Editing IPCC:AR6/WGI/Chapter-10 (section)

=== 10.1.5 Regional Climate Information in the AR6 WGI Report ===

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This chapter is part of a cluster devoted to regional climate (Chapters 10, 11, 12 and Atlas). It introduces many of the aspects relevant to the generation of regional climate information that are dealt with in detail elsewhere. Figure 10.4 summarizes how these chapters relate to one another and to the rest of the report.

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'''Figure 10.4''' '''|''' '''Schematic diagram that illustrates the treatment of regional climate change in the different parts of the WGI Report and how the chapters relate to each other.'''

( [[IPCC:Wg1:Chapter:Chapter-11|Chapter 11]] assesses observed, attributed and projected changes in weather and climate extremes, provides a mechanistic understanding on how changes in extremes are related to human-induced climate change and provides regional, continental and global-scale assessments on changes in extremes, including compound events. [[IPCC:Wg1:Chapter:Chapter-12|Chapter 12]] identifies elements of the climate system relevant for sectoral impacts referred to as climatic impact-drivers (CIDs), assesses past and future evolutions of sector-relevant CIDs for each AR6 region, synthesizes such evolutions for different time periods and by GWL, and assesses how CIDs are used in climate services. The ( [[IPCC:Wg1:Chapter:Atlas|Atlas]] assesses observed, attributed and projected changes in mean climate, performs a comparison of CMIP5, CMIP6 and CORDEX simulations, evaluates downscaling performance and assesses approaches to communicate climate information. The Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] facilitates the exploration of datasets assessed in all chapters through a wide range of maps, graphs and tables generated in an interactive manner. This allows for the comparison of changes at warming levels and scenario/time-period combinations, display of indices for extremes and CIDs, and serves all chapters in the report to facilitate synthesis information and support the Technical Summary and the Summary for Policymakers.

Other chapters also include a strong regional component and provide context for the assessment of regional climate. [[IPCC:Wg1:Chapter:Chapter-1|Chapter 1]] introduces the different types of climatic regions used in the AR6 WGI Report and the main types of climatic models. [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] describes the recent and current state of the climate from observations, most of which are key for the production of regional information. [[IPCC:Wg1:Chapter:Chapter-3|Chapter 3]] assesses human influence on the climate system and [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] assesses climate change projections, with a global focus. These three chapters include phenomena that are important for shaping regional climate such as general circulation, jets, storm tracks, blocking and modes of variability. At the same time, the visualization of information in global maps in these chapters provides valuable information for the sub-continental scale. [[IPCC:Wg1:Chapter:Chapter-5|Chapter 5]] assesses the knowledge about the carbon and biogoechemical cycles, whose fluxes and responses show variability that is strongly regional in nature. [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] assesses the regional evolution of short-lived climate forcers as well as their influence on regional climate and air quality. [[IPCC:Wg1:Chapter:Chapter-8|Chapter 8]] assesses observed and projected changes in the variability of the regional water cycle, including monsoons, while changes of the regional oceans, changes in cryosphere and regional sea level change are assessed in Chapter 9.

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'''Box 10.1 | Regional Climate in AR5 and the Special Reports SRCCL, SROCC and SR1.5'''

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This box summarizes the information on linking global and regional climate change information in the Fifth Assessment Report (AR5) and the three Special Reports of the IPCC Sixth Assessment Cycle. This information frames the treatment of the production of regional climate information in previous reports and identifies some of the gaps that the AR6 WGI Report needs to address.

'''Fifth Assessment Report, AR5'''

In WGI [[IPCC:Wg1:Chapter:Chapter-9|Chapter 9]] ( [[#Flato--2014|Flato et al., 2014]] ), regional downscaling methods were addressed as tools to provide climate information at the scales needed for many climate impact studies. The assessment found ''high confidence'' that downscaling adds value both in regions with highly variable topography and for various small-scale phenomena. Regional models necessarily inherit biases from the global models used to provide boundary conditions. Furthermore, the ability of AR5 to systematically evaluate regional climate models (RCMs), and statistical downscaling schemes, were hampered because coordinated intercomparison studies were still emerging. However, several studies demonstrated that added value arises from higher resolution in regions where stationary small-scale features like topography and complex coastlines are present, and from improved representation of small-scale processes like convective precipitation.

