Editing IPCC:AR6/WGI/Chapter-1 (section)

== 1.3 How We Got Here: The Scientific Context ==

<div id="h1-4-siblings" class="h1-siblings"></div>

Scientific understanding of the climate system’s fundamental features is robust and well established. This section briefly presents the major lines of evidence in climate science (Figure 1.6). It illustrates their long history and summarizes key findings from the WGI contribution to AR5, referencing previous IPCC assessments for comparison, where relevant. Box 1.2 summarizes major findings from three Special Reports already released during the IPCC Sixth Assessment Cycle. This chapter’s Appendix 1A summarizes the principal findings of all six IPCC WGI Assessment Reports, including the present Report, in a single table for ease of reference.

<div id="_idContainer029" class="•-Graphic-insert"></div>

[[File:b73a12c9d8aa7c7ab6c647b5d05f21c8 IPCC_AR6_WGI_Figure_1_6.png]]

'''Figure 1.6 |''' '''Climate science milestones, between 1817 and 2021.''' '''Top:''' Milestones in observations. '''Middle:''' Curves of global surface air temperature (GMST) anomaly relative to 1850–1900, using HadCRUT5 ( [[#Morice--2021|Morice et al., 2021]] ); atmospheric CO <sub>2</sub> concentrations from Antarctic ice cores ( [[#Lüthi--2008|Lüthi et al., 2008]] ; [[#Bereiter--2015|Bereiter et al., 2015]] ); direct air measurements from 1957 onwards (see Figure 1.4 for details; [[#Tans--2020|Tans and Keeling, 2020]] ). '''Bottom:''' Milestones in scientific understanding of the CO <sub>2</sub> -enhanced greenhouse effect. Further details on each milestone are available in [[#1.3|Section 1.3]] , and in [https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-1 Chapter 1] of AR4 ( [[#Le%20Treut--2007|Le Treut et al., 2007]] ).

<div id="1.3.1" class="h2-container"></div>

<span id="lines-of-evidence-instrumental-observations"></span>
=== 1.3.1 Lines of Evidence: Instrumental Observations ===

<div id="h2-12-siblings" class="h2-siblings"></div>

Instrumental observations of the atmosphere, ocean, land, biosphere and cryosphere underpin all understanding of the climate system. This section describes the evolution of instrumental data for major climate variables at Earth’s land and ocean surfaces, at altitude in the atmosphere, and at depth in the ocean. Many data records exist, of varying length, continuity and spatial distribution; Figure 1.7 gives a schematic overview of temporal coverage.

<div id="_idContainer031" class="•-Graphic-insert"></div>

[[File:2d9a8a86fa1401714166104d4c232339 IPCC_AR6_WGI_Figure_1_7.png]]

'''Figure 1.7 |''' '''Schematic of temporal coverage of (a) selected instrumental climate observations and (b) selected paleoclimate archives.''' The satellite era began in 1979 CE. The width of the taper gives an indication of the amount of available records.

Instrumental weather observation at the Earth’s surface dates to the invention of thermometers and barometers in the 17th century. National and colonial weather services built networks of surface stations in the 19th century. By the mid-19th century, semi-standardized naval weather logs recorded winds, currents, precipitation, air pressure, and temperature at sea, initiating the longest continuous quasi-global instrumental record ( [[#Maury--1849|Maury, 1849]] , 1855, 1860). Because the ocean covers over 70% of global surface area and constantly exchanges energy with the atmosphere, both air and sea surface temperatures (SST) recorded in these naval logs are crucial variables in climate studies. [[#Dove--1853|Dove (1853)]] mapped seasonal isotherms over most of the globe. By 1900, a patchy weather data-sharing system reached all continents except Antarctica. Regular compilation of climatological data for the world began in 1905 with the Réseau Mondial (Air Ministry – Meteorological Office, 1921), and similar compilations – the World Weather Records ( [[#Clayton--1927|Clayton, 1927]] ) and Monthly Climatic Data for the World (est. 1948) – have been published continuously since their founding.

Landand ocean surface temperature data have been repeatedly evaluated, refined and extended ( [[#1.5.1|Section 1.5.1]] ). As computer power increased and older data were recovered from handwritten records, the number of surface station records used in published global land temperature time series grew. A pioneering study for 1880–1935 used fewer than 150 stations ( [[#Callendar--1938|Callendar, 1938]] ). A benchmark study of 1880–2005 incorporated 4300 stations ( [[#Brohan--2006|Brohan et al., 2006]] ). A study of the 1753–2011 period included previously unused station data, for a total of 36,000 stations ( [[#Rohde--2013|Rohde et al., 2013]] ); recent versions of this dataset comprise over 40,000 land stations ( [[#Rohde--2020|Rohde and Hausfather, 2020]] ). Several centres, including the National Oceanic and Atmospheric Administration (NOAA), Hadley, and Japan Meteorological Agency (JMA), produce SST datasets independently calculated from instrumental records. In the 2000s, adjustments for bias due to different measurement methods (buckets, engine intake thermometers, moored and drifting buoys) resulted in major improvements of SST data ( [[#Thompson--2008|Thompson et al., 2008]] ), and these improvements continue ( [[#Huang--2017|Huang et al., 2017]] ; [[#Kennedy--2019|Kennedy et al., 2019]] ). SST and land-based data are incorporated into global surface temperature datasets calculated independently by multiple research groups, including NOAA, NASA, Berkeley Earth, Hadley-CRU, JMA, and China Meteorological Administration (CMA). Each group aggregates the raw measurement data, applies various adjustments for non-climatic biases such as urban heat-island effects, and addresses unevenness in geospatial and temporal sampling with various techniques (see ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.1.3|Section 2.3.1.1.3]] and Table 2.4 for references). Other research groups provide alternative interpolations of these datasets using different methods (e.g., [[#Cowtan--2014|Cowtan and Way, 2014]] ; [[#Kadow--2020|Kadow et al., 2020]] ). Using the then available global surface temperature datasets, AR5 WGI assessed that the GMST increased by 0.85°C from 1880 to 2012 and found that each of the three decades following 1980 was successively warmer at the Earth’s surface than any preceding decade since 1850 ( [[#IPCC--2013b|IPCC, 2013b]] ). Marine air temperatures, especially those measured during nighttime, are increasingly also used to examine variability and long-term trends (e.g., [[#Rayner--2006|Rayner et al., 2006]] ; [[#Kent--2013|Kent et al., 2013]] ; [[#Cornes--2020|Cornes et al., 2020]] ; [[#Junod--2020|Junod and Christy, 2020]] ). Cross-Chapter Box 2.3 discusses updates to the global temperature datasets, provides revised estimates for the observed changes and considers whether marine air temperatures are changing at the same rate as SSTs.

Data at altitude came initially from scattered mountain summits, balloons and kites, but the upper troposphere and stratosphere were not systematically observed until radiosonde (weather balloon) networks emerged in the 1940s and 1950s. These provide the longest continuous quasi-global record of the atmosphere’s vertical dimension ( [[#Stickler--2010|Stickler et al., 2010]] ). New methods for spatial and temporal homogenisation (intercalibration and quality control) of radiosonde records were introduced in the 2000s ( [[#Sherwood--2008|Sherwood et al., 2008]] , 2015; [[#Haimberger--2012|Haimberger et al., 2012]] ). Since 1978, Microwave Sounding Units (MSU) mounted on Earth-orbiting satellites have provided a second high-altitude data source, measuring temperature, humidity, ozone, and liquid water throughout the atmosphere. Over time, these satellite data have required numerous adjustments to account for such factors as orbital precession and decay ( [[#Edwards--2010|Edwards, 2010]] ). Despite repeated adjustments, however, marked differences remain in the temperature trends from surface, radiosonde, and satellite observations; between the results from three research groups that analyse satellite data (University of Alabama in Huntsville (UAH), Remote Sensing Systems (RSS), and NOAA); and between modelled and satellite-derived tropospheric warming trends ( [[#Thorne--2011|Thorne et al., 2011]] ; [[#Santer--2017|Santer et al., 2017]] ). These differences are the subject of ongoing research ( [[#Maycock--2018|Maycock et al., 2018]] ). In the 2000s, Atmospheric Infrared Sounder (AIRS) and radio occultation (GNSS-RO) measurements provided new ways to measure temperature at altitude, complementing data from the MSU. GNSS-RO is a new independent, absolutely calibrated source, using the refraction of radio-frequency signals from the Global Navigation Satellite System (GNSS) to measure temperature, pressure and water vapour ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.2.1|Section 2.3.1.2.1]] ; [[#Foelsche--2008|Foelsche et al., 2008]] ; [[#Anthes--2011|Anthes, 2011]] ).

