Editing IPCC:AR6/WGI/TS (section)

== TS.4 Regional Climate Change ==

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This section focuses on how to generate regional climate change information and its relevance for climate services; the drivers of regional climate variability and change and how they are being affected by anthropogenic factors; and observed, attributed and projected changes in climate, including extreme events and climatic impact-drivers (CIDs), across all regions of the world. There is a small set of CID changes common to all land or ocean regions and a specific set of changes from a broader range of CIDs seen in each region. This regional diversity results from regional climate being determined by a complex interplay between the seasonal-to-multi-decadal variation of large-scale modes of climate variability, external natural and anthropogenic forcings, local climate processes and related feedbacks.

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=== TS.4.1 Generation and Communication of Regional Climate Change Information ===

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'''Climate change information at regional scale is generated using a range of data sources and methodologies. Multi-model ensembles and models with a range of resolutions are important data sources, and discarding models that fundamentally misrepresent relevant processes improves the credibility of ensemble information related to these processes. A key methodology is distillation – combining lines of evidence and accounting for stakeholder context and values – which helps ensure the information is relevant, useful and trusted for decision-making (see Core Concepts Box) ( ''high confidence'' ).''' '''Since AR5, physical climate storylines have emerged as a complementary approach to ensemble projections for generating more accessible climate information and promoting a more comprehensive treatment of risk. They have been used as part of the distillation process within climate services to generate the required context-relevant, credible and trusted climate information.''' '''Since AR5, climate change information produced for climate services has increased significantly due to scientific and technological advancements and growing user awareness, requirements, and demand ( ''very high confidence'' ). The decision-making context, level of user engagement, and co-production between scientists, practitioners and users are important determinants of the type of climate service developed and its utility in supporting adaptation, mitigation and risk management decisions. Links to chapters 10.3, 10.6, Cross-Chapter Box 10.3, 12.6, Cross-Chapter Box 12.2'''
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==== TS.4.1.1 Sources and Methodologies for Generating Regional Climate Information ====

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Climate change information at regional scale is generated using a range of data sources and methodologies (Section TS.1.4). Understanding of observed regional climate change and variability is based on the availability and analysis of multiple observational datasets that are suitable for evaluating the phenomena of interest (e.g., extreme events), including accounting for observational uncertainty (Section TS.1.2.1). These datasets are combined with climate model simulations of observed changes and events to attribute causes of those changes and events to large- and regional-scale anthropogenic and natural drivers and to assess the performance of the models. Future simulations with many climate models (multi-model ensembles) are then used to generate and quantify ranges of projected regional climate responses (Section TS.4.2). Discarding models that fundamentally misrepresent relevant processes improves the credibility of regional climate information generated from these ensembles ( ''high confidence'' ). However, multi-model mean and ensemble spread are not a full measure of the range of projection uncertainty and are not sufficient to characterize low-likelihood, high-impact changes (Box TS.3) or situations where different models simulate substantially different or even opposite changes ( ''high confidence'' ) ''.'' Large single-model ensembles are now available and provide a more comprehensive spectrum of possible changes associated with internal variability ( ''high confidence'' ) (Section TS.1.2.3). Links to chapters 1.5.1, 1.5.4, 10.2, 10.3.3, 10.3.4, 10.4.1, 10.6.2, 11.2, Box 11.2, Cross-Chapter Box 11.1, 12.4, Atlas.1.4.1

Depending on the region of interest, representing regionally important forcings (e.g., aerosols, land-use change and ozone concentrations) and feedbacks (e.g., between snow and albedo, soil moisture and temperature, or soil moisture and precipitation) in climate models is a prerequisite for them to reproduce past regional trends to underpin the reliability of future projections ( ''medium confidence'' ) (Section TS.1.2.2). In some cases, even the sign of a projected change in regional climate cannot be trusted if relevant regional processes are not represented, for example, for variables such as precipitation and wind speed ( ''medium confidence'' ) ''.'' In some regions, either geographical (e.g., Central Africa, Antarctica) or typological (e.g., mountainous areas, Small Islands and cities), and for certain phenomena, fewer observational records are available or accessible, which limits the assessment of regional climate change in these cases. Links to chapters 1.5.1, 1.5.3, 1.5.4, 8.5.1, 10.2, 10.3.3, 10.4.1, 11.1.6, 11.2, 12.4, Atlas.8.3, Atlas.11.1.5, Cross-Chapter Box Atlas.2

Methodologies such as statistical downscaling, bias adjustment and weather generators are beneficial as an interface between climate model projections and impact modelling and for deriving user-relevant indicators ( ''high confidence'' ). However, the performance of these techniques depends on that of the driving climate model: in particular, bias adjustment cannot overcome all consequences of unresolved or strongly misrepresented physical processes, such as large-scale circulation biases or local feedbacks ( ''medium confidence'' ). Links to chapters 10.3.3, Cross-Chapter Box 10.2, 12.2, Atlas.2.2

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'''Box TS.10 | Event Attribution'''

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'''The attribution of observed changes in extremes to human influence (including greenhouse gas and aerosol emissions and land-use changes) has substantially advanced since AR5, in particular for extreme precipitation, droughts, tropical cyclones, and compound extremes ( ''high confidence'' ). There is limited evidence for windstorms and convective storms. Some recent hot extreme events would have been ''extremely unlikely'' to occur without human influence on the climate system. (Section TS.1) Links to chapters Cross-Working Group Box: Attribution in Chapter 1, 11.2, 11.3, 11.4, 11.6, 11.7, 11.8'''
Since AR5, the attribution of extreme weather events has emerged as a growing field of climate research with an increasing body of literature. It provides evidence that greenhouse gases and other external forcings have affected individual extreme weather events by disentangling anthropogenic drivers from natural variability. Event attribution is now an important line of evidence for assessing changes in extremes on regional scales. (Section TS.1) Links to chapters Cross-Working Group Box: Attribution, 11.1.4

The regional extremes and events that have been studied are geographically uneven (Section TS.4.1). A few events, for example, extreme rainfall events in the United Kingdom, heatwaves in Australia, or Hurricane Harvey that hit Texas in 2017, have been heavily studied. Many highly impactful extreme weather events have not been studied in the event attribution framework, particularly in the developing world where studies are generally lacking. This is due to various reasons, including lack of observational data, lack of reliable climate models, and lack of scientific capacity. While the events that have been studied are not representative of all extreme events that have occurred, and results from these studies may also be subject to selection bias, the large number of event attribution studies provide evidence that changes in the properties of these local and individual events are in line with expected consequences of human influence on the climate and can be attributed to external drivers. Links to chapters Cross-Working Group Box: Attribution, 11.1.4, 11.2.2

It is ''very likely'' that human influence is the main contributor to the observed increase in the intensity and frequency of hot extremes and the observed decrease in the intensity and frequency of cold extremes on continental scales. Some specific recent hot extreme events would have been ''extremely unlikely'' to occur without human influence on the climate system. Changes in aerosol concentrations have ''likely'' slowed the increase in hot extremes in some regions, in particular from 1950–1980. No-till farming, irrigation and crop expansion have similarly attenuated increases in summer hot extremes in some regions, such as central North America ( ''medium confidence'' ). Links to chapters 11.3.4

Human influence has contributed to the intensification of heavy precipitation in three continents where observational data are most abundant: North America, Europe and Asia ( ''high confidence'' ). On regional scales, evidence of human influence on extreme precipitation is limited, but new evidence from attributing individual heavy precipitation events found that human influence was a significant driver of the events. Links to chapters 11.4.4

There is ''low confidence'' that human influence has affected trends in meteorological droughts in most regions, but ''medium confidence'' that they have contributed to the severity of some specific events. There is ''medium confidence'' that human-induced climate change has contributed to increasing trends in the probability or intensity of recent agricultural and ecological droughts, leading to an increase of the affected land area. Links to chapters 11.6.4

Event attribution studies of specific strong tropical cyclones provide ''limited evidence'' for anthropogenic effects on tropical cyclone intensifications so far, but ''high confidence'' for increases in precipitation. There is ''high confidence'' that anthropogenic climate change contributed to extreme rainfall amounts during Hurricane Harvey (in 2017) and other intense tropical cyclones. Links to chapters 11.7.3

The number of evident attribution studies on compound events is limited. There is ''medium confidence'' that weather conditions that promote wildfires have become more probable in southern Europe, northern Eurasia, the USA, and Australia over the last century. In Australia a number of event attribution studies show that there is ''medium confidence'' of increase in fire weather conditions due to human influence. Links to chapters 11.8.3, 12.4.3.2

[[File:ee580d1fcb8436a63af6f5e5adc3f5d0 IPCC_AR6_WGI_TS_Box_10_Figure_1.png]]

'''Box TS.10, Figure 1 |'''

'''Synthesis of assessed observed and attributable regional changes.''' The IPCC AR6 WGI inhabited regions are displayed as '''hexagons''' of identical sizes in their approximate geographical location (see legend for regional acronyms). All assessments are made for each region as a whole and for the 1950s to the present. Assessments made on different time scales or more local spatial scales might differ from what is shown in the figure. The '''colours''' in each panel represent the four outcomes of the assessment on observed changes. Striped hexagons (white and light-grey) are used where there is ''low agreement'' in the type of change for the region as a whole, and grey hexagons are used when there is limited data and/or literature that prevents an assessment of the region as a whole. Other colours indicate at least ''medium confidence'' in the observed change. The '''confidence level''' for the human influence on these observed changes is based on assessing trend detection and attribution and event attribution literature, and it is indicated by the number of dots: three dots for ''high confidence'' , two dots for ''medium confidence'' and one dot for ''low confidence'' (single, filled dot: limited agreement; single, empty dot: ''limited evidence'' ).
'''Panel (a) For hot extremes,''' the evidence is mostly drawn from changes in metrics based on daily maximum temperatures; regional studies using other indices (heatwave duration, frequency and intensity) are used in addition. Red hexagons indicate regions where there is at least ''medium confidence'' in an observed increase in hot extremes.

'''Panel (b) For heavy precipitation,''' the evidence is mostly drawn from changes in indices based on one-day or five-day precipitation amounts using global and regional studies. Green hexagons indicate regions where there is at least ''medium confidence'' in an observed increase in heavy precipitation.

'''Panel (c) Agricultural and ecological droughts''' are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water balance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. Yellow hexagons indicate regions where there is at least ''medium confidence'' in an observed increase in this type of drought and green hexagons indicate regions where there is at least ''medium confidence'' in an observed decrease in agricultural and ecological drought.

For all regions, Table TS.5 shows a broader range of observed changes besides the ones shown in this figure. Note that Southern South America (SSA) is the only region that does not display observed changes in the metrics shown in this figure, but is affected by observed increases in mean temperature, decreases in frost and increases in marine heatwaves. (Table TS.5) Links to chapters 11.9, Atlas, 1.3.3, Figure Atlas.2

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==== TS.4.1.2 Regional Climate Information Distillation and Climate Services ====

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The construction of regional climate information involves people with a variety of backgrounds, from various disciplines, who have different sets of experiences, capabilities and values. The process of synthesizing climate information from different lines of evidence from a number of sources, taking into account the context of a user vulnerable to climate variability and change and the values of all relevant actors, is called distillation. Distillation is conditioned by the sources available, the actors involved, and the context, which all depend heavily on the regions considered, and is framed by the question being addressed. Distilling regional climate information from multiple lines of evidence and taking the user context into account increases fitness, usefulness, relevance and trust in that information for use in climate services (Box TS.11) and decision-making ( ''high confidence'' ). Links to chapters 1.2.3, 10.1.4, 10.5, Cross-Chapter Box 10.3, 12.6

The distillation process can vary substantially, as it needs to consider multiple lines of evidence on all physically plausible outcomes (especially when they are contrasting) relevant to a specific decision required in response to a changing climate. Confidence in the distilled regional climate information is enhanced when there is agreement across multiple lines of evidence, so the outcome can be limited if these are inconsistent or contradictory. For example, in the Mediterranean region the agreement between different lines of evidence, such as observations, projections by regional and global models, and understanding of the underlying mechanisms, provides ''high confidence'' in summer warming that exceeds the global average (see Box TS.12). In a less clear-cut case for Cape Town, South Africa, despite consistency among global model future projections, there is ''medium confidence'' in a projected future drier climate due to the lack of consistency in links between increasing greenhouse gases, changes in a key mode of variability (the Southern Annular Mode) and drought in Cape Town among different observation periods and in model simulations. Links to chapters 10.5.3, 10.6, 10.6.2, 10.6.4, Cross-Chapter Box 10.3, 12.4

Since AR5, physical climate storyline approaches have emerged as a complementary instrument to provide a different perspective, or additional climate information, to facilitate communication of the information or provide a more flexible consideration of risk. Storylines that condition climatic events and processes on a set of plausible but distinct large-scale climatic changes enable the exploration of uncertainties in regional climate projections. For example, they can explicitly address low-likelihood, high-impact outcomes, which would be less emphasized in a probabilistic approach, and can be embedded in a user’s risk landscape, taking account of socio-economic factors as well as physical climate changes. Storylines can also be used to communicate climate information by narrative elements describing and contextualizing the main climatological features and the relevant consequences in the user context and, as such, can be used as part of a climate information distillation process. Links to chapters 1.4.4., Box 10.2, 11.2, Box 11.2, Cross-Chapter Box 12.2

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'''Box TS.11 | Climate Services'''

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'''Climate services involve providing climate information to assist decision-making, for example, about how extreme rainfall will change to inform improvements in urban drainage. Since AR5, there has been a significant increase in the range and diversity of climate service activities ( ''very'' ''high confidence'' ). The level of user-engagement, co-design and co-production are factors determining the utility of climate services, while resource limitations for these activities constrain their full potential. Links to chapters 12.6, Cross-Chapter Box 12.2'''
Climate services include engagement from users and providers and an effective access mechanism; they are responsive to user needs and based on integrating scientifically credible information and relevant expertise. Climate services are being developed across regions, sectors, time scales and user-groups and include a range of knowledge brokerage and integration activities. These involve identifying knowledge needs; compiling, translating and disseminating knowledge; coordinating networks and building capacity through informed decision-making; analysis, evaluation and development of policy; and personal consultation.