WGI Chapter 14 ( [[#Christensen--2013|Christensen et al., 2013]] ) stressed that credibility in regional climate change projections increases when key drivers of the change are known to be well-simulated and well-projected by climate models.

Working Group II (WGII) Chapter 21 ( [[#Hewitson--2014b|Hewitson et al., 2014b]] ) addressed the regional climate change context from the perspective of impacts, vulnerability and adaptation. This chapter emphasized that a good understanding of decision-making contexts is essential to define the type and scale of information required from physical climate. Further, the chapter identified that the regional climate information was limited by the paucity of comprehensive observations and their analysis along with the different levels of confidence in projections ( ''high confidence'' ). Notably, at the time of AR5, many studies still relied on global datasets, models, and assessment methods to inform regional decisions, which were not considered as effective as tailored regional approaches. The regional scale was not defined but instead it was emphasized that climate change responses play out on a range of scales, and the relevance and limitations of information differ strongly from global to local scales, and from one region to another.

Chapter 21 noted that the production of downscaled datasets (by both dynamical and statistical methods) remains weakly coordinated, and that results indicate that high-resolution downscaled reconstructions of the current climate can have significant errors. Key in this was that the increase in downscaled datasets has not narrowed the uncertainty range, and that integrating these data with historical change and process-based understanding remains an important challenge.

The chapter identified the common perception that higher resolution (i.e., more spatial detail) equates to more usable and robust information, which is not necessarily true. Instead, it is through the integration of multiple sources of information that robust understanding of change is developed.

WGII Chapter 21 highlighted that the different contexts of an impact study are defining features for how climate risk is perceived. Perspectives were characterized as top-down (physical vulnerability) and bottom-up perspectives (social vulnerability). The top-down perspective uses climate change impacts as the starting point of how people and/or ecosystems are vulnerable to climate change, and commonly applies global-scale scenario information or refines this to the region of interest through downscaling procedures. Conversely, in the ‘bottom-up’ approach the development context is the starting point, focusing on local scales, and layers climate change on top of this. An impact focus tends to look to the future to see how to adjust to expected changes, whereas a vulnerability-focused approach is centred on addressing the drivers of current vulnerability.

Box 10.1

'''Special Report on Climate Change and Land (SRCCL; [[#IPCC--2019a|IPCC, 2019a]] )'''

The SRCCL ( [[#Jia--2019|Jia et al., 2019]] ) assessed that there is ''robust evidence'' and ''high agreement'' that land cover and land use or management exert significant influence on atmospheric states (e.g., temperature, rainfall, wind intensity) and phenomena (e.g., monsoons), at various spatial and temporal scales, through their biophysical influences on climate. There is ''robust evidence'' that dry soil moisture anomalies favour summer heatwaves. Part of the projected increase in heatwaves and droughts can be attributed to soil moisture feedbacks in regions where evapotranspiration is limited by moisture availability ( ''medium confidence'' ). Vegetation changes can also amplify or dampen extreme events through changes in albedo and evapotranspiration, which will influence future trends in extreme events ( ''medium confidence'' ).

The influence of different changes in land use (e.g., afforestation, urbanization), on the local climate depends on the background climate ( ''robust evidence'' , ''high agreement'' ). There is ''high confidence'' that regional climate change can be dampened or enhanced by changes in local land cover and land use, with sign and magnitude depending on region and season.