Heat-retaining properties of the atmosphere’s constituent gases were closely investigated in the 19th century. [[#Foote--1856|Foote (1856)]] measured solar heating of CO <sub>2</sub> experimentally and argued that higher concentrations in the atmosphere would increase Earth’s temperature. Water vapour, ozone, CO <sub>2</sub> and certain hydrocarbons were found to absorb longwave (infrared) radiation, the principal mechanism of the greenhouse effect ( [[#Tyndall--1861|Tyndall, 1861]] ). Nineteenth-century investigators also established the existence of a natural biogeochemical carbon cycle. Carbon dioxide emitted by volcanoes is removed from the atmosphere through a combination of silicate rock weathering, deep-sea sedimentation, oceanic absorption, and biological storage in plants, shellfish, and other organisms. On multi-million-year time scales, the compression of fossil organic matter is stored as carbon as coal, oil and natural gas ( [[#Chamberlin--1897|Chamberlin, 1897]] , 1898; [[#Ekholm--1901|Ekholm, 1901]] ).

Arrhenius (1896) calculated that a doubling of atmospheric CO <sub>2</sub> would produce warming of 5°C–6°C, but in 1900 new measurements seemed to rule out CO <sub>2</sub> as a greenhouse gas due to overlap with the absorption bands of water vapour ( [[#Ångström--1900|Ångström, 1900]] ; [[#Very--1901|Very and Abbe, 1901]] ). Further investigation and more sensitive instruments later overturned Ångström’s conclusion ( [[#Fowle--1917|Fowle, 1917]] ; [[#Callendar--1938|Callendar, 1938]] ). Nonetheless, the major role of CO <sub>2</sub> in the energy balance of the atmosphere was not widely accepted until the 1950s ( [[#Callendar--1949|Callendar, 1949]] ; [[#Plass--1956|Plass, 1956]] , 1961; [[#Manabe--1961|Manabe and Möller, 1961]] ; [[#Weart--2008|Weart, 2008]] ; [[#Edwards--2010|Edwards, 2010]] ). Revelle and Keeling established CO <sub>2</sub> monitoring stations in Antarctica and Hawaii during the 1957–1958 International Geophysical Year ( [[#Revelle--1957|Revelle and Suess, 1957]] ; [[#Keeling--1960|Keeling, 1960]] ). These stations have tracked rising atmospheric CO <sub>2</sub> concentrations from 315 ppm in 1958 to 414 ppm in 2020. Ground-based monitoring of other GHGs followed. The Greenhouse Gases Observing Satellite (GOSat) was launched in 2009, and two Orbiting Carbon Observatory satellite instruments have been in orbit since 2014.

The AR5 WGI highlighted ‘the other CO <sub>2</sub> problem’ ( [[#Doney--2009|Doney et al., 2009]] ), that is, ocean acidification caused by the absorption of some 20–30% of anthropogenic CO <sub>2</sub> from the atmosphere and its conversion to carbonic acid in seawater. The AR5 WGI assessed that the pH of ocean surface water has decreased by 0.1 since the beginning of the industrial era ( ''high confidence'' ), indicating approximately a 30% increase in acidity ( [[#IPCC--2013b|IPCC, 2013b]] ).

With a heat capacity about 1000 times greater than that of the atmosphere, Earth’s ocean stores the vast majority of energy retained by the planet. Ocean currents transport the stored heat around the globe and, over decades to centuries, from the surface to its greatest depths. The ocean’s thermal inertia moderates faster changes in radiative forcing on land and in the atmosphere, reaching full equilibrium with the atmosphere only after hundreds to thousands of years ( [[#Yang--2011|Yang and Zhu, 2011]] ). The earliest subsurface measurements in the open ocean date to the 1770s ( [[#Abraham--2013|Abraham et al., 2013]] ). From 1872–76, the research ship ''HMS Challenger'' measured global ocean temperature profiles at depths up to 1700 m along its cruise track. By 1900, research ships were deploying instruments such as Nansen bottles and mechanical bathythermographs (MBTs) to develop profiles of the upper 150 m in areas of interest to navies and commercial shipping ( [[#Abraham--2013|Abraham et al., 2013]] ). Starting in 1967, eXpendable BathyThermographs (XBTs) were deployed by scientific and commercial ships along repeated transects to measure temperature to 700 m ( [[#Goni--2019|Goni et al., 2019]] ). Ocean data collection expanded in the 1980s with the Tropical Ocean Global Experiment (TOGA; [[#Gould--2003|Gould, 2003]] ). Marine surface observations for the globe, assembled in the mid-1980s in the International Comprehensive Ocean-Atmosphere Data Set (ICOADS; [[#Woodruff--1987|Woodruff et al., 1987]] , 2005), were extended to 1662–2014 using newly recovered marine records and metadata ( [[#Woodruff--1998|Woodruff et al., 1998]] ; [[#Freeman--2017|Freeman et al., 2017]] ). The Argo submersible float network, developed in the early 2000s, provided the first systematic global measurements of the 700–2000 m layer. Comparing the ''HMS Challenger'' data to data from Argo submersible floats revealed global subsurface ocean warming on the centennial scale ( [[#Roemmich--2012|Roemmich et al., 2012]] ). The AR5 WGI assessed with ''high confidence'' that ocean warming accounted for more than 90% of the additional energy accumulated by the climate system between 1971 and 2010 ( [[#IPCC--2013b|IPCC, 2013b]] ). In comparison, warming of the atmosphere corresponds to only about 1% of the additional energy accumulated over that period ( [[#IPCC--2013a|IPCC, 2013a]] ). [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] summarizes the ocean heat content datasets used in AR6 ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.1|Section 2.3.3.1]] and Table 2.7).

Water expands as it warms. This thermal expansion, along with glacier mass loss, were the dominant contributors to GMSL rise during the 20th century ( ''high confidence'' ) according to AR5 ( [[#IPCC--2013b|IPCC, 2013b]] ). Sea level can be measured by averaging across tide gauges, some of which date to the 18th century. However, translating tide gauge readings into GMSL is challenging, since their spatial distribution is limited to continental coasts and islands, and their readings are relative to local coastal conditions that may shift vertically over time. Satellite radar altimetry, introduced operationally in the 1990s, complements the tide gauge record with geocentric measurements of GMSL at much greater spatial coverage ( [[#Katsaros--1991|Katsaros and Brown, 1991]] ; [[#Fu--1994|Fu et al., 1994]] ). The AR5 WGI assessed that GMSL rose by 0.19 [0.17 to 0.21] m over the period 1901–2010, and that the rate of sea level rise increased from 2.0 [1.7 to 2.3] mm yr <sup>–1</sup> in 1971–2010 to 3.2 [2.8 to 3.6] mm yr <sup>–1</sup> from 1993–2010. Warming of the ocean ''very likely'' contributed 0.8 [0.5 to 1.1] mm yr <sup>–1</sup> of sea level change during 1971–2010, with the majority of that contribution coming from the upper 700 m ( [[#IPCC--2013b|IPCC, 2013b]] ). [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.3|Section 2.3.3.3]] ) assesses current understanding of the extent and rate of sea level rise, past and present.

Satellite remote sensing alsorevolutionized studies of the cryosphere (Sections 2.3.2 and 9.3–9.5), particularly near the poles, where conditions make surface observations very difficult. Satellite mapping and measurement of snow cover began in 1966, with land and sea ice observations following in the mid-1970s. Yet prior to the Third Assessment Report, researchers lacked sufficient data to tell whether the Greenland and Antarctic ice sheets were shrinking or growing. Through a combination of satellite and airborne altimetry and gravity measurements, and improved knowledge of surface mass balance and perimeter fluxes, a consistent signal of ice loss for both ice sheets was established by the time of AR5 ( [[#Shepherd--2012|Shepherd et al., 2012]] ). After 2000, satellite radar interferometry revealed rapid changes in surface velocity at ice-sheet margins, often linked to reduction or loss of ice shelves ( [[#Scambos--2004|Scambos et al., 2004]] ; [[#Rignot--2006|Rignot and Kanagaratnam, 2006]] ). Whereas sea ice area and concentration have been continuously monitored since 1979 via microwave imagery, datasets for ice thickness emerged later from upward sonar profiling by submarines ( [[#Rothrock--1999|Rothrock et al., 1999]] ) and radar altimetry of sea ice freeboards ( [[#Laxon--2003|Laxon et al., 2003]] ). A recent reconstruction of Arctic sea ice extent back to 1850 found no historical precedent for the Arctic sea ice minima of the 21st century ( [[#Walsh--2017|Walsh et al., 2017]] ). Glacier length has been monitored for decades to centuries; internationally coordinated activities now compile worldwide glacier length and mass balance observations (World Glacier Monitoring Service, [[#Zemp--2015|Zemp et al., 2015]] ), global glacier outlines (Randolph Glacier Inventory, [[#Pfeffer--2014|Pfeffer et al., 2014]] ), and ice thickness data for about 1100 glaciers (Glacier Thickness Database (GlaThiDa), [[#Gärtner-Roer--2014|Gärtner-Roer et al., 2014]] ). In summary, these data allowed AR5 WGI to assess that over the last two decades, the Greenland and Antarctic ice sheets have been losing mass, glaciers have continued to shrink almost worldwide, and Arctic sea ice and Northern Hemisphere spring snow cover have continued to decrease in extent ( ''high confidence'' ) ( [[#IPCC--2013b|IPCC, 2013b]] ).

