Editing IPCC:Wg1:Chapter:Chapter-1-comments (section)

== 1.2 Where We Are Now ==

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The IPCC Sixth Assessment Cycle occurs in the context of increasingly apparent climatic changes observed across the physical climate system. Many of these changes can be attributed to anthropogenic influences, with impacts on natural and human systems. The AR6 also occurs in the context of efforts in international climate governance such as the Paris Agreement, which sets a long-term goal to hold the increase in global average temperature to ‘well below 2°C above pre-industrial levels, and to pursue efforts to limit the temperature increase to 1.5°C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change.’ This section summarizes key elements of the broader context surrounding the assessments made in the present report.

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=== 1.2.1 The Changing State of the Physical Climate System ===

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The WGI contribution to AR5 (AR5 WGI; [[#IPCC--2013a|IPCC, 2013a]] ) assessed that ‘warming of the climate system is unequivocal’, and that since the 1950s, many of the observed changes are unprecedented over decades to millennia. Changes are evident in all components of the climate system: the atmosphere and the ocean have warmed, amounts of snow and ice have diminished, sea level has risen, the ocean has acidified and its oxygen content has declined, and atmospheric concentrations of greenhouse gases (GHGs) have increased ( [[#IPCC--2013b|IPCC, 2013b]] ). This Report documents that, since the AR5, changes to the state of the physical and biogeochemical climate system have continued, and these are assessed in full in later chapters. Here, we summarize changes to a set of key large-scale climate indicators over the modern era (1850 to present). We also discuss the changes in relation to the longer-term evolution of the climate. These ongoing changes throughout the climate system form a key part of the context of the present Report.

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==== 1.2.1.1 Recent Changes in Multiple Climate Indicators ====

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The physical climate system comprises all processes that combine to form weather and climate. The early chapters of this report broadly organize their assessments according to overarching realms: the atmosphere, the biosphere, the cryosphere (surface areas covered by frozen water, such as glaciers and ice sheets), and the ocean. Elsewhere in the report, and in previous IPCC assessments, the land is also used as an integrating realm that includes parts of the biosphere and the cryosphere. These overarching realms have been studied and measured in increasing detail by scientists, institutions and the general public since the 18th century, throughout the era of instrumental observation ( [[#1.3|Section 1.3]] ). Today, observations include those taken by numerous land surface stations, ocean surface measurements from ships and buoys, underwater instrumentation, satellite and surface-based remote sensing, and in situ atmospheric measurements from aeroplanes and balloons. These instrumental observations are combined with paleoclimate reconstructions and historical documentations to produce a highly detailed picture of the past and present state of the whole climate system, and to allow assessments about rates of change across the different realms ( [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] and [[#1.5|Section 1.5]] ).

Figure 1.4 documents that the climate system is undergoing a comprehensive set of changes. It shows a selection of key indicators of change through the instrumental era that are assessed and presented in the subsequent chapters of this report. Annual mean values are shown as stripes, with colours indicating their value. The transitions from one colour to another over time illustrate how conditions are shifting in all components of the climate system. For these particular indicators, the observed changes go beyond the yearly and decadal variability of the climate system. In this Report, this is termed an ‘emergence’ of the climate signal ( [[#1.4.2|Section 1.4.2]] and FAQ 1.2).

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'''Figure 1.4 |''' '''Changes are occurring throughout the climate system.''' '''Left:''' Main realms of the climate system: atmosphere, biosphere, cryosphere and ocean. '''Right:''' Six key indicators of ongoing changes since 1850, or the start of the observational or assessed record, through 2018. Each stripe indicates the global (except for precipitation which shows two latitude band means), annual mean anomaly for a single ye ar, relative to a multi-year baseline (except for CO2 concentration and glacier mass loss, which are absolute values). Grey indicates that data are not available. Datasets and baselines used are: (i) CO2: Antarctic ice cores ( [[#Lüthi--2008|Lüthi et al., 2008]] ; [[#Bereiter--2015|Bereiter et al., 2015]] ) and direct air measurements ( [[#Tans--2020|Tans and Keeling, 2020]] ) (see Figure 1.5 for details); (ii) precipitation: Global Precipitation Climatology Centre (GPCC) V8 (updated from Becker et al., 2013), baseline 1961–1990 using land areas only with latitude bands 33°N–66°N and 15°S–30°S; (iii) glacier mass loss: [[#Zemp--2019|Zemp et al. (2019)]] ; (iv) global surface air temperature (GMST): HadCRUT5 ( [[#Morice--2021|Morice et al., 2021]] ), baseline 1961–1990; (v) sea level change: ( [[#Dangendorf--2019|Dangendorf et al., 2019]] ), baseline 1900–1929; (vi) ocean heat content (model–observation hybrid): [[#Zanna--2019|Zanna et al. (2019)]] , baseline 1961–1990. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).
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Warming of the climate system is most commonly presented through the observed increase in global mean surface temperature (GMST). Taking a baseline of 1850–1900, GMST change until present (2011–2020) is 1.09°C [0.95 to 1.20] °C ( [[IPCC:Wg1:Chapter:Chapter-2#2.3|Section 2.3]] and Cross-Chapter Box 2.3). This evolving change has been documented in previous assessment reports, with each reporting a higher total global temperature change ( [[#1.3|Section 1.3]] and Cross-Chapter Box 1.2). The total change in global surface air temperature (GSAT) ( [[#1.4.1|Section 1.4.1]] and Cross-Chapter Box 2.3) attributable to anthropogenic activities is assessed to be consistent with the observed change in GSAT ( [[IPCC:Wg1:Chapter:Chapter-3#3.3|Section 3.3]] ). <sup>[[#footnote-007|1]]</sup>

Similarly, atmospheric concentrations of a range of GHGs are increasing. Carbon dioxide (CO <sub>2</sub> , shown in Figure 1.4 and Figure 1.5a, found in AR5 and earlier reports to be the current strongest driver of anthropogenic climate change), has increased from 285.5 ± 2.1 ppm in 1850 to 409.9 ± 0.4 ppm in 2019; concentrations of methane (CH <sub>4</sub> ), and nitrous oxide (N <sub>2</sub> O) have increased as well (Sections 2.2 and 5.2, and Annex V). These observed changes are assessed to be in line with known anthropogenic and natural emissions, when accounting for observed and inferred uptake by land, ocean and biosphere respectively (Section 5.2), and are a key source of anthropogenic changes to the global energy balance (or radiative forcing; Sections 2.2 and 7.3).

The hydrological (or water) cycle is also changing and is assessed to be intensifying, through a higher exchange of water between the surface and the atmosphere (Sections 2.3 and 8.3). The resulting regional patterns of changes to precipitation are, however, different from surface temperature change, and interannual variability is larger, as illustrated in Figure 1.4. Annual land area mean precipitation in the Northern Hemisphere temperate regions has increased, while the subtropical dry regions have experienced a decrease in precipitation in recent decades ( [[IPCC:Wg1:Chapter:Chapter-2#2.3|Section 2.3]] ).

The cryosphere is undergoing rapid changes, with increased melting and loss of frozen water mass in most regions. This includes all frozen parts of the globe, such as terrestrial snow, permafrost, sea ice, glaciers, freshwater ice, solid precipitation, and the ice sheets covering Greenland and Antarctica (Chapter 9; SROCC, [[#IPCC--2019b|IPCC, 2019b]] ). Figure 1.4 illustrates how, globally, glaciers have been increasingly losing mass for the last fifty years. The total glacier mass in the most recent decade (2010–2019) was the lowest since the beginning of the 20th century (Sections 2.3 and 9.5).

The global ocean has warmed unabatedly since at least 1970 (Sections 1.3, 2.3 and 9.2; SROCC, [[#IPCC--2019b|IPCC, 2019b]] ). Figure 1.4 shows how the averaged ocean heat content is steadily increasing, with a total increase of [0.28 to 0.55] yottajoule (YJ; 10 <sup>24</sup> joule) between 1971 and 2018 (Section 9.2). In response to this ocean warming, as well as to the loss of mass from glaciers and ice sheets, the global mean sea level (GMSL) has risen by 0.20 [0.15 to 0.25] metres between 1900 and 2018. GMSL rise has accelerated since the late 1960s (see Section 9.6).

Overall, the changes in these selected climatic indicators have progressed beyond the range of natural year-to-year variability (Chapters 2, 3, 8 and 9, and Sections [[#1.2.1.2|1.2.1.2]] and [[#1.4.2|1.4.2]] ). The indicators presented in Figure 1.4 document a broad set of concurrent and emerging changes across the physical climate system. All indicators shown here, along with many others, are further presented in the coming chapters, together with a rigorous assessment of the supporting scientific literature. Later chapters (Chapters 10, 11, 12 and Atlas) present similar assessments at the regional level, where observed changes do not always align with the global mean picture shown here.

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==== 1.2.1.2 Long-Term Perspectives on Anthropogenic Climate Change ====

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Paleoclimate archives (e.g., ice cores, corals, marine and lake sediments, speleothems, tree rings, borehole temperatures, soils) permit the reconstruction of climatic conditions before the instrumental era. This establishes an essential long-term context for the climate change of the past 150 years and the projected changes in the 21st century and beyond (Chapter 3; [[#IPCC--2013a|IPCC, 2013a]] ; [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ). Figure 1.5 shows reconstructions of three key indicators of climate change over the past 800,000 years (800 kyr) <sup>[[#footnote-006|2]]</sup> – atmospheric CO <sub>2</sub> concentrations, global mean surface temperature (GMST) and global mean sea level (GMSL) – comprising at least eight complete glacial–interglacial cycles ( [[#EPICA%20Community%20Members--2004|EPICA Community Members, 2004]] ; [[#Jouzel--2007|Jouzel et al., 2007]] ), which are largely driven by oscillations in the Earth’s orbit and consequent feedbacks on multi-millennial time scales ( [[#Berger--1978|Berger, 1978]] ; [[#Laskar--1993|Laskar et al., 1993]] ). The dominant cycles – recurring approximately every 100 kyr – can be found imprinted in the natural variations of these three key indicators. Before industrialisation, atmospheric CO <sub>2</sub> concentrations varied between 174 ppm and 300 ppm, as measured directly in air trapped in ice at Dome Concordia, Antarctica ( [[#Bereiter--2015|Bereiter et al., 2015]] ; [[#Nehrbass-Ahles--2020|Nehrbass-Ahles et al., 2020]] ). Relative to 1850–1900 CE, the reconstructed GMST changed in the range of –6°C to +1°C across these glacial–interglacial cycles (see Chapter 2, [[IPCC:Wg1:Chapter:Chapter-2#2.3.1|Section 2.3.1]] for an assessment of different paleo-reference periods). GMSL varied between about –130 m during the coldest glacial maxima and +5 to +25 m during the warmest interglacial periods (Chapter 2; [[#Spratt--2016|Spratt and Lisiecki, 2016]] ). They represent the amplitudes of natural, global-scale climate variations over the last 800 kyr prior to the influence of human activity. Further climate information from a variety of paleoclimatic archives is assessed in Chapters 2, 5, 7 and 9.