Water management and irrigation were generally not accounted for by CMIP5 global models available at the time of SRCCL. Additional water can modify regional energy and moisture balance particularly in areas with highly productive agricultural crops with high rate of evapotranspiration. Urbanization increases the risks associated with extreme events ( ''high confidence'' ). Urbanization suppresses evaporative cooling and amplifies heatwave intensity ( ''high confidence'' ) with a strong influence on minimum temperatures ( ''high confidence'' ).

'''Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC; [[#IPCC--2019b|IPCC, 2019b]] )'''

The SROCC ( [[#IPCC--2019b|IPCC, 2019b]] ) stated that observations and models for assessing changes in the ocean and the cryosphere have been developed considerably during the past century but observations in some key regions remain under-sampled and were very short relative to the time scales of natural variability and anthropogenic changes. Retreat of mountain glaciers and thawing of mountain permafrost continues and will continue due to significant warming in those regions, where it is ''likely'' to exceed global temperature increase.

The SROCC assessed that it is ''virtually certain'' that Antarctica and Greenland have lost mass over the past decade and observed glacier mass loss over the last decades is attributable to anthropogenic climate change ( ''high confidence'' ). It is ''virtually certain'' that projected warming will result in continued loss in Arctic sea ice in summer, but there is ''low confidence'' in climate model projections of Antarctic sea ice change because of model biases and disagreement with observed trends. Knowledge and observations of the polar regions were sparse compared to many other regions, due to remoteness and challenges of operating in them.

The sensitivity of small islands and coastal areas to increased sea levels differs between emissions scenarios and regionally, and a consideration of local processes is critical for projections of sea level influences at local scales.

'''Special Report on Global Warming of 1.5°C (SR1.5; [[#IPCC--2018b|IPCC, 2018b]] )'''

The SR1.5 ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) assessed that most land regions were experiencing greater warming than the global average, with annual average warming already exceeding 1.5°C in many regions. Over one quarter of the global population live in regions that have already experienced more than 1.5°C of warming in at least one season. Land regions will warm more than ocean regions over the coming decades (transient climate conditions).

Transient climate projections reveal observable differences between 1.5°C and 2°C global warming in terms of mean temperature and extremes, both at a global scale and for most land regions. Such studies also reveal detectable differences between 1.5°C and 2°C precipitation extremes in many land regions. For mean precipitation and various drought measures there is substantially lower risk for human systems and ecosystems in the Mediterranean region at 1.5°C compared to 2°C.

The different pathways to a 1.5°C warmer world may involve a transition through 1.5°C, with both short- and long-term stabilization (without overshoot), or a temporary rise and fall over decades and centuries (overshoot). The influence of these pathways is small for some climate variables at the regional scale (e.g., regional temperature and precipitation extremes) but can be very large for others (e.g., sea level).

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'''Cross-Chapter Box 10.1 | Influence of the Arctic on Mid-latitude Climate'''

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'''Coordinator:''' Rein Haarsma (The Netherlands)

'''Contributors:''' Francisco J. Doblas-Reyes (Spain), Hervé Douville (France), Nathan P. Gillett (Canada), Gerhard Krinner (France/Germany, France), Dirk Notz (Germany), Krishnan Raghavan (India), Alex C. Ruane (United States of America), Sonia I. Seneviratne (Switzerland), Laurent Terray (France), Cunde Xiao (China)

The Arctic has ''very likely'' warmed more than twice the global rate over the past 50 years with the greatest increase during the cold season (Atlas.11.2). Several mechanisms are responsible for the enhanced lower troposphere warming of the Arctic, including ice albedo, lapse rate, Planck and cloud feedbacks ( [[IPCC:Wg1:Chapter:Chapter-7#7.4.4.1|Section 7.4.4.1]] ). The rapid Arctic warming strongly affects the ocean, atmosphere, and cryosphere in that region ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.2.1|Section 2.3.2.1]] and Atlas.11.2). Averaged over the decade 2010–2019, monthly average sea ice area in August, September and October has been about 25% smaller than during 1979–1988 ( ''high confidence'' ) ( [[IPCC:Wg1:Chapter:Chapter-9#9.3.1.1|Section 9.3.1.1]] ). It is ''very likely'' that anthropogenic forcings mainly due to greenhouse gas increases have contributed substantially to Arctic sea ice loss since 1979, explaining at least half of the observed long-term decrease in summer sea ice extent ( [[IPCC:Wg1:Chapter:Chapter-3#3.4.1.1|Section 3.4.1.1]] ).

