Low-frequency variability of the atmospheric circulation: a comparison of statistical properties in both hemispheres and extreme seasons

1988 ◽  
Vol 11 (5-6) ◽  
pp. 467-488 ◽  
Author(s):  
A. Buzzi ◽  
E. Tosi
Keyword(s):  
Atmospheric Circulation ◽  
Low Frequency ◽  
Statistical Properties ◽  
Low Frequency Variability

scholarly journals Atmospheric Circulation Regimes in a Nonlinear Quasi-Geostrophic Model

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Henriette Labsch ◽  
Dörthe Handorf ◽  
Klaus Dethloff ◽  
Michael V. Kurgansky
Keyword(s):  
Atmospheric Circulation ◽  
Arctic Oscillation ◽  
Significant Contribution ◽  
Decadal Variability ◽  
Low Frequency ◽  
The Arctic ◽  
Satisfactory Model ◽  
Low Frequency Variability ◽  
Interannual And Decadal Variability ◽  
The Arctic Oscillation

Atmospheric low-frequency variability and circulation regime behavior are investigated in the context of a quasi-geostrophic (QG) three-level T63 model of the wintertime atmospheric circulation over the Northern Hemisphere (NH). The model generates strong interannual and decadal variability, with the domination of the annular mode of variability. It successfully reproduces a satisfactory model climatology and the most important atmospheric circulation regimes. The positive phase of the Arctic Oscillation is a robust feature of the quasi-geostrophic T63 model. The model results based on QG dynamics underlie atmospheric regime behavior in the extratropical NH and suggest that nonlinear internal processes deliver significant contribution to the atmospheric climate variability on interannual and decadal timescales.

Dynamics of Synoptic Eddy and Low-Frequency Flow Interaction. Part I: A Linear Closure

2006 ◽  
Vol 63 (7) ◽  
pp. 1677-1694 ◽  
Author(s):  
F-F. Jin ◽  
L-L. Pan ◽  
M. Watanabe
Keyword(s):  
Atmospheric Circulation ◽  
Low Frequency ◽  
Equation Model ◽  
The Self ◽  
Quasi Equilibrium ◽  
Mean Flow ◽  
Linear Dynamic ◽  
Synoptic Eddy ◽  
Linear Framework ◽  
Low Frequency Variability

Abstract The interaction between synoptic eddy and low-frequency flow (SELF) has been recognized for decades to play an important role in the dynamics of the low-frequency variability of the atmospheric circulation. In this three-part study a linear framework with a stochastic basic flow capturing both the climatological mean flow and climatological measures of the synoptic eddy flow is proposed. Based on this linear framework, a set of linear dynamic equations is derived for the ensemble-mean eddy forcing that is generated by anomalous time-mean flows. By assuming that such dynamically determined eddy-forcing anomalies approximately represent the time-mean anomalies of the synoptic eddy forcing and by using a quasi-equilibrium approximation, an analytical nonlocal dynamical closure is obtained for the two-way SELF feedback. This linear closure, directly relating time-mean anomalies of the synoptic eddy forcing to the anomalous time–mean flow, becomes an internal part of a new linear dynamic system for anomalous time–mean flow that is referred to as the low-frequency variability of the atmospheric circulation in this paper. In Part I, the basic approach for the SELF closure is illustrated using a barotropic model. The SELF closure is tested through the comparison of the observed eddy-forcing patterns associated with the leading low-frequency modes with those derived using the SELF feedback closure. Examples are also given to illustrate an important role played by the SELF feedback in regulating the atmospheric responses to remote forcing. Further applications of the closure for understanding the dynamics of low-frequency modes as well as the extension of the closure to a multilevel primitive equation model will be given in Parts II and III, respectively.

scholarly journals The Influence of Midlatitude Ocean–Atmosphere Coupling on the Low-Frequency Variability of a GCM. Part II: Interannual Variability Induced by Tropical SST Forcing*

1999 ◽  
Vol 12 (1) ◽  
pp. 21-45 ◽  
Author(s):  
Ileana Bladé
Keyword(s):  
Atmospheric Circulation ◽  
Mixed Layer ◽  
Low Frequency ◽  
Ocean Dynamics ◽  
Western Pacific ◽  
Sst Variability ◽  
Low Frequency Variability ◽  
Ocean Atmosphere ◽  
Sst Forcing ◽  
Sst Anomalies

Abstract This study extends the investigation of the impact of midlatitude ocean–atmosphere interactions on the atmospheric circulation to the interannual timescale by incorporating SST variability in the tropical Pacific representative of observed conditions. Two perpetual January GCM simulations are performed to examine the changes in the low-frequency atmospheric variability brought about by the inclusion of an interactive slab mixed layer in midlatitudes, in particular the changes in the extratropical response to ENSO-like tropical 90-day mean SST anomalies. It is found that midlatitude coupling alters the spatial organization of the low-frequency variability in qualitatively the same manner (but not to the same extent) as tropical SST variability—namely, by selectively enhancing (in terms of amplitude, persistence, and/or frequency of occurrence) certain of the preexisting (natural) dominant modes without significantly modifying them or generating new ones. While tropical SST forcing results in a notable amplification of the Pacific–North American (PNA) mode of the model, midlatitude SST anomalies appear to favor the regional zonal index circulations in the eastern and western Pacific (through decreased thermal damping at the surface). As a result, the PNA response to ENSO-like tropical SST forcing is not reinforced but slightly weakened by the presence of interactions with the underlying mixed layer. On the other hand, coupling increases the persistence of the overall extratropical signal and causes it to acquire distinct Western Pacific–like features, thus improving its resemblance to the observed ENSO teleconnection pattern. The leading mode of covariability between the hemispheric atmospheric circulation and North Pacific SST qualitatively reproduces its observational counterpart, with the atmosphere leading by about one month and surface atmospheric variations consistent with the notion that the atmosphere is driving the ocean. This agreement suggests that, even on interannual timescales, two-way air–sea interactions and ocean dynamics do not play an essential role in establishing the large-scale spatial structure of this observed dominant mode of ocean–atmosphere interaction. In addition, the simulated patterns of covariability in this sector possess the same kind of interannual–intraseasonal duality exhibited by the observations. In the North Atlantic the model essentially recovers the results from Part I of this study.

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