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'''Figure 1.5 |''' '''Long-term context of anthropogenic climate change''' '''based on selected paleoclimatic reconstructions over the past 800,000 years (800 kyr) for three key indicators: atmospheric CO''' <sub>2</sub> '''concentrations, global mean surface temperature (GMST), and global mean sea level (GMSL).'''
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'''(a)''' '''Measurements of CO''' '''<sub>2</sub>''' '''in air enclosed in Antarctic ice cores''' (Lüthi et al. , 2008; Bereiter et al. , 2015 [a compilation]; uncertainty ±1.3 ppm; see Sections 2.2.3 and 5.1.2 for an assessment) '''and direct air measurements''' ( [[#Tans--2020|Tans and Keeling, 2020]] ; uncertainty ±0.12 ppm). Projected CO <sub>2</sub> concentrations for five Shared Socio-economic Pathways (SSP) scenarios are indicated by dots on the right-hand side of each panel (grey background; (Meinshausen et al. , 2020; SSPs are described in [[#1.6|Section 1.6]] ). '''(b)''' Reconstruction of GMST from marine paleoclimate proxies (light-grey line: [[#Snyder--2016|Snyder (2016)]] ; dark grey line: Hansen et al. (2013); see [[IPCC:Wg1:Chapter:Chapter-2#2.3.1|Section 2.3.1]] for an assessment). Observed and reconstructed temperature changes since 1850 are the AR6 assessed mean (referenced to 1850–1900; Box TS.3; 2.3.1.1); dots/whiskers on the right-hand panels (grey background) indicate the projected mean and ranges of warming derived from Coupled Model Intercomparison Project Phase 6 (CMIP6) SSP-based (2081–2100) and Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC7; 2300) simulations (Tables 4.5 and 4.9). '''(c)''' Sea level changes reconstructed from a stack of oxygen isotope measurements on seven ocean sediment cores ( [[#Spratt--2016|Spratt and Lisiecki, 2016]] ; see Chapter 2, [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.3|Section 2.3.3.3]] and Chapter 9, Section 9.6.2 for an assessment). The sea level record from 1850–1900 is from Kopp et al. (2016), while the 20th century record is an updated ensemble estimate of GMSL change (Palmer et al. , 2021; Sections 2.3.3.3 and 9.6.1.1). Dots/whiskers on the right-hand panels of the figure (grey background) indicate the projected median and ranges derived from SSP-based simulations (2081–2100: Table 9.9; 2300: Section 9.6.3.5). Best estimates (dots) and uncertainties (whiskers), as assessed in Chapter 2, are included in the left and middle panels for each of the three indicators and selected paleo-reference periods used in this report (CO <sub>2</sub> : Table 2.1; GMST: [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.1|Section 2.3.1.1]] and Cross-Chapter Box 2.3, Table 1; GMSL: Sections 2.3.3.3 and 9.6.2. See also Cross-Chapter Box 2.1). Selected paleo-reference periods: LIG – Last Interglacial; LGM – Last Glacial Maximum; MH – mid-Holocene (Cross-Chapter Box 2.1, Table 1). The non-labelled best estimate in panel (c) corresponds to the sea level high-stand during Marine Isotope Stage 11, about 410 ka (410,000 years ago; Section 9.6.2). Further details on data sources and processing are available in the chapter data Table (Table 1.SM.1).

Paleoclimatic information also provides a long-term perspective on rates of change of these three key indicators. In high-resolution reconstructions from polor ice cores, the rate of increase in atmospheric CO <sub>2</sub> observed over 1919–2019 CE is one order of magnitude higher than the fastest CO <sub>2</sub> fluctuations documented during the Last Glacial Maximum and the last deglacial transition ( [[#Marcott--2014|Marcott et al., 2014]] , see Chapter 2, [[IPCC:Wg1:Chapter:Chapter-2#2.2.3.2.1|Section 2.2.3.2.1]] ). Current multi-decadal GMST exhibit a higher rate of increase than over the past 2 kyr ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.1.2|Section 2.3.1.1.2]] ; [[#PAGES%202k%20Consortium--2019|PAGES 2k Consortium, 2019]] ), and in the 20th century GMSL rise was faster than during any other century over the past 3 kyr ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.3|Section 2.3.3.3]] ).

Paleoclimate reconstructions also shed light on the causes of these variations, revealing processes that need to be considered when projecting climate change. The paleorecords show that sustained changes in global mean temperature of a few degrees Celsius are associated with increases in sea level of several tens of metres (Figure 1.5). During two extended warm periods (interglacials) of the last 800 kyr, sea level is estimated to have been at least six metres higher than today (Chapter 2; [[#Dutton--2015|Dutton et al., 2015]] ). During the last interglacial, sustained warmer temperatures in Greenland preceded the peak of sea level rise (Figure 5.15 in [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ). The paleoclimate record therefore provides substantial evidence directly linking warmer GMST to substantially higher GMSL.

GMST will remain above present-day levels for many centuries even if net CO <sub>2</sub> emissions are reduced to zero, as shown in simulations with coupled climate models ( [[IPCC:Wg1:Chapter:Chapter-4#4.7.1|Section 4.7.1]] ; [[#Plattner--2008|Plattner et al., 2008]] ; Section 12.5.3 in [[#Collins--2013|Collins et al., 2013]] ; [[#Zickfeld--2013|Zickfeld et al., 2013]] ; [[#MacDougall--2020|MacDougall et al., 2020]] ). Such persistent warm conditions in the atmosphere represent a multi-century commitment to long-term sea level rise, summer sea ice reduction in the Arctic, substantial ice-sheet melting, potential ice-sheet collapse, and many other consequences in all components of the climate system (Section 9.4 and Figure 1.5; [[#Clark--2016|Clark et al., 2016]] ; [[#Pfister--2016|Pfister and Stocker, 2016]] ; H. [[#Fischer--2018|]] [[#Fischer--2018|Fischer et al., 2018]] ).

Paleoclimate records also show centennial- to millennial-scale variations, particularly during the ice ages, which indicate rapid or abrupt changes of the Atlantic Meridional Overturning Circulation (AMOC; Section 9.2.3.1) and the occurrence of a ‘bipolar seesaw’ (opposite-phase surface temperature changes in both hemispheres; [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.4.1|Section 2.3.3.4.1]] ; [[#Stocker--2003|Stocker and Johnsen, 2003]] ; [[#EPICA%20Community%20Members--2006|EPICA Community Members, 2006]] ; WAIS Divide Project Members et al., 2015; [[#Lynch-Stieglitz--2017|Lynch-Stieglitz, 2017]] ; [[#Pedro--2018|Pedro et al., 2018]] ; [[#Weijer--2019|Weijer et al., 2019]] ). This process suggests that instabilities and irreversible changes could be triggered if critical thresholds are passed ( [[#1.4.4.3|Section 1.4.4.3]] ). Several other processes involving instabilities are identified in climate models ( [[#Drijfhout--2015|Drijfhout et al., 2015]] ), some of which may now be close to critical thresholds ( [[#1.4.4.3|Section 1.4.4.3]] ; see also Chapters 5, 8 and 9 regarding tipping points; [[#Joughin--2014|Joughin et al., 2014]] ).

Based on Figure 1.5, the reconstructed, observed and projected ranges of changes in the three key indicators can be compared. By the first decade of the 20th century, atmospheric CO <sub>2</sub> concentrations had already moved outside the reconstructed range of natural variation over the past 800 kyr. On the other hand, GMST and GMSL were higher than today during several interglacials of that period (Sections [[IPCC:Wg1:Chapter:Chapter-2#2.3.1|2.3.1]] and [[IPCC:Wg1:Chapter:Chapter-2#2.3.3|2.3.3]] , and Figure 2.34). Projections for the end of the 21st century, however, show that GMST will have moved outside of its natural range within the next few decades, except for the strong mitigation scenarios ( [[#1.6|Section 1.6]] ). There is a risk that GMSL may potentially leave the reconstructed range of natural variations over the next few millennia (Section 9.6.3.5; [[#Clark--2016|Clark et al., 2016]] ; SROCC, [[#IPCC--2019b|IPCC, 2019b]] ). In addition, abrupt changes can not be excluded ( [[#1.4.4.3|Section 1.4.4.3]] ).

An important time period in the assessment of anthropogenic climate change is the last 2 kyr. Since AR5, new global datasets have been produced that aggregate aggregating local and regional paleorecords ( [[#PAGES%202k%20Consortium--2013|PAGES 2k Consortium, 2013]] , 2017, 2019; [[#McGregor--2015|McGregor et al., 2015]] ; [[#Tierney--2015|Tierney et al., 2015]] ; [[#Abram--2016|Abram et al., 2016]] ; [[#Hakim--2016|Hakim et al., 2016]] ; [[#Steiger--2018|Steiger et al., 2018]] ; [[#Brönnimann--2019b|Brönnimann et al., 2019b]] ). Before the global warming that began around the mid-19th century ( [[#Abram--2016|Abram et al., 2016]] ), a slow cooling in the Northern Hemisphere from roughly 1450–1850 CE is consistently recorded in paleoclimate archives ( [[#PAGES%202k%20Consortium--2013|PAGES 2k Consortium, 2013]] ; [[#McGregor--2015|McGregor et al., 2015]] ). While this cooling, primarily driven by an increased number of volcanic eruptions ( [[IPCC:Wg1:Chapter:Chapter-3#3.3.1|Section 3.3.1]] ; [[#PAGES%202k%20Consortium--2013|PAGES 2k Consortium, 2013]] ; [[#Owens--2017|Owens et al., 2017]] ; [[#Brönnimann--2019b|Brönnimann et al., 2019b]] ), shows regional differences, the subsequent warming over the past 150 years exhibits a global coherence that is unprecedented in the last 2 kyr ( [[#Neukom--2019|Neukom et al., 2019]] ).