Cross-Chapter Box 10.1

In this box, the possible influences of the Arctic warming on the lower latitudes are assessed. This linkage was also the topic of Box 3.2 of the Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC; [[#IPCC--2019b|IPCC, 2019b]] ). It is a topic that has been strongly debated ( [[#Ogawa--2018|Ogawa et al., 2018]] ; K. [[#Wang--2018|]] [[#Wang--2018|Wang et al., 2018]] ). Separate hypotheses have emerged for winter and summer that describe possible mechanisms of how the Arctic can influence the weather and climate at lower latitudes. They involve changes in the polar vortex, storm tracks, jet stream, planetary waves, stratosphere-troposphere coupling, and eddy-mean flow interactions, thereby affecting the mid-latitude atmospheric circulation, and the frequency, intensity, duration, seasonality and spatial extent of extremes and climatic impact-drivers like cold spells, heatwaves, and floods (Cross-Chapter Box 10.1, Figure 1). However, we note that a decrease in the intensity of cold extremes has been observed in the Northern Hemisphere mid-latitudes in winter since 1950 ( [[IPCC:Wg1:Chapter:Chapter-11#11.3.2|Section 11.3.2]] ; [[#van%20Oldenborgh--2019|van Oldenborgh et al., 2019]] ). Since SROCC, new literature has appeared, and the mechanisms and their criticisms are assessed here as an update and extension to the SROCC box.

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'''Cross-Chapter Box 10.1, Figure 1''' 

'''|'''

'''Mechanisms of potential influences of recent and future Arctic warming on mid-latitude climate and variability.''' Mechanisms are different for winter and summer with different associated influences on mid-latitudes. The mechanisms involve changes in the polar vortex, storm tracks, planetary waves and jet stream.

'''Mechanisms for a potential influence in winter'''

It has been proposed that Arctic amplification, by reducing the equator–pole temperature contrast, could result in a weaker and more meandering jet with Rossby waves of larger amplitude ( [[#Francis--2017|Francis et al., 2017]] ; [[#Zhang--2020|Zhang and Luo, 2020]] ). This may cause weather systems to travel eastward more slowly and thus, all other things being equal, Arctic amplification could lead to more persistent weather patterns over the mid-latitudes ( [[#Francis--2012|Francis and Vavrus, 2012]] ). The persistent large meandering flow may increase the likelihood of connected patterns of temperature and precipitation climatic impact-drivers because they frequently occur when atmospheric circulation patterns are persistent, which tends to occur with a strong meridional wind component. Another possible consequence of Arctic warming is on the NAO/AO that shows a negative trend over the 1990s and early 2000s ( [[#Robson--2016|Robson et al., 2016]] ; [[#Iles--2017|Iles and Hegerl, 2017]] ), and has been linked to the reduction of sea ice in the Barents and Kara seas, and the increase in Eurasian snow cover ( [[#Cohen--2012|Cohen et al., 2012]] ; [[#Nakamura--2015|Nakamura et al., 2015]] ; [[#Yang--2016|Yang et al., 2016]] ). During negative NAO/AO the storm tracks shift equatorward and winters are predominantly more severe across northern Eurasia and the eastern United States, but relatively mild in the Arctic. This temperature pattern is sometimes referred to as the ‘warm Arctic–cold continents (WACC)’ pattern ( [[#Chen--2018|Chen et al., 2018]] ). However, L. [[#Sun--2016|]] [[#Sun--2016|Sun et al. (2016)]] noticed that the WACC is a manifestation of natural variability. Enhanced sea ice loss in the Barents-Kara Sea has also been related to a weakening of the stratospheric polar vortex ( [[#Kretschmer--2020|Kretschmer et al., 2020]] ) and its increased variability ( [[#Kretschmer--2016|Kretschmer et al., 2016]] ) that would induce a negative NAO/AO ( [[#Kim--2014|Kim et al., 2014]] ), the WACC pattern ( [[#Kim--2014|Kim et al., 2014]] ), and an increase in cold air outbreaks (CAO) in mid-latitudes ( [[#Kretschmer--2018|Kretschmer et al., 2018]] ). Arctic warming might also increase Eurasian snow cover in autumn caused by the moister air that is advected into Eurasia from the Arctic with reduced sea ice cover ( [[#Cohen--2014|Cohen et al., 2014]] ; [[#Jaiser--2016|Jaiser et al., 2016]] ), although [[#Peings--2019|Peings (2019)]] suggests a possible influence of Ural blockings on both the autumn snow cover and the early winter polar stratosphere. The circulation changes over the Ural-Siberian region are also suggested to provide a link between Barents-Kara sea ice and the NAO ( [[#Santolaria-Otín--2021|Santolaria-Otín et al., 2021]] ).

