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The variability of the Southern Hemisphere (SH) extratropical large‐scale circulation is dominated by the Southern Annular Mode (SAM), whose timescale is extensively used as a key metric in evaluating state‐of‐the‐art climate models. Past observational and theoretical studies suggest that the SAM lacks any internally generated (intrinsic) periodicity. Here, we show, using observations and a climate model hierarchy, that the SAM has an intrinsic 150‐day periodicity. This periodicity is robustly detectable in the power spectra and principal oscillation patterns (aka dynamical mode decomposition) of the zonal‐mean circulation, and in hemispheric‐scale precipitation and ocean surface wind stress. The 150‐day period is consistent with the predictions of a new reduced‐order model for the SAM, which suggests that this periodicity is associated with a complex interaction of turbulent eddies and zonal wind anomalies, as the latter propagate from low to high latitudes. These findings present a rare example of periodic oscillations arising from the internal dynamics of the extratropical turbulent circulations. Based on these findings, we further propose a new metric for evaluating climate models, and show that some of the previously reported shortcomings and improvements in simulating SAM's variability connect to the models' ability in reproducing this periodicity. We argue that this periodicity should be considered in evaluating climate models and understanding the past, current, and projected Southern Hemisphere climate variability.

 

Abstract To better understand the dynamics and impacts of blocking events, their 3D structure needs to be further investigated. We present a comprehensive composite analysis of the 3D structure of blocks and its response to future climate change over North Pacific, North Atlantic, and Russia in summers and winters using reanalysis and two large-ensemble datasets from CESM1 and GFDLCM3. In reanalysis, over both ocean and land, the anomalous winds are equivalent-barotropic in the troposphere and stratosphere, and temperature anomalies are positive throughout the troposphere and negative in the lower stratosphere. The main seasonal and regional differences are that blocks are larger/stronger in winters; over oceans, the temperature anomaly is shifted westward due to latent heating. Analyzing the temperature tendency equation shows that in all three sectors, adiabatic warming due to subsidence is the main driver of the positive temperature anomaly; however, depending on season and region, meridional thermal advection and latent heating might have leading-order contributions too. Both GCMs are found to reproduce the climatological 3D structure remarkably well, but sometimes disagree on future changes. Overall, the future summertime response is weakening of all fields (except for specific humidity), although the impact on near-surface temperature is not necessarily weakened; e.g., the blocking-driven near-surface warming over Russia intensifies. The wintertime response is strengthening of all fields, except for temperature in some cases. Responses of geopotential height and temperature are shifted westward in winters, most likely due to latent heating. Results highlight the importance of process-level analyses of blocks’ 3D structure for improved understanding of the resulting temperature extremes and their future changes. 

The forecast skill of numerical weather prediction (NWP) models and the intrinsic predictability can be different among weather regimes. Here, we examine the predictability of distinct Pacific‐North American weather regimes during extended boreal summer. The four identified weather regimes include Pacific trough, Arctic low, Arctic high, and Alaskan ridge. The medium range forecast skill of these regimes is quantified in the ECMWF and the National Centers for Environmental Prediction models from the TIGGE project. Based on anomaly correlation coefficient, persistence, and transition frequency, the highest forecast skill is consistently found for the Arctic high regime. Based on the instantaneous local dimension and persistence from a dynamical systems analysis, the Arctic high regime has the highest intrinsic predictability. The analysis also suggests that overall, the Pacific trough regime has the lowest intrinsic predictability. These findings are consistent with the forecast skills of the NWP models, and highlight the link between prediction skill and intrinsic predictability.

 

Abstract The variability of the zonal-mean large-scale extratropical circulation is often studied using individual modes obtained from empirical orthogonal function (EOF) analyses. The prevailing reduced-order model of the leading EOF (EOF1) of zonal-mean zonal wind, called the annular mode, consists of an eddy–mean flow interaction mechanism that results in a positive feedback of EOF1 onto itself. However, a few studies have pointed out that under some circumstances in observations and GCMs, strong couplings exist between EOF1 and EOF2 at some lag times, resulting in decaying-oscillatory, or propagating, annular modes. Here, we introduce a reduced-order model for coupled EOF1 and EOF2 that accounts for potential cross-EOF eddy–zonal flow feedbacks. Using the analytical solution of this model, we derive conditions for the existence of the propagating regime based on the feedback strengths. Using this model, and idealized GCMs and stochastic prototypes, we show that cross-EOF feedbacks play an important role in controlling the persistence of the annular modes by setting the frequency of the oscillation. We find that stronger cross-EOF feedbacks lead to less persistent annular modes. Applying the coupled-EOF model to the Southern Hemisphere reanalysis data shows the existence of strong cross-EOF feedbacks. The results highlight the importance of considering the coupling of EOFs and cross-EOF feedbacks to fully understand the natural and forced variability of the zonal-mean large-scale circulation. 

This paper examines the role of wave–mean flow interaction in the onset and suddenness of stratospheric sudden warmings (SSWs). Evidence is presented that SSWs are, on average, a threshold behavior of finite-amplitude Rossby waves arising from the competition between an increasing wave activity A and a decreasing zonal-mean zonal wind [Formula: see text]. The competition puts a limit to the wave activity flux that a stationary Rossby wave can transmit upward. A rapid, spontaneous vortex breakdown occurs once the upwelling wave activity flux reaches the limit, or equivalently, once [Formula: see text] drops below a certain fraction of u REF , a wave-free, reference-state wind inverted from the zonalized quasigeostrophic potential vorticity. This fraction is 0.5 in theory and about 0.3 in reanalyses. We propose [Formula: see text] as a local, instantaneous measure of the proximity to vortex breakdown (i.e., preconditioning). The ratio r generally stays above the threshold during strong-vortex winters until a pronounced final warming, whereas during weak-vortex winters it approaches the threshold early in the season, culminating in a precipitous drop in midwinter as SSWs form. The essence of the threshold behavior is captured by a semiempirical 1D model of SSWs, similar to the “traffic jam” model of Nakamura and Huang for atmospheric blocking. This model predicts salient features of SSWs including rapid vortex breakdown and downward migration of the wave activity/zonal wind anomalies, with analytical expressions for the respective time scales. The model’s response to a variety of transient wave forcing and damping is discussed.