Editing IPCC:AR6/WGI/Chapter-3 (section)

=== 3.7.2 Southern Annular Mode ===

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The Southern Annular Mode (SAM) consists of a meridional redistribution of atmospheric mass around Antarctica (Figure 3.33c,f), associated with a meridional shift of the jet and surface westerlies over the Southern Ocean. SAM indices are variously defined as the difference in zonal-mean sea level pressure or geopotential height between middle and high latitudes or via a principal-component analysis (Annex IV.2.2). Observational aspects of the SAM are assessed in [[IPCC:Wg1:Chapter:Chapter-2#2.4.1.2|Section 2.4.1.2]] .

AR5 assessed that CMIP5 models have medium performance in reproducing the SAM with biases in pattern ( [[#Flato--2013|Flato et al., 2013]] ). It also concluded that the trend of the SAM toward its positive phase in austral summer since the mid-20th century is ''likely'' to be due in part to stratospheric ozone depletion, and there was ''medium confidence'' that greenhouse gases have also played a role ( [[#Bindoff--2013|Bindoff et al., 2013]] ). Based on proxy reconstructions, AR5 found with ''medium confidence'' that the positive SAM trend since 1950 was anomalous compared to the last 400 years ( [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ).

Additional research has shown that CMIP5 models reproduce the spatial structure of the SAM well, but tend to overestimate its variability in austral summer at interannual time scales, although this variability is within the observational uncertainty (Figure 3.33c,f,i; [[#Zheng--2013|Zheng et al., 2013]] ; [[#Schenzinger--2015|Schenzinger and Osprey, 2015]] ). This is related to the models’ tendency to simulate slightly more persistent SAM anomalies in summer compared to reanalyses ( [[#Schenzinger--2015|Schenzinger and Osprey, 2015]] ; [[#Bracegirdle--2020|Bracegirdle et al., 2020]] ). This may be due in part to too weak a negative feedback from tropospheric planetary waves ( [[#Simpson--2013|Simpson et al., 2013]] ). CMIP6 models show improved performance in reproducing the spatial structure and interannual variance of the SAM in summer based on [[#Lee--2019|Lee et al. (2019)]] diagnostics (Figure 3.33i), with a better match of its trend with reanalyses over 1979–2014 (Figure 3.33l), more realistic persistence and improved positioning of the westerly jet, which in CMIP5 models on average is located too far equatorward ( [[#Bracegirdle--2020|Bracegirdle et al., 2020]] ; [[#Grose--2020|Grose et al., 2020]] ). In CMIP5, it is also found that models which extend above the stratopause tend to simulate stronger summertime trends in the late 20th century than their counterparts with tops within the stratosphere ( [[#Rea--2018|Rea et al., 2018]] ; [[#Son--2018|Son et al., 2018]] ), though other differences between these sets of models, such as additional physical processes operating in the stratosphere or interactive ozone chemistry, may have also affected these results ( [[#Gillett--2003a|Gillett et al., 2003a]] ; [[#Sigmond--2008|Sigmond et al., 2008]] ; [[#Rea--2018|Rea et al., 2018]] ). At the surface, [[#Ogawa--2015|Ogawa et al. (2015)]] demonstrate with an atmospheric model the importance of sharp mid-latitude SST gradients for stratospheric ozone depletion to affect the SAM in summer. These studies imply that the well resolved stratosphere combined with finer ocean horizontal resolution has contributed to the stronger simulated trends in CMIP6 than in CMIP5.

CMIP6 historical simulations capture the observed positive trend of the summertime SAM when calculated from the 1970s to the 2010s (Figure 3.34b). J.L. [[#Thomas--2015|]] [[#Thomas--2015|Thomas et al. (2015)]] found that the chance of the observed 1980–2004 trend occurring only due to internal variability is less than 10% in many of the CMIP5 models, and results from CMIP6 models suggest that the chance of the 1979–2019 trend being due to internal variability could be even lower (Figure 3.34b). Although paleo-reconstructions of the SAM index are uncertain and vary in terms of long-term trends ( [[IPCC:Wg1:Chapter:Chapter-2#2.4.1.2|Section 2.4.1.2]] ), new reconstructions show that the 60-year summertime SAM trend since the mid-20th century is outside the 5th–95th percentile range of the trends in the pre-industrial variability, which matches the trend range of CMIP5 pre-industrial control simulations well ( [[#Dätwyler--2018|Dätwyler et al., 2018]] ).