<div id="1.3.2" class="h2-container"></div>

<span id="lines-of-evidence-paleoclimate"></span>
=== 1.3.2 Lines of Evidence: Paleoclimate ===

<div id="h2-13-siblings" class="h2-siblings"></div>

With the gradual acceptance of evidence for geological ‘deep time’ in the 19th century came investigation of fossils, geological strata, and other evidence pointing to large shifts in the Earth’s climate, from ice ages to much warmer periods, across thousands to billions of years. This awareness set off a search for the causes of climatic changes. The long-term perspective provided by paleoclimate studies is essential to understanding the causes and consequences of natural variations in climate, as well as crucial context for recent anthropogenic climatic change. The reconstruction of climate variability and change over recent millennia began in the 1800s ( [[#Brückner--1890|Brückner, 1890]] ; [[#Stehr--2000|Stehr and von Storch, 2000]] ; [[#Coen--2018|Coen, 2018]] , 2020). In brief, paleoclimatology reveals the key role of CO <sub>2</sub> and other greenhouse gases in past climatic variability and change, the magnitude of recent climate change in comparison to past glacial–interglacial cycles, and the unusualness of recent climate change ( [[#1.2.1.2|Section 1.2.1.2]] and Cross-Chapter Box 2.1; [[#Tierney--2020a|Tierney et al., 2020a]] ). FAQ 1.3 provides a plain-language summary of its importance.

Paleoclimate studies reconstruct the evolution of Earth’s climate over hundreds to billions of years using pre-instrumental historical archives, indigenous knowledge, and natural archives left behind by geological, chemical and biological processes (Figure 1.7). Paleoclimatology covers a wide range of temporal scales, ranging from the human historical past (decades to millennia) to geological deep time (millions to billions of years). Paleoclimate reference periods are presented in Cross-Chapter Box 2.1.

Historical climatology aids near-term paleoclimate reconstructions using media such as diaries, almanacs and merchant accounts that describe climate-related events such as frosts, thaws, flowering dates, harvests, crop prices and droughts ( [[#Lamb--1965|Lamb, 1965]] , 1995; [[#Le%20Roy%20Ladurie--1967|Le Roy Ladurie, 1967]] ; [[#Brázdil--2005|Brázdil et al., 2005]] ). Meticulous records by Chinese scholars and government workers, for example, have permitted detailed reconstructions of China’s climate back to 1000 CE, and even beyond ( [[#Louie--2003|Louie and Liu, 2003]] ; [[#Ge--2008|Ge et al., 2008]] ). Climatic phenomena such as large-scale, regionally and temporally distributed warmer and cooler periods of the past 2000 years were reconstructed from European historical records ( [[#Lamb--1965|Lamb, 1965]] , 1995; [[#Le%20Roy%20Ladurie--1967|Le Roy Ladurie, 1967]] ; [[#Neukom--2019|Neukom et al., 2019]] ).

Indigenous and local knowledge has played an increasing role in historical climatology, especially in areas where instrumental observations are sparse. Peruvian fishermen named the periodic El Niño warm current in the Pacific, which was linked by later researchers to the Southern Oscillation ( [[#Cushman--2004|Cushman, 2004]] ). Inuit communities have contributed to climatic history and community-based monitoring across the Arctic ( [[#Riedlinger--2001|Riedlinger and Berkes, 2001]] ; [[#Gearheard--2010|Gearheard et al., 2010]] ). Indigenous Australian knowledge of climatic patterns has been offered as a complement to sparse observational records ( [[#Green--2010|Green et al., 2010]] ; [[#Head--2014|Head et al., 2014]] ), such as those of sea-level rise ( [[#Nunn--2016|Nunn and Reid, 2016]] ). Ongoing research seeks to conduct further dialogue, utilize indigenous and local knowledge as an independent line of evidence complementing scientific understanding, and analyse their utility for multiple purposes, especially adaptation ( [[#Laidler--2006|Laidler, 2006]] ; [[#Alexander--2011|Alexander et al., 2011]] ; [[#IPCC--2019c|IPCC, 2019c]] ). Indigenous and local knowledge is used most extensively by IPCC WGII.

Certain geological and biological materials preserve evidence of past climate changes. These ‘natural archives’ include corals, trees, glacier ice, speleothems (stalactites and stalagmites), loess deposits (dust sediments), fossil pollen, peat, lake sediment and marine sediment ( [[#Stuiver--1965|Stuiver, 1965]] ; [[#Eddy--1976|Eddy, 1976]] ; [[#Haug--2001|Haug et al., 2001]] ; [[#Wang--2001|Wang et al., 2001]] ; [[#Jones--2009|Jones et al., 2009]] ; [[#Bradley--2015|Bradley, 2015]] ). By the early 20th century, laboratory research had begun to use tree rings to reconstruct precipitation and the possible influence of sunspots on climatic change ( [[#Douglass--1914|Douglass, 1914]] , 1919, 1922). Radiocarbon dating, developed in the 1940s ( [[#Arnold--1949|Arnold and Libby, 1949]] ), allows accurate determination of the age of carbon-containing materials from the past 50,000 years; this dating technique ushered in an era of rapid progress in paleoclimate studies.

On longer time scales, tiny air bubbles trapped in polar ice sheets provide direct evidence of past atmospheric composition, including CO <sub>2</sub> levels ( [[#Petit--1999|Petit et al., 1999]] ), and the <sup>18</sup> O isotope in frozen precipitation serves as a proxy marker for temperature ( [[#Dansgaard--1954|Dansgaard, 1954]] ). Sulphate deposits in glacier ice and as ash layers within sediment record major volcanic eruptions, providing another mechanism for dating. The first paleoclimate reconstructions used an almost 100-kyr ice core taken at Camp Century, Greenland ( [[#Dansgaard--1969|Dansgaard et al., 1969]] ; [[#Langway%20Jr--2008|Langway Jr, 2008]] ). Subsequent cores from Antarctica extended this climatic record to 800 kyr ( [[#EPICA%20Community%20Members--2004|EPICA Community Members, 2004]] ; [[#Jouzel--2013|Jouzel, 2013]] ). Comparisons of air contained in these ice samples against measurements from the recent past enabled AR5 WGI to assess that atmospheric concentrations of CO <sub>2</sub> , methane (CH <sub>4</sub> ), and nitrous oxide (N <sub>2</sub> O) had all increased to levels unprecedented in at least the last 800,000 years (Figure 1.5; [[#IPCC--2013b|IPCC, 2013b]] ).

Global reconstructions of sea surface temperature were developed from material contained in deep-sea sediment cores (CLIMAP Project Members et al., 1976), providing the first quantitative constraints for model simulations of ice-age climates (e.g., [[#Rind--1985|Rind and Peteet, 1985]] ). Paleoclimate data and modelling showed that the Atlantic Ocean circulation has not been stable over glacial–interglacial time periods, and that many changes in ocean circulation are associated with abrupt transitions in climate in the North Atlantic region ( [[#Ruddiman--1981|Ruddiman and McIntyre, 1981]] ; [[#Broecker--1985|Broecker et al., 1985]] ; [[#Boyle--1987|Boyle and Keigwin, 1987]] ; [[#Manabe--1988|Manabe and Stouffer, 1988]] ).

By the early 20th century, cyclical changes in insolation due to the interacting periodicities of orbital eccentricity, axial tilt and axial precession had been hypothesized as a chief pacemaker of ice age–interglacial cycles on multi-millennial time scales ( [[#Milankovitch--1920|Milankovitch, 1920]] ). Paleoclimate information derived from marine sediment provides quantitative estimates of past temperature, ice volume and sea level over millions of years (Figure 1.5; [[#Emiliani--1955|Emiliani, 1955]] ; [[#Shackleton--1973|Shackleton and Opdyke, 1973]] ; [[#Siddall--2003|Siddall et al., 2003]] ; [[#Lisiecki--2005|Lisiecki and Raymo, 2005]] ; [[#Past%20Interglacials%20Working%20Group%20of%20PAGES--2016|Past Interglacials Working Group of PAGES, 2016]] ). These estimates have bolsteredthe orbital cycles hypothesis ( [[#Hays--1976|Hays et al., 1976]] ; [[#Berger--1977|Berger, 1977]] , 1978). However, paleoclimatology of multi-million to billion-year periods reveals that CH <sub>4</sub> , CO <sub>2</sub> , continental drift, silicate rock weathering and other factors played a greater role than orbital cycles in climate changes during ice-free ‘hothouse’ periods of Earth’s distant past ( [[#Frakes--1992|Frakes et al., 1992]] ; [[#Bowen--2015|Bowen et al., 2015]] ; [[#Zeebe--2016|Zeebe et al., 2016]] ).

The AR5 WGI ( [[#IPCC--2013b|IPCC, 2013b]] ) used paleoclimatic evidence to put recent warming and sea level rise in a multi-century perspective and assessed that 1983–2012 was ''likely'' to have been the warmest 30-year period of the last 1400 years in the Northern Hemisphere ( ''medium confidence'' ). The AR5 also assessed that the rate of sea level rise since the mid-19th century has been larger than the mean rate during the previous two millennia ( ''hi'' ''gh confidence'' ).