Since AR5, climate change information produced in climate service contexts has increased significantly due to scientific and technological advancements and growing user awareness, requirements and demand ( ''very'' ''high confidence'' ). Climate services are growing rapidly and are highly diverse in their practices and products. The decision-making context, level of user engagement and co-production between scientists, practitioners and intended users are important determinants of the type of climate service developed and their utility for supporting adaptation, mitigation and risk management decisions. They require different types of user–producer engagement depending on what the service aims to deliver ( ''high confidence'' ), and these fall into three broad categories: website-based services, interactive group activities and focused relationships ''.''

Realization of the full potential of climate services is often hindered by limited resources for the co-design and co-production process, including sustained engagement between scientists, service providers and users ( ''high confidence'' ). Further challenges relate to the development and provision of climate services, generation of climate service products, communication with users, and evaluation of their quality and socio-economic benefit. (Section TS.4.1) Links to chapters 1.2.3, 10.5.4, 12.6, Cross-Chapter Box 12.2, Glossary

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'''Box TS.12 | Multiple Lines of Evidence for Assessing Regional Climate Change and the''' '''Interactive''' '''Atlas'''

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'''A key novel element in the AR6 is the Working Group I Atlas, which includes the Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] ( https://interactive-atlas.ipcc.ch/ ). The Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] provides the ability to explore much of the observational and climate model data used as lines of evidence in this assessment to generate regional climate information. Links to chapters Atlas.2'''
A significant innovation in the AR6 WGI Report is the Atlas. Part of its remit is to provide region-by-region assessment on changes in mean climate and to link with other WGI chapters to generate climate change information for the regions. An important component is the new online interactive tool, the Interactive Atlas, with flexible spatial and temporal analyses of much of the observed, simulated past and projected future climate change data underpinning the WGI assessment. This includes the ability to generate global maps and a number of regionally aggregated products (time series, scatter plots, tables, etc.) for a range of observations and ensemble climate change projections of variables (such as changes in the climatic impact-drivers summarized in Table TS.5) from the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5, CMIP6) and the Coordinated Regional Climate Downscaling Experiment (CORDEX). The data can be displayed and summarized under a range of SSP-RCP scenarios and future time slices and also for different global warming levels, relative to several different baseline periods. The maps and various statistics can be generated for annual mean trends and changes or for any user-specified season. A new set of WGI reference regions is used for the regional summary statistics and applied widely throughout the report (with the regions, along with aggregated datasets and the code to generate these, available at the ATLAS GitHub: https://github.com/IPCC-WG1/Atlas ).

Box TS.12, Figure 1 shows how the Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] products, together with other lines of evidence, can be used to generate climate information for an illustrative example of the Mediterranean summer warming. The lines of evidence include the understanding of relevant mechanisms, dynamic and thermodynamic processes and the effect of aerosols in this case (Box TS.12, Figure 1a); trends in observational datasets (which can have different spatial and temporal coverage; Box TS.12, Figure 1b, c); and attribution of these trends and temperature projections from global and regional climate models at different resolutions, including single-model initial-condition large ensembles (SMILEs; Box TS.12, Figure 1d, e). Taken together, this evidence shows there is ''high confidence'' that the projected Mediterranean summer temperature increase will be larger than the global mean, with consistent results from CMIP5 and CMIP6 (Box TS.12, Figure 1e). However, CMIP6 results project both more pronounced warming than CMIP5 for a given emissions scenario and time period and a greater range of changes (Box TS.12, Figure 1d). Links to chapters 10.6.4, Atlas.2, Atlas.8.4

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'''Box TS.12, Figure 1 |'''

'''Example of generating regional climate information from multiple lines of evidence for the case of Mediterranean summer warming.''' Box TS.12 ''The intent of this figure is to provide an example of using different lines of evidence to assess the confidence in or likelihood of a projected change in regional climate and which of these lines of evidence are available to view and explore in the Interactive Atlas.'' '''(a)''' Mechanisms and feedbacks involved in enhanced Mediterranean summer warming. '''(b)''' Locations of observing stations from different datasets. '''(c)''' Distribution of 1960–2014 summer temperature trends (°C per decade) for observations (black crosses), CMIP5 (blue circles), CMIP6 (red circles), HighResMIP (orange circles), CORDEX EUR-44 (light blue circles), CORDEX EUR-11 (green circles), and selected single model initial-condition large ensembles (SMILEs; grey boxplots, MIROC6, CSIRO-Mk3-6-0, MPI-ESM and d4PDF). '''(d)''' Time series of area averaged (25°N–50°N, 10°W–40°E) land point summer temperature anomalies (°C, baseline period is 1995–2014): the boxplot shows long term (2081–2100) temperature changes of different CMIP6 scenarios in respect to the baseline period. '''(e)''' Projected Mediterranean summer warming in comparison to global annual mean warming of CMIP5 (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) and CMIP6 (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) ensemble means (lines) and spread (shading). Links to chapters Figure 10.20, Figure 10.21, Figure Atlas.8

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=== TS.4.2 Drivers of Regional Climate Variability and Change ===

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'''Anthropogenic forcing, including GHGs and aerosols, but also regional land use and irrigation have all affected observed regional climate changes ( ''high confidence'' ) and will continue to do so in the future ( ''high confidence'' ), with various degrees of influence and response times, depending on warming levels, the nature of the forcing and the relative importance of internal variability.''' '''Since the late 19th century, major modes of variability (MoVs) exhibited fluctuations in frequency and magnitude at multi-decadal time scales, but no sustained trends outside the range of internal variability (Table TS.4). An exception is the Southern Annular Mode (SAM), which has become systematically more positive ( ''high confidence'' ) and is projected to be more positive in all seasons, except for December–January–February (DJF), in high CO <sub>2</sub> emissions scenarios ( ''high confidence'' ). The influence of stratospheric ozone forcing on the SAM trend has been reduced since the early 2000s compared to earlier decades, contributing to the weakening of its positive trend as observed over 2000–2019 ( ''medium confidence'' ).''' '''In the near term, projected changes in most of the MoVs and related teleconnections will ''likely'' be dominated by internal variability. In the long term, it is ''very likely'' that the precipitation variance related to El Niño–Southern Oscillation will increase. Physical climate storylines, including the complex interplay between climate drivers, MoVs, and local and remote forcing, increase confidence in the understanding and use of observed and projected regional changes. Links to chapters 2.4, 3.7, 4.3, 4.4, 4.5, 6.4, 8.3, 8.4, 10.3, 10.4, 11.3'''
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==== TS.4.2.1 Regional Fingerprints of Anthropogenic and Natural Forcing ====

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While anthropogenic forcing has contributed to multi-decadal mean precipitation changes in several regions, internal variability can delay emergence of the anthropogenic signal in long-term precipitation changes in many land regions ( ''high confidence'' ). At the regional scale, the effect of human-induced GHG forcing on extreme temperature is moderated or amplified by soil moisture feedback, snow/ice-albedo feedback, regional forcing from land-use/land-cover changes, forcing from aerosol concentrations, or decadal/multi-decadal natural variability. Changes in local and remote aerosol forcings lead to south–north gradients of the effective radiative forcing (hemispherical asymmetry). Along latitudes, it is more uniform, with strong amplification of the temperature response towards the Arctic ( ''medium confidence'' ). The decrease of SO <sub>2</sub> emissions since the 1980s reduces the damping effect of aerosols, leading to a faster increase in surface air temperature that is most pronounced at mid- and high latitudes of the Northern Hemisphere, where the largest emissions reductions have taken place ( ''medium confidence'' ). Links to chapters 1.3, 3.4.1, 6.3.4, 6.4.1, 6.4.3, 8.3.1, 8.3.2, Box 8.1, 10.4.2, 10.6, 11.1.6, 11.3

Multi-decadal dimming and brightening trends in incoming solar radiation at Earth’s surface occurred at widespread locations ( ''high confidence'' ). Multi-decadal variation in anthropogenic aerosol emissions are thought to be a major contributor ( ''medium confidence'' ), but multi-decadal variability in cloudiness may also have played a role. Volcanic eruptions affect regional climate through their spatially heterogeneous effect on the radiative budget as well as through triggering dynamical responses by favouring a given phase from some MoVs, for instance. Links to chapters 1.4.1, Cross-Chapter Box 1.2, 2.2.1, 2.2.2, 3.7.1, 3.7.3, 4.3.1, 4.4.1, 4.4.4, Cross-Chapter Box 4.1, 7.2.2, 8.5.2, 10.1.4, 11.1.6, 11.3.1

Historical urbanization affects the observed warming trends in cities and their surroundings ( ''very'' ''high confidence'' ). Future urbanization will amplify the projected air temperature under different background climates, with a strong effect on minimum temperatures that could be as large as the global warming signal ( ''very high confidence'' ) (Box TS.14). Irrigation and crop expansion have attenuated increases in summer hot extremes in some regions, such as central North America ( ''medium confidence'' ) (Box TS.6). Links to chapters Box 10.3, 11.1.6, 11.3

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==== TS.4.2.2 Modes of Variability and Regional Teleconnections ====

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Modes of variability (Annex IV, Table TS.4) have existed for millennia or longer ( ''high confidence'' ), but there is ''low confidence'' in detailed reconstructions of most of them prior to direct instrumental records. MoVs are treated as a main source of uncertainties associated with internal dynamics, as they can either accentuate or dampen, even mask, the anthropogenically forced responses. Links to chapters 2.4, 8.5.2, 10.4, 10.6, 11.1.5, Atlas.3.1

Since the late 19th century, major MoVs (Table TS.4) show no sustained trends, exhibiting fluctuations in frequency and magnitude at multi-decadal time scales, except for the Southern Annular Mode (SAM), which has become systematically more positive ( ''high confidence'' ) (Table TS.4). It is ''very likely'' that human influence has contributed to this trend from the 1970s to the 1990s, and to the associated strengthening and southward shift of the Southern Hemispheric extratropical jet in austral summer. The influence of stratospheric ozone forcing on the SAM trend has been reduced since the early 2000s compared to earlier decades, contributing to the weakening of its positive trend observed over 2000–2019 ( ''medium confidence'' ). By contrast, the cause of the Northern Annular Mode (NAM) trend toward its positive phase since the 1960s and associated northward shifts of Northern Hemispheric extratropical jet and storm track in boreal winter is not well understood. The evaluation of model performance on simulating MoVs is assessed in Section TS.1.2.2. Links to chapters 2.3.3, 2.4, 3.3.3, 3.7.1, 3.7.2

In the near term, the forced change in SAM in austral summer is ''likely'' to be weaker than observed during the late 20th century under all five SSPs assessed. This is because of the opposing influence in the near to mid-term from stratospheric ozone recovery and increases in other greenhouse gases on the Southern Hemisphere summertime mid-latitude circulation ( ''high confidence'' ). In the near term, forced changes in the SAM in austral summer are therefore ''likely'' to be smaller than changes due to natural internal variability. In the long term (2081–2100) under the SSP5-8.5 scenario, the SAM index is ''likely'' to increase in all seasons relative to 1995–2014. The CMIP6 multi-model ensemble projects a long-term (2081–2100) increase in the boreal wintertime NAM index under SSP3-7.0 and SSP5-8.5, but regional associated changes may deviate from a simple shift in the mid-latitude circulation due to a modified teleconnection resulting from interaction with a modified mean background state. Links to chapters 4.3.3, 4.4.3, 4.5.1, 4.5.3, 8.4.2

Human influence has not affected the principal tropical modes of interannual climate variability (Table TS.4) and their associated regional teleconnections beyond the range of internal variability ( ''high confidence'' ). It is ''virtually certain'' that the El Niño–Southern Oscillation (ENSO) will remain the dominant mode of interannual variability in a warmer world. There is no consensus from models for a systematic change in amplitude of ENSO sea surface temperature (SST) variability over the 21st century in any of the SSP scenarios assessed ( ''medium confidence'' ). However, it is ''very'' ''likely'' that rainfall variability related to ENSO will be enhanced significantly by the latter half of the 21st century in the SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios, regardless of the amplitude changes in SST variability related to the mode. It is ''very likely'' that rainfall variability related to changes in the strength and spatial extent of ENSO teleconnections will lead to significant changes at regional scale. Links to chapters 3.7.3, 3.7.4, 3.7.5, 4.3.3, 4.5.3, 8.4.2, 10.3.3

Modes of decadal and multi-decadal variability over the Pacific and Atlantic Ocean exhibit no significant changes in variance over the period of observational records ( ''high confidence'' ). There is ''medium confidence'' that anthropogenic and volcanic aerosols contributed to observed temporal evolution in the Atlantic Multi-decadal Variability (AMV) and associated regional teleconnections, especially since the 1960s, but there is ''low confidence'' in the magnitude of this influence and the relative contributions of natural and anthropogenic forcings. Internal variability is the main driver of Pacific Decadal Variability (PDV) observed since the start of the instrumental records ( ''high confidence'' ), despite some modelling evidence for potential external influence. There is ''medium confidence'' that the AMV will undergo a shift towards a negative phase in the near term. Links to chapters 2.4, 3.7.6, 3.7.7, 8.5.2, 4.4.3

'''Table TS.4 |''' '''Summary of the assessments on modes of variability (MoVs) and associated teleconnections.''' '''(a)''' Assessments on observed changes since the start of instrumental records, Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6) model performance, human influence on the observed changes, and near-term (2021–2040) and mid- to long-term (2041–2100) changes. Curves schematically illustrate the assessed overall changes, with the horizontal axis indicating time, and are not intended to precisely represent the time evolution. '''(b)''' Fraction of surface air temperature (SAT) and precipitation (pr) variance explained at interannual time scale by each MoV for each AR6 region (numbers in each cell; in percent). Values correspond to the average of significant explained variance fractions based on HadCRUT, GISTEMP, BerkeleyEarth and CRU-TS (for SAT) and GPCC and CRU-TS (for precipitation). Significance is tested based on F-statistics at the 95% level confidence, and a slash indicates that the value is not significant in more than half of the available data sets. The colour scale corresponds to the sign and values of the explained variance as shown at the bottom. The corresponding anomaly maps are shown in Annex IV. DJF: December–January–February. MAM: March–April–May. JJA: June–July–August. SON: September–October–November. In (b), Northern Annular Mode (NAM) and El Niño–Southern Oscillation (ENSO) teleconnections are evaluated for 1959–2019, Southern Annular Mode (SAM) for 1979–2019, Indian Ocean Basin (IOB), Indian Ocean Dipole (IOD), Atlantic Zonal Mode (AZM) and Atlantic Meridional Mode (AMM) for 1958–2019, and Pacific Decadal Variability (PDV) and Atlantic Multi-decadal Variability (AMV) for 1900–2019. All data are linearly detrended prior to computation. (Section TS.1.2.2) Links to chapters 2.4, 3.7, 4.3.3, 4.4.3, 4.5.3, Table Atlas.1, Annex IV

(a) Assessments on MoV.