The rate, scale and magnitude of anthropogenic changes in the climate system since the mid-20th century suggested the definition of a new geological epoch: the Anthropocene ( [[#Crutzen--2000|Crutzen and Stoermer, 2000]] ; [[#Steffen--2007|Steffen et al., 2007]] ), referring to an era in which human activity is altering major components of the Earth system and leaving measurable imprints that will remain in the permanent geological record (Figure 1.5; [[#IPCC--2018|IPCC, 2018]] ). These alterations include not only climate change itself, but also chemical and biological changes in the Earth system such as rapid ocean acidification due to uptake of anthropogenic CO <sub>2</sub> , massive destruction of tropical forests, a worldwide loss of biodiversity and the sixth mass extinction of species ( [[#Hoegh-Guldberg--2010|Hoegh-Guldberg and Bruno, 2010]] ; [[#Ceballos--2017|Ceballos et al., 2017]] ; [[#IPBES--2019|IPBES, 2019]] ). According to the key messages of the last global assessment of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services ( [[#IPBES--2019|IPBES, 2019]] ), climate change is a ‘direct driver that is increasingly exacerbating the impact of other drivers on nature and human well-being’, and ‘the adverse impacts of climate change on biodiversity are projected to increase with increasing warming.’

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=== 1.2.2 The Policy and Governance Context ===

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The contexts of both policymaking and societal understanding about climate change have evolved since AR5 was published (2013–2014). Increasing recognition of the urgency of the climate change threat, along with still-rising emissions and unresolved issues of mitigation and adaptation, including aspects of sustainable development, poverty eradication and equity, have led to new policy efforts. This section summarizes these contextual developments and how they have shaped, and been used during the preparation of this Report.

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==== 1.2.2.1 IPCC reports and the UN Framework Convention on Climate Change (UNFCCC) ====

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The IPCC First Assessment Report (FAR, [[#IPCC--1990a|IPCC, 1990a]] ) provided the scientific background for the establishment of the UNFCCC ( [[#UNFCCC--1992|UNFCCC, 1992]] ), which committed parties to negotiate ways to ‘prevent dangerous anthropogenic interference with the climate system’ (the ultimate objective of the UNFCCC). The Second Assessment Report (SAR, [[#IPCC--1996|IPCC, 1996]] ) informed governments in negotiating the Kyoto Protocol (1997), the first major agreement focusing on mitigation under the UNFCCC. The Third Assessment report (TAR, [[#IPCC--2001a|IPCC, 2001a]] ) highlighted the impacts of climate change and the need for adaptation, and introduced the treatment of new topics such as policy and governance in IPCC reports. The Fourth and Fifth Assessment Reports (AR4, [[#IPCC--2007a|IPCC, 2007a]] ; AR5, [[#IPCC--2013a|IPCC, 2013a]] ) provided the scientific background for the second major agreement under the UNFCCC: the Paris Agreement (2015), which entered into force in 2016.

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==== 1.2.2.2 The Paris Agreement (PA) ====

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Parties to the PA commit to the goal of limiting global average temperature increase to ‘well below 2°C above pre-industrial levels, and to pursue efforts to limit the temperature increase to 1.5°C in order to significantly reduce the risks and impacts of climate change’. InAR6, as in many previous IPCC reports, observations and projections of changes in global temperature are expressed relative to 1850–1900 as an approximation for pre-industrial levels (Cross-Chapter Box 1.2).

The PA further addresses mitigation (Article 4) and adaptation to climate change (Article 7), as well as loss and damage (Article 8), through the mechanisms of finance (Article 9), technology development and transfer (Article 10), capacity-building (Article 11) and education (Article 12). To reach its long-term temperature goal, the PA recommends ‘achieving a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century’, a state commonly described as ‘net zero’ emissions (Article 4) ( [[#1.6|Section 1.6]] and Box 1.4). Each Party to the PA is required to submit a Nationally Determined Contribution (NDC) and pursue, on a voluntary basis, domestic mitigation measures with the aim of achieving the objectives of its NDC (Article 4).

Numerous studies of the NDCs submitted since adoption of the PA in 2015 ( [[#Fawcett--2015|Fawcett et al., 2015]] ; [[#UNFCCC--2015|UNFCCC, 2015]] , 2016; [[#Lomborg--2016|Lomborg, 2016]] ; [[#Rogelj--2016|Rogelj et al., 2016]] , 2017; [[#Benveniste--2018|Benveniste et al., 2018]] ; [[#Gütschow--2018|Gütschow et al., 2018]] ; [[#UNEP--2019|UNEP, 2019]] ) conclude that they are insufficient to meet the Paris temperature goal. In the present IPCC Sixth Assessment Cycle, a Special Report on Global Warming of 1.5°C (SR1.5, [[#IPCC--2018|IPCC, 2018]] ) found, with ''high agreement'' , that current NDCs ‘are not in line with pathways that limit warming to 1.5°C by the end of the century.’ The PA includes a ratcheting mechanism designed to increase the ambition of voluntary national pledges over time. Under this mechanism, NDCs will be communicated or updated every five years. Each successive NDC will represent a ‘progression beyond’ the ‘then current’ NDC and reflect the ‘highest possible ambition’ (Article 4). These updates will be informed by a five-yearly periodic review including the Structured Expert Dialogue (SED), as well as a ‘global stocktake’, to assess collective progress toward achieving the PA long-term goals. These processes will rely upon the assessments prepared during the IPCC Sixth Assessment Cycle (e.g., Cross-Chapter Box 1.1; [[#Schleussner--2016b|Schleussner et al., 2016b]] ).

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==== 1.2.2.3 The Structured Expert Dialogue (SED) ====

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Since AR5, the formal dialogue between the scientific and policy communities has been strengthened through a new science– policy interface, the Structured Expert Dialogue (SED). The SED was established by UNFCCC to support the work of its two subsidiary bodies, the Subsidiary Body for Scientific and Technological Advice (SBSTA) and the Subsidiary Body for Implementation (SBI). The first SED aimed to ‘ensure the scientific integrity of the first periodic review’ of the UNFCCC, the 2013–2015 review. The Mandate of the periodic review is to ‘assess the adequacy of the long-term (temperature) goal in light of the ultimate objective of the convention’ and the ‘overall progress made towards achieving the long-term global goal, including a consideration of the implementation of the commitments under the Convention.’

The SED of the first periodic review (2013–2015) provided an important opportunity for face-to-face dialogue between decision makers and experts on review themes, based on ‘the best available scientific knowledge, including the assessment reports of the IPCC.’ That SED was instrumental in informing the long-term global goal of the PA and in providing the scientific argument for the consideration of limiting warming to 1.5°C warming ( [[#UNFCCC--2015|UNFCCC, 2015]] ; [[#Fischlin--2017|Fischlin, 2017]] ). The SED of the second periodic review, initiated in the second half of 2020, focuses on, among other things, ‘enhancing Parties’ understanding of the long-term global goal and the scenarios towards achieving it in the light of the ultimate objective of the Convention’. The second SED provides a formal venue for the scientific and the policy communities to discuss the requirements and benchmarks to achieve the ‘long-term temperature goal’ (LTTG) of 1.5°C and well below 2°C global warming. The discussions also concern the associated timing of net zero emissions targets and the different interpretations of the PA LTTG, including the possibility of overshooting the 1.5° C warming level before returning to it by means of negative emissions (e.g., [[#1.6|Section 1.6]] ; [[#Schleussner--2020|Schleussner and Fyson, 2020]] ). The second periodic review is planned to continue until November 2022 and its focus includes the review of the progress made since the first review, while minimising ‘possible overlaps’ and profiting from ‘synergies with the global stocktake’.

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==== 1.2.2.4 Sustainable Development Goals (SDGs) ====

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Many interactions among environmental problems and development are addressed in the United Nations 2030 Agenda for Sustainable Development and its Sustainable Development Goals. The 2030 Agenda, supported by the finance-oriented Addis Ababa Action Agenda ( [[#UN%20DESA--2015|UN DESA, 2015]] ), calls on nations to ‘take the bold and transformative steps which are urgently needed to shift the world onto a sustainable and resilient path.’ The 2030 Agenda recognizes that ‘climate change is one of the greatest challenges of our time and its adverse impacts undermine the ability of all countries to achieve sustainable development.’ SDG 13 deals explicitly with climate change, establishing several targets for adaptation, awareness-raising and finance. Climate and climate change are also highly relevant to most other SDGs, and UNFCCC is acknowledged as the main forum to negotiate the global response to climate change. For example, both long-lived GHGs (through mitigation decisions), and SLCFs (through air quality), are relevant to SDG 11 (sustainable cities and communities). [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] assesses the effects of SLCFs on climate and the implications of changing climate for air quality, including opportunities for mitigation relevant to the SDGs (Box 6.2). Also, the UN Conference on Housing and Sustainable Development established a New Urban Agenda ( [[#United%20Nations--2017|United Nations, 2017]] ) envisaging cities as part of the solutions for sustainable development, climate change adaptation and mitigation.

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==== 1.2.2.5 The Sendai Framework for Disaster Risk Reduction (SFDRR) ====

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The Sendai Framework for Disaster Risk Reduction is a non-binding agreement to reduce risks associated with disasters of all scales, frequencies and onset rates caused by natural or human-made hazards, including climate change. The SFDRR outlines targets and priorities for action including ‘understanding disaster risk’, along the dimensions of vulnerability, exposure of persons and assets, and hazard characteristics. [https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-12 Chapter 12] assesses climate information relevant to regional impact and risk assessment, with a focus on climate hazards and other aspects of climate that influence society and ecosystems and makes the link with Working Group II. AR6 adopts a consistent risk- and solution-oriented framing (Cross-Chapter Box 1.3) that calls for a multidisciplinary approach and cross-Working Group coordination in order to ensure integrative discussions of major scientific issues associated with integrative risk management and sustainable solutions ( [[#IPCC--2017|IPCC, 2017]] ).

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==== 1.2.2.6 The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) ====

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Efforts to address climate change take place alongside and in the context of other major environmental problems, such as biodiversity loss. IPBES, established in 2012, builds on the IPCC model of a science–policy interface and assessment. The Platform’s objective is to ‘strengthen the science–policy interface for biodiversity and ecosystem services for the conservation and sustainable use of biodiversity, long-term human well-being and sustainable development’ ( [[#UNEP--2012|UNEP, 2012]] ). The SROCC ( [[#IPCC--2019b|IPCC, 2019b]] ) and SRCCL ( [[#IPCC--2019a|IPCC, 2019a]] ) assessed the relations between changes in biodiversity and in the climate system. The rolling work programme of IPBES up to 2030 will address interlinkages among biodiversity, water, food and health. This assessment will use a nexus approach to examine interlinkages between biodiversity and the above-mentioned issues, including climate change mitigation and adaptation. Furthermore, IPBES and IPCC will directly collaborate on biodiversity and climate change under the rolling work programme.

