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(top) Transition in zonal mean zonal wind averaged from 608 to 708S for a 60-day period centered on SFW events for 28 years from the GCM run. The contour interval is 2 m s 21. (bottom) Time evolution of zonal mean zonal wind averaged from 608 to 708S for a 60-day period centered on SFW events for 28 years from the GCM run as differences from day 230. The contour interval is 0.25 m s 21 up to 22 m s 21 (filled color contours) and 5 m s 21 thereafter (unfilled black contours). Magenta and brown contours denote the 90% and 95% confidence intervals for a two-sided t test.
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The authors test the hypothesis that recent observed trends in surface westerlies in the Southern Hemisphere are directly consequent on observed trends in the timing of stratospheric final warming events. The analysis begins by verifying that final warming events have an impact on tropospheric circulation in a simplified GCM driven by specified equ...
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... our results significantly. Figure 1 shows the timing of SFW events for the 28 years analyzed from the model run. A similar run with no topography does not produce sudden warmings (Gerber and Polvani 2009), but the variability in the timing of final warmings is not profoundly different from the case with topography reported here. The top panel of Fig. 2 shows the zonal mean zonal wind averaged from 608 to 708S over a 60-day period centered on final warming events and averaged over the 28 years that were analyzed from the simplified GCM run. We see a clear transition from westerlies to easterlies in the stratosphere and a weakening of the westerlies below. The bottom panel of Fig. 2 is ...
Context 2
... top panel of Fig. 2 shows the zonal mean zonal wind averaged from 608 to 708S over a 60-day period centered on final warming events and averaged over the 28 years that were analyzed from the simplified GCM run. We see a clear transition from westerlies to easterlies in the stratosphere and a weakening of the westerlies below. The bottom panel of Fig. 2 is similar but presents the time evolution of zonal mean zonal winds averaged from 608 to 708S relative to day 230. We see from the bottom panel that SFW events in the model have a statistically significant impact that extends to the surface after day 0. Since there is no im- posed seasonal cycle in the troposphere, these surface ...
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Citations
... The cause of the trend reversal in the SH SFWOD should be considered. Many studies have suggested an association between stratospheric ozone and the breakdown timing of the polar vortex during the austral summer 20,[22][23][24][25]30,31 . The SH springtime ozone loss could lead to a colder and stronger polar vortex in the Antarctic stratosphere, through the reduced absorption of shortwave radiation. ...
Since the 2000s, the pause of the strong Antarctic cooling and later stratospheric final warming onset trends has been identified. Here we employ composite and congruence analysis using reanalysis and in-situ data to propose a linkage between pivotal changes in the surface temperature trends and the timing of stratospheric final warming events. In early stratospheric final warming events, the positive polar cap height anomaly developed in the stratosphere in early October, descending to the troposphere and surface in late spring and summer, resulting in high-pressure anomalies, which led to warmer surfaces in most of Antarctica. In late stratospheric final warming occurrences, opposing or weaker behaviors were observed. The trend toward earlier stratospheric final warming appears to play a considerable role in warmer summers over parts of interior Antarctica through the strengthening of the anti-cyclonic surface pressure anomaly. This could influence the regional sea-ice modulation over the Southern Ocean.
... Simultaneously, it amplifies the contracts between the tropics and the southern polar region and thereby changes the atmospheric circulation patterns around the world. Along with such stronger winds in the stratosphere, the descending of tropopause above Antarctica directly changes the southern polar weather patterns by influencing both line-up and expansion of high-and low-pressure areas (Sheshadri, Alan Plumb, & Domeisen, 2014) (Fig. 12.6). Thus, the band of westerly has shifted further toward the South Pole across the Southern Ocean (Hogg, Meredith, Blundel, & Wilson, 2008), while the temperature has changed across some coastal parts within Antarctica, particularly FIG. ...