[[File:6152601bbece01e0be6af5c25e977cb0 IPCC_AR6_WGI_TS_Table_TS_4a.png]]

'''Table TS.4 (continued): (b) Regional climate anomalies associated with MoV.'''

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<span id="ts.4.2.3-interplay-between-drivers-of-climate-variability-and-change-at-regional-scales"></span>
==== TS.4.2.3 Interplay Between Drivers of Climate Variability and Change at Regional Scales ====

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Anthropogenic forcing has been a major driver of regional mean temperature change since 1950 in many sub-continental regions of the world ( ''virtually certain'' ). At regional scales, internal variability is stronger, and uncertainties in observations, models and external forcing are all larger than at the global scale, hindering a robust assessment of the relative contributions of greenhouse gases, stratospheric ozone, and different aerosol species in most of the cases. Multiple lines of evidence, combining multi-model ensemble global projections with those coming from single-model initial-condition large ensembles, show that internal variability is largely contributing to the delayed or absent emergence of the anthropogenic signal in long-term regional mean precipitation changes ( ''high confidence'' ). Internal variability in ocean dynamics dominates regional patterns on annual to decadal time scales ( ''high confidence'' ). The anthropogenic signal in regional sea level change will emerge in most regions by 2100 ( ''medium confidence'' ). Links to chapters 9.2.4, 9.6.1, 10.4.1, 10.4.2, 10.4.3

Regional climate change is subject to the complex interplay between multiple external forcings and internal variability. Time evolution of mechanisms operating at different time scales can modify the amplitude of the regional-scale response of temperature, and both the amplitude and sign of the response of precipitation, to anthropogenic forcing ( ''high confidence'' ). These mechanisms include non-linear temperature, precipitation and soil moisture feedbacks; slow and fast responses of SST patterns; and atmospheric circulation changes to increasing GHGs. Land-use and aerosol forcings and land–atmosphere feedback play important roles in modulating regional changes, for instance in weather and climate extremes ( ''high confidence'' ). These can also lead to a higher warming of extreme temperatures compared to mean temperature ( ''high confidence'' ), and possibly cooling in some regions ( ''medium confidence'' ). The soil moisture–temperature feedback was shown to be relevant for past and present-day heatwaves based on observations and model simulations. Links to chapters 10.4.3, 11.1.6, 11.3.1

South-Eastern South America (SES) is one of the AR6 WGI reference regions (outlined with black thick contour in Figure TS.21a), and it is used here as an illustrative example of the interplay between drivers of climate variability and change at regional scale. Austral summer (DJF) precipitation positive trends have been observed over the region during 1950–2014. Drivers of this change include MoVs, such as AMV, ENSO, and PDV, as well as external forcing, like GHG increases and ozone depletion together with aerosols (as illustrated in Figure TS.21a). Modes of variability and external forcing collectively affect climate phenomena, such as the Hadley cell width and strength, Rossby waves activity emerging from the large-scale tropical SST anomalies, and the Southern Hemisphere polar vortex, which are relevant for the region. In fact, local changes over SES in terms of moisture convergence, ascending motion and storm-track locations depend on these climate phenomena, and they are overall responsible for the observed precipitation trends. Projections suggest continuing positive trends in rainfall over SES in the near-term in response to GHG emissions scenarios. Multi-model mean and ensemble spread are not sufficient to characterize situations where different models simulate substantially different or even opposite changes ( ''high confidence'' ) ''.'' In such cases, physical climate storylines addressing possible outcomes for climate phenomena shown to play a role in the variability of the region of interest can aid the interpretation of projection uncertainties. In addition, single-model initial-condition large ensembles of many realizations of internal variability are required to separate internal variability from forced changes ( ''high confidence'' ) and to partition the different sources of uncertainties as a function of future assessed periods. Links to chapters 10.3.4, 10.4.2, Figure 10.12a

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'''Figure TS.21 |''' '''Example of the interplay between drivers of climate variability and change at regional scale to understand past and projected changes.''' ''The figure intent is to show an illustrative pathway for understanding past, and anticipating future, climate change at regional scale in the presence of uncertainties.'' '''(a)''' Identification of the climate drivers and their influences on climate phenomena contributing through teleconnection to South-Eastern South America (SES) summer (December–January–February; DJF) precipitation variability and trends observed over 1950–2014. Drivers (red squares) include modes of variability as well as external forcing. Observed precipitation linear trend from GPCC is shown on continents (green-brown colour bar in mm month <sup>–1</sup> per decade) and the SES AR6 WGI reference region is outlined with the thick black contour. Climate phenomena leading to local effects on SES are schematically presented (blue ovals). '''(b)''' Time series of decadal precipitation anomalies for DJF SES simulated from seven large ensembles of historical plus RCP8.5 simulations over 1950–2100. Shading corresponds to the 5–95th range of climate outcomes given from each large ensemble for precipitation (in mm month <sup>–1</sup> ) and thick coloured lines stand for their respective ensemble mean. The thick time series in white corresponds to the multi-model multi-member ensemble mean, with model contribution being weighted according to their ensemble size. GPCC observation is shown in the light black line with squares over 1950–2014, and the 1995–2014 baseline period has been retained for calculation of anomalies in all datasets. '''(c)''' Quantification of the respective weight (in percent) between the individual sources of uncertainties (internal in grey, model in magenta and scenario in green) at near-term, mid-term and long-term temporal windows defined in AR6 and highlighted in (b) for SES DJF precipitation. All computations are done with respect to 1995–2014, taken as the reference period, and the scenario uncertainty is estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) using the same set of models as for the large ensembles that have run different Representative Concentration Pathway (RCP) scenarios. Links to chapters Figure 10.12a

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'''Box TS.13 | Monsoons'''

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'''Global land monsoon precipitation decreased from the 1950s to the 1980s, partly due to anthropogenic aerosols, but has increased since then in response to GHG forcing and large-scale multi-decadal variability ( ''medium confidence'' ). Northern Hemispheric anthropogenic aerosols weakened the regional monsoon circulations in South Asia, East Asia and West Africa during the second half of the 20th century, thereby offsetting the expected strengthening of monsoon precipitation in response to GHG-induced warming ( ''high confidence'' ).''' '''During the 21st century, global land monsoon precipitation is projected to increase in response to GHG warming in all time horizons and scenarios ( ''high confidence'' ). Over South and South East Asia, East Asia and the central Sahel, monsoon precipitation is projected to increase, whereas over North America and the far western Sahel it is projected to decrease ( ''medium confidence'' ). There is ''low confidence'' in projected precipitation changes in the South American and Australian-Maritime Continent monsoons. At global and regional scales, near-term monsoon changes will be dominated by the effects of internal variability ( ''medium confidence'' ). Links to chapters 2.3, Cross-Chapter Box 2.4, 3.3, 4.4, 4.5, 8.2, 8.3, 8.4, 8.5, Box 8.1, Box 8.2, 10.6''' '''Global Monsoon'''
Paleoclimate records indicate that during warm climates, like the mid-Pliocene Warm Period, monsoon systems were stronger ( ''medium confidence'' ). In the instrumental records, global summer monsoon precipitation intensity has ''likely'' increased since the 1980s, dominated by Northern Hemisphere summer trends and large multi-decadal variability. Contrary to the expected increase of precipitation under global warming, the Northern Hemisphere monsoon regions experienced declining precipitation from the 1950s to 1980s, which is partly attributable to the influence of anthropogenic aerosols ( ''medium confidence'' ) (Box TS.13, Figure 1). Links to chapters 2.3.1, Cross-Chapter Box 2.4, 3.3.2, 3.3.3

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'''Box TS.13, Figure 1 |'''

'''Global and regional monsoons: past trends and projected changes.''' ''The intent of this figure is to show changes in precipitation over regional monsoon domains in terms of observed past trends, how greenhouse gases and aerosols relate to these changes, and in terms of future projections in one intermediate emissions scenario in the near, medium and long term.'' (a) Global (black contour) and regional monsoons (colour shaded) domains. The global monsoon ( ''GM'' ) is defined as the area with local summer-minus-winter precipitation rate exceeding 2.5 mm day <sup>–1</sup> (see Annex V). The regional monsoon domains are defined based on published literature and expert judgement (see Annex V) and accounting for the fact that the climatological summer monsoon rainy season varies across the individual regions. Assessed regional monsoons are South and South East Asia ( ''SAsiaM, Jun–July–August–September'' ), East Asia ( ''EAsiaM, June–July–August'' ), West Africa ( ''WAfriM, June–July–August–September'' ) '','' North America ( ''NAmerM, July–August–-September'' ), South America ( ''SAmerM, December–January–February'' ), Australia and Maritime Continent Monsoon ( ''AusMCM, December–January–February'' ). Equatorial South America ( ''EqSAmer'' ) and South Africa ( ''SAfri'' ) regions are also shown, as they receive unimodal summer seasonal rainfall although their qualification as monsoons is subject to discussion. (b) Global and regional monsoons precipitation trends based on DAMIP CMIP6 simulations with both natural and anthropogenic (ALL), greenhouse gas only (GHG), aerosols only (AER) and natural only (NAT) radiative forcing. Weighted ensemble means are based on nine Coupled model Intercomparison Project Phase 6 (CMIP6) models contributing to the MIP (with at least three members). Observed trends computed from CRU, GPCP and APHRO (only for ''SAsiaM'' and ''EAsiaM'' ) datasets are shown as well. (c) Percentage change in projected seasonal mean precipitation over global and regional monsoons domain in the near term (2021–2040), mid-term (2041–2060), and long term (2081–2100) under SSP2-4.5 based on 24 CMIP6 models. Links to chapters Figures 8.11 and 8.22

With continued global warming, it is ''likely'' that global land monsoon precipitation will increase during this century (Box TS.13, Figure 1), particularly in the Northern Hemisphere, although the monsoon circulation is projected to weaken. A slowdown of the tropical circulation with global warming can partly offset the warming-induced strengthening of precipitation in monsoon regions ( ''high confidence'' ). In the near term, global monsoon changes are ''likely'' to be dominated by the effects of internal variability and model uncertainties ( ''medium confidence'' ). In the long term, global monsoon rainfall change will feature a robust north–south asymmetry characterized by a greater increase in the Northern Hemisphere than in the Southern Hemisphere and an east–west asymmetry characterized by enhanced Asian–African monsoons and a weakened North American monsoon ( ''medium confidence'' ). Links to chapters 4.4.1, 4.5.1, 8.4.1

'''Regional Monsoons'''

Paleoclimate reconstructions indicate stronger monsoons in the Northern Hemisphere but weaker ones in the Southern Hemisphere during warm periods, particularly for the South and South East Asian, East Asian, and North and South American monsoons, with the opposite occurring during cold periods ( ''medium confidence'' ). It is ''very likely'' that Northern Hemispheric anthropogenic aerosols weakened the regional monsoon circulations in South Asia, East Asia and West Africa during the second half of the 20th century, thereby offsetting the expected strengthening of monsoon precipitation in response to GHG-induced warming (Box TS.13, Figure 1). Multiple lines of evidence explain this contrast over South Asia, with the observed trends dominated by the effects of aerosols, while future projections are mostly driven by GHG increases. The recent partial recovery and enhanced intensity of monsoon precipitation over West Africa is related to the growing influence of GHGs with an additional contribution due to the reduced cooling effect of anthropogenic aerosols, emitted largely from North America and Europe ( ''medium confidence'' ). For other regional monsoons, that is, North and South America and Australia, there is ''low confidence'' in the attribution of recent changes in precipitation (Box TS.13, Figure 1) and winds. Links to chapters 2.3.1, 8.3.1, 8.3.2, Box 8.1, 10.6.3

Projections of regional monsoons during the 21st century indicate contrasting (region-dependent) and uncertain precipitation and circulation changes. The annual contrast between the wettest and driest month of the year is ''likely'' to increase by 3–5% per degree Celsius in most monsoon regions in terms of precipitation, precipitation minus evaporation, and runoff ( ''medium confidence'' ). For the North American monsoon, projections indicate a decrease in precipitation, whereas increased monsoon rainfall is projected over South and South East Asia and over East Asia ( ''medium confidence'' ) (Box TS.13, Figure 1). West African monsoon precipitation is projected to increase over the central Sahel and decrease over the far western Sahel ( ''medium confidence'' ). There is ''low confidence'' in projected precipitation changes in the South American and Australian-Maritime Continent regional monsoons (for both magnitude and sign) (Box TS.13, Figure 1). There is ''medium confidence'' that the monsoon season will be delayed in the Sahel and ''high confidence'' that it will be delayed in North and South America. Links to chapters 8.2.2, 8.4.2.4, Box 8.2

'''Building the Assessment from Multiple Lines of Evidence'''
Large natural variability of monsoon precipitation across different time scales, found in both paleoclimate reconstructions and instrumental measurements, poses an inherent challenge for robust quantification of future changes in precipitation at regional and smaller spatial scales. At both global and regional scales, there is ''medium confidence'' that internal variability contributes the largest uncertainty related to projected changes, at least in the near term (2021–2040). A collapse of the Atlantic Meridional Overturning Circulation could weaken the African and Asian monsoons but strengthen the Southern Hemisphere monsoons ( ''high confidence'' ). Links to chapters 4.4.4, 4.5.1, Cross-Chapter Box 4.1, 8.5.2, 8.6.1, 9.2.3, 10.6.3

Overall, long-term (2081–2100) future changes in regional monsoons like the South and South East Asian monsoon are generally consistent across global (including high-resolution) and regional climate models and are supported by theoretical arguments. Uncertainties in simulating the observed characteristics of regional monsoon precipitation are related to varying complexities of regional monsoon processes and their responses to external forcing, internal variability, and deficiencies in representing monsoon warm rain processes, organized tropical convection, heavy orographic rainfall and cloud–aerosol interactions. Links to chapters 8.3.2, 8.5.1, 10.3.3, 10.6.3

