of synoptic-scale eddies. However, for the NAO−, the EGR variation shows that synoptic eddies grow over the two upstream sides of the NAO− region by extracting energy from the NAO− shearing deformation field, while losing energy to the mean flow over the upstream middle region through the stretching deformation. This process results in the eddy straining (splitting and strengthening) associated with the CWB.

scholarly journals Linear Contributions of Different Time Scales to Teleconnectivity

2009 ◽  
Vol 22 (13) ◽  
pp. 3720-3728 ◽  
Author(s):  
Panos J. Athanasiadis ◽  
Maarten H. P. Ambaum
Keyword(s):  
Time Scales ◽  
Low Frequency ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Low Frequencies ◽  
Teleconnection Patterns ◽  
The North ◽  
The North Atlantic Oscillation ◽  
Different Time Scales

Abstract The contributions of different time scales to extratropical teleconnections are examined. By applying empirical orthogonal functions and correlation analyses to reanalysis data, it is shown that eddies with periods shorter than 10 days have no linear contribution to teleconnectivity. Instead, synoptic variability follows wavelike patterns along the storm tracks, interpreted as propagating baroclinic disturbances. In agreement with preceding studies, it is found that teleconnections such as the North Atlantic Oscillation (NAO) and the Pacific–North America (PNA) pattern occur only at low frequencies, typically for periods more than 20 days. Low-frequency potential vorticity variability is shown to follow patterns analogous to known teleconnections but with shapes that differ considerably from them. It is concluded that the role, if any, of synoptic eddies in determining and forcing teleconnections needs to be sought in nonlinear interactions with the slower transients. The present results demonstrate that daily variability of teleconnection indices cannot be interpreted in terms of the teleconnection patterns, only the slow part of the variability.

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