Addressing climate change alongside other environmental problems, while simultaneously supporting sustainable socio-economic development, requires a holistic approach. Since AR5, there is increasing attention on the need for coordination among previously independent international agendas, and a recognition that climate change, disaster risk, economic development, biodiversity conservation and human well-being are tightly interconnected. The current COVID-19 pandemic provides an example of the need for such interconnection, with its widespread impacts on economy, society and environment (e.g., [[#Shan--2021|Shan et al., 2021]] ). Cross-Chapter Box 6.1 assesses the consequences of the COVID-19 lockdowns for emissions of GHGs and SLCFs, and related implications for the climate. Another example of the interconnected nature of these issues is the close link between SLCF emissions, climate change and air quality concerns (Chapter 6). Emissions of halocarbons have previously been successfully regulated under the Montreal Protocol and its Kigali Amendment. This has been achieved in an effort to reduce ozone depletion that has also modulated other anthropogenic climate influence ( [[#Estrada--2013|Estrada et al., 2013]] ; [[#Wu--2013|Wu et al., 2013]] ). In the process, emissions of some SLCFs were jointly regulated to reduce environmental and health impacts from air pollution (e.g., Gothenburg Protocol; [[#Reis--2012|Reis et al., 2012]] ). Considering the recognized importance of SLCFs in climate change processes, the IPCC decided in May 2019 to approve that the IPCC Task Force on National Greenhouse Gas Inventories produces an IPCC Methodology Report on SLCFs to develop guidance for national SLCF inventories.

The evolving governance context since AR5 challenges the IPCC to provide policymakers and other actors with information relevant for both adaptation to and mitigation of climate change, and for the loss and damage induced.

<div id="cross-chapter-box-1.1" class="h2-container box-container"></div>

'''Cross-Chapter Box 1.1 | The WGI Contribution to AR6 and Its Potential Relevance for the Global Stocktake'''

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'''Contributing Authors:''' Malte Meinshausen (Australia/Germany), Gian-Kasper Plattner (Switzerland), Aïda Diongue-Niang (Senegal), Francisco J. Doblas-Reyes (Spain), David Frame (New Zealand), Nathan P. Gillett (Canada), Helene T. Hewitt (United Kingdom), Richard G. Jones (United Kingdom), Hong Liao (China), Jochem Marotzke (Germany), James Renwick (New Zealand), Joeri Rogelj (United Kingdom, Belgium), Maisa Rojas (Chile), Sonia I. Seneviratne (Switzerland), Claudia Tebaldi (United States of America), Blair Trewin (Australia)

'''The global stocktake under the Paris Agreement (PA) evaluates the collective progress of countries’ actions towards attaining the Agreement’s purpose and long-term goals every five years.''' The first global stocktake is due in 2023, and then every five years thereafter, unless otherwise decided by the Conference of the Parties. The purpose and long-term goals of the PA are captured inter alia in Article 2: to ‘strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty, including by’: ''mitigation'' ''[[#footnote-005|3]]'' specifically, ‘holding the increase in the global average temperature to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change’; ''adaptation'' , that is, ‘increasing the ability to adapt to the adverse impacts of climate change and foster climate resilience and low greenhouse gas (GHG) emissions development, in a manner that does not threaten food production’; and ''means of implementation and support'' , that is, ‘making finance flows consistent with a pathway towards low GHG emissions and climate-resilient development.’

The PA further specifies that the stocktake shall be undertaken in a ‘comprehensive and facilitative manner, considering mitigation, adaptation and the means of implementation and support, and in the light of equity and the best available science’ (Article 14). '''The sources of input''' envisaged for the global stocktake include the ‘latest reports of the Intergovernmental Panel on Climate Change’ as a central source of information. <sup>[[#footnote-004|4]]</sup> The global stocktake is one of the key formal avenues for scientific inputs into the UNFCCC and PA negotiation process alongside, for example, the Structured Expert Dialogues (SEDs) under the UNFCCC ( [[#1.2.2|Section 1.2.2]] ). <sup>[[#footnote-003|5]]</sup>

'''The WGI Assessment provides a wide range of information with potential relevance for the global stocktake, complementing the IPCC AR6 Special Reports, the contributions from WGII and WGIII and the Synthesis Report.''' This includes the state of GHG emissions and concentrations, the current state of the climate, projected long-term warming levels under different scenarios, near-term projections, the attribution of extreme events, and remaining carbon budgets. Cross-Chapter Box 1.1, Table 1 provides pointers to the in-depth material that WGI has assessed and that may be relevant for the global stocktake.

'''The following tabular overview of potentially relevant information from the WGI contribution for the global stocktake is structured into three sections: the current state of the climate, the long-term future, and the near-term.''' These sections and their order align with the three questions of the Talanoa dialogue, launched during COP23, based on the Pacific concept of ''talanoa'' ''[[#footnote-002|6]]'' : ‘ ''Where are we’, ‘Where do we want to go’'' and ‘ ''How do'' ''we get there?’''

<!-- START TABLE -->
'''Cross-Chapter Box 1.1, Table 1 |'''

'''WGI assessment findings and their potential relevance for the global stocktake.''' The table combines information assessed in this report that could potentially be relevant for the global stocktake process. Section 1 focuses on the current state of the climate and its recent past. Section 2 focuses on long-term projections in the context of the PA’s 1.5°C and 2.0°C goals and on progress towards net zero greenhouse gas emissions. Section 3 considers challenges and key insights for mitigation and adaptation in the near term from a WGI perspective. Further information on potential relevance of the aspects listed here in terms of, for example, impacts and socio-economic aspects can be found in the WGII and WGIII reports
<!-- TABLE -->
{| class="wikitable"
|-
! colspan="3"| '''Section 1: State of the Climate –''' ‘ ''Where are we?’''

''WGI Assessment to inform about past changes in the climate system, current climate and co'' ''mmitted changes''

|-
! '''Question'''

! '''Chapter/Section'''

! '''Potential Relevance and Expl''' '''anatory Remarks'''

|-
| How much warming have we observed in global mean surface air temperatures?

| Cross-Chapter Box 1.2; Cross-Chapter Box 2.3;

2.3.1.1, especially 2.3.1.1.3

| Knowledge about the current warming relative to pre-industrial levels allows us to quantify the remaining distance to the PA goal of keeping global mean temperatures well below 2°C above pre-industrial levels or pursue best efforts to limit warming to 1.5°C above pre-industrial levels. Many of the Report’s findings are provided against a proxy for pre-industrial temperature levels, with Cross-Chapter Box 1.2 examining the difference between pre-industrial levels and the 1850–1900 period.

|-
| How much has the ocean warmed?

| 2.3.3.1; 7.2; Box 7.2; 9.2.1.1; Box 9.1

| A warming ocean can affect marine life (e.g., coral bleaching) and is also one of the main contributors to long-term sea level rise (thermal expansion). Marine heatwaves can accentuate the impacts of ocean warming on marine ecosystems. Also, knowing the heat uptake of the ocean helps to better understand the response of the climate system and hence helps to project future warming.

|-
| How much have land areas warmed and how has precipitation changed?

| 2.3.4; 5.4.3; 5.4.8; 8.2.1; 8.2.3; 8.5.1

| A stronger than global-average warming over land, combined with changing precipitation patterns, and/or increased aridity in some regions (like the Mediterranean) can severely affect land ecosystems and species distributions, the terrestrial carbon cycle, and food production systems. Amplified warming in the Arctic can enhance permafrost thawing, which in turn can result in overall stronger anthropogenic warming (a positive feedback loop). Intensification of heavy precipitation events can cause more severe impacts related to flooding.

|-
| How did the sea ice area change in recent decades in both the Arctic and Antarctic?

| 2.3.2.1.1; 2.3.2.1.2;

9.3; Cross-Chapter Box 10.1; 12.4.9

| Sea ice area influences mass and energy (ice albedo, heat and momentum) exchange between the atmosphere and the ocean, and its changes in turn impact polar life, adjacent land and ice masses and complex dynamical flows in the atmosphere. The loss of a year-round sea ice cover in the Arctic can severely impact Arctic ecosystems, affect the livelihood of First Nations in the Arctic, and amplify Arctic warming with potential consequences for the warming of the surrounding permafrost regions and ice sheets.

|-
| How much have atmospheric CO <sub>2</sub> and other GHG concentrations increased?

| 2.2.3; 2.2.4; 5.1.1; 5.2.2; 5.2.3; 5.2.4

| The main human influence on the climate is via combustion of fossil fuels and CO <sub>2</sub> emissions related to land-use change: the principal causes of increased CO <sub>2</sub> concentrations since the pre-industrial period. Historical observations indicate that current atmospheric concentrations are unprecedented within at least the last 800 kyr. An understanding of historical fossil fuel emissions and carbon cycle interactions, as well as methane (CH <sub>4</sub> ) and nitrous oxide (N <sub>2</sub> O) sinks and sources, are crucial for better estimates of future GHG emissions compatible with the PA’s long-term goals.

|-
| How much did sea level rise in past centuries and how large is the long-term commitment?

| 2.3.3.3;

9.6.1; 9.6.2; FAQ 9.1; Box 9.1; 9.6.3; 9.6.4

| Sea level rise is a comparatively slow consequence of a warming world. Historical warming committed the world already to long-term sea level rise that is not reversed in even the lowest emissions scenarios (such as 1.5°C), which come with a commitment to a multi-metre sea level rise. Regional sea level change near coastlines differs from global mean sea level change due to vertical land movement, ice mass changes and ocean dynamical changes.

|-
| How much has the ocean acidified and how much oxygen has it lost?

| 2.3.4.3; 2.3.4.2; 5.3

| Ocean acidification is affecting marine life, especially organisms that build calciferous shells and structures (e.g., coral reefs). Together with less oxygen in upper ocean waters and increasingly widespread oxygen minimum zones, and in addition to ocean warming, this poses adaptation challenges for coastal and marine ecosystems and their services, including seafood supply.

|-
| How much of the observed warming was due to anthropogenic influences?

| 3.3.1

| To monitor progress toward the PA’s long-term goals it is important to know how much of the observed warming is due to human activities. [[IPCC:Wg1:Chapter:Chapter-3|Chapter 3]] assesses human-induced warming in global mean near-surface air temperature for the decade 2010–2019, relative to 1850–1900 with associated uncertainties, based on detection and attribution studies. This estimate can be compared with observed estimates of warming for the same decade reported in Chapter 2, and is typically used to calculate carbon budgets consistent with remaining below a particular temperature threshold.

|-
| How much has anthropogenic influence changed other aspects of the climate system?

| 3.3.2; 3.3.3; 3.4; 3.5; 3.6; 3.7; 8; 10.4; 12

| Climate change impacts are driven by changes in many aspects of the climate system, including changes in the water cycle, atmospheric circulation, ocean, cryosphere, biosphere and modes of variability. To better plan climate change adaptation it is relevant to know which observed changes have been driven by human influence.

|-
| How much are anthropogenic emissions contributing to changes in the severity and frequency of extreme events?

| 1.5; Cross-Chapter Box 1.3; Cross-Chapter Box 3.2; 9.6.4; 11.3–11.8; 12.3

| Adaptation challenges are often accentuated in the face of extreme events, including floods, droughts, bushfires and tropical cyclones. For agricultural management, infrastructure planning, and designing for climate resilience it is relevant to know whether extreme events will become more frequent in the near future. In that respect it is important to understand whether observed extreme events are part of a natural background variability or caused by past anthropogenic emissions. This attribution of extreme events is therefore key to understanding current events, as well as to better project the future evolution of these events, such as temperature extremes, heavy precipitation, floods, droughts, extreme storms and compound events, and extreme sea level. Also, loss and damage events are often related to extreme events, which means that future disasters can be fractionally attributed to past human emissions.

|}
<!-- END TABLE -->

<!-- START TABLE -->
<!-- TABLE -->
{| class="wikitable"
|-
! colspan="3"| '''Section 2: Long-Term Climate Futures –''' ''‘Where do'' ''we want to go?’''