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<span id="ts.4.3-regional-climate-change-and-implications-for-climate-extremes-and-climatic-impact-drivers"></span>
=== TS.4.3 Regional Climate Change and Implications for Climate Extremes and Climatic Impact-Drivers ===

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'''Current climate in all regions is already distinct from the climate of the early or mid-20th century with respect to several climatic impact-drivers (CIDs), resulting in shifting magnitude, frequency, duration, seasonality and spatial extent of associated climate indices ( ''high confidence'' ). It is ''very likely'' that mean temperatures have increased in all land regions and will continue to increase at rates greater than the global average ( ''high confidence'' ). The frequency of heat and cold extremes have increased and decreased, respectively. These changes are attributed to human influence in almost all regions ( ''medium'' to ''high confidence'' ) and will continue through the 21st century ( ''high confidence'' ). In particular, extreme heat would exceed critical thresholds for health, agriculture and other sectors more frequently by the mid 21st century with 2°C of global warming ( ''high confidence'' ).''' '''Relative sea level rise is ''very likely'' to ''virtually certain'' (depending on the region) to continue during the 21st century, contributing to increased coastal flooding in low-lying areas ( ''high confidence'' ) and coastal erosion along most sandy coasts ( ''high confidence'' ). Sea level will continue to rise beyond 2100 ( ''high confidence'' ) (Box TS.4).''' '''Every region of the world will experience concurrent changes in multiple CIDs by mid-century or at 2°C global warming and above ( ''high confidence'' ). Even for the current climate, climate change-induced shifts in CID distributions and event probabilities, some of which have occurred over recent decades, are relevant for risk assessments. Links to chapters 11.9, 12.1, 12.2, 12.4, 12.5, Atlas.3–Atlas.11'''
An overview of changes in regional CIDs (introduced in Section TS.1) is given in Table TS.5, which summarizes multiple lines of evidence on regional climate change derived from observed trends, attribution of these trends and future projections. The level of confidence and the amplitude in the projected direction of change in CIDs at a given time horizon depends on climate change mitigation efforts over the 21st century. It is evident from Table TS.5 that many heat, cold, snow and ice, coastal, and oceanic CID changes are projected with ''high confidence'' in most regions starting from a global warming level (GWL) of 2°C, indicating worldwide challenges. Changes in many other regional CIDs have higher confidence later in the 21st century or at higher GWLs ( ''high confidence'' ), and another small subset are projected with ''high confidence'' for the 1.5°C GWL. This section focuses on the 2°C GWL and mid-century time period because the signal emerges from natural variability for a wider range of CIDs at this higher warming level. Figure TS.22 shows the geographical location of regions belonging to one of five groups characterized by a specific combination of changing CIDs. The Regional Synthesis component of the Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] provides comprehensive synthesis information about changes in all of the individual CIDs across all of the AR6 WGI reference regions. Links to chapters 10.5, Cross-Chapter Box 10.3, 11.1, 11.9, Box 11.1, 12.1, 12.2, 12.4, 12.5

'''Table TS.5 | Summary of confidence for climatic impact-driver changes in each AR6 WGI reference region (illustrated in Figure TS.25) across multiple lines of evidence for observed, attributed and projected directional changes.''' The colours represent their projected aggregate characteristic changes for the mid-21st century, considering scenarios RCP4.5, SSP2-4.5, SRES A1B, or above (RCP6.0, RCP8.5, SSP3-7.0, SSP5-8.5, SRES A2), which approximately encompasses global warming levels of 2.0°C to 2.4°C. Arrows indicate ''medium'' to ''high confidence'' trends derived from observations, and asterisks indicate ''medium'' and ''high confidence'' in attribution of observed changes. (North Africa is not an AR6 WGI reference region, but assessment here is based upon the African portion of the Mediterranean reference region). Links to chapters Tables 12.3–12.11 and Tables 11.4–11.21

[[File:ebbd163afa3876e9b2291dc4f9f9dbd4 IPCC_AR6_WGI_TS_Table_TS_5_0.png]] [[File:b097977db61ce5a90bb428bc23902b26 IPCC_AR6_WGI_TS_Table_TS_5_1.png]] [[File:9b01b05c141a8ac14c2d1c8a27e300c2 IPCC_AR6_WGI_TS_Table_TS_5_2.png]] [[File:a4a7c408145259a8ede309d3821bbdff IPCC_AR6_WGI_TS_Table_TS_5_3.png]] [[File:077ff432853fcbe27d0a4e9495b46360 IPCC_AR6_WGI_TS_Table_TS_5_4.png]] [[File:ff701af814e2e7c73cdd323f3d20c848 IPCC_AR6_WGI_TS_Table_TS_5_5.png]] [[File:eaf04ada5cc083e86c6e98ff831101bb IPCC_AR6_WGI_TS_Table_TS_5_6.png]] [[File:a4050b013ddfcc9d5c28d64989bdfbb8 IPCC_AR6_WGI_TS_Table_TS_5_7.png]] [[File:bd829180c043ae4686232cab79d55e85 IPCC_AR6_WGI_TS_Table_TS_5_8.png]]
'''Notes:'''

'''Africa (projections)'''

1. Contrasted regional signal: drying in western portions and wetting in eastern portions

2. ''Likely'' increase over the Ethiopian Highlands

3. ''Medium confidence'' of decrease in frequency and increase in intensity

4. Along sandy coasts and in the absence of sufficient sediment supply from terrestrial or offshore sources

5. Substantial parts of the East Southern Africa and Madagascar coast are projected to prograde if present-day ambient shoreline change rates continue

'''Asia (projections)'''

1. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat.

2. Substantial parts of the coasts in these regions are projected to prograde if present-day ambient shoreline change rates continue

3. Tropical cyclones decrease in number but increase in intensity

4. ''High confidence'' of decrease in Indonesia (Atlas.5.4.5)

5. ''Medium confidence'' of decreasing in summer and increasing in winter

'''Australasia (projections)'''

1. ''High confidence'' of decrease in the south-west of the state of Western Australia

2. ''Medium confidence'' of decrease in north and east and increase in south and west

3. ''High confidence'' of increase in the south-west of the state of Western Australia

4. ''Medium confidence'' of increase in the north and east and decrease in south and west

5. ''Low confidence'' of increasing intensity, and ''high confidence'' of decreasing occurrence

6. ''High confidence'' of decrease in glacier volume, ''medium confidence'' of decrease in snow

7. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat

'''Central and South America (projections)'''

1. Increase in extreme flow in the Amazon basin

2. Tropical cyclones decrease in number but increase in intensity

3. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat.

4. Substantial parts of the North-Western South America, Northern South America and North-Eastern South America coasts are projected to prograde if present-day ambient shoreline change rates continue

'''Europe (projections)'''

1. Excluding southern United Kingdom

2. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat

3. The Baltic Sea shoreline is projected prograde if present-day ambient shoreline change rates continue.

4. For the Alps, conditions conducive to landslides are expected to increase

5. ''Low confidence'' of decrease in the southernmost part of the region

6. General decrease except in Aegean Sea

7. ''Medium confidence'' of decrease in frequency and increase in intensities

8. Except in the Northern Baltic Sea region

'''North America (projections)'''

1. Snow may increase in some high elevations and during the cold season and decrease in other seasons and at lower elevations

2. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat.

3. Increasing in northern regions and decreasing toward the south

4. Decreasing in northern regions and increasing toward the south

5. Higher confidence in northern regions and lower toward the south

6. Higher confidence in southern regions and lower toward the north

7. Higher confidence in increase for some climatic impact-driver indices during summertime

8. Increase in convective conditions but decrease in winter extratropical cyclones

9. Relative sea level rise reduced given land uplift in Southern Alaska

'''Small Islands (projections)'''

1. ''Very high confidence'' in the direction of change, but ''low'' to ''medium confidence'' in the magnitude of change due to model uncertainty

2. Decrease in eastern Pacific and southern Pacific subtropics, but increase in parts of western and equatorial Pacific; with seasonal variation in future changes

3. ''High confidence'' in increase in extreme rain frequency and intensity in western tropical Pacific; ''low confidence'' in magnitude of change due to model bias

4. Increase in southern Pacific

5. Increase in intensity; decrease in frequency except over central North Pacific.

6. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat.

'''Polar Terrestrial Regions (projections)'''

1. Snow may increase in some high elevations and during the cold season and decrease in other seasons and at lower elevations

2. ''Higher confidence'' in southern regions and lower toward the north

3. ''Higher confidence'' in increase for some climatic impact-driver indices during summertime

4. Glaciers decline even as some regional snow climatic impact-driver indices increase

5. Decreasing in west and increasing in east

6. Except for Northern Baltic Sea coasts where relative sea levels fall

7. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat

[[File:4ac5d3c31010ac83cc64396bb80977ec IPCC_AR6_WGI_TS_Figure_22.png]]

'''Figure TS.22 |''' '''Synthesis of the geographical distribution of climatic impact-drivers changes and the number of AR6 WGI reference regions where they are projected to change.'''

'''Panel (a)''' shows the geographical location of regions belonging to one of five groups characterized by a specific combination of changing climatic impact-drivers (CIDs). The five groups are represented by the five different colours, and the CID combinations associated with each group are represented in the corresponding ‘fingerprint’ and text below the map. Each fingerprint comprises a set of CIDs projected to change with ''high confidence'' in every region in the group and a second set of CIDs, one or more of which are projected to change in each region with ''high'' or ''medium confidence'' . The CID combinations follow a progression from those becoming hotter and drier (group 1) to those becoming hotter and wetter (group 5). In between (groups 2–4), the CIDs that change include some becoming drier and some wetter and always include a set of CIDs which are getting hotter. Tropical cyclones and severe wind CID changes are represented on the map with black dots in the regions affected. Regions affected by coastal CID changes are described by text on the map. The five groups are chosen to provide a reasonable level of detail for each region while not overwhelming the map with a full summary of all aspects of the assessment, which is available in Table TS.5 and can be visualized in the Regional Synthesis component of the Interactive Atlas. The CID changes summarized in the figure represent ''high'' and ''medium confidence'' changes for the mid-21st century, considering scenarios SSP2-4.5, RCP4.5, SRES A1B, or above (SSP3-7.0, SSP5-8.5, RCP6.0, RCP8.5, SRES A2), which approximately encompasses global warming levels of 2.0°C to 2.4°C.

The bar chart in '''panel''' '''(b)''' shows the numbers of regions where each CID is increasing or decreasing with ''medium'' or ''high confidence'' for all land regions and ocean regions listed in Table TS.5. The colours represent the direction of change and the level of confidence in the change: purple indicates an increase while brown indicates a decrease; darker and lighter shades refer to ''high'' and ''medium confidence'' , respectively. Lighter background colours represent the maximum number of regions for which each CID is broadly relevant. Sub-panel (i) shows the 30 CIDs relevant to the land and coastal regions while sub-panel (ii) shows the 5 CIDs relevant to the open ocean regions. Marine heatwaves and ocean acidity are assessed for coastal ocean regions in panel (i) and for open ocean regions in panel (ii). Changes refer to a 20- to 30-year period centred around 2050 and/or consistent with 2°C global warming compared to a similar period within 1960–2014, except for hydrological drought and agricultural and ecological drought, which is compared to 1850–1900. Definitions of the regions are provided in Atlas.1, the Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] (https://interactive-atlas.ipcc.ch/) and Chapter 12. (Table TS.5, Figure TS.24) Links to chapters 11.9, 12.2, 12.4, Atlas.1

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==== TS.4.3.1 Common Regional Changes in Climatic Impact-Drivers ====

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'''Heat and cold:''' Changes in temperature-related CIDs such as mean temperatures, growing season length, and extreme heat and frost have already occurred ( ''high confidence'' ), and many of these changes have been attributed to human activities ( ''medium confidence'' ). Over all land regions with sufficient data (i.e., all except Antarctica), observed changes in temperature have already clearly emerged outside the range of internal variability, relative to 1850–1900 (Figure TS.23). In tropical regions, recent past temperature distributions have already shifted to a range different to that of the early 20th century ( ''high confidence'' ) (Section TS.1.2.4). Most land areas have ''very likely'' warmed by at least 0.1°C per decade since 1960, and faster in recent decades. On regional-to-continental scales, trends of increased frequency of hot extremes and decreased frequency of cold extremes are generally consistent with the global-scale trends in mean temperature ( ''high confidence'' ). In a few regions, trends are difficult to assess due to limited data availability. Links to chapters 2.3.1.1, 11.3, 11.9, 12.4, Atlas.3.1

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'''Figure TS.23 |''' '''Time period during which the signals of temperature change in observed data aggregated over the reference regions emerged from the noise of annual variability in the respective aggregated data, using a signal-to-noise ratio of two as the threshold for emergence.''' ''The intent of this figure is to show, for the AR6 WGI reference regions, when a signal of annual mean surface temperature change emerged from the noise of annual variability in two global datasets and thus also provide some information on observational uncertainty.'' Emergence time is calculated for two global observational datasets: (a) Berkeley Earth and (b) CRUTEM5. Regions in the CRUTEM5 map are shaded grey when data are available over less than 50% of the area of the region. (Section TS.1.2.4) Links to chapters Figure Atlas.11

Warming trends observed in recent decades are projected to continue over the 21st century and over most land regions at a rate higher than the global average ( ''high confidence'' ). For given global warming levels, model projections from CMIP6 show future regional warming changes that are similar to those projected by CMIP5. However, projected regional warming in CMIP6 for given time periods and emissions scenarios has a wider range with a higher upper limit compared to CMIP5 because of the higher climate sensitivity in some CMIP6 models and differences in the forcings. Links to chapters Atlas.3–Atlas.11