<div id="1.3.3" class="h2-container"></div>

<span id="lines-of-evidence-identifying-natural-and-human-drivers"></span>
=== 1.3.3 Lines of Evidence: Identifying Natural and Human Drivers ===

<div id="h2-14-siblings" class="h2-siblings"></div>

The climate is a globally interconnected system driven by solar energy. Scientists in the 19th century established the main physical principles governing Earth’s temperature. By 1822, the principle of radiative equilibrium (the balance between absorbed solar radiation and the energy Earth re-radiates into space) had been articulated, and the atmosphere’s role in retaining heat had been likened to a greenhouse ( [[#Fourier--1822|Fourier, 1822]] ). The primary explanations for natural climate change – greenhouse gases, orbital factors, solar irradiance, continental position, volcanic outgassing, silicate rock weathering, and the formation of coal and carbonate rock – were all identified by the late 19th century ( [[#Fleming--1998|Fleming, 1998]] ; [[#Weart--2008|Weart, 2008]] ).

The natural and anthropogenic factors responsible for climate change are known today as radiative ‘drivers’ or ‘forcers’. The net change in the energy budget at the top of the atmosphere, resulting from a change in one or more such drivers, is termed ‘radiative forcing’ (RF; Glossary) and measured in watts per square metre (W m <sup>–2</sup> ). The total radiative forcing over a given time interval (often since 1750) represents the sum of positive drivers (inducing warming) and negative ones (inducing cooling). Past IPCC reports have assessed scientific knowledge of these drivers, quantified their range for the period since 1750, and presented the current understanding of how they interact in the climate system. Like all previous IPCC reports, AR5 assessed that total radiative forcing has been positive at least since 1850–1900, leading to an uptake of energy by the climate system, and that the largest single contribution to total radiative forcing is the rising atmospheric concentration of CO <sub>2</sub> since 1750 (Chapter 7, and Cross-Chapter Box 1.2; [[#IPCC--2013a|IPCC, 2013a]] ).

Natural drivers include changes in solar irradiance, ocean currents, naturally occurring aerosols, and natural sources and sinks of radiatively active gases such as water vapour, CO <sub>2</sub> , CH <sub>4</sub> , and sulphur dioxide (SO <sub>2</sub> ). Detailed global measurements of surface-level solar irradiance were first conducted during the 1957–1958 International Geophysical Year ( [[#Landsberg--1961|Landsberg, 1961]] ), while top-of-atmosphere irradiance has been measured by satellites since 1959 ( [[#House--1986|House et al., 1986]] ). Measured changes in solar irradiance have been small and slightly negative since about 1980 ( [[#Matthes--2017|Matthes et al., 2017]] ). Water vapour is the most abundant radiatively active gas, accounting for about 75% of the terrestrial greenhouse effect, but because its residence time in the atmosphere averages just 8–10 days, its atmospheric concentration is largely governed by temperature ( [[#van%20der%20Ent--2017|van der Ent and Tuinenburg, 2017]] ; [[#Nieto--2019|Nieto and Gimeno, 2019]] ). As a result, non-condensing GHGs with much longer residence times serve as ‘control knobs’, regulating planetary temperature, with water vapour concentrations as a feedback effect ( [[#Lacis--2010|Lacis et al., 2010]] , 2013). The most important of these non-condensing gases is CO <sub>2</sub> (a positive driver), released naturally by volcanism at about 637 MtCO <sub>2</sub> yr <sup>–1</sup> in recent decades, or roughly 1.6% of the 37 GtCO <sub>2</sub> emitted by human activities in 2018 ( [[#Burton--2013|Burton et al., 2013]] ; [[#Le%20Quéré--2018|Le Quéré et al., 2018]] ). Absorption by the ocean and uptake by plants and soils are the primary natural CO <sub>2</sub> sinks on decadal to centennial time scales (Section 5.1.2 and Figure 5.3).

Aerosols (tiny airborne particles) interact with climate in numerous ways, some direct (e.g., reflecting solar radiation back into space) and others indirect (e.g., cloud droplet nucleation); specific effects may cause either positive or negative radiative forcing. Major volcanic eruptions inject SO <sub>2</sub> (a negative driver) into the stratosphere, creating aerosols that can cool the planet for years at a time by reflecting some incoming solar radiation. The history and climatic effects of volcanic activity have been traced through historical records, geological traces, and observations of major eruptions by aircraft, satellites and other instruments ( [[#Dörries--2006|Dörries, 2006]] ). The negative RF of major volcanic eruptions was considered in the First Assessment Report (FAR; [[#IPCC--1990a|IPCC, 1990a]] ). In subsequent assessments, the negative RF of smaller eruptions has also been considered (e.g., Cross-Chapter Box 4.1 in [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] of this Report; [[IPCC:Wg1:Chapter:Chapter-2#2.4.3|Section 2.4.3]] in [[#IPCC--1996|IPCC, 1996]] ). Dust and other natural aerosols have been studied since the 1880s (e.g., [[#Aitken--1889|Aitken, 1889]] ; [[#Ångström--1929|Ångström, 1929]] , 1964; [[#Twomey--1959|Twomey, 1959]] ), particularly in relation to their role in cloud nucleation, an aerosol indirect effect whose RF may be either positive or negative depending on such factors as cloud altitude, depth and albedo ( [[#Stevens--2009|Stevens and Feingold, 2009]] ; [[#Boucher--2013|Boucher et al., 2013]] ).

Anthropogenic drivers of climatic change were hypothesized as early as the 17th century, with a primary focus on forest clearing and agriculture ( [[#Grove--1995|Grove, 1995]] ; [[#Fleming--1998|Fleming, 1998]] ). In the 1890s, Arrhenius was first to calculate the effects of increased or decreased CO <sub>2</sub> concentrations on planetary temperature, and Högbom estimated that worldwide coal combustion of about 500 Mt yr <sup>–1</sup> had already completely offset the natural absorption of CO <sub>2</sub> silicate rock weathering ( [[#Högbom--1894|Högbom, 1894]] ; [[#Arrhenius--1896|Arrhenius, 1896]] ; [[#Berner--1995|Berner, 1995]] ; [[#Crawford--1997|Crawford, 1997]] ). As coal consumption reached 900 Mt yr <sup>–1</sup> only a decade later, Arrhenius wrote that anthropogenic CO <sub>2</sub> from fossil fuel combustion might eventually warm the planet ( [[#Arrhenius--1908|Arrhenius, 1908]] ). In 1938, analysing records from 147 stations around the globe, Callendar calculated atmospheric warming over land at 0.3°C–0.4°C from 1880–1935 and attributed about half of this warming to anthropogenic CO <sub>2</sub> (Figure 1.8; [[#Callendar--1938|Callendar, 1938]] ; [[#Fleming--2007|Fleming, 2007]] ; [[#Hawkins--2013|Hawkins and Jones, 2013]] ).

<div id="_idContainer033" class="•-Graphic-insert"></div>

[[File:f3b251d27a6a58f6882493e7cca85c31 IPCC_AR6_WGI_Figure_1_8.png]]

'''Figure 1.8 |''' '''G.S. Callendar’s estimates of global land temperature variations and their possible causes.''' '''(a)''' The original figure from [[#Callendar--1938|Callendar (1938)]] , using measurements from 147 surface stations for 1880–1935, showing: '''(top)''' ten-year moving departures from the mean of 1901–1930 (°C), with the dashed line representing his estimate of the ‘CO <sub>2</sub> effect’ on temperature rise, and '''(bottom)''' annual departures from the 1901–1930 mean (°C). '''(b)''' Comparing the estimates of global land (60°S–60°N) temperatures tabulated in Callendar (1938, 1961) with a modern reconstruction (CRUTEM5, [[#Osborn--2021|Osborn et al., 2021]] ) for the same period, following [[#Hawkins--2013|Hawkins and Jones (2013)]] . Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).

Studiesof radiocarbon ( <sup>14</sup> C) in the 1950s established that increasing atmospheric CO <sub>2</sub> concentrations were due to fossil fuel combustion. Since all the <sup>14</sup> C once contained in fossil fuels long ago decayed into non-radioactive <sup>12</sup> C, the CO <sub>2</sub> produced by their combustion reduces the overall concentration of atmospheric <sup>14</sup> C ( [[#Suess--1955|Suess, 1955]] ). Related work demonstrated that while the ocean was absorbing around 30% of anthropogenic CO <sub>2</sub> , these emissions were also accumulating in the atmosphere and biosphere ( [[#1.3.1|Section 1.3.1]] and Chapter 5, Section 5.2.1.5). Further work later established that atmospheric oxygen levels were decreasing in inverse relation to the anthropogenic CO <sub>2</sub> increase, because combustion of carbon consumes oxygen to produce CO <sub>2</sub> (Chapters 2 and 6; [[#Keeling--1992|Keeling and Shertz, 1992]] ; [[#IPCC--2013a|IPCC, 2013a]] ). [[#Revelle--1957|Revelle and Suess (1957)]] famously described fossil fuel emissions as a ‘large scale geophysical experiment’, in which ‘within a few centuries we are returning to the atmosphere and ocean the concentrated organic carbon stored in sedimentary rocks over hundreds of millions of years.’ The 1960s saw increasing attention to other radiatively active gases, especially ozone (O <sub>3</sub> ; [[#Manabe--1961|Manabe and Möller, 1961]] ; [[#Plass--1961|Plass, 1961]] ). Methane and nitrous oxide (N <sub>2</sub> O) were not considered systematically until the 1970s, when anthropogenic increases in those gases were first noted ( [[#Wang--1976|Wang et al., 1976]] ). In the 1970s and 1980s, scientists established that synthetic halocarbons (see Glossary), including widely used refrigerants and propellants, were extremely potent greenhouse gases (Sections 2.2.4.3 and 6.2.2.9; [[#Ramanathan--1975|Ramanathan, 1975]] ). When these chemicals were also found to be depleting the stratospheric ozone layer, they were stringently and successfully regulated on a global basis by the 1987 Montreal Protocol on the Ozone Layer and successor agreements ( [[#Parson--2003|Parson, 2003]] ).