''WGI Assessment to inform how long-term climate change could unfold depending on chosen em'' ''issions futures''

|-
! '''Question'''

! '''Chapter'''

! '''Potential Relevance and Expl''' '''anatory Remarks'''

|-
| How are climate model projections used to project the range of future global and regional climate changes?

| 3.8.2; Cross-Chapter Box 3.1; Box 4.1; 10.3; 10.4; 12.4

| The scientific literature provides new insights in a developing field of scientific research regarding evaluating model performance and weighting. This can lead to more constrained projection ranges for a given scenario and some variables, which take into account the performance of climate models and interdependencies among them. These techniques have a strong relevance to quantifying future uncertainties, for example regarding the likelihood of the various scenarios exceeding the PA’s long-term temperature goals of 1.5°C or 2°C.

|-
| If emissions scenarios are pursued that achieve mitigation goals by 2050, what will be the difference in climate over the 21st century compared to emissions scenarios where no additional climate policies are implemented?

| 1.2.2; 4.6; FAQ 4.2; Chapters 9 and 11; 12.4; Atlas;

Interactive Atlas

| Estimating the scale and timing of mitigation compatible with the PA’s long-term goals requires an understanding of the climate system response to a change in anthropogenic emissions. The new generation of scenarios spans the response space from very low emissions scenarios (SSP1-1.9) under the assumption of accelerated and effective climate policy implementation, to very high emissions scenarios in the absence of additional climate policies (SSP3-7.0 or SSP5-8.5). It can be informative to place current NDCs and their emissions mitigation pledges within this low- and high-end scenario range, that is, in the context of intermediate-high emissions scenarios (RCP4.5, RCP6.0 or SSP4-6.0). Climate response differences between those future intermediate or high emissions scenarios and those compatible with the PA’s long-term temperature goals can help inform policymakers about the corresponding adaptation challenges.

|-
| What is the climatic effect of net zero GHG emissions and a balance between anthropogenic sources and anthropogenic sinks?

| Box 1.4; 4.7.2; 5.2.2–5.2.4; 7.6

| Understanding the long-term climate effect of global emissions levels, including the effect of net zero emissions targets adopted by countries as part of their long-term climate strategies, can be important when assessing whether the collective level of mitigation action is consistent with the long-term goals of the PA. Understanding the dynamics of natural sources of CO <sub>2</sub> , CH <sub>4</sub> and N <sub>2</sub> O is a fundamental prerequisite to derive climate projections. Net zero GHG emissions, that is, the balance between anthropogenic sources and anthropogenic sinks of CO <sub>2</sub> and other GHGs, will halt human-induced global warming and/or lead to slight reversal below peak warming levels. Net zero CO <sub>2</sub> emissions will approximately lead to a stabilization of CO <sub>2</sub> -induced global warming.

|-
| What is the remaining carbon budget that is consistent with the PA’s long-term temperature goals?

| 5.5

| The remaining carbon budget provides an estimate of how much CO <sub>2</sub> can still be emitted into the atmosphere by human activities while keeping GMST to a specific warming level. It thus provides key geophysical information about emissions limits consistent with limiting global warming to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C. Remaining carbon budgets can be seen in the context of historical CO <sub>2</sub> emissions to date. The concept of the transient climate response to cumulative CO <sub>2</sub> emissions (TCRE) indicates that one tonne of CO <sub>2</sub> has the same effect on global warming irrespective of whether it is emitted in the past, today, or in the future. In contrast, the global warming from short-lived climate forcers (SLCFs) is dependent on their rate of emission rather than their cumulative emissions.

|-
| What is our current knowledge on the ‘Reasons for Concern’ related to the PA’s long-term temperature goals and higher warming levels?

| Cross-Chapter Box 12.1; individual domains are discussed in 2.3.3; 3.5.4; 4.3.2; 5.3; 8.4.1; 9.4.2, 9.5; Chapters 11 and 12

| Synthesis information on projected changes in indices of climatic impact-drivers feeds into different Reasons for Concern. Where possible, an explicit transfer function between different warming levels and indices quantifying characteristics of these hazards is provided, or the difficulties in doing so documented. Those indices include Arctic sea ice area in September; global average change in ocean acidification; volume of glaciers or snow cover; ice volume change for the West Antarctic Ice Sheet (WAIS) and Greenland Ice Sheet (GrIS); Atlantic Meridional Overturning Circulation (AMOC) strength; amplitude and variance of El Niño–Southern Oscillation (ENSO) mode (Niño 3.4 index); and weather and climate extremes.

|-
| What are the climate effects and air pollution co-benefits of rapid decarbonisation due to the reduction of co-emitted short-lived climate forcers (SLCFs)?

| 6.6.3; 6.7.3; Box 6.2

| Understanding to what degree rapid decarbonization strategies bring about reduced air pollution due to reductions in co-emitted SLCFs can help inform considerations of integrated and/or complementary policies, with synergies for pursuing the PA goals, the World Health Organization (WHO) air quality guidelines and the Sustainable Development Goals (SDGs).

|-
| What are the equilibrium climate sensitivity (ECS), the transient climate response (TCR), and transient climate response to CO <sub>2</sub> emissions (TCRE) and what do these indicators tell us about expected warming over the 21st century under various scenarios?

| Box 4.1; 5.4; 5.5.1; 7.5

| ECS measures the long-term global mean warming in response to doubling CO <sub>2</sub> concentrations from pre-industrial levels, while TCR also takes into account the inertia of the climate system and is an indicator for the near- and medium-term warming. TCRE is similar to TCR, but asks the question of what is the implied warming in response to cumulative CO <sub>2</sub> emissions (rather than CO <sub>2</sub> concentration changes). The higher the ECS, TCR or TCRE, the lower are the GHG emissions that are consistent with the PA’s long-term temperature goals.

|-
| What is the Earth’s energy imbalance and why does it matter?

| 7.2.2

| The current global energy imbalance implies that one can expect additional warming before the Earth’s climate system attains equilibrium with the current level of concentrations and radiative forcing. Note though, that future warming commitments can be different depending on how future concentrations and radiative forcing change.

|-
| What are the regional and long-term changes in precipitation, evaporation and runoff?

| 8.4.1; 8.5; 8.6; 10.4; 10.6; 11.4; 11.9; 11.6; 11.7; 12.4; Atlas; Interactive Atlas

| Changes in regional precipitation – in terms of both extremes and long-term averages – are important for estimating adaptation challenges. Projected changes of precipitation minus evaporation (P–E) are closely related to surface water availability and drought probability. Understanding water cycle changes over land, including seasonality, variability and extremes, and their uncertainties, is important to estimate a broad range of climate impacts and adaptation, including food production, water supply and ecosystem functioning.

|-
| Are we committed to irreversible sea level rise and what is the expected sea level rise by the end of the century if we pursue strong mitigation or high emissions scenarios?

| 4.7.2; 9.6.3; 9.6.4; 12.4;

Interactive Atlas

| Unlike many regional climate responses, global mean sea level (GMSL) keeps rising, even in the lowest emissions scenarios and is not halted when warming is halted. This is due to the long time scales on which ocean heat uptake, glacier melt and ice sheets react to temperature changes. Tipping points and thresholds in polar ice sheets need to be considered. Thus, sea level rise commitments and centennial-scale irreversibility of ocean warming and sea level rise are important for future impacts under even the lowest of the emissions scenarios.

|-
| Can we project future climate extremes under various global warming levels in the long term?

| Chapter 11; 12.4;

Interactive Atlas

| Projections of future extreme weather and climate events and their regional occurrence, including at different global warming levels, are important for adaptation and disaster risk reduction. The attribution of these extreme events to natural variability and human-induced changes can be of relevance for both assessing adaptation challenges and issues of loss and damage.

|-
| What is the current knowledge of potential surprises, abrupt changes, tipping points and low-likelihood, high-impact outcomes related to different levels of future emissions or warming?

| 1.4.4; 4.7.2; 4.8; 5.4.8; Box 5.1; 8.5.3.2; 8.6.2; Box 9.4; 11.2.4; Cross-Chapter Box 4.1; Cross-Chapter Box 12.1

| From a risk perspective, it is useful to have information about lower-probability events and system changes, if they have the potential to result in high impacts, given the dynamic interactions between climate-related hazards and socio-economic drivers (i.e., exposure and vulnerability of the affected human or ecological systems). Examples include permafrost thaw, CH <sub>4</sub> clathrate feedbacks, ice-sheet mass loss and ocean turnover circulation changes, all of which can accelerate warming globally or yield particular regional responses and impacts.

|}
<!-- END TABLE -->

<!-- START TABLE -->
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{| class="wikitable"
|-
! colspan="3"| '''Section 3: The Near Term –''' ‘ ''How do'' ''we get there?’''

