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

=== 3.7.5 Atlantic Meridional and Zonal Modes ===

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The Atlantic Zonal Mode (AZM), often referred to as the Atlantic Equatorial Mode or Atlantic Niño, and the Atlantic Meridional Mode (AMM) are the two leading basin-wide patterns of interannual to decadal variability in the tropical Atlantic. Akin to ENSO in the Pacific, the term Atlantic Niño is broadly used to refer to years when the SSTs in the tropical eastern Atlantic basin along the cold tongue are significantly warmer than the climatological average. The AMM is characterized by anomalous cross-equatorial gradients in SST. Both modes are associated with altered strength of the Inter-tropical Convergence Zone (ITCZ) and/or latitudinal shifts in the ITCZ, which locally affect African and American monsoon systems and remotely affect tropical Pacific and Indian Ocean variability through inter-basins teleconnections. A detailed description of both AZM and AMM, as well as their associated teleconnection over land, is given in Annex IV.2.5

AR5 mentioned the considerable difficulty in simulating both Atlantic Niño and AMM despite some improvements in CMIP5 for some models ( [[#Flato--2013|Flato et al., 2013]] ). Severe biases in mean state and variance for both SST and atmospheric dynamics including rainfall (e.g., a double ITCZ) as well as teleconnections were reported. The AR5 highlighted the complexity of the tropical Atlantic biases, which were explained by multiple factors both in the ocean and atmosphere.

Since AR5, further analysis of the major persistent biases in models has been reported ( [[#Xu--2014|Xu et al., 2014]] ; [[#Jouanno--2017|Jouanno et al., 2017]] ; Y. [[#Yang--2017|]] [[#Yang--2017|Yang et al., 2017]] ; [[#Dippe--2018|Dippe et al., 2018]] ; [[#Lübbecke--2018|Lübbecke et al., 2018]] ; [[#Voldoire--2019a|Voldoire et al., 2019a]] ). Errors in equatorial and basin wide trade winds, cloud cover and ocean vertical mixing and dynamics both locally and in remote subtropical upwelling regions, key thermodynamic ocean–atmosphere feedbacks, and tropical land–atmosphere interaction have been shown to be detrimental to the representation of both the Atlantic Niño and AMM leading to poor teleconnectivity over land ( [[#Rodríguez-Fonseca--2015|Rodríguez-Fonseca et al., 2015]] ; [[#Wainwright--2019|Wainwright et al., 2019]] ) and between tropical basins ( [[#Ott--2015|Ott et al., 2015]] ).

Despite some improvements ( [[#Richter--2014|Richter et al., 2014]] ; [[#Nnamchi--2015|Nnamchi et al., 2015]] ), biases in the mean state are so large that the mean east–west temperature gradient at the equator along the thermocline remains opposite to observed in two thirds of the CMIP5 models ( [[#3.5.1.2.2|Section 3.5.1.2.2]] ), which clearly affects the simulation of the Atlantic Niño and associated dynamics ( [[#Muñoz--2012|Muñoz et al., 2012]] ; [[#Ding--2015|Ding et al., 2015]] ; [[#Deppenmeier--2016|Deppenmeier et al., 2016]] ). The interhemispheric SST gradient is also systematically underestimated in models, with a too cold mean state in the northern part of the tropical Atlantic ocean and too warm conditions in the South Atlantic basin. The seasonality is poorly reproduced and the wind–SST coupling is weaker than observed so that altogether, and despite AMM-like variability in 20th century climate simulations, AMM is not the dominant Atlantic mode in all CMIP5 models ( [[#Liu--2013|Liu et al., 2013]] ; [[#Amaya--2017|Amaya et al., 2017]] ). These biases in mean state translate into biases in modelling the mean ITCZ ( [[#Flato--2013|Flato et al., 2013]] ). Similar biases were found in experiments using CMIP5 models but with different climate background states, such as Last Glacial Maximum, mid-Holocene and future scenario simulations ( [[#Brierley--2018|Brierley and Wainer, 2018]] ). Analyses of CMIP6 show encouraging results in the representation of Atlantic Niño and AMM modes of variability in terms of amplitude and seasonality. Some models now display reduced biases in the spatial structure of the modes and related explained variance but persistent errors still remain on average in the timing of the modes and in the coupled nature of the modes, that is, the strength of the link between ocean (SST, mixed layer depth) and atmospheric (wind) anomalies ( [[#Richter--2020|Richter and Tokinaga, 2020]] ), as well as in the Atlantic Ocean equatorial east–west temperature gradient ( [[#3.5.1.2.2|Section 3.5.1.2.2]] , Figure 3.24).

There are some recent indications that increasing model resolution both vertically and horizontally, in the ocean and atmospheric component ( [[#Richter--2015|Richter, 2015]] ; [[#Small--2015|Small et al., 2015]] ; [[#Harlaß--2018|Harlaß et al., 2018]] ), could partly alleviate some tropical Atlantic biases in mean state ( [[#3.5.1.2.2|Section 3.5.1.2.2]] ), seasonality, interannual- to decadal-variability and associated teleconnectivity over land, such as with the West African monsoon ( [[#Steinig--2018|Steinig et al., 2018]] ). Results from CMIP6 tend to confirm that increasing resolution is not the unique way to address the biases in the tropical Atlantic ( [[#Richter--2020|Richter and Tokinaga, 2020]] ). For instance, the inclusion of a stochastic physics scheme has a nearly equivalent effect in the improvement of the mean number and the strength distribution of tropical Atlantic cyclones ( [[#Vidale--2021|Vidale et al., 2021]] ).

( [[IPCC:Wg1:Chapter:Chapter-2#2.4.4|Section 2.4.4]] assess that there is ''low confidence'' in any sustained changes to the AZM and AMM variability in instrumental observations. Moreover, any attribution of possible human influence on the Atlantic modes and associated teleconnections is limited by the poor fidelity of CMIP5 and CMIP6 models in reproducing the mean tropical Atlantic climate, its seasonality and variability, despite hints of some improvement in CMIP6, as well as other sources of uncertainties related to limited process understanding in the observations ( [[#Foltz--2019|Foltz et al., 2019]] ), the response of the tropical Atlantic climate to anthropogenic aerosol forcing ( [[#Booth--2012|Booth et al., 2012]] ; [[#Zhang--2013a|Zhang et al., 2013a]] ) and the presence of strong multi-decadal fluctuations related to AMV ( [[#3.7.7|Section 3.7.7]] ) and cross-tropical basin interactions ( [[#Martín-Rey--2018|Martín-Rey et al., 2018]] ; [[#Cai--2019|Cai et al., 2019]] ). The fact that most models poorly represent the climatology and variability of the tropical Atlantic combined with the short observational record makes it difficult to place the recent observed changes in the context of internal multi-annual variability versus anthropogenic forcing.

In summary, based on CMIP5 and CMIP6 results, there is no robust evidence that the observed changes in either the Atlantic Niño or AMM modes and associated teleconnections over the second half of the 20th century are beyond the range of internal variability or have been influenced by natural or anthropogenic forcing. Considering the physical processes responsible for model biases in these modes, increasing resolution in both ocean and atmosphere components may be an opportunity for progress in the simulation of the tropical Atlantic changes as evidenced by some individual model studies ( [[#Roberts--2018|Roberts et al., 2018]] ), but this needs confirmation from a multi-model perspective.

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