Under RCP8.5/SSP5-8.5, it is ''likely'' that most land areas will experience further warming of at least 4°C compared to a 1995–2014 baseline by the end of the 21st century, and in some areas significantly more. At increasing warming levels, extreme heat will exceed critical thresholds for health, agriculture and other sectors more frequently ( ''high confidence'' ), and it is ''likely'' that cold spells will become less frequent towards the end of the century. For example, by the end of the 21st century, dangerous humid heat thresholds, such as the National Oceanic and Atmospheric Administration (NOAA) heat index (HI) threshold of 41°C, will be exceeded much more frequently under the SSP5-8.5 scenario than under SSP1-2.6 and will affect many regions ( ''high confidence'' ). In many tropical regions, the number of days per year where a heat index of 41°C is exceeded would increase by more than 100 days relative to the recent past under SSP5-8.5, while this increase will be limited to less than 50 days under SSP1-2.6 ( ''high confidence'' ) (Figure TS.6). The number of days per year where temperature exceeds 35°C would increase by more than 150 days in many tropical areas, such as the Amazon basin and South East Asia, by the end of century for the SSP5-8.5 scenario, while it is expected to increase by less than 60 days in these areas under SSP1-2.6 (except for the Amazon Basin) ( ''high confidence'' ) (Figure TS.24). Links to chapters 4.6.1, 11.3, 11.9, 12.4, 12.5.2, Atlas

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'''Figure TS.24 |''' '''Projected change in the mean number of days per year with maximum temperature exceeding 35°C for Coupled Model Intercomparison Project Phase 5 (CMIP5; first column), Phase 6 (CMIP6; second column) and Coordinated Regional Climate Downscaling Experiment (CORDEX; third column) ensembles.''' ''The intent of this figure is to show that there is a consistent message about the patterns of projected change in extreme daily temperatures from the CMIP5, CMIP6 and CORDEX ensembles.'' The map shows the median change in the number of days per year between the mid-century (2041–2060) or end-century (2081–2100) and historical (1995–2014) periods for the CMIP5 and CORDEX RCP8.5 and RCP2.6 scenario ensembles and the CMIP6 SSP5-8.5 and SSP1-2.6 scenario ensembles. Hatching indicates areas where less than 80% of the models agree on the sign of change. Links to chapters Interactive Atlas

'''Wet and dry:''' Compared to the global scale, precipitation internal variability is stronger at the regional scale while uncertainties in observations, models and external forcing are all larger. However, GHG forcing has driven increased contrasts in precipitation amounts between wet and dry seasons and weather regimes over tropical land areas ( ''medium confidence'' ), with a detectable precipitation increase in the northern high latitudes ( ''high confidence'' ) (Box TS.6). The frequency and intensity of heavy precipitation events have increased over a majority of land regions with good observational coverage ( ''high confidence'' ). A majority of land areas have experienced decreases in available water in dry seasons due to human-induced climate change associated with changes in evapotranspiration ( ''medium confidence'' ). Global hydrological models project a larger fraction of land areas to be affected by an increase rather than by a decrease in river floods ( ''medium confidence'' ). Extreme precipitation and pluvial flooding will increase in many regions around the world on almost all continents ( ''high confidence'' ), but regional changes in river floods are more uncertain than changes in pluvial floods because complex hydrological processes, including land cover and human water management, are involved. Links to chapters 8.2.2.1, 8.3.1, Box 8.2, 10.4.1, 11.5, 11.6, 11.9, 12.4, 12.5.1, Atlas.3.1

'''Wind:''' Mean wind speed has decreased over most land areas with good observational coverage ( ''medium confidence'' ). It is ''likely'' that the global proportion of major tropical cyclone (TC) intensities (Categories 3–5) over the past four decades has increased. The proportion of intense TCs, average peak TC wind speeds, and peak wind speeds of the most intense TCs will increase on the global scale with increasing global warming ( ''high confidence'' ). Links to chapters 11.7.1

'''Snow and ice:''' Many aspects of the cryosphere either have seen significant changes in the recent past or will see them during the 21st century ( ''high confidence'' ). Glaciers will continue to shrink and permafrost to thaw in all regions where they are present ( ''high confidence'' ). Also, it is ''virtually certain'' that snow cover will experience a decline over most land regions during the 21st century, in terms of water equivalent, extent and annual duration. There is ''high confidence'' that the global warming-induced earlier onset of spring snowmelt and increased melting of glaciers have already contributed to seasonal changes in streamflow in high-latitude and low-elevation mountain catchments. Nevertheless, it is ''very likely'' that some high-latitude regions will experience an increase in winter snow water equivalent due to the effect of increased snowfall prevailing over warming-induced increased snowmelt. (Section TS.2.5) Links to chapters 8.2.2.1, 8.3.1, Box 8.2, 9.4, 9.5.1, 9.5.2, 12.4, Atlas.4–Atlas.9, Atlas.11

'''Coastal and oceanic:''' There is ''high confidence'' that SST will increase in all oceanic regions except the North Atlantic. Regional sea level change has been the main driver of changes in extreme sea levels across the quasi-global tide gauge network over the 20th century ( ''high confidence'' ). With the exception of a few regions with substantial land uplift, relative sea level rise is ''very likely to virtually certain'' (depending on the region) to continue during the 21st century, contributing to increased coastal flooding in low-lying areas ( ''high confidence'' ) and coastal erosion along most sandy coasts ( ''high confidence'' ) over the 21st century. In the open ocean, acidification, changes in sea ice, and deoxygenation have already emerged in many areas ( ''high confidence'' ). Marine heatwaves are also expected to increase around the globe over the 21st century ( ''high confidence'' ). (Section TS.2.4) Links to chapters Box 9.2, 9.2.1.1, 9.6, 9.6.4, 9.6.4.2, 12.4

'''Other variables and concurrent CID changes:''' It is ''virtually certain'' that atmospheric CO <sub>2</sub> and oceanic pH will increase in all climate scenarios, until net zero CO <sub>2</sub> emissions are achieved (Section TS.2.2). In nearly all regions, there is ''low confidence'' in changes in hail, ice storms, severe storms, dust storms, heavy snowfall, and avalanches, although this does not indicate that these CIDs will not be affected by climate change. For such CIDs, observations are often short-term or lack homogeneity, and models often do not have sufficient resolution or accurate parametrizations to adequately simulate them over climate change time scales. The probability of compound events has increased in the past due to human-induced climate change and will ''likely'' continue to increase with further global warming, including for concurrent heatwaves and droughts, compound flooding, and the possibility of connected sectors experiencing multiple regional extreme events at the same time (for example, in multiple breadbaskets) ( ''high confidence'' ). Links to chapters 5.3.4.2, 11.8, Box 11.3, Box 11.4, 12.4

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==== TS.4.3.2 Region-by-Region Changes in Climatic Impact-Drivers ====

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This section provides a continental synthesis of changes in CIDs, some examples of which are presented in Figure TS.25.

'''With 2°C global warming, and as early as the mid-21st century, a wide range of CIDs, particularly related to the water cycle and storms, are expected to show simultaneous region-specific changes relative to the recent past with ''high'' or ''medium confidence'' . In a number of regions (Southern Africa, the Mediterranean, North Central America, Western North America, the Amazon regions, South-Western South America, and Australia), increases in one or more of drought, aridity and fire weather ( ''high confidence'' ) will affect a wide range of sectors, including agriculture, forestry, health and ecosystems. In another group of regions (North-Western, Central and Eastern North America, Arctic regions, North-Western South America, Northern, Western and Central and Eastern Europe, Siberia, Central, South and East Asia, Southern Australia and New Zealand), decreases in snow and/or ice or increases in pluvial/river flooding ( ''high confidence'' ) will affect sectors such as winter tourism, energy production, river transportation and infrastructure. Links to chapters 11.9, 12.3, 12.4, 12.5, Table 12.2'''
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===== TS.4.3.2.1 Africa =====

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'''Additional regional changes in Africa, besides those described in Section TS.4.3.1, include a projected decrease in total precipitation in the northernmost and southernmost regions ( ''high confidence'' ), with Western Africa having a west-to-east pattern of decreasing-to-increasing precipitation ( ''medium confidence'' ). Increases in heavy precipitation that can lead to pluvial floods ( ''high confidence'' ) are projected for most African regions, even as increasing dry CIDs (aridity; hydrological, agricultural and ecological droughts; fire weather) are projected in the western part of Western Africa, Southern Africa and Northern Africa and the Mediterranean regions ( ''medium'' to ''high confidence'' ). Links to chapters 8.4, 11.3, 11.6, 11.9, 12.4, Atlas.4'''
In addition to the main changes summarized above and in Section TS.4.3.1, additional details per CID are given below.

'''Heat and cold:''' Observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Links to chapters 2.3.1.1.2, 11.3, 11.9, 12.4.1.1, Atlas.4.2, Atlas.4.4

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'''Figure TS.25 |''' '''Distribution of projected changes in selected climatic impact-driver (CID) indices for selected regions for Coupled Model Intercomparison Project Phases 5 and 6 (CMIP6, CMIP5) and Coordinated Regional Downscaling Experiment (CORDEX) model ensembles.''' ''The intent of this figure is to show that many CID projections for multiple global warming levels and scenarios time slices are available for all the AR6 WGI reference regions and are based on both global (CMIP5, CMIP6) and regional (CORDEX) model ensembles.'' Different indices are shown for different region: for Eastern Europe and North Asia, the mean number of days per year with maximum temperature exceeding 35°C; for Central America, the Caribbean, South West Asia, South Asia and South East Asia, the mean number of days per year with the National Oceanic and Atmospheric Administration (NOAA) Heat Index exceeding 41°C; for Australasia, East Asia and Russian Far East, the average shoreline position change; for South America, Europe and Africa, the mean change in 1-in-100-year river discharge per unit catchment area (m <sup>3</sup> s <sup>–1</sup> km <sup>–2</sup> ); and for North America, the median change in the number of days with snow water equivalent (SWE) over 100 mm. For each box plot, the changes or the climatological values are reported with respect to, or compared to, the recent past (1995–2014) period for 1.5°C, 2 <sup>°</sup> C and 4 <sup>°</sup> C global warming levels and for mid-century (2041–2060) or end-century (2081–2100) periods for the CMIP5 and CORDEX RCP8.5 and RCP2.6 and CMIP6 SSP5-8.5 and SSP1-2.6 scenarios ensembles. Links to chapters Figures 12.5, 12.6, 12.9, 12.SM.1, 12.SM.2, and 12.SM.6

'''Wet and dry:''' Mean precipitation changes have been observed over Africa, but the historical trends are not spatially coherent ( ''high confidence'' ). North Eastern Africa, East Southern Africa and Central Africa have experienced a decline in rainfall since about 1980 and parts of West Africa an increase ( ''high confidence'' ). Increases in the frequency and/or the intensity of heavy rainfall have been observed in East and West Southern Africa, and the eastern Mediterranean region ( ''medium confidence'' ). Increasing trends in river flood occurrence can be identified beyond 1980 in East and West Southern Africa ( ''medium confidence'' ) and Western Africa ( ''high confidence'' ). However, Northern Africa and West Southern Africa are ''likely'' to have a reduction in precipitation. Over West Africa, rainfall is projected to decrease in the western Sahel subregion and increase along the Guinea Coast subregion ( ''medium confidence'' ). Rainfall is projected to increase over Eastern Africa ( ''medium confidence'' ). Links to chapters 8.3.1.6, 11.4, 11.9, 12.4.1.2, Atlas.4.2, Atlas.4.4, Atlas.4.5

Precipitation declines and aridity trends in Western Africa, Central Africa, Southern Africa and the Mediterranean co-occur with trends towards increased agricultural and ecological droughts in the same regions ( ''medium confidence'' ). Trends towards increased hydrological droughts have been observed in the Mediterranean ( ''high confidence'' ) and Western Africa ( ''medium confidence'' ). These trends correspond with projected regional increases in aridity and fire weather conditions ( ''high confidence'' ). Links to chapters 8.3.1.6, 8.4.1.6, 11.6, 11.9, 12.4.1.2

'''Wind:''' Mean wind, extreme winds and the wind energy potential in North Africa and the Mediterranean are projected to decrease across all scenarios ( ''high confidence'' ). Over Western Africa and Southern Africa, a future significant increase in wind speed and wind energy potential is projected ( ''medium confidence'' ). There is a projected decrease in the frequency of tropical cyclones making landfall over Madagascar, East Southern Africa and East Africa ( ''medium confidence'' ). Links to chapters 12.4.1.3

'''Snow and ice:''' There is ''high confidence'' that African glaciers and snow have very significantly decreased in the last decades and that this trend will continue in the 21st century. Links to chapters 12.4.1.4

'''Coastal and oceanic:''' Relative sea level has increased at a higher rate than GMSL around Africa over the last 3 decades. The present day 1-in-100-year extreme total water level (ETWL) is between 0.1 m and 1.2 m around Africa, with values around 1 m or above along the East and West Southern and Central Eastern Africa coasts. Satellite-derived shoreline retreat rates up to 1 m yr <sup>–1</sup> have been observed around the continent from 1984 to 2015, except in South Eastern Africa, which has experienced a shoreline progradation (growth) rate of 0.1 m yr <sup>–1</sup> over the same period. Links to chapters 12.4.1.5

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===== TS.4.3.2.2 Asia =====

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Due to the high climatological and geographical heterogeneity of Asia, some assessment findings below are summarized over five sub-continental areas comprising one or more of the AR6 WGI reference regions (Box TS.12): East Asia (EAS+ECA), North Asia (WSB+ESB+RFE), South Asia (SAS), South East Asia (SEA) and South West Asia (ARP+WCA).