'''Mechanisms for a potential influence in summer'''

As in winter, Arctic summer warming may result in a weakening of the westerly jet and mid-latitude storm tracks, as suggested for the recent period of Arctic warming ( [[#Coumou--2015|Coumou et al., 2015]] ; [[#Petrie--2015|Petrie et al., 2015]] ; [[#Chang--2016|Chang et al., 2016]] ). Additional proposed consequences are a southward shift of the jet ( [[#Butler--2010|Butler et al., 2010]] ) and a double jet structure associated with an increase of the land–ocean thermal gradient at the coastal boundary ( [[#Coumou--2018|Coumou et al., 2018]] ). It is hypothesized that weaker jets, diminished meridional temperature contrast, and reduced baroclinicity might induce a larger amplitude in stationary wave response to stationary forcings ( [[#Zappa--2011|Zappa et al., 2011]] ; [[#Petoukhov--2013|Petoukhov et al., 2013]] ; [[#Hoskins--2015|Hoskins and Woollings, 2015]] ; [[#Coumou--2018|Coumou et al., 2018]] ; [[#Mann--2018|Mann et al., 2018]] ; R. [[#Zhang--2020|]] [[#Zhang--2020|Zhang et al., 2020]] ), and also that a double jet structure would favour wave resonance ( [[#Kornhuber--2017|Kornhuber et al., 2017]] ; [[#Mann--2017|Mann et al., 2017]] ). Some studies suggest that this is corroborated by an observed increase of quasi-stationary waves ( [[#Di%20Capua--2016|Di Capua and Coumou, 2016]] ; [[#Vavrus--2017|Vavrus et al., 2017]] ; [[#Coumou--2018|Coumou et al., 2018]] ).

'''Assessment'''

The above proposed hypotheses are based on concepts of geophysical fluid dynamics and surface coupling and can, in principle, help explain the existence of a link between the Arctic changes and the mid-latitudes with the potential to affect many impact sectors ( [[#Barnes--2015|Barnes and Screen, 2015]] ). However, the validity of some dynamical underlying mechanisms, such as a reduced meridional temperature contrast inducing enhanced wave amplitude, has been questioned ( [[#Hassanzadeh--2014|Hassanzadeh et al., 2014]] ; [[#Hoskins--2015|Hoskins and Woollings, 2015]] ). On the contrary, the reduced meridional temperature contrast has been related to reduced meridional temperature advection and thereby reduced winter temperature variability ( [[#Collow--2019|Collow et al., 2019]] ).