Radioactive fallout from atmospheric nuclear weapons testing (1940s–1950s) and urban smog (1950s–1960s) first provoked widespread attention to anthropogenic aerosols and ozone in the troposphere ( [[#Edwards--2012|Edwards, 2012]] ). Theory, measurement and modelling of these substances developed steadily from the 1950s ( [[#Hidy--2019|Hidy, 2019]] ). However, the radiative effects of anthropogenic aerosols did not receive sustained study until around 1970 ( [[#Bryson--1970|Bryson and Wendland, 1970]] ; [[#Rasool--1971|Rasool and Schneider, 1971]] ), when their potential as cooling agents was recognized ( [[#Peterson--2008|Peterson et al., 2008]] ). The US Climatic Impact Assessment Program (CIAP) found that proposed fleets of supersonic aircraft, flying in the stratosphere, might cause substantial aerosol cooling and depletion of the ozone layer, stimulating efforts to understand and model stratospheric circulation, atmospheric chemistry, and aerosol radiative effects ( [[#Mormino--1975|Mormino et al., 1975]] ; [[#Toon--1976|Toon and Pollack, 1976]] ). Since the 1980s, aerosols have increasingly been integrated into comprehensive modelling studies of transient climate evolution and anthropogenic influences, through treatment of volcanic forcing, links to global dimming and cloud brightening, and their influence on cloud nucleation and other properties (e.g., thickness, lifetime and extent), and precipitation (e.g., [[#Hansen--1981|Hansen et al., 1981]] ; [[#Charlson--1987|Charlson et al., 1987]] , 1992; [[#Albrecht--1989|Albrecht, 1989]] ; [[#Twomey--1991|Twomey, 1991]] ).

The FAR (1990) focused attention on human emissions of CO <sub>2</sub> , CH <sub>4</sub> , tropospheric O <sub>3</sub> , chlorofluorocarbons (CFCs), and N <sub>2</sub> O. Of these, at that time only the emissions of CO <sub>2</sub> and CFCs were well measured, with methane sources known only ‘semi-quantitatively’ ( [[#IPCC--1990a|IPCC, 1990a]] ). The FAR assessed that some other trace gases, especially CFCs, have global warming potentials hundreds to thousands of times greater than CO <sub>2</sub> and CH <sub>4</sub> , but are emitted in much smaller amounts. As a result, CO <sub>2</sub> remains by far the most important positive anthropogenic driver, with CH <sub>4</sub> next most significant ( [[#1.6.3|Section 1.6.3]] ); anthropogenic methane stems from such sources as fossil fuel extraction, natural gas pipeline leakage, agriculture and landfills. In 2001, increased greenhouse forcing attributable to CO <sub>2</sub> , CH <sub>4</sub> , O <sub>3</sub> , CFC-11 and CFC-12 was detected by comparing satellite measurements of outgoing longwave radiation measurements taken in 1970 and in 1997 ( [[#Harries--2001|Harries et al., 2001]] ). AR5 assessed that the 40% increase in atmospheric CO <sub>2</sub> contributed most to positive RF since 1750. Together, changes in atmospheric concentrations of CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O and halocarbons from 1750–2011 were assessed to contribute a positive RF of 2.83 [2.26 to 3.40] W m <sup>–2</sup> ( [[#IPCC--2013b|IPCC, 2013b]] ).

All IPCC reports have assessed the total RF as positive when considering all sources. However, due to the considerable variability of both natural and anthropogenic aerosol loads, FAR characterized total aerosol RF as ‘highly uncertain’ and was unable even to determine its sign (positive or negative). Major advances in quantification of aerosol loads and their effects have taken place since then, and IPCC reports since 1992 have consistently assessed total forcing by anthropogenic aerosols as negative ( [[#IPCC--1992|IPCC, 1992]] , 1995a, 1996). However, due to their complexity and the difficulty of obtaining precise measurements, aerosol effects have been consistently assessed as the largest single source of uncertainty in estimating total RF ( [[#Stevens--2009|Stevens and Feingold, 2009]] ; [[#IPCC--2013a|IPCC, 2013a]] ). Overall, AR5 assessed that total aerosol effects, including cloud adjustments, resulted in a negative RF of –0.9 [–1.9 to −0.1] W m <sup>−2</sup> ( ''medium confidence'' ), offsetting a substantial portion of the positive RF resulting from the increase in GHGs ( ''high confidence'' ) ( [[#IPCC--2013b|IPCC, 2013b]] ). [[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] provides an updated assessment of the total and per-component RF for the WGI contribution to AR6.

<div id="1.3.4" class="h2-container"></div>

<span id="lines-of-evidence-understanding-and-attributing-climate-change"></span>
=== 1.3.4 Lines of Evidence: Understanding and Attributing Climate Change ===

<div id="h2-15-siblings" class="h2-siblings"></div>

Understanding the global climate system requires both theoretical understanding and empirical measurement of the major forces and factors that govern the transport of energy and mass (air, water and water vapour) around the globe; the chemical and physical properties of the atmosphere, ocean, cryosphere and land surfaces; and the biological and physical dynamics of natural ecosystems, as well as the numerous feedbacks (both positive and negative) among these processes. Attributing climatic changes or extreme weather events to human activity (Cross-Working Group Box: Attribution) also requires an understanding of the many ways that human activities may affect the climate, along with statistical and other techniques for separating the ‘signal’ of anthropogenic climate change from the ‘noise’ of natural climate variability ( [[#1.4.2|Section 1.4.2]] ). This inter- and trans-disciplinary effort requires contributions from many sciences.

Due to the complexity of many interacting processes, ranging in scale from the molecular to the global, and occurring on time scales from seconds to millennia, attribution makes extensive use of conceptual, mathematical, and computer simulation models. Modelling allows scientists to combine a vast range of theoretical and empirical understanding from physics, chemistry and other natural sciences, producing estimates of their joint consequences as simulations of past, present or future states and trends ( [[#Nebeker--1995|Nebeker, 1995]] ; [[#Edwards--2010|Edwards, 2010]] , [[#Edwards--2011|2011]] ).

In addition to radiative transfer (discussed above in [[#1.3.3|Section 1.3.3]] ), forces and factors such as thermodynamics (energy conversions), gravity, surface friction, and the Earth’s rotation govern the planetary-scale movements or ‘circulation’ of air and water in the climate system. The scientific theory of climate began with [[#Halley--1686|Halley (1686)]] , who hypothesized vertical atmospheric circulatory cells driven by solar heating, and [[#Hadley--1735|Hadley (1735)]] , who showed how the Earth’s rotation affects that circulation. [[#Ferrel--1856|Ferrel (1856)]] added the Coriolis force to existing theory, explaining the major structures of the global atmospheric circulation. In aggregate, prevailing winds and ocean currents move energy poleward from the equatorial regions where the majority of incoming solar radiation is received.

Climate models provide the ability to simulate these complex circulatory processes, and to improve the physical theory of climate by testing different mathematical formulations of those processes. Since controlled experiments at planetary scale are impossible, climate simulations provide one important way to explore the differential effects and interactions of variables such as solar irradiance, aerosols and GHGs. To assess their quality, models or components of models may be compared with observations. For this reason, they can be used to attribute observed climatic effects to different natural and human drivers ( [[#Hegerl--2011|Hegerl et al., 2011]] ). As early as [[#Arrhenius--1896|Arrhenius (1896)]] , simple mathematical models were used to calculate the effects of doubling atmospheric carbon dioxide over pre-industrial concentrations (approximately 550 ppm vs approximately 275 ppm respectively). In the early 20th century Bjerknes formulated the Navier–Stokes equations of fluid dynamics for motion of the atmosphere ( [[#Bjerknes--1906|Bjerknes, 1906]] ; [[#Bjerknes--1910|Bjerknes et al., 1910]] ), and [[#Richardson--1922|Richardson (1922)]] developed a system for numerical weather prediction based on these equations. When electronic computers became available in the late 1940s, the methods of Bjerknes and Richardson were successfully applied to weather forecasting ( [[#Charney--1950|Charney et al., 1950]] ; [[#Nebeker--1995|Nebeker, 1995]] ; [[#Harper--2008|Harper, 2008]] ).