The Indian subcontinent is home to 1.39 billion people, mainly dependent on the agrarian-based economy. The Indian summer monsoon rainfall from June to September plays a vital role in providing water for agricultural and other lively needs. This rainfall is highly varying in the spatiotemporal domain and thus, leads to localized and organized extreme events in the form of floods on micro to mesoscale. The extreme rainfall events aggravate developing countries like India since the country's 54.6% human resources are involved in agriculture and allied sectors. Thus, understanding the characteristics of extreme events throughout India is important for the country's overall development. This chapter explores the systematic evolution of the studies of the extreme rainfall events over the Indian subcontinent and the regional characteristics. The linear trends reported by various studies are also explored and found that the trends are nonuniform throughout the nation. The nature and frequency of occurrence of these events are showing regional features. Therefore, the focus is on the extreme events in Peninsular India, central India, northeast regions, and the Himalayan regions. The dynamics of extreme events in all these regions are different. In general, Himalayan areas are controlled by extratropical intrusion and low-pressure systems. However, in the northeast regions, the main dynamic reason is the westerly regimes of the southerly wind and synoptic systems from the nearby oceans. Central India is governed by varying mechanisms from oceanic warming to topographical features. However, Peninsular India received its extremes in two seasons. The Tamil Nadu region experiences it in the northeast monsoon season, and the windward side of the Western Ghats experiences it during the southwest monsoon period. Hence, both areas have different attributing mechanisms. Additionally, the chapter investigates the future projections of the extreme events.
... As sunlight returns to the south pole every year in late September, a cascade of chemical reactions rapidly destroys stratospheric ozone, which further cools and strengthens the polar vortex and allows the vortex to persist longer. The SH thus exhibits a long-term trend in the timing of FSW events that is linked to ozone depletion (e.g., Zhou et al., 2000;Haigh and Roscoe, 2009;Sheshadri et al., 2014). In the NH, where spring temperatures are rarely cold enough to support chemical reactions for rapid ozone loss, the persistence of the vortex in the NH spring is more closely linked to interannual variations in tropospheric wave forcing than to feedbacks with stratospheric ozone (Chipperfield and Jones, 1999;Newman et al., 2001;Savenkova et al., 2012). ...
Every spring, the stratospheric polar vortex transitions from its westerly wintertime state to its easterly summertime state due to seasonal changes in incoming solar radiation, an event known as the “final stratospheric warming” (FSW). While FSWs tend to be less abrupt than reversals of the boreal polar vortex in midwinter, known as sudden stratospheric warming (SSW) events, their timing and characteristics can be significantly modulated by atmospheric planetary-scale waves. While SSWs are commonly classified according to their wave geometry, either by how the vortex evolves (whether the vortex displaces off the pole or splits into two vortices) or by the dominant wavenumber of the vortex just prior to the SSW (wave-1 vs. wave-2), little is known about the wave geometry of FSW events. We here show that FSW events for both hemispheres in most cases exhibit a clear wave geometry. Most FSWs can be classified into wave-1 or wave-2 events, but wave-3 also plays a significant role in both hemispheres. The timing and classification of the FSW are sensitive to which pressure level the FSW central date is defined, particularly in the Southern Hemisphere (SH) where trends in the FSW dates associated with ozone depletion and recovery are more evident at 50 than 10 hPa. However, regardless of which FSW definition is selected, we find the wave geometry of the FSW affects total column ozone anomalies in both hemispheres and tropospheric circulation over North America. In the Southern Hemisphere, the timing of the FSW is strongly linked to both total column ozone before the event and the tropospheric circulation after the event.
... In particular, stratospheric polar vortex variations and their downward coupling to the troposphere are regarded as critical drivers of variations in the southern annular mode (SAM) in austral spring and summer (Thompson and Wallace 2000). As a possible driver of the strengthening of the SSPV, ozone depletion and associated vortex strengthening have been examined in several studies (Thompson and Solomon 2002, Polvani et al 2011, Thompson et al 2011, Sheshadri et al 2014, Sun and Robinson, 2014, Ogawa et al 2015, Kidston et al 2015, Hirano et al 2016. However, only a few studies have examined the downward coupling following a large SSPV fluctuation (Thompson et al 2005, Lim et al 2018, Byrne and Shepherd 2018, Wang et al 2019. ...