Studies that support the Arctic influence are mostly based on observational relationships between the Arctic temperature or sea ice extent and mid-latitude anomalies or extremes ( [[#Cohen--2012|Cohen et al., 2012]] ; [[#Francis--2012|Francis and Vavrus, 2012]] , 2015; [[#Budikova--2017|Budikova et al., 2017]] ). They are often criticized for the lack of statistical significance and the inability to disentangle cause and effect ( [[#Barnes--2013|Barnes, 2013]] ; [[#Barnes--2013|Barnes and Polvani, 2013]] ; [[#Screen--2013|Screen and Simmonds, 2013]] ; [[#Barnes--2014|Barnes et al., 2014]] ; [[#Hassanzadeh--2014|Hassanzadeh et al., 2014]] ; [[#Barnes--2015|Barnes and Screen, 2015]] ; [[#Sorokina--2016|Sorokina et al., 2016]] ; [[#Douville--2017|Douville et al., 2017]] ; [[#Gastineau--2017|Gastineau et al., 2017]] ; [[#Blackport--2020a|Blackport and Screen, 2020a]] ; [[#Oudar--2020|Oudar et al., 2020]] ; [[#Riboldi--2020|Riboldi et al., 2020]] ). The role of the Barents-Kara sea ice loss is challenged by [[#Blackport--2019|Blackport et al. (2019)]] who find a minimal influence of reduced sea ice on severe mid-latitude winters, and by [[#Warner--2020|Warner et al. (2020)]] who suggest thatthe apparent winter NAO response to the Barents-Kara sea ice variability is mainly an artefact of the Aleutian Low internal variability and of the co-variability between sea ice and the Aleutian Low originating from tropical-extratropical teleconnections. Also [[#Gong--2020|Gong et al. (2020)]] do not find a link between Rossby wave propagation into the mid-latitudes and Arctic sea ice loss. [[#Mori--2019|Mori et al. (2019)]] argue that models underestimate the influence of the Barents-Kara Sea ice loss on the atmosphere, which is disputed by [[#Screen--2019|Screen and Blackport (2019)]] . Other studies have stressed the importance of atmospheric variability as a driver of Arctic variability ( [[#Lee--2014|Lee, 2014]] ; [[#Woods--2016|Woods and Caballero, 2016]] ; [[#Praetorius--2018|Praetorius et al., 2018]] ; [[#Olonscheck--2019|Olonscheck et al., 2019]] ). Analysing observed key variables of mid-latitude climate for 1980–2020, [[#Blackport--2020b|Blackport and Screen (2020b)]] and [[#Riboldi--2020|Riboldi et al. (2020)]] argue that the Arctic influence on mid-latitudes is small compared to other aspects of climate variability, and that observed periods of strong correlation are an artefact of internal variability or intermittency ( [[#Kolstad--2019|Kolstad and Screen, 2019]] ; [[#Siew--2020|Siew et al., 2020]] ; [[#Warner--2020|Warner et al., 2020]] ).

An additional argument in the criticism is the inability of climate models to simulate a significant response to Arctic sea ice loss, larger than the natural variability (Screen et al., 2014; [[#Walsh--2014|Walsh, 2014]] ; H.W. [[#Chen--2016|Chen et al., 2016]] ; [[#Peings--2017|Peings et al., 2017]] ; [[#Dai--2020|Dai and Song, 2020]] ), or that a very large multi-model ensemble is needed ( [[#Liang--2020|Liang et al., 2020]] ), although some studies find a significant response in summer, because then the internal variability is weaker ( [[#Petrie--2015|Petrie et al., 2015]] ).

Finally, a warmer Arctic climate can, without any additional changes in atmospheric dynamics, reduce cold extremes in winter due to advection of increasingly warmer air from the Arctic into the mid-latitudes ( [[#Screen--2014|Screen, 2014]] ; [[#Ayarzagüena--2016|Ayarzagüena and Screen, 2016]] ; [[#Ayarzagüena--2018|Ayarzagüena et al., 2018]] ).