In the 1960s similar approaches to modelling the weather were used to model the climate, but with much longer runs than daily forecasting ( [[#Smagorinsky--1965|Smagorinsky et al., 1965]] ; [[#Manabe--1967|Manabe and Wetherald, 1967]] ). Simpler statistical and one- and two-dimensional modelling approaches continued in tandem with the more complex general circulation models (GCMs; [[#Manabe--1967|Manabe and Wetherald, 1967]] ; [[#Budyko--1969|Budyko, 1969]] ; [[#Sellers--1969|Sellers, 1969]] ). The first coupled atmosphere–ocean model (AOGCM) with realistic topography appeared in 1975 ( [[#Bryan--1975|Bryan et al., 1975]] ; [[#Manabe--1975|Manabe et al., 1975]] ). Rapid increases in computer power enabled higher resolutions, longer model simulations, and the inclusion of additional physical processes in GCMs, such as aerosols, atmospheric chemistry, sea ice, and snow.

In the 1990s, AOGCMs were state of the art. By the 2010s, Earth system models (ESMs, also known as coupled carbon-cycle climate models) incorporated land surface, vegetation, the carbon cycle, and other elements of the climate system. Since the 1990s, some major modelling centres have deployed ‘unified’ models for both weather prediction and climate modelling, with the goal of a seamless modelling approach that uses the same dynamics, physics and parameterisations at multiple scales of time and space (Section 10.1.2; [[#Cullen--1993|Cullen, 1993]] ; [[#Brown--2012|Brown et al., 2012]] ; [[#NRC--2012|NRC, 2012]] ; [[#WMO--2015|WMO, 2015]] ). Because weather forecast models make short-term predictions that can be frequently verified, and improved models are introduced and tested iteratively on cycles as short as 18 months, this approach allows major portions of the climate model to be evaluated as a weather model and more frequently improved. However, all climate models exhibit biases of different degrees and types, and the practice of ‘tuning’ parameter values in models to make their outputs match variables such as historical warming trajectories has generated concern throughout their history ( [[#1.5.3.2|Section 1.5.3.2]] ; [[#Randall--1997|Randall and Wielicki, 1997]] ; [[#Edwards--2010|Edwards, 2010]] ; [[#Hourdin--2017|Hourdin et al., 2017]] ). Overall, AR5 WGI assessed that climate models had improved since previous reports ( [[#IPCC--2013b|IPCC, 2013b]] ).

Since climate models vary along many dimensions, such as grid type, resolution, and parameterizations, comparing their results requires special techniques. To address this problem, the climate modelling community developed increasingly sophisticated model intercomparison projects (MIPs; [[#Gates--1999|Gates et al., 1999]] ; [[#Covey--2003|Covey et al., 2003]] ). MIPs prescribe standardized experiment designs, time periods, output variables or observational reference data to facilitate direct comparison of model results. This aids in diagnosing the reasons for biases and other differences among models, and furthers process understanding ( [[#1.5|Section 1.5]] ). Both the CMIP3 and CMIP5 model intercomparison projects included experiments testing the ability of models to reproduce 20th-century global surface temperature trends both with and without anthropogenic forcings. Although some individual model runs failed to achieve this ( [[#Hourdin--2017|Hourdin et al., 2017]] ), the mean trends of multi-model ensembles did so successfully ( [[#Meehl--2007a|Meehl et al., 2007a]] ; [[#Taylor--2012|Taylor et al., 2012]] ). When only natural forcings were included (creating the equivalent of a ‘control Earth’ without human influence), similar multi-model ensembles could not reproduce the observed post-1970 warming at either global or regional scales ( [[#Edwards--2010|Edwards, 2010]] ; [[#Jones--2013|Jones et al., 2013]] ). The GCMs and ESMs compared in CMIP6 (used in this Report) offer more explicit documentation and evaluation of tuning procedures ( [[#1.5|Section 1.5]] ; [[#Schmidt--2017|Schmidt et al., 2017]] ; [[#Burrows--2018|Burrows et al., 2018]] ; [[#Mauritsen--2020|Mauritsen and Roeckner, 2020]] ).

The FAR (IPCC, 1990a) concluded that while both theory and models suggested that anthropogenic warming was already well underway, its signal could not yet be detected in observational data against the ‘noise’ of natural variability (see also [[#1.4.2|Section 1.4.2]] ; and [[#Barnett--1987|Barnett and Schlesinger, 1987]] ). Since then, increased warming and progressively more conclusive attribution studies have identified human activities as the ‘dominant cause of the observed warming since the mid-20th century’ ( [[#IPCC--2013b|IPCC, 2013b]] ). ‘Fingerprint’ studies seek to detect specific observed changes – expected from theoretical understanding and model results – that could not be explained by natural drivers alone, and to attribute statistically the proportion of such changes that is due to human influence. These include global-scale surface warming, nights warming faster than days, tropospheric warming and stratospheric cooling, a rising tropopause, increasing ocean heat content, changed global patterns of precipitation and sea level air pressure, increasing downward longwave radiation, and decreasing upward longwave radiation ( [[#Hasselmann--1979|Hasselmann, 1979]] ; [[#Karoly--1994|Karoly et al., 1994]] ; [[#Schneider--1994|Schneider, 1994]] ; [[#Santer--1995|Santer et al., 1995]] , [[#Santer--2013|2013]] ; [[#Hegerl--1996|Hegerl et al., 1996]] , [[#Hegerl--1997|1997]] ; [[#Gillett--2003|Gillett et al., 2003]] ; [[#Santer--2003|Santer, 2003]] ; [[#Zhang--2007|Zhang et al., 2007]] ; [[#Stott--2010|Stott et al., 2010]] ; [[#Davy--2017|Davy et al., 2017]] ; [[#Mann--2017|Mann et al., 2017]] ). The Cross-Working Group Box on Attribution outlines attribution methods and uses from across AR6, now including event attribution (specifying the influence of climate change on individual extreme events such as floods, or on the frequency of classes of events such as tropical cyclones). Overall, the evidence for human influence has grown substantially over time and from each IPCC report to the next.

A key indicator of climate understanding is whether theoretical climate system budgets or ‘inventories’, such as the balance of incoming and outgoing energy at the surface and at the top of the atmosphere, can be quantified and balanced observationally. The global energy budget, for example, includes energy retained in the atmosphere, upper ocean, deep ocean, ice, and land surface. [[#Church--2013|Church et al. (2013)]] assessed in AR5 with ''high confidence'' that independent estimates of effective radiative forcing (ERF), observed heat storage, and surface warming combined to give an energy budget for the Earth that is consistent with the AR5 WGI assessed ''likely'' range of equilibrium climate sensitivity (ECS) [1.5°C to 4.5°C] to within estimated uncertainties (on ECS, see ( [[#1.3.5|Section 1.3.5]] ; [[#IPCC--2013a|IPCC, 2013a]] ). Similarly, over the period 1993–2010, when observations of all sea level components were available, AR5 WGI assessed the observed global mean sea level rise to be consistent with the sum of the observed contributions from ocean thermal expansion (due to warming) combined with changes in glaciers, the Antarctic and Greenland ice sheets, and land-water storage ( ''high confidence'' ). Verification that the terms of these budgets balance over recent decades provides strong evidence for our understanding of anthropogenic climate change (Cross-Chapter Box 9.1).

The Appendix to ( [https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-1 Chapter 1] (Appendix 1A) lists the key detection and attribution statements in the Summaries for Policymakers of WGI reports since 1990. The evolution of these statements over time reflects the improvement of scientific understanding and the corresponding decrease in uncertainties regarding human influence. The Second Assessment Report (SAR) stated that ‘the balance of evidence suggests a discernible human influence on global climate’ ( [[#IPCC--1995b|IPCC, 1995b]] ). Five years later, the Third Assessment Report (TAR) concluded that ‘there is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities’ ( [[#IPCC--2001b|IPCC, 2001b]] ). The AR4 further strengthened previous statements, concluding that ‘most of the observed increase in global average temperatures since the mid-20th century is ''very likely'' due to the observed increase in anthropogenic greenhouse gas concentrations’ ( [[#IPCC--2007b|IPCC, 2007b]] ). The AR5 assessed that a human contribution had been detected in: changes in warming of the atmosphere and ocean; changes in the global water cycle; reductions in snow and ice; global mean sea level rise; and changes in some climate extremes. The AR5 concluded that ‘it is ''extremely likely'' that human influence has been the dominant cause of the observed warming since the mid-20th century’ ( [[#IPCC--2013b|IPCC, 2013b]] ).