'''Additional regional changes in Asia, besides those features described in Section TS.4.3.1, include historical trends of annual precipitation that show considerable regional differences ( ''high confidence'' ). East Asian Monsoon precipitation has changed, with drying in the north and wetting in the south since the 1950s, and annual mean precipitation totals ''very likely'' have increased over most territories of North Asia since the mid-1970s ( ''high confidence'' ). South Asian summer monsoon precipitation decreased over several areas since the mid-20th century ( ''high confidence'' ) but is ''likely'' to increase during the 21st century, with enhanced interannual variability. (Box TS.13)''' '''Increases in precipitation and river floods are projected over much of Asia: in the annual mean precipitation in East, North, South and South East Asia ( ''high confidence'' ); for extremes in East, South, West Central, North and South East Asia ( ''high confidence'' ) and Arabian Peninsula ( ''medium confidence'' ); and for river floods in East, South and South East Asia and East Siberia ( ''medium confidence'' ). Aridity in East and West Central Asia is projected to increase, especially beyond the middle of the 21st century and global warming levels beyond 2°C ( ''medium confidence'' ). Fire weather seasons are projected to lengthen and intensify everywhere except South East Asia, Tibetan Plateau and Arabian Peninsula ( ''medium confidence'' ).''' '''Surface wind speeds have been decreasing in Asia ( high confidence ), but there is a large uncertainty in future trends, with medium confidence that mean wind speeds will decrease in North Asia, East Asia and Tibetan Plateau and that tropical cyclones will have decreasing frequency and increasing intensity overall in South East and East Asia.''' '''Over North Asia, increases in permafrost temperature and its thawing have been observed over recent decades ( ''high confidence'' ). Future projections indicate continuing decline in seasonal snow duration, glacial mass, and permafrost area by mid-century ( ''high confidence'' ). Snow-covered areas and snow volumes will decrease in most regions of the Hindu Kush Himalaya (HKH) during the 21st century, and snowline elevations will rise ( ''high confidence'' ) and glacier volumes are ''likely'' to decline with greater mass loss in higher CO <sub>2</sub> emissions scenarios. Heavy snowfall is increasing in East Asia and North Asia ( ''medium confidence'' ) but with limited evidence on future changes in hail and snow avalanches.''' '''Links to chapters 2.3, 8.3, 8.4, 9.5, 9.6, 10.6, Box 10.4, 11.4, 11.5, 11.7, 11.9, 12.4.2, Atlas.3.1, Atlas.5, Atlas.5.2, Atlas.5.3, Atlas.5.4, Atlas.5.5'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Over all regions of Asia, observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Over South East Asia, annual mean surface temperature will ''likely'' increase by a slightly smaller amount than the global average. Links to chapters Atlas.5.4.4

'''Wet and dry:''' Over East Asia, historical trends of annual precipitation show considerable regional differences but with increases over north-west China and South Korea ( ''high confidence'' ). Daily precipitation extremes have increased over part of the region ( ''high confidence'' ). Extreme hydrological drought frequency has increased in a region extending from south-west to north-east China, with projected increases of agricultural and ecological drought for 4°C GWL and fire weather for 2°C and above ( ''medium confidence'' ) ''.'' Links to chapters 8.3.2, 8.4.2, 11.4.4, 11.4.5, 11.9, 12.4.2.2, Atlas.5.1.2

Over North Asia, annual mean precipitation totals have ''very likely'' increased, causing more intense flooding events, and there is ''medium confidence'' that the number of dry days has decreased. Concurrently, total soil moisture is projected to decline extensively ( ''medium confidence'' ). Links to chapters 8.3.1.3, 8.4.1.6, 11.4.5, 11.5.2, 11.5.5, 12.4.2.2, Atlas.5.2.2

Over South Asia, the summer monsoon precipitation decreased over several areas since the mid-20th century ( ''high confidence'' ), while it increased in parts of the western HKH and decreased over eastern-central HKH ( ''medium confidence'' ). The frequency of heavy precipitation and flood events has increased over several areas during the last few decades ( ''medium confidence'' ). Links to chapters 8.3.1.3, 8.3.2.4.1, 8.4.1.5, 8.4.2.4.1, 10.6.3.3, 10.6.3.5, 10.6.3.6, 10.6.3.8, Cross-Chapter Box 10.4, 11.4.1, 11.4.2, 11.4.5, 11.5.5, 12.4.2.2, Box 10.4, [[IPCC:Wg1:Chapter:Atlas|Atlas]] 5.3.2

Over South East Asia, mean precipitation trends are not spatially coherent or consistent across datasets and seasons ( ''high confidence'' ). Most of the region has experienced an increase in rainfall intensity but with a reduced number of wet days ( ''medium confidence'' ). Rainfall is projected to increase in the northern parts of South East Asia and decrease in areas in the Maritime Continent ( ''medium confidence'' ). Links to chapters 8.4.1, 11.4.2, 11.5.5, 11.9, 12.4.2.2, Atlas.3.1, Atlas.5.4.2, Atlas.5.4.4

Over South West Asia, an observed annual precipitation decline over the Arabian Peninsula since the 1980s of 6.3 mm per decade is contrasted with observed increases between 1.3 mm and 4.8 mm per decade during 1960–2013 over the elevated part of eastern West Central Asia ( ''very high confidence'' ), along with an increase of the frequency and intensity of extreme precipitation. Links to chapters Figure 8.19, Figure 8.20, 8.3.1.6, 8.4.1.6, 11.9, Table 11.2A, 12.4.2.2, Atlas.5.5

'''Wind:''' Over East Asia, the terrestrial near-surface wind speed has decreased and is projected to decrease further in the future ( ''medium confidence'' ). Since the mid 1980’s, there has been an increase in the number and intensification rate of intense TCs ( ''medium confidence'' ), with a significant north-westward shift in tracks and a northward shift in their average latitude, increasing exposure over East China, the Korean Peninsula and the Japanese Archipelago ( ''medium confidence'' ). Links to chapters 11.7.1, 12.4.2.3

Over North Asia, there is ''medium confidence'' for a decreasing trend in wind speed during 1979–2018 and for projected continuing decreases of terrestrial near-surface wind speed. Links to chapters 2.3.1.4.4, 12.4.2.3

Over South East Asia, although there is no significant long-term trend in the number of TCs, fewer but more extreme TCs have affected the Philippines during 1951–2013. Links to chapters 11.7.4, 12.4.2.3

'''Snow and ice:''' Over East Asia, decreases have been observed in the frequency, and increases in the mean intensity, of snowfall in north-western, north-eastern and south-eastern China and the eastern Tibetan Plateau since the 1960s. Heavy snowfall is projected to occur more frequently in some parts of Japan ( ''medium confidence'' ). Links to chapters 12.4.2.4, Atlas.5.1.2

Over North Asia, seasonal snow duration and extent have decreased in recent decades ( ''high confidence'' ), and maximum snow depth ''likely'' has increased since the mid-1970s, particularly over the south of the Russian Far East. Links to chapters 2.3.2.5, 8.3.1.7.2, 9.5, 12.4.2.4, Atlas.5.2, Atlas.5.4

Over South Asia, snow cover has reduced over most of the HKH since the early 21st century, and glaciers have thinned, retreated, and lost mass since the 1970s ( ''high confidence'' ), although the Karakoram glaciers have either slightly gained mass or are in an approximately balanced state ( ''medium confidence'' ). Links to chapters 8.3.1.7.1, Cross-Chapter Box 10.4

Over South West Asia, mountain permafrost degradation at high altitudes has increased the instability of mountain slopes in the past decade ( ''medium confidence'' ). More than 60% of glacier mass in the Caucasus is projected to disappear under RCP8.5 emissions by the end of the 21st century ( ''medium confidence'' ). Links to chapters 9.5.1, 9.5.3, 12.4.2.4

'''Coastal and oceanic:''' Over the last three decades, relative sea level has increased at a rate higher than GMSL around Asia ( ''high confidence'' ). Gross coastal area loss and shoreline retreat has been observed over 1984–2015, but with localized shoreline progradation in the Russian Far East, East and South East Asia. Links to chapters 12.4.2.5

Projections show that regional mean sea level continues to rise ( ''high confidence'' ), ranging from 0.4–0.5 m under SSP1-2.6 to 0.8–1.0 m under SSP5-8.5 for 2081–2100 relative to 1995–2014 (median values). This will contribute to more frequent coastal flooding and higher ETWL in low-lying areas and coastal erosion along sandy beaches ( ''high confidence'' ). There is ''high confidence'' that compound effects of climate change, land subsidence, and human factors will lead to higher flood levels and prolonged inundation in the Mekong Delta and other Asian coasts. Links to chapters 9.6.1, 9.6.3, 12.4.2.5

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<span id="ts.4.3.2.3-australasia"></span>
===== TS.4.3.2.3 Australasia =====

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'''Additional regional changes in Australasia, besides those features described in Section TS.4.3.1, include a significant decrease in April to October rainfall in the south-west of the state of Western Australia, observed from 1910 to 2019 and attributable to human influence ( ''high confidence'' ), which is ''very likely'' to continue in future. Agricultural and ecological droughts and hydrological droughts have increased over Southern Australia ( ''medium confidence'' ), and meteorological droughts have decreased over Northern and Central Australia ( ''medium confidence'' ). Relative sea level has increased over the period 1993–2018 at a rate higher than GMSL around Australasia ( ''high confidence'' ). Sandy shorelines have retreated around the region, except in Southern Australia, where a shoreline progradation rate of 0.1 m yr <sup>–1</sup> has been observed.''' '''In the future, heavy precipitation and pluvial flooding are ''very likely'' to increase over Northern Australia and Central Australia, and they are ''likely'' to increase elsewhere in Australasia for global warming levels (GWLs) exceeding 2°C and with ''medium confidence'' for a 2°C GWL. Agricultural and ecological droughts are projected to increase in Southern and Eastern Australia ( ''medium confidence'' ) for a 2°C GWL. Fire weather is projected to increase throughout Australia ( ''high confidence'' ) and New Zealand ( ''medium confidence'' ). Snowfall is expected to decrease throughout the region at high altitudes in both Australia ( ''high confidence'' ) and New Zealand ( ''medium confidence'' ), with glaciers receding in New Zealand ( ''high confidence'' ). Links to chapters 11.4, Table 11.6, 12.3, 12.4.3, Atlas.6.4, Atlas.6.5'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Links to chapters 11.9, 12.4.3.1, Atlas.6

'''Wet and dry:''' There is ''medium confidence'' that heavy precipitation has increased in Northern Australia since 1950. Annual mean precipitation is projected to increase in the south and west of New Zealand ( ''medium confidence'' ) and is projected to decrease in south-west Southern Australia ( ''high confidence'' ), Eastern Australia ( ''medium confidence'' ), and in the north and east of New Zealand ( ''medium confidence'' ) for a GWL of 2°C. There is ''medium confidence'' that river flooding will increase in New Zealand and Australia, with higher increases in Northern Australia. Aridity is projected to increase with ''medium confidence'' in Southern Australia ( ''high confidence'' in south-west Southern Australia), Eastern Australia ( ''medium confidence'' ) and in the north and east of New Zealand ( ''medium confidence'' ) for GWLs around 2°C. Links to chapters 11.4, 11.9, Table 11.6, 12.4.3.2, Atlas.6.2

'''Wind:''' Mean wind speeds are projected to increase in parts of north-eastern Australia ( ''medium confidence'' ) by the end of the 21st century under high CO <sub>2</sub> emissions scenarios. TCs in north-eastern and north Australia are projected to decrease in number ( ''high confidence'' ) but increase in intensity except for ‘east coast lows’ ( ''low confidence'' ). Links to chapters 12.4.3.3

'''Snow and ice:''' Observations in Australia show that the snow season length has decreased by 5% in the last five decades. Furthermore, the date of peak snowfall in Australia has advanced by 11 days over the last 5 decades. Glacier ice volume in New Zealand has decreased by 33% from 1977 to 2018. Links to chapters 12.4.3.4, Atlas.6.2

'''Coastal and oceanic:''' Observed changes in marine heatwaves (MHWs) over the 20th century in the region show an increase in their occurrence frequency, except along the south-east coast of New Zealand, an increase in duration per event, and the total number of MHW days per decade, with the change being stronger in the Tasman Sea than elsewhere. The present day 1-in-100-year ETWL is between 0.5–2.5 m around most of Australia, except the north-western coast where 1-in-100-year ETWL can be as high as 6–7 m. Links to chapters Box 9.1, 12.3.1.5, 12.4.3.5

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<span id="ts.4.3.2.4-central-and-south-america"></span>
===== TS.4.3.2.4 Central and South America =====

<div id="h4-5-siblings" class="h4-siblings"></div>

'''Additional regional changes in Central and South America, besides those features described in Section TS.4.3.1, include increases in mean and extreme precipitation in South-Eastern South America since the 1960s ( ''high confidence'' ) (Section TS.4.2.3). Decreasing trends in mean precipitation and increasing trends in agricultural and ecological drought are observed over North-Eastern South America ( ''medium confidence'' ). The intensity and frequency of extreme precipitation and pluvial floods is projected to increase over South-Eastern South America, Southern South America, Northern South America, South American Monsoon and North-Eastern South America ( ''medium confidence'' ) for a 2°C GWL and above. Increases of agricultural and ecological drought are projected in South America Monsoon and Southern South America, and fire weather is projected to increase over several regions (Northern South America, the South American Monsoon, North-Eastern South America and South-Western South America) ( ''high confidence'' ). Links to chapters 8.3, 8.4, 11.3, 11.4, 11.9, Table 11.13, Table 11.14, Table 11.15, 12.4.4.2, Atlas.7.1, Atlas.7.2'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Links to chapters 11.3.2, 11.3.5, Table 11.13, 12.4.4.1, Atlas.7.1.2, Atlas.7.2.2, Atlas.7.2.4

'''Wet and dry:''' Mean precipitation is projected to change in a dipole pattern with increases in North-Western and South-Eastern South America and decreases in North-Eastern and South-Western South America ( ''high confidence'' ) and with further decreases in Northern South America and Southern Central America ( ''medium confidence'' ). In Northern South America and Southern Central America, aridity and agricultural and ecological droughts are increasing with ''medium confidence'' . Fire weather is projected to increase over Southern Central America and Southern South America with ''medium confidence'' . Links to chapters 8.3.1.3, 8.4.2.4.5, 11.4.2, 11.9, Table 11.14, Table 11.15, 12.4.4.2, Atlas.7.2.2, Atlas.7.2.4

'''Wind:''' Climate projections indicate an increase in mean wind speed and in wind power potential over the Amazonian region (Northern South America, South American Monsoon, North-Eastern South America) ( ''medium confidence'' ). Links to chapters 12.4.4.3

'''Snow and ice:''' Glacier volume loss and permafrost thawing will ''likely'' continue in the Andes Cordillera under all climate scenarios, causing important reductions in river flow and potentially high-magnitude glacial lake outburst floods. Links to chapters 9.5.1.1, 12.4.4.4