Summarizing, different hypotheses have been developed about the influence of recent Arctic warming on the mid-latitudes in both winter and summer. Although some of the proposed mechanisms seem to be supported by various studies, the underlying mechanisms and relative strength compared to internal climate variability have been questioned. A recent review ( [[#Cohen--2020|Cohen et al., 2020]] ) states that divergent conclusions between model and observational studies, and also between different model studies, continue to obfuscate a clear understanding of how Arctic warming is influencing mid-latitude weather. In this context, [[#Shepherd--2016b|Shepherd (2016b)]] stresses the need for collaboration between scientists with different viewpoints for further understanding that could be achieved by carefully designed, multi-investigator, coordinated, multi-model simulations, data analyses and diagnostics ( [[#Overland--2016|Overland et al., 2016]] ). In agreement with Box 3.2 of SROCC, there is ''low to medium confidence'' in the exact role and quantitative effect of historical Arctic warming and sea ice loss on mid-latitude atmospheric variability.

Regarding future climate, it is important to note that mid-latitude variability is also affected by many drivers other than the Arctic changes and that those drivers as well as the linkages to mid-latitude variability might change in a warmer world. The AMV, PDV, ENSO (see Annex IV), upper tropospheric tropical heating, polar stratospheric vortex, and land surface processes associated with soil moisture ( [[#Miralles--2014|Miralles et al., 2014]] ; [[#Hauser--2016|Hauser et al., 2016]] ) and snow cover ( [[#Nakamura--2019|Nakamura et al., 2019]] ; Sato and Nakamura, 2019) are a few examples. A considerable body of literature has shown that changes to the NAO/AO on seasonal and climate change time scales can be driven by variations in the wavelength and amplitude of Rossby waves, mainly of tropical origin ( [[#Fletcher--2011|Fletcher and Kushner, 2011]] ; [[#Cattiaux--2013|Cattiaux and Cassou, 2013]] ; [[#Ding--2014|Ding et al., 2014]] ; [[#Goss--2016|Goss et al., 2016]] ). The influence of future Arctic warming on mid-latitude circulation is difficult to disentangle from the effect of such a plethora of drivers ( [[#Blackport--2017|Blackport and Kushner, 2017]] ; F. [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|Li et al., 2018]] ). One of the consequences of climate change is a poleward shift of the jet induced by the tropical warming ( [[#Barnes--2013|Barnes and Polvani, 2013]] ), which is less obvious in winter especially over the North Atlantic ( [[#Peings--2018|Peings et al., 2018]] ; [[#Oudar--2020|Oudar et al., 2020]] ), and the increase of the meridional temperaturegradient in the upper troposphere, which increases storm track activity ( [[#Barnes--2015|Barnes and Screen, 2015]] ; [[#Parding--2019|Parding et al., 2019]] ). Although climate models indicate that future Arctic warming and the associated equator–pole temperature gradient decrease could affect mid-latitude climate and variability ( [[#Haarsma--2013a|Haarsma et al., 2013a]] ; [[#McCusker--2017|McCusker et al., 2017]] ; [[#Zappa--2018|Zappa et al., 2018]] ), and even the tropics and subtropics ( [[#Deser--2015|Deser et al., 2015]] ; [[#Cvijanovic--2017|Cvijanovic et al., 2017]] ; K. [[#Wang--2018|]] [[#Wang--2018|Wang et al., 2018]] ; [[#England--2020|England et al., 2020]] ; [[#Kennel--2020|Kennel and Yulaeva, 2020]] ), they do not reveal a strong influence on extreme weather ( [[#Woollings--2014|Woollings et al., 2014]] ).

In conclusion, there is ''low confidence'' in the relative contribution of Arctic warming to mid-latitude atmospheric changes compared to other drivers. Future climate change could affect mid-latitude variability in a number of ways that are still to be clarified, and which may also include the influence of Arctic warming. The linkages between the Arctic warming and the mid-latitude circulation are an example of contrasting lines of evidence that cannot yet be reconciled ( [[#10.5|Section 10.5]] ).

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