<div id="1.3.5" class="h2-container"></div>

<span id="projections-of-future-climate-change"></span>
=== 1.3.5 Projections of Future Climate Change ===

<div id="h2-16-siblings" class="h2-siblings"></div>

It was recognized in IPCC AR5 that information about the near term was increasingly relevant for adaptation decisions. In response, AR5 WGI made a specific assessment for how global surface temperature was projected to evolve over the next two decades, concluding that the change for the period 2016–2035 relative to 1986–2005 will ''likely'' be in the range of 0.3°C–0.7°C ( ''medium confidence'' ), assuming no major volcanic eruptions or secular changes in total solar irradiance ( [[#IPCC--2013b|IPCC, 2013b]] ). The AR5 was also the first IPCC assessment report to assess ‘decadal predictions’ of the climate, where the observed state of the climate system was used as a starting point for forecasts several years ahead. The AR6 examines updates to these decadal predictions ( [[IPCC:Wg1:Chapter:Chapter-4#4.4.1|Section 4.4.1]] ).

The assessments and predictions for the near-term evolution of global climate features are largely independent of future CO <sub>2</sub> emissions pathways. However, AR5 WGI assessed that limiting climate change in the long-term future will require substantial and sustained reductions of GHG emissions ( [[#IPCC--2013b|IPCC, 2013b]] ). This assessment results from decades of research on understanding the climate system and its perturbations, and projecting climate change into the future. Each IPCC report has considered a range of emissions scenarios, typically including a scenario in which societies choose to continue on their present course, as well as several others reflecting socio-economic and policy responses that may limit emissions and/or increase the rate of CO <sub>2</sub> removal from the atmosphere. Climate models are used to project the outcomes of each scenario. However, future human climate influence cannot be precisely predicted because GHG and aerosol emissions, land use, energy use and other human activities may change in numerous ways. Common emissions scenarios used in the WGI contribution to AR6 are detailed in [[#1.6|Section 1.6]] .

Based on model results and steadily increasing CO <sub>2</sub> concentrations ( [[#Bolin--1970|Bolin and Bischof, 1970]] ; [[#SMIC--1971|SMIC, 1971]] ; [[#Meadows--1972|Meadows et al., 1972]] ), concerns about future ‘risk of effects on climate’ were addressed in Recommendation 70 of the Stockholm Action Plan, resulting from the 1972 United Nations Conference on the Human Environment ( [[#UN--1973|UN, 1973]] ). Numerous other scientific studies soon amplified these concerns (summarized in [[#Schneider--1975|Schneider (1975)]] and [[#Williams--1978|Williams (1978)]] ; see also Nordhaus (1975, 1977). In 1979, a US National Research Council (NRC) group led by Jule Charney reported on the ‘best present understanding of the carbon dioxide/climate issue for the benefit of policymakers’, initiating an era of regular and repeated large-scale assessments of climate science findings.

The 1979 Charney NRC report estimated ECS at 3°C, stating the range as 2°C–4.5°C, based on ‘consistent and mutually supporting’ model results and expert judgment ( [[#NRC--1979|NRC, 1979]] ). ECS is defined in IPCC assessments as the global surface air temperature (GSAT) response to CO <sub>2</sub> doubling (from pre-industrial levels) after the climate has reached equilibrium (stable energy balance between the atmosphere and ocean). Another quantity, transient climate response (TCR), was later introduced as the change in GSAT, averaged over a 20-year period, at the time of CO <sub>2</sub> doubling in a scenario of concentration increasing at 1% per year. Calculating ECS from historical or paleoclimate temperature records, in combination with energy budget models, has produced estimates both lower and higher than those calculated using GCMs and ESMs; in this Report, these are assessed in Chapter 7, Section 7.5.2.

ECS is typically characterized as most relevant on centennial time scales, while TCR was long seen as a more appropriate measure of the 50–100-year response to gradually increasing CO <sub>2</sub> . However, recent studies have raised new questions about how accurately both quantities are estimated by GCMs and ESMs ( [[#Grose--2018|Grose et al., 2018]] ; [[#Meehl--2020|Meehl et al., 2020]] ; [[#Sherwood--2020|Sherwood et al., 2020]] ). Further, as climate models evolved to include a full-depth ocean, the time scale for reaching full equilibrium became longer and new methods to estimate ECS had to be developed ( [[#Gregory--2004|Gregory et al., 2004]] ; [[#Meehl--2020|Meehl et al., 2020]] ; [[#Meinshausen--2020|Meinshausen et al., 2020]] ). Because of these considerations, as well as new estimates from observation-based, paleoclimate, and emergent-constraints studies ( [[#Sherwood--2020|Sherwood et al., 2020]] ), the AR6 definition of ECS has changed from previous reports; it now includes all feedbacks except those associated with ice sheets. Accordingly, unlike previous reports, the AR6 assessments of ECS and TCR are not based primarily on GCM and ESM model results (see Section 7.5.5 and Box. 7.1 for a full discussion).

Today, other sensitivity terms are sometimes used, such as ‘transient climate response to emissions’ (TCRE, defined as the ratio of warming to cumulative CO <sub>2</sub> emissions in a CO <sub>2</sub> -only simulation) and ‘Earth system sensitivity’ (ESS), which includes multi-century Earth system feedbacks such as changes in ice sheets.

Table 1.2 shows estimates of ECS and TCR for major climate science assessments since 1979. The table shows that despite some variation in the range of GCM and (for the later assessments) ESM results, expert assessment of ECS changed little between 1979 and the present Report. Based on multiple lines of evidence, AR6 has narrowed the ''likely'' range of ECS to 2.5°C–4.0°C (Chapter 7, Section 7.5.5).

'''Table 1.2 |'''

'''Estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) from successive major scientific assessments since 1979.''' No likelihood statements are available for reports prior to 2001 because those reports did not use the IPCC calibrated uncertainty language. The assessed range of ECS differs from the range derived from general circulation model (GCM) and Earth system model (ESM) results because assessments take into account other evidence, other types of models, and expert judgment. The AR6 definition of ECS differs from previous reports, now including all long-term feedbacks except those associated with ice sheets. AR6 estimates of ECS are derived primarily from process understanding, historical observations and emergent constraints, informed by (but not based on) GCM and ESM model results. CMIP6 is the 6th phase of the Coupled Model Intercomparison Project (Section 7.5.5 and Box 7.1).
[[File:c0dbc0614a0a77c3833f127fc722582e IPCC_AR6_WGI_Chapter_1_Table_1_2.png]]
The AR5 WGI assessed that there is a close relationship of cumulative total emissions of CO <sub>2</sub> and GMST response that is approximately linear ( [[#IPCC--2013b|IPCC, 2013b]] ). This finding implies that continued emissions of CO <sub>2</sub> will cause further warming and changes in all components of the climate system, independent of any specific scenario or pathway. Scenario-based climate projections using the Representative Concentration Pathways (RCPs) assessed in AR5 WGI result in continued warming over the 21st <sup></sup> century in all scenarios except a strong climate change mitigation scenario (RCP2.6). Similarly, under all RCP scenarios, AR5 assessed that the rate of sea level rise over the 21st century will ''very likely'' exceed that observed during 1971–2010 due to increased ocean warming and increased loss of mass from glaciers and ice sheets. Further increases in atmospheric CO <sub>2</sub> will also lead to further uptake of carbon by the ocean, which will increase ocean acidification. By the mid-21st century the magnitudes of the projected changes are substantially affected by the choice of scenario. The set of scenarios used in climate change projections assessed as part of AR6 is discussed in [[#1.6|Section 1.6]] .

From the close link between cumulative emissions and warming it follows that any given level of global warming is associated with a total budget of GHG emissions, especially CO <sub>2</sub> as it is the largest long-lived contributor to radiative forcing ( [[#Allen--2009|Allen et al., 2009]] ; [[#Collins--2013|Collins et al., 2013]] ; [[#Rogelj--2019|Rogelj et al., 2019]] ). Higher emissions in earlier decades imply lower emissions later on to stay within the Earth’s carbon budget. Stabilizing the anthropogenic influence on global surface temperature thus requires that CO <sub>2</sub> emissions and removals reach net zero once the remaining carbon budget is exhausted (Cross-Chapter Box 1.4).

Past, present and future emissions of CO <sub>2</sub> therefore commit the world to substantial multi-century climate change, and many aspects of climate change would persist for centuries even if emissions of CO <sub>2</sub> were stopped immediately ( [[#IPCC--2013b|IPCC, 2013b]] ). According to AR5, a large fraction of this change is essentially irreversible on a multi-century to millennial time scale, barring large net removal (‘negative emissions’) of CO <sub>2</sub> from the atmosphere over a sustained period through as yet unavailable technological means (Chapters 4 and 5l; [[#IPCC--2013a|IPCC, 2013a]] , 2018). However, significant reductions of warming due to short-lived climate forcers (SLCFs) could reduce the level at which temperature stabilizes once CO <sub>2</sub> emissions reach net zero, and also reduce the long-term global warming commitment by reducing radiative forcing from SLCFs (Chapter 5).

In summary, major lines of evidence – observations, paleoclimate, theoretical understanding and natural and human drivers – have been studied and developed for over 150 years. Methods for projecting climate futures have matured since the 1950s and attribution studies since the 1980s. We conclude that understanding of the principal features of the climate system is robust and well established.