The variability in the southern stratospheric polar vortex (SSPV) and its downward coupling with the troposphere are known to play a crucial role in driving climate variability over Antarctica. In this study, SSPV weakening events and their impacts on the surface climate of Antarctica are examined using in-situ observation and reanalysis data. Combining criteria from several previous studies, we introduce a new detection method for SSPV weakening events. Based on the new criteria, the occurrence frequency of SSPV weakening events has exhibited a systematic increasing trend since the 2000 s. However, the weakened anomalies of individual SSPV events are not statistically different (95% confidence level) between the earlier (1979–1999) and later (2000–2017) periods examined in this study. The recent increase in the occurrence of SSPV weakening events is largely controlled by tropospheric mechanisms, i.e. the poleward heat flux carried by southern hemispheric planetary waves and associated vertical wave propagation. Among the various scales of planetary waves, the wavenumber 1 contributes most of the poleward eddy heat flux. We show that SSPV weakening events induce statistically significant cooling over the Antarctic Peninsula (AP) region and warming over the rest of Antarctica. Typically, surface air temperature anomalies with large negative values smaller than − 0.6 °C and positive values larger than + 0.8 °C are observed over the east coast of the tip of the AP and King Edward VII Land, respectively. The influence of an SSPV weakening event on the surface lasts for approximately three months with higher height anomalies off western Antarctica, providing favorable conditions for the atmosphere to transport cold air from the interior of Antarctica to the AP via the Weddell Sea. Distinct positive surface air temperature anomalies over the rest of Antarctica are associated with the northerly circulation anomaly from the eastern Weddell Sea to east Antarctica.
... Due to the relatively quiescent nature of the SH stratospheric winter, the timing of the final warming is not as variable in the SH compared to the NH [Waugh and Rong, 2002;Black et al., 2006]. However, a trend towards a later break-up of the polar vortex due to the stratospheric cooling trend has been observed [Waugh et al., 1999], with potentially important implications for the SH troposphere [Sheshadri et al., 2014;Sun et al., 2014;Byrne et al., 2017]. ...
El Niño and La Niña events in the tropical Pacific have significant and disrupting impacts on the global atmospheric and oceanic circulation. El Niño Southern Oscillation (ENSO) impacts also extend above the troposphere, affecting the strength and variability of the stratospheric polar vortex in the high latitudes of both hemispheres, as well as the composition and circulation of the tropical stratosphere. El Niño events are associated with a warming and weakening of the polar vortex in the polar stratosphere of both hemispheres, while a cooling can be observed in the tropical lower stratosphere. These impacts are linked by a strengthened Brewer‐Dobson circulation. Anomalous upward wave propagation is observed in the extratropics of both hemispheres. For La Niña, these anomalies are often opposite. The stratosphere in turn affects surface weather and climate over large areas of the globe. Since these surface impacts are long‐lived, the changes in the stratosphere can lead to improved surface predictions on time scales of weeks to months. Over the past decade, our understanding of the mechanisms through which ENSO can drive impacts remote from the tropical Pacific has improved. This study reviews the possible mechanisms connecting ENSO to the stratosphere in the tropics and the extratropics of both hemispheres while also considering open questions, including nonlinearities in the teleconnections, the role of ENSO diversity, and the impacts of climate change and variability.