In general agreement with AR5, new research continues to indicate that both stratospheric ozone depletion and increasing greenhouse gases have contributed to the trend of the SAM during austral summer toward its positive phase in recent decades ( [[#Solomon--2016|Solomon and Polvani, 2016]] ), with the ozone depletion influence dominating ( [[#Gerber--2014|Gerber and Son, 2014]] ; [[#Son--2018|Son et al., 2018]] ). In CMIP6 historical simulations there are significant positive SAM trends over the 1979–2019 period in austral summer, although the contribution from ozone forcing evaluated with the four available models is not significant (Figure 3.34b). Three of these models share the same standard prescribed ozone forcing and produce significantly positive SAM trends over an extended period (1957–2019). The fourth model, MRI-ESM2-0, has the option of interactive ozone chemistry. Its ozone-only experiment is forced by prescribed ozone derived from its own historical simulations and produces a negative SAM trend associated with weak ozone depletion ( [[#Morgenstern--2020|Morgenstern et al., 2020]] ). [[#Morgenstern--2014|Morgenstern et al. (2014)]] and [[#Morgenstern--2021|Morgenstern (2021)]] find an indirect influence of greenhouse gases on the SAM via induced ozone changes in coupled chemistry-climate simulations, which differ from the prescribed ozone simulations shown in Figure 3.34b. Since about 1997, the effective abundance of ozone-depleting halogen has been decreasing in the stratosphere ( [[#WMO--2018|WMO, 2018]] ), leading to a stabilization or even a reversal of stratospheric ozone depletion (Sections 2.2.5.2 and 6.3.2.2). The ozone stabilization and slight recovery since about 2000 may have caused a pause in the summertime SAM trend (Figure 3.34c; [[#Saggioro--2019|Saggioro and Shepherd, 2019]] ; [[#Banerjee--2020|Banerjee et al., 2020]] ), although some influence from internal variability cannot be ruled out. While some studies find an anthropogenic aerosol influence on the summertime SAM ( [[#Gillett--2013|Gillett et al., 2013]] ; [[#Rotstayn--2013|Rotstayn, 2013]] ), recent studies with larger multi-model ensembles find that this effect is not robust ( [[#Steptoe--2016|Steptoe et al., 2016]] ; [[#Choi--2019|Choi et al., 2019]] ), consistent with CMIP6 single forcing ensembles (Figure 3.34). In the CMIP5 simulations, volcanic stratospheric aerosol has a significant weakening effect on the SAM in autumn and winter (Cross-Chapter Box 4.1; [[#Gillett--2013|Gillett and Fyfe, 2013]] ), but there is no evidence that this effect leads to a significant multi-decadal trend since the late 20th century. Beyond external forcing, [[#Fogt--2017|Fogt et al. (2017)]] show a significant association of tropical SST variability with the summertime SAM trend since the mid-20th century in agreement with [[#Lim--2016|Lim et al. (2016)]] , who, however, demonstrate that such a teleconnection between the summertime SAM and El Niño–Southern Oscillation (Annex IV.2.3), found in observations, is missing in many CMIP5 models.

On longer time scales, last millennium experiments from CMIP5 models fail to capture multicentennial variability evident in the reconstructions for the pre-industrial era ( [[#Abram--2014|Abram et al., 2014]] ; [[#Dätwyler--2018|Dätwyler et al., 2018]] ), which is also the case in those from available CMIP6 models (Figure 3.35). However, there is large uncertainty among reconstructions ( [[IPCC:Wg1:Chapter:Chapter-2#2.4.1.2|Section 2.4.1.2]] ). It is therefore unclear whether this disagreement reflects this observational uncertainty, whether forcings such as variations in the imposed insolation may be too weak, whether models are insufficiently sensitive to such variations, or whether internal variability including that associated with tropical Pacific variability is under-represented ( [[#Abram--2014|Abram et al., 2014]] ). The explanation could be a combination of all these factors. However, despite the aforementioned limitations of the reconstructions, [[IPCC:Wg1:Chapter:Chapter-2#2.4.1.2|Section 2.4.1.2]] assesses that the recent positive trend in the SAM is ''likely'' unprecedented in at least the past millennium ( ''medium confidence'' ). CMIP5 and CMIP6 last-millennium simulations only capture the present anomalous state during the final decades of the simulations which are dominated by human influence; this state is also outside the range of simulated variability characteristic of pre-industrial times.

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[[File:2a303798adcb7e1651d072fc363abf1f IPCC_AR6_WGI_Figure_3_35.png]]

Figure 3.35 | '''Southern Annular Mode (SAM) indices in the last millennium. (a)''' Annual-mean SAM reconstructions by [[#Abram--2014|Abram et al. (2014)]] and [[#Dätwyler--2018|Dätwyler et al. (2018)]] . '''(b)''' The annual-mean SAM index defined by [[#Gong--1999|Gong and Wang (1999)]] in CMIP5 and CMIP6 last millennium simulations extended by historical simulations. All indices are normalized with respect to 1961–1990 means and standard deviations. Thin lines and thick lines show seven-year and 70-year moving averages, respectively. Further details on data sources and processing are available in the chapter data table (Table 3.SM.1).

In summary, it is ''very likely'' that anthropogenic forcings have contributed to the observed trend of the summer SAM toward its positive phase since the 1970s. This assessment is supported by further model studies that confirm the human influence on the summertime SAM with improved models since AR5. While ozone depletion contributed to the trend from the 1970s to the 1990s ( ''medium confidence'' ), its influence has been small since 2000, leading to a weaker summertime SAM trend over 2000–2019 ( ''medium confidence'' ). Climate models reproduce the spatial structure of the summertime SAM observed since the late 1970s well ( ''high confidence'' ). CMIP6 models reproduce the spatiotemporal features and recent multi-decadal trend of the summertime SAM better than CMIP5 models ( ''medium confidence'' ). However, there is a large spread in the intensity of the SAM response to ozone and greenhouse gas changes in both CMIP5 and CMIP6 models ( ''high confidence'' ), which limits the confidence in the assessment of the ozone contribution to the observed trends. CMIP5 and CMIP6 models do not capture multicentennial variability of the SAM found in proxy reconstructions ( ''low confidence'' ). This confidence level reflects that it is unclear whether this is due to a model or an observational shortcoming.

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