''WGI Assessment to inform near-term adaptation and mit'' ''igation options''

|-
! '''Questions'''

! '''Chapter'''

! '''Potential Relevance and Expl''' '''anatory Remarks'''

|-
| What are projected key climate indices under low, intermediate and high emissions scenarios in the near term, that is, the next 20 years?

| 4.3; 4.4; FAQ 4.1, 10.6; 12.3; Atlas; Interactive Atlas

| Much of the near-term information and comparison to historical observations allows us to quantify the climate adaptation challenges for the next decades as well as the opportunities to reduce climate change by pursuing lower emissions. For this time scale both the forced changes and the internal variability are important.

|-
| How can the climate benefit of mitigating emissions of different GHGs be compared?

| 7.6

| For mitigation challenges, it is important to compare efforts to reduce emissions of CO <sub>2</sub> versus emissions of other climate forcers, such as short-lived CH <sub>4</sub> or long-lived N <sub>2</sub> O. Global warming potentials (GWPs), which are used in the UNFCCC and in emissions inventories, are updated and various other metrics are also investigated in this Report. While the NDCs of Parties to the PA, emissions inventories under the UNFCCC, and various emissions trading schemes work on the basis of GWP-weighted emissions, some recent discussion in the scientific literature also considers projecting temperatures induced by SLCFs on the basis of emissions changes, not emissions per se.

|-
| Do mountain glaciers shrink, currently and in the near future, in regions that are currently dependent on them for seasonal freshwater supply?

| 2.3.2.3; 8.4.1;

9.5; Cross-Chapter Box 10.4; 12.4:

Atlas.5.2.2;

Atlas.5.3.2;

Atlas.6.2; Atlas.9.2

| Mountain glaciers and seasonal snow cover often feed downstream river systems during the melting period, and can be an important source of freshwater. Changing river discharge can pose adaptation challenges. Melting mountain glaciers are among the main contributors to observed GMSL rise.

|-
| What are the capacities and limitations in the provision of regional climate information for adaptation and risk management?

| Cross-Chapter Box 1.3; 10.5; 10.6; Box 10.2; Cross-Chapter Box 10.4; 11.9; 12.6; Cross-Chapter Box 12.1

| Challenges for adaptation and risk management are predominantly local, even if globally interlinked. There are a number of approaches used in the production of regional climate information for adaptation purposes focusing on regional scales. All of them consider a range of sources of data and knowledge that are distilled into, at times contextual, climate information. A wealth of examples can be found in this Report, including assessments of extremes and climatic impact-drivers, and attribution at regional scales. Specific regions and case studies for regional projections are considered, like the Sahel and West African monsoon drought and recovery, the southern Australian rainfall decline, and the Caribbean small island summer drought, and regional projections are discussed for Cape Town, the Mediterranean region and Hindu Kush Himalaya.

|-
| How important are reductions in short-lived climate forcers compared to the reduction of CO <sub>2</sub> and other long-lived GHGs?

| 6.1; 6.6; 6.7; 7.6

| While most of the radiative forcing which causes climate change comes from CO <sub>2</sub> emissions, short-lived climate forcers also play an important role in the anthropogenic effect on climate change. Many aerosol species, especially SO4, tend to cool the climate and mask some GHG-induced warming, so reductions in these SLCFs would have a warming effect. On the other hand, many short-lived species themselves exert a warming effect, including black carbon and CH <sub>4</sub> , the second most important anthropogenic GHG (in terms of current radiative forcing). Notably, the climate response to aerosol emissions has a strong regional pattern and is different from that of GHG-driven warming.

|-
| What are potential co-benefits and side effects of climate change mitigation?

| 5.6.2; 6.1; 6.7.5

| The reduction of fossil fuel-related emissions often goes hand-in-hand with a reduction of air pollutants, such as aerosols and ozone. Reductions will improve air quality and result in broader environmental benefits (reduced acidification, eutrophication, and often tropospheric ozone recovery). More broadly, various co-benefits are discussed in WGII and WGIII, as well as co-benefits and side effects related to certain mitigation actions, like increased biomass use and associated challenges to food security and biodiversity conservation.

|-
| What large near-term surprises could result in particular adaptation challenges?

| 1.4; 4.4.4; Cross-Chapter Box 4.1; 8.5.2; 11.2.4; Cross-Chapter Box 12.1

| Surprises can come from a range of sources: from incomplete understanding of the climate system, from surprises in emissions of natural (e.g., volcanic) sources, or from disruptions to the carbon cycle associated with a warming climate (e.g., methane release from permafrost thawing, tropical forest dieback). There could be large natural variability in the near term; or also accelerated climate change due to a markedly more sensitive climate than previously thought. When the next large explosive volcanic eruption will happen is unknown. The largest volcanic eruptions over the last few hundred years led to substantial but temporary cooling, including precipitation changes.

|}
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=== 1.2.3 Linking Science and Society: Communication, Values, and the IPCC Assessment Process ===

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This section assesses how the process of communicating climate information has evolved since AR5. It summarizes key issues regarding scientific uncertainty addressed in previous IPCC assessments and introduces the IPCC calibrated uncertainty language. Next it discusses the role of values in problem-driven, multidisciplinary science assessments such as this one. The section introduces climate services and how climate information can be tailored for greatest utility in specific contexts, such as the global stocktake. Finally, we briefly evaluate changes in media coverage of climate information since AR5, including the increasing role of Internet sources and social media.

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==== 1.2.3.1 Climate Change Understanding, Communication and Uncertainties ====

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Responses to climate change are facilitated when leaders, policymakers, resource managers and their constituencies share a basic understanding of the causes, effects, and possible future course of climate change (SR1.5, [[#IPCC--2018|IPCC, 2018]] ; SRCCL, [[#IPCC--2019a|IPCC, 2019a]] ). Achieving shared understanding is complicated, since scientific knowledge interacts with pre-existing conceptions of weather and climate that have built up in diverse world cultures over centuries, and which are often embedded in strongly held values and beliefs stemming from ethnic or national identities, traditions, religions, and lived relationships to weather, land and sea (Van Asselt and Rotmans, 1996; [[#Rayner--1998|Rayner and Malone, 1998]] ; [[#Hulme--2009|Hulme, 2009]] , 2018; [[#Green--2010|Green et al., 2010]] ; [[#Jasanoff--2010|Jasanoff, 2010]] ; [[#Orlove--2010|Orlove et al., 2010]] ; [[#Nakashima--2012|Nakashima et al., 2012]] ; [[#Shepherd--2020|Shepherd and Sobel, 2020]] ).These diverse, more local understandings can both contrast with and enrich the planetary-scale analyses of global climate science ( ''hi'' ''gh confidence'' ).

Political cultures also give rise to variation in how climate science knowledge is interpreted, used and challenged ( [[#Leiserowitz--2006|Leiserowitz, 2006]] ; [[#Oreskes--2010|Oreskes and Conway, 2010]] ; [[#Brulle--2012|Brulle et al., 2012]] ; [[#Dunlap--2013|Dunlap and Jacques, 2013]] ; [[#Mahony--2014|Mahony, 2014]] , 2015; [[#Brulle--2019|Brulle, 2019]] ). A meta-analysis of 87 studies carried out between 1998 and 2016 (62 USA national, 16 non-USA national, 9 cross-national) found that political orientation and political party identification were the second most important predictors of views on climate change after environmental values (McCright et al. 2016). [[#Ruiz--2020|Ruiz et al. (2020)]] systematically reviewed 34 studies of non-US nations or clusters of nations and 30 studies of the USA alone. They found that in the non-US studies, ‘changed weather’ and ‘socio-altruistic values’ were the most important drivers of public attitudes. For the USA case, by contrast, political affiliation and the influence of corporations were most important. Widely varying media treatment of climate issues also affects public responses ( [[#1.2.3.4|Section 1.2.3.4]] ). In summary, environmental and socio-altruistic values are the most significant influences on public opinion about climate change globally, while political views, political party affiliation, and corporate influence also had strong effects, especially in the USA ( ''hi'' ''gh confidence'' ).

Furthermore, climate change itself is not uniform. Some regions face steady, readily observable change, while others experience high variability that masks underlying trends ( [[#1.4.1|Section 1.4.1]] ); mostregions are subject to hazards, but some may also experience benefits, at least temporarily (Chapters 11, 12 and Atlas). This non-uniformity may lead to wide variation in public climate change awareness and risk perceptions at multiple scales ( [[#Howe--2015|Howe et al., 2015]] ; [[#Lee--2015|Lee et al., 2015]] ). For example, short-term temperature trends, such as cold spells or warm days, have been shown to influence public concern ( [[#Hamilton--2013|Hamilton and Stampone, 2013]] ; [[#Zaval--2014|Zaval et al., 2014]] ; [[#Bohr--2017|Bohr, 2017]] ).

Given these manifold influences and the highly varied contexts of climate change communication, special care is required when expressing findings and uncertainties, including IPCC assessments that inform decision making. Throughout the IPCC’s history, all three Working Groups have sought to explicitly assess and communicate scientific uncertainty ( [[#Le%20Treut--2007|Le Treut et al., 2007]] ; [[#Cubasch--2013|Cubasch et al., 2013]] ). Over time, the IPCC has developed and revised a framework to treat uncertainties consistently across assessment cycles, reports, and Working Groups through the use of calibrated language ( [[#Moss--2000|Moss and Schneider, 2000]] ; [[#IPCC--2005|IPCC, 2005]] ). Since its First Assessment Report (FAR; [[#IPCC--1990a|IPCC, 1990a]] ), the IPCC has specified terms and methods for communicating authors’ expert judgments ( [[#Mastrandrea--2011|Mastrandrea and Mach, 2011]] ). During the AR5 cycle, this calibrated uncertainty language was updated and unified across all Working Groups ( [[#Mastrandrea--2010|Mastrandrea et al., 2010]] , 2011). Box 1.1 summarizes this framework as it is used in AR6.

'''Box 1.1 | Treatment of Uncertainty and Calibrated Uncertainty''' '''Language in AR6'''

The AR6 follows the approach developed for AR5 (Box 1.1, Figure 1), as described in the ‘Guidance Notes for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties’ ( [[#Mastrandrea--2010|Mastrandrea et al., 2010]] ). The uncertainty Guidance Note used in AR6 clarifies the relationship between the qualitative description of confidence and the quantitative representation of uncertainty expressed by the likelihood scale. The calibrated uncertainty language emphasizes traceability of the assessment throughout the process. Key chapter findings presented in each chapter’s Executive Summary are supported in the chapter text by a summary of the underlying literature that is assessed in terms of evidence and agreement, confidence, and also likelihood, if applicable.

In all three Working Groups, author teams evaluate underlying scientific understanding and use two metrics to communicate the degree of certainty in key findings. These metrics are:

# ''confidence:'' a qualitative measure of the validity of a finding, based on the type, amount, quality and consistency of evidence (e.g., data, mechanistic understanding, theory, models, expert judgment) and the degree of agreement.
# ''Likelihood:'' a quantitative measure of uncertainty in a finding, expressed probabilistically (e.g., based on statistical analysis of observations or model results, or both, and expert judgement by the author team or from a formal quantitative survey of expert views, or both).

Throughout IPCC reports, the calibrated language indicating a formal confidence assessment is clearly identified by ''italics'' (e.g., ''medium confidence'' ). Where appropriate, findings can also be formulated as statements of fact without uncertainty qualifiers.

Box.1.1, Figure 1 (adapted from [[#Mach--2017|Mach et al., 2017]] ) shows the idealized step-by-step process by which IPCC authors assess scientific understanding and uncertainties. It starts with the evaluation of the available evidence and agreement (steps 1–2). The following summary terms are used to describe the available evidence: ''limited, medium,'' or ''robust'' ; and the degree of agreement: ''low, medium,'' or ''high'' . Generally, evidence is most robust when there are multiple, consistent, independent lines of high-quality evidence.