... While the SH tropospheric response to ozone depletion in December is simulated by the climate models, it is unclear based on the current literature whether the response can be quantitatively explained by the strengthened stratospheric westerly winds and the delay in the breakdown of the stratospheric polar vortex only. Two studies (Sun et al., 2014;Byrne et al., 2017) conclude that the delay in the breakdown can account for the tropospheric impacts, but a third study (Sheshadri et al., 2014) argues that it cannot account for the full impact (though it does contribute). Finally, the onset date for the vortex breakdown is generally too late in the current climate models (e.g., Wilcox and Charlton-Perez, 2013), in part due to too-weak gravity wave drag in the polar stratosphere near 60°S (McLandress et al., 2012;Geller et al., 2013;Garcia et al., 2017;, and this bias impacts the magnitude and seasonality of the tropospheric response to ozone depletion Lin et al., 2017). ...
... [Note, here we should distinguish SSW and stratospheric final warming (SFW); the latter is characteristic of the breakdown of the polar vortices (Black et al. 2006;Black and McDaniel 2007;Sheshadri et al. 2014)]. In such characterizing, a significant rise in temperature is generally required, but in recent decades zonal wind reversal has been the dominant basis for the definition of major warmings (e.g., McInturff 1978). ...
Using a newly developed analysis tool, multiscale window transform (MWT), and the MWT-based localized multiscale energetics analysis, the 2012/13 sudden stratospheric warming (SSW) is diagnosed for an understanding of the underlying dynamics. The fields are first reconstructed onto three scale windows: that is, mean window, sudden warming window or SSW window, and synoptic window. According to the reconstructions, the major warming period may be divided into three stages: namely, the stages of rapid warming, maintenance, and decay, each with different mechanisms. It is found that the explosive growth of temperature in the rapid warming stage (28 December-10 January) results from the collaboration of a strong poleward heat flux and canonical transfers through baroclinic instabilities in the polar region, which extract available potential energy (APE) from the mean-scale reservoir. In the course, a portion of the acquired APE is converted to and stored in the SSW-scale kinetic energy (KE), leading to a reversal of the polar night jet. In the stage of maintenance (11-25 January), the mechanism is completely different: First the previously converted energy stored in the SSW-scale KE is converted back, and, most importantly, in this time a strong barotropic instability happens over Alaska-Canada, which extracts the mean-scale KE to maintain the high temperature, while the mean-scale KE is mostly from the lower atmosphere, in conformity with the classical paradigm of mean flow-wave interaction with the upward-propagating planetary waves. This study provides an example that a warming may be generated in different stages through distinctly different mechanisms.
... Model I is forced with a 360-day seasonal cycle (as defined in [48]) and wave-2 topography, Model II is run without a seasonal cycle, i.e. in perpetual winter conditions for the analysed hemisphere and including topography, while Model III is run without a seasonal cycle and without topography and thus lacks the main drivers of large-scale stratospheric variability at the considered pressure level. The specific run performed for model I is further documented by Sheshadri et al. [49], while the run performed for Model II is described by Gerber & Polvani [47] (their run 9), except here run on hybrid levels (instead of σ levels). See BD14a for a qualitative description of the variability of the Model I and Model II integrations. ...
Characterising the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study, the different scaling laws in the long term stratospheric variability are studied using Multifractal de-trended Fluctuation Analysis. The analysis is performed comparing four re-analysis products and different realisations of an idealised numerical model, isolating the role of topographic forcing and seasonal variability, as well as the absence of climate teleconnections and small-scale forcing.
The Northern Hemisphere (NH) shows a transition of scaling exponents for time scales shorter than about one year, for which the variability scales in time with a power law corresponding to a red spectrum, to longer time scales, for which the variability scales in time with a power law corresponding to white noise. Southern Hemisphere (SH) variability also shows a transition at annual scales. The SH also shows a narrower dynamical range in multifractality than the NH, as seen in the generalised Hurst exponent and in the singularity spectra. The numerical integrations show that the models are able to reproduce the low-frequency variability but are not able to fully capture the shorter term variability of the stratosphere.
... FWs are also observed to have a similar tropospheric impact, although its latitudinal structure differs somewhat from the annular-mode form (Black et al. 2006;Black and McDaniel 2007a,b;Hu et al. 2014b), and uppertropospheric planetary-scale waves may play a role (Sun et al. 2011). Similar results have been found in simplified global models (Sun and Robinson 2009;Sun et al. 2011;Sheshadri et al. 2014). ...
