Editing IPCC:AR6/WGI/Chapter-4 (section)

===== 4.4.3.1.1 The NorthernAnnular Mode =====

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The AR5 assessed from CMIP5 simulations that there is only ''medium confidence'' in near-term projections of a northward shift of NH storm track and westerlies, and an associated increase in the NAM index, because of the large response uncertainty and the potentially large influence of internal variability. A tendency in the near term towards a slightly more positive NAM in the three highest emissions scenarios during boreal fall, winter, and spring is apparent in Figure 4.17a. However, in general the projected near-term multi-model mean change in the NAM is small in magnitude compared to the inter-model and/or multi-realization variability within the ensemble (Figure 4.17a; [[#Deser--2012b|Deser et al., 2012b]] , 2017; [[#Barnes--2015|Barnes and Polvani, 2015]] ).

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[[File:8869dd2f6128b93d068ceef75f2e735c IPCC_AR6_WGI_Figure_4_17.png]]

'''Figure 4.17''' '''|''' '''CMIP6 Annular Mode index change (hPa) from 1995–2014 to 2021–2040. (a)''' Northern Annular Mode (NAM); '''(b)''' Southern Annular Mode (SAM). The NAM is defined as the difference in zonal mean sea level pressure (SLP) at 35°N and 65°N ( [[#Li--2003|Li and Wang, 2003]] ) and the SAM as the difference in zonal mean SLP at 40°S and 65°S ( [[#Gong--1999|Gong and Wang, 1999]] ). The shadings are the 5–95% ranges across the simulations. The numbers near the top of each panel are the numbers of model simulations in each SSP ensemble. Further details on data sources and processing are available in the chapter data table (Table 4.SM.1).

On seasonal to interannual time scales, there is new evidence since AR5 that initialized predictions show lower potential predictability for the boreal winter NAO than the correlation skill with respect to observations ( [[#Eade--2014|Eade et al., 2014]] ; [[#Baker--2018|Baker et al., 2018]] ; [[#Scaife--2018|Scaife and Smith, 2018]] ; [[#Athanasiadis--2020|Athanasiadis et al., 2020]] ). This has been referred to in the literature as a ‘signal-to-noise paradox’ and means that very large ensembles of predictions are needed to isolate the predictable component of the NAO. While the processes that contribute to the predictability of the winter NAO on seasonal time scales may be distinct from the processes that drive multi-decadal trends, there is emerging evidence that initialized predictions also underrepresent the predictability of the winter NAO on decadal time scales (D.M. [[#Smith--2019|]] [[#Smith--2019|Smith et al., 2019]] ). Post-processing and aggregation of initialized predictions may therefore reveal significant skill for predicting the winter NAO on decadal time scales ( [[#Smith--2020|Smith et al., 2020]] ). Considering these new results since AR5, in the near-term it is ''likely'' that any anthropogenic forced signal in the NAM will be of comparable magnitude or smaller than natural internal variability in the NAM ( ''medium confidence'' ).

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