If the author team concludes that there is sufficient evidence and agreement, the level of confidence can be evaluated. In this step, assessments of evidence and agreement are combined into a single metric (steps 3–5). The assessed level of confidence is expressed using five qualifiers: ''very low, low, medium, high,'' and ''very high'' . Step 4 depicts how summary statements for evidence and agreement relate to confidence levels. For a given evidence and agreement statement, different confidence levels can be assigned depending on the context, but increasing levels of evidence and degrees of agreement correlate with increasing confidence. When confidence in a finding is assessed to be ''low'' , this does not necessarily mean that confidence in its opposite is ''high,'' and vice versa. Similarly, ''low'' ''confidence'' does not imply distrust in the finding; instead, it means that the statement is the best conclusion based on currently available knowledge. Further research and methodological progress may change the level of confidence in any finding in future assessments.

Ifthe expert judgement of the author team concludes that there is sufficient confidence and quantitative/probabilistic evidence, assessment conclusions can be expressed with likelihood statements (steps 5–6). Unless otherwise indicated, likelihood statements are related to findings for which the authors’ assessment of confidence is ''high'' or ''very high'' . Terms used to indicate the assessed likelihood of an outcome include: ''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.

Likelihood can indicate probabilities for single events or broader outcomes. The probabilistic information may build from statistical or modelling analyses, other quantitative analyses, or expert elicitation. The framework encourages authors, where appropriate, to present probability more precisely than can be done with the likelihood scale, for example with complete probability distributions or percentile ranges, including quantification of tails of distributions, which are important for risk management (Sections [[#1.2.2|1.2.2]] and [[#1.4.4|1.4.4]] ; [[#Mach--2017|Mach et al., 2017]] ). In some instances, multiple combinations of confidence and likelihood are possible to characterize key findings

Box 1.1

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[[File:6793eab315c3a891be05e64e729d221c IPCC_AR6_WGI_Box_1_1_Figure_1.png]]
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'''Box 1.1, Figure 1 |'''
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'''The IPCC AR6 approach for characterizing understanding and uncertainty in assessment findings.''' This diagram illustrates the step-by-step process authors use to evaluate and communicate the state of knowledge in their assessment ( [[#Mastrandrea--2010|Mastrandrea et al., 2010]] ). Authors present evidence/agreement, confidence, or likelihood terms with assessment conclusions, communicating their expert judgments accordingly. Example conclusions drawn from Report are presented in the box at the bottom of the figure. Figure adapted from [[#Mach--2017|Mach et al. (2017)]] .
For example, a ''very likely'' statement might be made with ''high confidence'' , whereas a ''likely'' statement might be made with ''very high confidence'' . In these instances, the author teams consider which statement will convey the most balanced information to the reader.

Throughout this WGI Report, 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 (as in the illustrative example in the figure), 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’.

Considerable critical attention has focused on whether applying the IPCC framework effectively achieves consistent treatment of uncertainties and clear communication of findings to users ( [[#Shapiro--2010|Shapiro et al., 2010]] ; [[#Adler--2014|Adler and Hirsch Hadorn, 2014]] ). Specific concerns include, for example, the transparency and traceability of expert judgements underlying the assessment conclusions ( [[#Oppenheimer--2016|Oppenheimer et al., 2016]] ) and the context-dependent representations and interpretations of probability terms ( [[#Budescu--2009|Budescu et al., 2009]] , 2012; [[#Janzwood--2020|Janzwood, 2020]] ). [[#Budescu--2014|Budescu et al. (2014)]] surveyed 25 samples in 24 countries (a total of 10,792 individual responses), finding that even when shown IPCC uncertainty guidance, lay readers systematically misunderstood IPCC likelihood statements. When presented with a ‘high likelihood’ statement, they understood it as indicating a lower likelihood than intended by the IPCC authors. Conversely, they interpreted ‘low likelihood’ statements as indicating a higher likelihood than intended. In another study, British lay readers interpreted uncertainty language somewhat differently from IPCC guidance, but Chinese lay people reading the same uncertainty language translated into Chinese differed much more in their interpretations ( [[#Harris--2013|Harris et al., 2013]] ). Further, even though it is objectively more probable that wide uncertainty intervals will encompass true values, wide intervals were interpreted by lay people as implying subjective uncertainty or lack of knowledge on the part of scientists ( [[#Løhre--2019|Løhre et al., 2019]] ). [[#Mach--2017|Mach et al. (2017)]] investigated the advances and challenges in approaches to expert judgment in AR5. Their analysis showed that the shared framework increased the overall comparability of assessment conclusions across all Working Groups and topics related to climate change, from the physical science basis to resulting impacts, risks, and options for response. Nevertheless, many challenges in developing and communicating assessment conclusions persist, especially for findings drawn from multiple disciplines and Working Groups, for subjective aspects of judgements, and for findings with substantial uncertainties ( [[#Adler--2014|Adler and Hirsch Hadorn, 2014]] ). In summary, the calibrated language cannot entirely prevent misunderstandings, including a tendency to systematically underestimate the probability of the IPCC’s higher-likelihood conclusions and overestimate the probability of the lower-likelihood ones ( ''high confidence'' ). However, a consistent and systematic approach across Working Groups to communicate the assessment outcomes is an important characteristic of the IPCC.

Some suggested alternatives are impractical, such as always including numerical values along with calibrated language ( [[#Budescu--2014|Budescu et al., 2014]] ). Others, such as using positive instead of negative expressions of low-to-medium probabilities, show promise but were not proposed in time for adoption in AR6 ( [[#Juanchich--2020|Juanchich et al., 2020]] ). This report therefore retains the same calibrated language used in AR5 (Box 1.1). Like previous reports, AR6 also includes FAQs that express its chief conclusions in plain language designed for lay readers.

The framework for communicating uncertainties does not allow for indicating cases where ‘deep uncertainty’ is identified in the assessment ( [[#Adler--2014|Adler and Hirsch Hadorn, 2014]] ). The definition of deep uncertainty in IPCC assessments has been described in the context of SROCC ( [[#IPCC--2019b|IPCC, 2019b]] ; Box 5 in [[#Abram--2019|Abram et al., 2019]] ): a situation of deep uncertainty exists when experts or stakeholders do not know or cannot agree on: (i) appropriate conceptual models that describe relationships among key driving forces in a system; (ii) the probability distributions used to represent uncertainty about key variables and parameters; and/or (iii) how to weigh and value desirable alternative outcomes (Cross-Chapter Box 1.2 and Annex VII: Glossary; [[#Abram--2019|Abram et al., 2019]] ). Since AR5, ‘storylines’ or ‘narratives’ approaches have been used to address issues related to deep uncertainty, for example low-likelihood events that would have high impact if they occurred, to better inform risk assessment and decision making ( [[#1.4.4|Section 1.4.4]] ). [[IPCC:Wg1:Chapter:Chapter-9|Chapter 9]] (Section 9.2.3) notes deep uncertainty in long-term projections for sea level rise, and in processes related to marine ice-sheet instability and marine ice cliff instability.

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<span id="values-science-and-climate-change-communication"></span>
==== 1.2.3.2 Values, Science and Climate Change Communication ====

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As noted above, values – fundamental attitudes about what is important, good, and right – play critical roles in all human endeavours, including climate science. In AR5, Chapters 3 and 4 of the WGIII Assessment addressed the role of cultural, social and ethical values in climate change mitigation and sustainable development ( [[#Fleurbaey--2014|Fleurbaey et al., 2014]] ; [[#Kolstad--2014|Kolstad et al., 2014]] ). These values include widely accepted concepts of human rights, enshrined in international law, that are relevant to climate impacts and policy objectives ( [[#Hall--2012|Hall and Weiss, 2012]] ; [[#Peel--2018|Peel and Osofsky, 2018]] ; [[#Setzer--2019|Setzer and Vanhala, 2019]] ). Specific values – human life, subsistence, stability, and equitable distribution of the costs and benefits of climate impacts and policies – are explicit in the texts of the UNFCCC and the PA ( [[#Breakey--2016|Breakey et al., 2016]] ; [[#Dooley--2016|Dooley and Parihar, 2016]] ). Here we address the role of values in how scientific knowledge is created, verified and communicated. Chapters 10, 12 and Cross-Chapter Box 12.2 address how the specific values and contexts of users can be addressed in the co-production of climate information.

The epistemic (knowledge-related) values of science include explanatory power, predictive accuracy, falsifiability, replicability, and justification of claims by explicit reasoning ( [[#Popper--1959|Popper, 1959]] ; [[#Kuhn--1977|Kuhn, 1977]] ). These are supported by key institutional values, including openness, ‘organized scepticism’, and objectivity or ‘disinterestedness’ ( [[#Merton--1973|Merton, 1973]] ), operationalized as well-defined methods, documented evidence, publication, peer review, and systems for institutional review of research ethics (COSEPUP, 2009; [[#Elliott--2017|Elliott, 2017]] ). In recent decades, open data, open code and scientific cyber-infrastructure (notably the Earth System Grid Federation, a partnership of climate modelling centers dedicated to supporting climate research by providing secure, web-based, distributed access to climate model data) have facilitated scrutiny from a larger range of participants, and FAIR data stewardship principles – making data Findable, Accessible, Interoperable and Reusable (FAIR) – are being mainstreamed in many fields ( [[#Wilkinson--2016|Wilkinson et al., 2016]] ). Climate science norms and practices embodying these scientific values and principles include the publication of data and model code, multiple groups independently analysing the same problems and data, model intercomparison projects (MIPs), explicit evaluations of uncertainty, and comprehensive assessments by national academies of science and the IPCC.

The formal Principles Governing IPCC Work (1998, amended 2003, 2006, 2012, 2013) specify that assessments should be ‘comprehensive, objective, open and transparent.’ The IPCC assessment process seeks to achieve these goals in several ways: by evaluating evidence and agreement across all relevant peer-reviewed literature, especially that published or accepted since the previous assessment; by maintaining a traceable, transparent process that documents the reasoning, data and tools used in the assessment; and by maximizing the diversity of participants, authors, experts, reviewers, institutions and communities represented, across scientific discipline, geographical location, gender, ethnicity, nationality and other characteristics. The multi-stage review process is critical to ensure an objective, comprehensive and robust assessment, with hundreds of scientists, other experts and governments providing comments to a series of drafts before the report is finalized.