'''Coastal and oceanic:''' Around Central and South America, relative sea level has increased at a higher rate than GMSL in the South Atlantic and the subtropical North Atlantic, and at a rate lower than GMSL in the East Pacific over the last 3 decades. The present day 1-in-100-year ETWL is highest in Southern and South-Western South America subregions, where it can be as large as 5 to 6 m. Satellite observations for 1984–2015 show shoreline retreat rates along the sandy coasts of Southern Central America, South-Eastern South America and Southern South America, while shoreline progradation rates have been observed in North-Western South America and Northern South America. Over the period 1982–2016, the coastlines experienced at least one MHW per year, and more along the Pacific coast of North Central America and the Atlantic coast of South-Eastern South America. Links to chapters 12.4.4.5

<div id="TS.4.3.2.5" class="h4-container"></div>

<span id="ts.4.3.2.5-europe"></span>
===== TS.4.3.2.5 Europe =====

<div id="h4-6-siblings" class="h4-siblings"></div>

'''Additional regional changes in Europe, besides those features described in Section TS.4.3.1, include observed increases in pluvial flooding in Northern Europe and hydrological and agricultural/ecological droughts in the Mediterranean ( ''high confidence'' ), which have been attributed to human influence with ''high'' and ''medium confidence'' , respectively. Increased mean precipitation amounts at high latitudes in boreal winter and reduced summer precipitation in southern Europe are projected starting from a 2°C GWL ( ''high confidence'' ). Aridity, agricultural and hydrological droughts and fire weather conditions will increase in the Mediterranean region starting from 2°C GWL ( ''high confidence'' ). Pluvial flooding will increase everywhere with ''high confidence'' except for ''medium confidence'' in the Mediterranean; in Western and Central Europe this also applies to river flooding starting from a 2°C GWL ( ''high confidence'' ). Most periglacial processes in Northern Europe are projected to disappear by the end of the 21st century, even for a low warming scenario ( ''medium confidence'' ). Links to chapters 8.3, 11.3, 11.9, 12.4.5, 12.5.2, Atlas.8.2, Atlas.8.4'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Links to chapters 11.3, 11.9, 12.4.5.1, 12.5.2, Atlas.8.2, Atlas.8.4

'''Wet and dry:''' There is ''medium confidence'' that annual mean precipitation has increased in Northern Europe, West and Central Europe, and Eastern Europe since the early 20th century and ''high confidence'' for increases in extreme precipitation. In the European Mediterranean, the magnitude and sign of observed land precipitation trends depend on time period and exact study region ( ''medium confidence'' ). There is ''medium confidence'' that river floods will decrease in Northern, Eastern and southern Europe for high warming levels. Links to chapters 8.3.1.3, 11.3, 11.9, 12.4.5.2, Atlas.8.2, Atlas.8.4

'''Wind:''' Mean wind speed over land has decreased ( ''medium confidence'' ), but the role of human-induced climate change has not been established. There is ''high confidence'' that mean wind speeds will decrease in Mediterranean areas and ''medium confidence'' for such decreases in Northern Europe for GWLs exceeding 2°C. The frequency of Medicanes (tropical-like cyclones in the Mediterranean) is projected to decrease ( ''medium confidence'' ). Links to chapters 11.9, 12.4.5.3

'''Snow and ice:''' In the Alps, snow cover will decrease below elevations of 1500–2000 m throughout the 21st century ( ''high confidence'' ). A reduction of glacier ice volume is projected in the European Alps and Scandinavia with ''high confidence'' and with ''medium confidence'' for the timing and mass change rates. Links to chapters 9.5.2, 12.4.5.4

'''Coastal and oceanic:''' Over the last three decades, relative sea level has increased at a lower rate than GMSL in the sub-polar North Atlantic coasts of Europe. The present-day 1-in-100-year ETWL is between 0.5–1.5 m in the Mediterranean basin and 2.5–5.0 m in the western Atlantic European coasts, around the United Kingdom and along the North Sea coast, and lower at 1.5–2.5 m along the Baltic Sea coast. Satellite-derived shoreline change estimates over 1984–2015 indicate shoreline retreat rates of around 0.5 m yr <sup>–1</sup> along the sandy coasts of Central Europe and the Mediterranean and more or less stable shorelines in Northern Europe. Over the period 1982–2016, the coastlines of Europe experienced on average more than 2.0 MHW per year, with the eastern Mediterranean and Scandinavia experiencing 2.5–3 MHWs per year. Links to chapters 12.4.5.5

<div id="TS.4.3.2.6" class="h4-container"></div>

<span id="ts.4.3.2.6-north-america"></span>

===== TS.4.3.2.6 North America =====

<div id="h4-7-siblings" class="h4-siblings"></div>

'''Additional regional changes in North America, besides those features described in Section TS.4.3.1, include changes in North American wet and dry CIDs, which are largely organized by the north-east (more wet) to south-west (more dry) pattern of mean precipitation change, although heavy precipitation increases are widespread ( ''high confidence'' ). Increasing evaporative demand will expand agricultural and ecological drought and fire weather (particularly in summertime) in Central North America, Western North America and Northern Central America (from ''medium'' to ''high confidence'' ). Severe wind storms, tropical cyclones and dust storms in North America are shifting toward more extreme characteristics ( ''medium confidence'' ), and both observations and projections point to strong changes in the seasonal and geographic range of snow and ice conditions in the coming decades ( ''very high confidence'' ). General findings for relative sea level, coastal flooding and erosion will not apply for areas with substantial land uplift around the Hudson Bay and Southern Alaska. Links to chapters 8.4, 11.4, 11.5, 11.7, 11.9, 12.4, Atlas.9.4'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Observed and projected increases in mean temperature and a shift toward heat extreme characteristics are broadly similar to the generic pattern described in Section TS.4.3.1. Links to chapters 11.3, 11.9, 12.4.6.1, Atlas.9.2, Atlas.9.4

'''Wet and dry:''' Annual precipitation increased over parts of Eastern and Central North America during 1960–2015 ( ''high confidence'' ) and has decreased in parts of south-western United States and north-western Mexico ( ''medium confidence'' ). River floods are projected to increase for all North American regions other than Northern Central America (med ''ium confidence'' ). Links to chapters 8.4.2.4, 11.4, 11.5, 11.9, 12.4.6.2, Atlas.9.2, Atlas.9.4

Agricultural and ecological drought increases have been observed in Western North America ( ''medium confidence'' ), and aridity is projected to increase in the south-western United States and Northern Central America, with lower summer soil moisture across much of the continental interior ( ''medium confidence'' ). Links to chapters 8.4.1, 11.6.2, 12.4.6.2

'''Wind:''' Projections indicate a greater number of the most intense TCs, with slower translation speeds and higher rainfall potential for Mexico’s Pacific Coast, the Gulf Coast and the United States East Coast ( ''medium confidence'' ). Mean wind speed and wind power potential are projected to decrease in Western North America ( ''high confidence'' ), with differences between global and regional models lending ''low confidence'' elsewhere. Links to chapters 11.4, 11.7, 12.4.6.3

'''Snow and ice:''' It is ''likely'' that some high-latitude regions will experience an increase in winter snow water equivalent due to the snowfall increase prevailing over the warming trend. At sustained GWLs between 3°C and 5°C, nearly all glacial mass in Western Canada and Western North America will disappear ( ''medium confidence'' ). Links to chapters 9.5.1, 9.5.3, 12.4.6.4, Atlas.9.4

'''Coastal and oceanic:''' Around North America, relative sea level has increased over the last three decades at a rate lower than GMSL in the subpolar North Atlantic and in the East Pacific, while it has increased at a rate higher than GMSL in the subtropical North Atlantic. Observations indicate that episodic coastal flooding is increasing along many coastlines in North America. Shoreline retreat rates of around 1 m yr <sup>–1</sup> have been observed during 1984–2015 along the sandy coasts of North-Western North America and Northern Central America, while portions of the United States Gulf Coast have seen a retreat rate approaching 2.5 m yr <sup>–1</sup> . Sandy shorelines along Eastern North America and Western North America have remained more or less stable during 1984–2014, but a shoreline progradation rate of around 0.5 m yr <sup>–1</sup> has been observed in North-Eastern North America. Links to chapters 12.4.6.5

<div id="TS.4.3.2.7" class="h4-container"></div>

<span id="ts.4.3.2.7-small-islands"></span>
===== TS.4.3.2.7 Small Islands =====

<div id="h4-8-siblings" class="h4-siblings"></div>

'''Additional regional changes in Small Islands, besides those features described in Section TS.4.3.1, include a ''likely'' decrease in rainfall during boreal summer in the Caribbean and in some parts of the Pacific islands poleward of 20° latitude in both the Northern and Southern Hemispheres. These drying trends will ''likely'' continue in coming decades. Fewer but more intense tropical cyclones are projected starting from a 2°C GWL ( ''medium confidence'' ). Links to chapters 9.6, 11.3, 11.4, 11.7, 11.9, 12.4.7, Atlas.10.2, Atlas.10.4, Cross-Chapter Box Atlas.2'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' It is ''very likely'' that most Small Islands have warmed over the period of instrumental records, and continued temperature increases in the 21st century will further increase heat stress in these regions. Links to chapters 11.3.2, 11.9, 12.4.7.1, Atlas.10.2, Atlas.10.4, Cross-Chapter Box Atlas.2

'''Wet and dry:''' Observed and projected rainfall trends vary spatially across the Small Islands. Higher evapotranspiration under a warming climate can partially offset future increases or amplify future reductions in rainfall, resulting in increased aridity as well as more severe agricultural and ecological drought in the Caribbean ( ''medium confidence'' ). Links to chapters 11.4.2, 11.9, 12.4.7.2, Atlas.10.2, Atlas.10.4, Cross-Chapter Box Atlas.2

'''Wind:''' Global changes indicate that Small Islands will face fewer but more intense TCs, with spatial inconsistency in projections given poleward shifts in TC tracks ( ''medium confidence'' ). Links to chapters 11.7.1.2, 11.7.1.5, 12.4.7.3

'''Coastal and oceanic:''' Continued relative sea level rise is ''very likely'' in the ocean around Small Islands and, along with storm surges and waves, will exacerbate coastal inundation with the potential to increase saltwater intrusion into aquifers in small islands. Shoreline retreat is projected along sandy coasts of most small islands ( ''high confidence'' ). Links to chapters 9.6.3.3, 12.4.7.4, Cross-Chapter Box Atlas.2

<div id="TS.4.3.2.8" class="h4-container"></div>

<span id="ts.4.3.2.8-polar"></span>

===== TS.4.3.2.8 Polar =====

<div id="h4-9-siblings" class="h4-siblings"></div>

'''It is ''virtually certain'' that surface warming in the Arctic will continue to be more pronounced than the global average warming over the 21st century. An intensification of the polar water cycle will increase mean precipitation, with precipitation intensity becoming stronger and more ''likely'' to be rainfall rather than snowfall ( ''high confidence'' ). Permafrost warming, loss of seasonal snow cover, and glacier melt will be widespread ( ''high confidence'' ). There is ''high confidence'' that both the Greenland and Antarctic ice sheets have lost mass since 1992 and will continue to lose mass throughout this century under all emissions scenarios. Relative sea level and coastal flooding are projected to increase in areas other than regions with substantial land uplift ( ''medium confidence'' ). Links to chapters 2.3, 3.4, 4.3, 4.5, 7.4, 8.2, 8.4, Box 8.2, 9.5, 12.4.9, Atlas.11.1, Atlas.11.2'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Heat and cold:''' Changes in Antarctica showed larger spatial variability, with ''very likely'' warming in the Antarctic Peninsula since the 1950s and no overall trend in East Antarctica. Less warming and weaker polar amplification are projected as ''very likely'' over the Antarctic than in the Arctic, with a weak polar amplification projected as ''very likely'' by the end of the 21st century. Links to chapters 4.3.1, 4.5.1, 7.4.4, 12.4.9.1, Atlas.11.1, Atlas.11.2

'''Wet and dry:''' Recent decades have seen a general decrease in Arctic aridity ( ''high confidence'' ), with increased moisture transport leading to higher precipitation, humidity and streamflow and a corresponding decrease in dry days. Antarctic precipitation showed a positive trend during the 20th century. The water cycle is projected to intensify in both polar regions, leading to higher precipitation totals (and a shift to more heavy precipitation) and higher fraction of precipitation falling as rain. In the Arctic, this will result in higher river flood potential and earlier meltwater flooding, altering seasonal characteristics of flooding ( ''high confidence'' ). A lengthening of the fire season ( ''medium confidence'' ) and encroachment of fire regimes into tundra regions ( ''high confidence'' ) are projected. Links to chapters 8.2.3, 8.4.1, Box 8.2, 9.4.1, 9.4.2, 12.4.9.2, Atlas.11.1, Atlas.11.2

'''Wind:''' There is ''medium confidence'' in mean wind decrease over the Russian Arctic and Arctic North-East North America, but ''low confidence'' of changes in other Arctic regions and Antarctica. Links to chapters 12.4.9.3

'''Snow and ice:''' Reductions in spring snow cover extent have occurred across the Northern Hemisphere since at least 1978 ( ''very high confidence'' ). Permafrost warming and thawing have been widespread in the Arctic since the 1980s ( ''high confidence'' ), causing strong heterogeneity in surface conditions. There is ''high confidence'' in future glacier- and ice-sheet loss, permafrost warming, decreasing permafrost extent and decreasing seasonal duration and extent of snow cover in the Arctic. Decline in seasonal sea ice coverage along the majority of the Arctic coastline in recent decades is projected to continue, contributing to an increase in coastal hazards (including open water storm surge, coastal erosion and flooding). Links to chapters 2.3.2, 3.4.2, 3.4.3, 9.4.1, 9.4.2, 9.5, 12.4.6, 12.4.9, Atlas.11.2

'''Coastal and oceanic:''' Higher sea levels contribute to ''high confidence'' for projected increases of Arctic coastal flooding and higher coastal erosion (aided by sea ice loss) ( ''medium confidence'' ), with lower confidence for those regions with substantial land uplift (Arctic North-East North America and Greenland). Links to chapters 12.4.9.5

<div id="TS.4.3.2.9" class="h4-container"></div>

<span id="ts.4.3.2.9-ocean"></span>

===== TS.4.3.2.9 Ocean =====

<div id="h4-9-siblings" class="h4-siblings"></div>

'''The Indian Ocean, western equatorial Pacific Ocean and western boundary currents have warmed faster than the global average ( ''very high confidence'' ), with the largest changes in the frequency of marine heatwaves (MHWs) projected in the western tropical Pacific and the Arctic Ocean ( ''medium confidence'' ). The Pacific and Southern Ocean are projected to freshen and the Atlantic to become more saline ( ''medium confidence'' ). Anthropogenic warming is ''very likely'' to further decrease ocean oxygen concentrations, and this deoxygenation is expected to persist for thousands of years ( ''medium confidence'' ). Arctic sea ice losses are projected to continue, leading to a practically ice-free Arctic in September by the end of the 21st century under high CO <sub>2</sub> emissions scenarios ( ''high confidence'' ). Links to chapters 2.3, 5.3, 9.2, 9.3, Box 9.2, 12.3.6, 12.4.8'''
In addition to the main changes summarized above and in Section TS.4.3.1, further details are given below.