The seasonal variability of the polar stratospheric vortex is studied in a simplified AGCM driven by specified equilibrium temperature distributions. Seasonal variations in equilibrium temperature are imposed in the stratosphere only, enabling the study of stratosphere-troposphere coupling on seasonal time scales, without the complication of an internal tropospheric seasonal cycle. The model is forced with different shapes and amplitudes of simple bottom topography, resulting in a range of stratospheric climates. The effect of these different kinds of topography on the seasonal variability of the strength of the polar vortex, the average timing and variability in timing of the final breakup of the vortex (final warming events), the conditions of occurrence and frequency of midwinter warming events, and the impact of the stratospheric seasonal cycle on the troposphere are explored. The inclusion of wavenumber-1 and wavenumber-2 topographies results in very different stratospheric seasonal variability. Hemispheric differences in stratospheric seasonal variability are recovered in the model with appropriate choices of wave-2 topography. In the model experiment with a realistic Northern Hemisphere-like frequency of midwinter warming events, the distribution of the intervals between these events suggests that the model has no year-to-year memory. When forced with wave-1 topography, the gross features of seasonal variability are similar to those forced with wave-2 topography, but the dependence on forcing magnitude is weaker. Further, the frequency of major warming events has a nonmonotonic dependence on forcing magnitude and never reaches the frequency observed in the Northern Hemisphere.
... In the Southern Hemisphere, the polar vortex also exhibits a strong long-term trend: a strengthening trend can be observed for the season from November to March (Thompson and Solomon 2002), accompanied by a trend in the timing of the final warming toward a later breakup of the polar vortex (Waugh et al. 1999;Black and McDaniel 2007;Sheshadri et al. 2014), which is suggested to be caused by ozone depletion in spring (Ramaswamy et al. 2001;Thompson et al. 2011). Ozone depletion was observed to be especially strong between 1979 and about 2000 (Solomon 1999), with a recovery starting after that (Oman et al. 2010). ...
... The summer season for the SH is here defined as January-March (JFM), which represents a shift from December-February (DJF), which is commonly defined as NH midwinter. Here, JFM is used for the definition of the summer season to avoid including the large variability due to mixing following Rossby wave breaking, which is associated with the final warming, which, for example, in NCEP reanalysis for 1960-2010 occurs between late October and early December (e.g., Sheshadri et al. 2014). Indeed, the PDF for the summer period defined as DJF instead shows a non-Gaussian distribution (not shown) because of the inclusion of SFW events. ...
Southern Hemisphere (SH) stratospheric variability is investigated with respect to chaotic behavior using time series from three different variables extracted from four different reanalysis products. The results are compared with the same analysis applied to the Northern Hemisphere (NH). The probability density functions (PDFs) for the SH show persistent deviations from a Gaussian distribution. The variability is given by white spectra for low frequencies, a slope of 21 for intermediate frequencies, and 23 slopes for high frequencies. Considering the time series for winter and summer separately, PDFs show a Gaussian distribution and the variability spectra change their slopes, indicating the role of the transition between winter and summer variability in shaping the time series. The correlation (D 2) and the Kaplan–Yorke (D KY) dimensions are estimated. A finite value of the dimensions can be computed for each variable and data product, except for the NCEP zonal-mean zonal wind and temperature data, which violate the requirement D 2 # D KY , possibly owing to the presence of spurious trends and inconsistencies in the data. The value of D 2 ranges between 2.6 and 3.9, while D KY ranges between 3.0 and 4.5. The results show that both D 2 and D KY display large variability in their values both for different datasets and for different variables within the same dataset. The variability of the values of D 2 and D KY thus leaves open the question about the existence of a low-dimensional attractor or if the finite dimensions of the system are the result of the projection of a larger attractor in a low-dimensional embedding space.