Social values are implicit in many choices made during the construction, assessment and communication of climate science information ( [[#Heymann--2017|Heymann et al., 2017]] ; [[#Skelton--2017|Skelton et al., 2017]] ). Some climate science questions are prioritized for investigation, or given a specific framing or context, because of their relevance to climate policy and governance. One example is the question of how the effects of a 1.5°C global warming would differ from those of a 2°C warming, an assessment specifically requested by Parties to the PA. The SR1.5 (2018) explicitly addressed this issue ‘within the context of sustainable development; considerations of ethics, equity and human rights; and the problem of poverty’ (Chapters 1 and 5; see also [[#Hoegh-Guldberg--2019|Hoegh-Guldberg et al., 2019]] ) following the outcome of the approval of the outline of the Special Report by the IPCC during its 44th Session (Bangkok, Thailand, 17–20 October 2016). Likewise, particular metrics are sometimes prioritized in climate model improvement efforts because of their practical relevance for specific economic sectors or stakeholders. Examples include reliable simulation of precipitation in a specific region, or attribution of particular extreme weather events to inform rebuilding and future policy (Chapters 8 and 11; [[#Intemann--2015|Intemann, 2015]] ; [[#Otto--2018|Otto et al., 2018]] ; [[#James--2019|James et al., 2019]] ). Sectors or groups whose interests do not influence research and modelling priorities may thus receive less information in support of their climate-related decisions ( [[#Parker--2018|Parker and]] [[#Winsberg--2018|Winsberg, 2018]] ).

Recent work also recognizes that choices made throughout the research process can affect the relative likelihood of false alarms (overestimating the probability and/or magnitude of hazards) or missed warnings (underestimating the probability and/or magnitude of hazards), known respectively as Type I and Type II errors. Researchers may choose different methods depending on which type of error they view as most important to avoid, a choice that may reflect social values ( [[#Douglas--2009|Douglas, 2009]] ; [[#Knutti--2018|Knutti, 2018]] ; [[#Lloyd--2018|Lloyd and Oreskes, 2018]] ). This reflects a fundamental trade-off between the values of reliability and informativeness. When uncertainty is large, researchers may choose to report a wide range as ''very likely'' , even though it is less informative about potential consequences. By contrast, high-likelihood statements about a narrower range may be more informative, yet also prove less reliable if new evidence later emerges that widens the range. Furthermore, the difference between narrower and wider uncertainty intervals has been shown to be confusing to lay readers, who often interpret wider intervals as less certain ( [[#Løhre--2019|Løhre et al., 2019]] ).

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==== 1.2.3.3 Climate Information, Co-production and Climate Services ====

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In AR6, ‘climate information’ refers to specific information about the past, current or future state of the climate system that is relevant for mitigation, adaptation and risk management. Cross-Chapter Box 1.1 is an example of climate information at the global scale. It provides climate change information with potential relevance for the global stocktake, and indicates where in AR6 this information may be found.

Responding to national and regional policymakers’ needs for tailored information relevant to risk assessment and adaptation, AR6 emphasizes assessment of regional information more than earlier reports. Here the phrase ‘regional climate information’ refers to predefined reference sets of land and ocean regions; various typological domains (such as mountains or monsoons); temporal frames including baseline periods as well as near term (2021–2040), medium term (2041–2060) and long term (2081–2100); and global warming levels (Chapters 10 and 12, Sections [[#1.4.1|1.4.1]] and [[#1.4.5|1.4.5]] , and Atlas). Regional climate change information is constructed from multiple lines of evidence including observations, paleoclimate proxies, reanalyses, attribution of changes and climate model projections from both global and regional climate models (Sections 1.5.3 and 10.2–10.4). The constructed regional information needs to take account of user context and values for risk assessment, adaptation and policy decisions (Sections 1.2.3 and 10.5).

As detailed in Chapter 10, scientific climate information often requires ‘tailoring’ to meet the requirements of specific decision-making contexts. In a study of the UK Climate Projections 2009 (UKCP09) project, researchers concluded that climate scientists struggled to grasp and respond to users’ information needs because they lacked experience interacting with users, institutions and scientific idioms outside the climate science domain ( [[#Porter--2017|Porter and Dessai, 2017]] ). Economic theory predicts the value of ‘polycentric’ approaches to climate change informed by specific global, regional and local knowledge and experience ( [[#Ostrom--1996|Ostrom, 1996]] , 2012). This is confirmed by numerous case studies of extended, iterative dialogue among scientists, policymakers, resource managers and other stakeholders to produce mutually understandable, usable, task-related information and knowledge, policymaking and resource management around the world ( [[#Lemos--2005|Lemos and Morehouse, 2005]] ; [[#Lemos--2012|Lemos et al., 2012]] , 2014, 2018; see [[#Vaughan--2014|Vaughan and Dessai, 2014]] for a critical view). The SR1.5 (2018) assessed that ‘education, information, and community approaches, including those that are informed by indigenous knowledge and local knowledge, can accelerate the wide-scale behaviour changes consistent with adapting to and limiting global warming to 1.5°C. These approaches are more effective when combined with other policies and tailored to the motivations, capabilities and resources of specific actors and contexts ( ''high confidence'' ).’ These extended dialogic co-production and education processes have thus been demonstrated to improve the quality of both scientific information and governance ( ''high confidence'' ) (Section 10.5 and Cross Chapter Box 12.2).

Since AR5, climate services have increased at multiple levels (local, national, regional and global) to aid decision-making of individuals and organizations and to enable preparedness and early climate change action. These services include appropriate engagement from users and providers, are based on scientifically credible information and producer and user expertise, have an effective access mechanism, and respond to the users’ needs (Glossary; [[#Hewitt--2012|Hewitt et al., 2012]] ). A Global Framework for Climate Services (GFCS) was established in 2009 by the World Meteorological Organization (WMO) in support of these efforts ( [[#Hewitt--2012|Hewitt et al., 2012]] ; [[#Lúcio--2016|Lúcio and Grasso, 2016]] ). Climate services are provided across sectors and time scales, from sub-seasonal to multi-decadal, and support co-design and co-production processes that involve climate information providers, resource managers, planners, practitioners and decision makers ( [[#Brasseur--2016|Brasseur and Gallardo, 2016]] ; [[#Trenberth--2016|Trenberth et al., 2016]] ; C.D. [[#Hewitt--2017|]] [[#Hewitt--2017|Hewitt et al., 2017]] ). For example, they may provide high-quality data on temperature, rainfall, wind, soil moisture and ocean conditions, as well as maps, risk and vulnerability analyses, assessments, and future projections and scenarios. These data and information products may be combined with non-meteorological data, such as agricultural production, health trends, population distributions in high-risk areas, road and infrastructure maps for the delivery of goods, and other socio-economic variables, depending on users’ needs ( [[#WMO--2020a|WMO, 2020a]] ). Cross-Chapter Box 12.2 illustrates the diversity of climate services with three examples from very different contexts.

The current landscapeof climate services is assessed in detail in [https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-12 Chapter 12] (Section 12.6), with a focus on multi-decadal time scales relevant for climate change risk assessment. Other information relevant to improving climate services for decision-making includes the assessment of methods to construct regional information (Chapter 10), as well as projections at the regional level (Atlas) relevant for impact and risk assessment in different sectors (Chapter 12).

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==== 1.2.3.4 Media Coverage of Climate Change ====

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Climate services focus on users with specific needs for climate information, but most people learn about climate science findings from media coverage. Since AR5, research has expanded on how mass media report climate change and how their audiences respond ( [[#Dewulf--2013|Dewulf, 2013]] ; [[#Jaspal--2014|Jaspal and Nerlich, 2014]] ; [[#Jaspal--2014|Jaspal et al., 2014]] ). For example, in five European Union (EU) countries, television coverage of AR5 used ‘disaster’ and ‘opportunity’ as its principal themes, but virtually ignored the ‘risk’ framing introduced by AR5 WGII ( [[#Painter--2015|Painter, 2015]] ) and now extended by the AR6 (Cross-Chapter Box 1.3). Other studies show that people react differently to climate change news when it is framed as a catastrophe ( [[#Hine--2016|Hine et al., 2016]] ), as associated with local identities ( [[#Sapiains--2016|Sapiains et al., 2016]] ), or as a social justice issue ( [[#Howell--2013|Howell, 2013]] ). Similarly, audience segmentation studies show that responses to climate change vary between groups of people with different, although not necessarily opposing, views on this phenomenon (e.g., [[#Maibach--2011|Maibach et al., 2011]] ; [[#Sherley--2014|Sherley et al., 2014]] ; [[#Detenber--2016|Detenber et al., 2016]] ). In Brazil, two studies have shown the influence of mass media on the high level of public climate change concern in that country (Rodasand Di Giulio, 2017; [[#Dayrell--2019|Dayrell, 2019]] ). In the USA, analyses of television network news show that climate change receives minimal attention, is most often framed in a political context, and largely fails to link extreme weather events to climate change using appropriate probability framing ( [[#Hassol--2016|Hassol et al., 2016]] ). However, recent evidence suggests that Climate Matters (an Internet resource to help US television weather forecasters link weather to climate change trends) may have had a positive effect on public understanding of climate change ( [[#Myers--2020|Myers et al., 2020]] ). Also, some media outlets have recently adopted and promoted terms and phrases stronger than the more neutral ‘climate change’ and ‘global warming’, including ‘climate crisis’, ‘global heating’, and ‘climate emergency’ ( [[#Zeldin-O’Neill--2019|Zeldin-O’Neill, 2019]] ). Google searches on those terms, and on ‘climate action’, increased 20-fold in 2019, when large social movements such as School Strikes forClimate gained worldwide attention ( [[#Thackeray--2020|Thackeray et al., 2020]] ). We thus assess that specific characteristics of media coverage play a major role in climate understanding and perception ( ''high confidence'' ), including how IPCC assessments are received by the general public.

Since AR5, social media platforms have dramatically altered the mass-media landscape, bringing about a shift from uni-directional transfer of information and ideas to more fluid, multi-directional flows ( [[#Pearce--2019|Pearce et al., 2019]] ). A survey covering 18 Latin American countries ( [[#StatKnows-CR2--2019|StatKnows-CR2, 2019]] ) found that the main sources of information about climate change mentioned were the Internet (52% of mentions), followed by social media (18%). There are well-known challenges with social media, such as misleading or false presentations of scientific findings, incivility that diminishes the quality of discussion around climate change topics, and ‘filter bubbles’ that restrict interactions to those with broadly similar views ( [[#Anderson--2017|Anderson and Huntington, 2017]] ). However, at certain moments (such as at the release of the AR5 WGI report), Twitter studies have found that more mixed, highly-connected groups existed, within which members were less polarized ( [[#Pearce--2014|Pearce et al., 2014]] ; [[#Williams--2015|Williams et al., 2015]] ). Thus, social media platforms may in some circumstances support dialogic or co-production approaches to climate communication. Because the contents of IPCC reports speak not only to policymakers, but also to the broader public, the character and effects of media coverage are important considerations across Working Groups.

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