'''Ocean surface temperature:''' The Southern Ocean, the eastern equatorial Pacific, and the North Atlantic Ocean have warmed more slowly than the global average or slightly cooled. Global warming of 2°C above 1850–1900 levels would result in the exceedance of numerous hazard thresholds for pathogens, seagrasses, mangroves, kelp forests, rocky shores, coral reefs and other marine ecosystems ( ''medium confidence'' ). Links to chapters 9.2.13, 12.4.8

'''Marine heatwaves:''' Moderate increases in MHW frequency are projected for mid-latitudes, and only small increases are projected for the Southern Ocean ( ''medium confidence'' ). Under the SSP5-8.5 scenario, permanent MHWs (more than 360 days per year) are projected to occur in the 21st century in parts of the tropical ocean, the Arctic Ocean, and around 45°S; however, the occurrence of such permanent MHWs can be largely avoided under the SSP1-2.6 scenario. Links to chapters Box 9.2, 12.4.8

'''Ocean acidity:''' With the rising CO <sub>2</sub> concentration, the ocean surface pH has declined globally over the past four decades ( ''virtually certain'' ). Links to chapters 2.3.3.5, 5.3.3.2, 12.4.8

'''Ocean salinity:''' At the basin scale, it is ''very likely'' that the Pacific and the Southern Ocean have freshened while the Atlantic has become more saline. Links to chapters 2.3.3.2, 9.2.2.2, 12.4.8

'''Dissolved oxygen:''' In recent decades, low oxygen zones in ocean ecosystems have expanded. Links to chapters 2.3.4.2, 5.3.3.2, 12.4.8

'''Sea ice:''' Arctic perennial sea ice is being replaced by thin, seasonal ice, with earlier spring melt and delayed fall freeze up. There is no clear trend in the Antarctic sea ice area over the past few decades and ''low confidence'' in its future change. Links to chapters 2.3.2.1.1, 9.3.1.1, 12.4.8, 12.4.9

<div id="TS.4.3.2.10" class="h4-container"></div>

<span id="ts.4.3.2.10-other-typological-domains"></span>

===== TS.4.3.2.10 Other Typological Domains =====

<div id="h4-10-siblings" class="h4-siblings"></div>

'''Some types of regions found in different continents face common climate challenges regardless of their location. These include biodiversity hot spots that will ''very likely'' see even more extreme heat and droughts, mountain areas where a projected raising in the freezing level height will alter snow and ice conditions ( ''high confidence'' ), and tropical forests that are increasingly prone to fire weather ( ''medium confidence'' ). Links to chapters 8.4, Box 8.2, 9.5, 12.3, 12.4'''
Biodiversity hotspots located around the world will each face unique challenges in CID changes. Heat, drought and length of dry season, wildfire weather, sea surface temperature and deoxygenation are relevant drivers to terrestrial and freshwater ecosystems and have marked increasing trends. Links to chapters 12.3, 12.4.10.1

Desert and semi-arid areas are strongly affected by CIDs such as extreme heat, drought and dust storms, with large-scale aridity trends contributing to expanding drylands in some regions ( ''high confidence'' ). Links to chapters 12.3, 12.4.10.3

Average warming in mountain areas varies with elevation, but the pattern is not globally uniform ( ''medium confidence'' ). Extreme precipitation is projected to increase in major mountainous regions ( ''medium'' to ''high confidence'' depending on location), with potential cascading consequences of floods, landslides and lake outbursts in all scenarios ( ''medium confidence'' ). Links to chapters 8.4.1.5, Box 8.2, 9.5.1.3, 9.5.3.3, 9.5.2.3, Cross-Chapter Box 10.4, 11.5.5, 12.3, 12.4.1–12.4.6, 12.4.10.4

Most tropical forests are challenged by a mix of emerging warming trends that are particularly large in comparison to historical variability ( ''medium confidence'' ). Water cycle changes bring prolonged drought, longer dry seasons and increased fire weather to many tropical forests ( ''medium confidence'' ). Links to chapters 10.5, 12.3, 12.4

<div id="box-ts.14" class="h2-container box-container"></div>

'''Box TS.14 | Urban Areas'''

<div id="h2-35-siblings" class="h2-siblings"></div>

'''With global warming, urban areas and cities will be affected by more frequent occurrences of extreme climate events, such as heatwaves, with more hot days and warm nights as well as sea level rise and increases in tropical cyclone storm surge and rainfall intensity that will increase the probability of coastal city flooding ( ''high confidence'' ). Links to chapters Box 10.3, 11.3, 11.5, 12.3, 12.4'''
Urban areas have special interactions with the climate system, for instance in terms of heat islands and altering the water cycle, and thereby will be more affected by extreme climate events such as extreme heat ( ''high confidence'' ). With global warming, increasing relative sea level compounded by increasing tropical cyclone storm surge and rainfall intensity will increase the probability of coastal city flooding ( ''high confidence'' ). Arctic coastal settlements are particularly exposed to climate change due to sea ice retreat ( ''high confidence'' ). Improvements in urban climate modelling and climate monitoring networks have contributed to understanding the mutual interaction between regional and urban climate ( ''high confidence'' ). Links to chapters Box 10.3, 11.3, 11.5, 12.3, 12.4

Despite having a negligible effect on global surface temperature ( ''high confidence'' ), urbanization has exacerbated the effects of global warming through its contribution to the observed warming trend in and near cities, particularly in annual mean minimum temperature ( ''very high confidence'' ) and increases in mean and extreme precipitation over and downwind of the city, especially in the afternoon and early evening ( ''medium confidence'' ). Links to chapters 2.3, Box 10.3, 11.3, 11.4, 12.3, 12.4

Combining climate change projections with urban growth scenarios, future urbanization will amplify ( ''very high confidence'' ) the projected local air temperature increase, particularly by strong influence on minimum temperatures, which is approximately comparable in magnitude to global warming ( ''high confidence'' ). Compared to present day, large implications are expected from the combination of future urban development and more frequent occurrence of extreme climate events, such as heatwaves, with more hot days and warm nights adding to heat stress in cities ( ''very high confidence'' ). Links to chapters Box 10.2, 11.3, 12.4

Both sea levels and air temperatures are projected to rise in most coastal settlements ( ''high confidence'' ). There is ''high confidence'' in an increase in pluvial flood potential in urban areas where extreme precipitation is projected to increase, especially at high global warming levels. Links to chapters 11.4, 11.5, 12.4

-----

<div id="footnote-020" class="_idFootnote"></div>

[[#footnote-020-backlink|1]] In this Technical Summary, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., ''medium confidence'' . For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence (see Chapter 1, Box 1.1 for more details).

<div id="footnote-019" class="_idFootnote"></div>

[[#footnote-019-backlink|2]] In this Technical Summary, the following terms are used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely : 95–100%, more likely than not &gt;50–100%, and extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., ''very likely'' (see Chapter 1, Box 1.1 for more details). Throughout the WGI report and unless stated otherwise, uncertainty is quantified using 90% uncertainty intervals. The 90% uncertainty interval, reported in square brackets [x to y], is estimated to have a 90% likelihood of covering the value that is being estimated. The range encompasses the median value, and there is an estimated 10% combined likelihood of the value being below the lower end of the range (x) and above its upper end (y). Often, the distribution will be considered symmetric about the corresponding best estimate, but this is not always the case. In this Report, an assessed 90% uncertainty interval is referred to as a ‘ ''very likely'' range’. Similarly, an assessed 66% uncertainty interval is referred to as a ‘ ''likely'' range’.

<div id="footnote-018" class="_idFootnote"></div>

[[#footnote-018-backlink|3]] The regional traceback matrices that provide the location of the assessment findings synthesized in Section TS.4 are in the Supplementary Material (SM) of Chapter 10.

<div id="footnote-017" class="_idFootnote"></div>

[[#footnote-017-backlink|4]] Data archive is available at https://catalogue.ceda.ac.uk/uuid/3234e9111d4f4354af00c3aaecd879b7 .

<div id="footnote-016" class="_idFootnote"></div>

[[#footnote-016-backlink|5]] https://interactive-atlas.ipcc.ch/

<div id="footnote-015" class="_idFootnote"></div>

[[#footnote-015-backlink|6]] The AR6 figures use one of the following approaches. For observations, the absence of ‘x’ symbols shows areas with statistical significance, while the presence of ‘x’ indicates non-significance. For model projections, the method offers two approaches with varying complexity. In the simple approach, ''high agreement'' (≥80%) is indicated with no overlay, and diagonal lines (///) show ''low agreement'' (&lt;80%); In the advanced approach, areas with no overlay display robust signal (≥66% of models show change greater than the variability threshold and ≥80% of all models agree on the sign of change), reverse diagonal lines () show no robust signal, and crossed lines show conflicting signals (i.e., significant change but ''low agreement'' ). Cross-Chapter Box Atlas.1 provides more information on the AR6 method for visualizing robustness and uncertainty on maps.

<div id="footnote-014" class="_idFootnote"></div>

[[#footnote-014-backlink|7]] Although not a core concept of the WGI Report, deep uncertainty is used in the Technical Summary in the following sense: ‘A situation of deep uncertainty exists when experts or stakeholders do not know or cannot agree on: (1) appropriate conceptual models that describe relationships among key driving forces in a system; (2) the probability distributions used to represent uncertainty about key variables and parameters; and/or (3) how to weigh and value desirable alternative outcomes’ (Lempert et al., 2003). Lempert, R. J., Popper, S. W., and Bankes, S. C. (2003). ''Shaping the next one hundred years: New methods for quantitative long-term strategy analysis (MR-1626-RPC)'' . Santa Monica, CA: The RAND Pardee Center.

<div id="footnote-013" class="_idFootnote"></div>

[[#footnote-013-backlink|8]] The assessment covers scientific literature accepted for publication by 31 January 2021.

<div id="footnote-012" class="_idFootnote"></div>

[[#footnote-012-backlink|9]] Human influence on the climate system refers to human-driven activities that lead to changes in the climate system due to perturbations of Earth’s energy budget (also called anthropogenic forcing). Human influence results from emissions of greenhouse gases, aerosols and tropospheric ozone precursors, ozone-depleting substances, and land-use change.

<div id="footnote-011" class="_idFootnote"></div>

[[#footnote-011-backlink|10]] Throughout this Technical Summary, ‘main driver’ means responsible for more than 50% of the change.

<div id="footnote-010" class="_idFootnote"></div>

[[#footnote-010-backlink|11]] Throughout the WGI report and unless stated otherwise, uncertainty is quantified using 90% uncertainty intervals. The 90% uncertainty interval, reported in square brackets [x to y], is estimated to have a 90% likelihood of covering the value that is being estimated. The range encompasses the median value and there is an estimated 10% combined likelihood of the value being below the lower end of the range (x) and above its upper end (y). Often the distribution will be considered symmetric about the corresponding best estimate, but this is not always the case. In this Report, an assessed 90% uncertainty interval is referred to as a ‘ ''very likely'' range’. Similarly, an assessed 66% uncertainty interval is referred to as a ‘ ''likely'' range’.

<div id="footnote-009" class="_idFootnote"></div>

[[#footnote-009-backlink|12]] Increased stratification reduces the vertical exchange of heat, salinity, oxygen, carbon and nutrients. Stratification is an important indicator for ocean circulation.

<div id="footnote-008" class="_idFootnote"></div>

[[#footnote-008-backlink|13]] Several baselines or reference periods are used consistently throughout this Report. Baseline refers to a period against which anomalies (i.e., differences from the average value for the baseline period) are calculated. Examples include the 1750 baseline (used for anthropogenic radiative forcings), the 1850–1900 baseline (an approximation for pre-industrial global surface temperature from which global warming levels are calculated) and the 1995–2014 baseline (used for many climate model projections). A reference period indicates a time period over which various statistics are calculated (e.g., the near-term reference period, 2021–2040). Paleo reference periods are listed in Box TS.2. Links to chapters 1.4.1, Cross-Chapter Boxes 1.2 and 2.1

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[[#footnote-007-backlink|14]] Please refer to Section TS.1.3.1 for an overview of the climate change scenarios used in this Report.

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[[#footnote-006-backlink|15]] In this Report, equilibrium climate sensitivity is defined as the equilibrium (steady state) change in the surface temperature following a doubling of the atmospheric carbon dioxide (CO 2 ) concentration from pre-industrial conditions.

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[[#footnote-005-backlink|16]] In this Report, transient climate response is defined as the surface temperature response for the hypothetical scenario in which atmospheric carbon dioxide (CO 2 ) increases at 1% yr <sup>–1</sup> from pre-industrial to the time of a doubling of atmospheric CO 2 concentration.

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[[#footnote-004-backlink|17]] Throughout this Report, scenarios are referred to as SSPx-y, where “SSPx” refers to the Shared Socio-economic Pathway or “SSP” describing the socio-economic trends underlying the scenario, and “y” refers to the approximate target level of radiative forcing (in W m <sup>–-2</sup> ) resulting from the scenario in the year 2100.

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[[#footnote-003-backlink|18]] The transient surface temperature change per unit of cumulative CO 2 emissions, usually 1000 GtC.

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[[#footnote-002-backlink|19]] Throughout this Technical Summary, ‘main driver’ means responsible for more than 50% of the change.

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[[#footnote-001-backlink|20]] For reference, the Planck temperature response for a doubling of atmospheric CO 2 is approximately 1.2°C at equilibrium.

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[[#footnote-000-backlink|21]] Although cirrus cloud thinning aims to cool the planet by increasing longwave emissions to space, it is included in the portfolio of SRM options for consistency with AR5 and SR1.5. Links to chapters 4.6.3.3