<div id="1.3.6" class="h2-container"></div>

<span id="how-do-previous-climate-projections-compare-with-subsequent-observations"></span>
=== 1.3.6 How do Previous Climate Projections Compare with Subsequent Observations? ===

<div id="h2-17-siblings" class="h2-siblings"></div>

Many different sets of climate projections have been produced over the past several decades, so it is valuable to assess how well those projections have compared against subsequent observations. Consistent findings build confidence in the process of making projections for the future. For example, [[#Stouffer--2017|Stouffer and Manabe (2017)]] compared projections made in the early 1990s with subsequent observations. They found that the projected surface pattern of warming, and the vertical structure of temperature change in both the atmosphere and ocean, were realistic. Rahmstorf et al. (2007, 2012) examined projections of global surface temperature and GMSL assessed by TAR and AR4 and found that the global surface temperature projections were in good agreement with the subsequent observations, but that sea level projections were underestimates compared to subsequent observations. The AR5 WGI also examined earlier IPCC assessment reports to evaluate their projections of how global surface temperature and GMSL would change ( [[#Cubasch--2013|Cubasch et al., 2013]] ) with similar conclusions.

Although these studies generally showed good agreement between past projections and subsequent observations, this type of analysis is complicated because the scenarios of future radiative forcing used in earlier projections do not precisely match the actual radiative forcings that subsequently occurred. Mismatches between the projections and subsequent observations could be due to incorrectly projected radiative forcings (e.g., aerosol emissions, GHG concentrations or volcanic eruptions that were not included), an incorrectly modelled response to those forcings, or both. Alternatively, agreement between projections and observations could be fortuitous due to a compensating balance of errors, for example, too low climate sensitivity but too strong radiative forcings.

One approach to partially correct for mismatches between the forcings used in the projections and the forcings that actually occurred is described by [[#Hausfather--2020|Hausfather et al. (2020)]] . Model projections of global surface temperature and estimated radiative forcings were taken from several historical studies, along with the baseline ‘no-policy’ scenarios from the first four IPCC assessment reports. These model projections of temperature and radiative forcing are then compared to (i) the observed change in temperature through time over the projection period, and (ii) the observed change in temperature relative to the observationally estimated radiative forcing over the projection period (Figure 1.9; data from [[#Hausfather--2020|Hausfather et al., 2020]] ).

<div id="_idContainer035" class="•-Graphic-insert"></div>

[[File:5414ad1d54dff94367e1c8c16a324ba8 IPCC_AR6_WGI_Figure_1_9.png]]

'''Figure 1.9 |''' '''Assessing past projections of global temperature change.''' '''(Top)''' Projected temperature change post-publication on a temperature vs time (1970–2020) and '''(bottom)''' temperature vs radiative forcing (1970–2017) basis for a selection of prominent climate model projections (taken from [[#Hausfather--2020|Hausfather et al., 2020]] ). Model projections (using global surface air temperature, GSAT) are compared to temperature observations (using global mean surface temperature, GMST) from HadCRUT5 (black) and anthropogenic forcings (through 2017) from [[#Dessler--2018|Dessler and Forster (2018)]] , and have a baseline generated from the first five years of the projection period. Projections shown are: [[#Manabe--1970|Manabe (1970)]] , [[#Rasool--1971|Rasool and Schneider (1971)]] , [[#Broecker--1975|Broecker (1975)]] , [[#Nordhaus--1977|Nordhaus (1977)]] , Hansen et al. (1981, H81), Hansen et al. (1988, H88), [[#Manabe--1993|Manabe and Stouffer (1993)]] , along with the Energy Balance Model (EBM) projections from FAR, SAR and TAR, and the multi-model mean projection using CMIP3 simulations of the Special Report on Emissions Scenarios (SRES) A1B scenario from AR4. H81 and H88 show most expected scenarios 1 and B, respectively. See [[#Hausfather--2020|Hausfather et al. (2020)]] for more details of the projections. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).

Although this approach has limitations when the modelled forcings differ greatly from the forcings subsequently experienced, they were generally able to project actual future global warming when the mismatches between forecast and observed radiative forcings are accounted for. For example, Scenario B presented in [[#Hansen--1988|Hansen et al. (1988)]] projected around 50% more warming than has been observed during the 1988–2017 period, but this is largely because it overestimated subsequent radiative forcings. Similarly, while FAR ( [[#IPCC--1990a|IPCC, 1990a]] ) projected a higher rate of global surface temperature warming than has been observed, this is largely because it overestimated future GHG concentrations: FAR’s projected increase in total anthropogenic forcing between 1990 and 2017 was 1.6 W m <sup>–2</sup> , while the observational estimate of actual forcing during that period is 1.1 W m <sup>–2</sup> ( [[#Dessler--2018|Dessler and Forster, 2018]] ). Under these actual forcings, the change in temperature in FAR aligns with observations ( [[#Hausfather--2020|Hausfather et al., 2020]] ).

Inaddition to global surface temperature, past regional projections can be evaluated. For example, FAR ( [[#IPCC--1990a|IPCC, 1990a]] ) presented a series of temperature projections for 1990–2030 for several regions around the world. Regional projections were given for the best estimate of 1.8°C of global warming by 2030, compared to a baseline of 1850–1900, and were assigned ''low confidence'' . The FAR also suggested that regional temperature changes should be scaled by –30% to +50% to account for the uncertainty in projected global warming.

The regional projections presented in FAR are compared to the observed temperature change in the period since 1990 (Figure 1.10), following Groseet al. (2017). Subsequent observed temperature change has tracked within the FAR projected range for the best estimate of regional warming in the Sahel, South Asia and southern Europe. Temperature change has tracked at or below this range for the central North America and Australia regions, yet remains within the range reduced by 30% to generate FAR’s lower global warming estimate. This is consistent with the smaller observed estimate of radiative forcing compared to the FAR central estimate. Note that the projections assessed in [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] of this Report suggest that global temperatures will be around 1.2°C–1.8°C above 1850–1900 levels by 2030, a range which is also lower than the FAR central estimate.

<div id="_idContainer037" class="_idGenObjectStyleOverride-1"></div>

[[File:c8ea2228f5e35fb4898e625752e60dbe IPCC_AR6_WGI_Figure_1_10.png]]

'''Figure 1.10 |''' '''Range of projected temperature change for 1990–2030 for various regions defined in IPCC First Assessment Report (FAR).''' The '''left-hand''' panel shows the FAR projections ( [[#IPCC--1990a|IPCC, 1990a]] ) for southern Europe, with the darker blue shade representing the range of projected change given for the best estimate of 1.8°C global warming by 2030 compared with pre-industrial levels, and the fainter blue shade showing the range scaled by '''–''' 30% to +50% for lower and higher estimates of global warming. Blue lines show the regionally averaged observations from five global temperature gridded datasets, and blue dashed lines show the linear trends in those datasets for 1990–2020 extrapolated to 2030. Observed datasets are: HadCRUT5, Cowtan and Way, GISTEMP, Berkeley Earth and NOAA GlobalTemp. The inset map shows the definition of the FAR regions used. The '''right-hand''' panel shows projected temperature changes by 2030 for the various FAR regions, compared to the extrapolated observational trends, following [[#Grose--2017|Grose et al. (2017)]] . Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).

Overall, there is ''medium confidence'' that past projections of global temperature are consistent with subsequent observations, especially when accounting for the difference in radiative forcings used and those which actually occurred ( ''limited evidence, high agreement'' ). The FAR regional projections are broadly consistent with subsequent observations, allowing for regional-scale climate variability and differences in projected and actual forcings. There is ''medium confidence'' that the spatial warming pattern has been reliably projected in past IPCC reports ( ''limited evidence, h'' ''igh agreement'' ).

<div id="box-1.2" class="h2-container box-container"></div>

'''Box 1.2 | Special Reports in the IPCC Sixth Assessment Cycl''' '''e: Key Findings'''

<div id="h2-18-siblings" class="h2-siblings"></div>

The Sixth Assessment Cycle started with three Special Reports. The Special Report on Global Warming of 1.5°C (SR1.5, [[#IPCC--2018|IPCC, 2018]] ), invited by the Parties to the UNFCCC in the context of the Paris Agreement, assessed current knowledge on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas (GHG) emissions pathways. The Special Report on Climate Change and Land (SRCCL, [[#IPCC--2019a|IPCC, 2019a]] ) addressed GHG fluxes in land-based ecosystems, land use and sustainable land management in relation to climate change adaptation and mitigation, desertification, land degradation and food security. The Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC, [[#IPCC--2019b|IPCC, 2019b]] ) assessed new literature on observed and projected changes of the ocean and the cryosphere, and their associated impacts, risks and responses.

The SR1.5 and SRCCL were produced through a collaboration between the three IPCC Working Groups, SROCC by only Working Groups I and II. Here we focus on key findings relevant to the physical science basis covered by WGI.

'''Observations of climate change'''

The SR1.5 estimated with ''high confidence'' that human activities caused a global warming of approximately 1°C between the 1850–1900 period and 2017. For the period 2006–2015, observed global mean surface temperature (GMST <sup>[[#footnote-001|7]]</sup> ) was 0.87°C ± 0.12°C higher than the average over the 1850–1900 period ( ''very high confidence'' ). Anthropogenic global warming was estimated to be increasing at 0.2 ± 0.1°C per decade ( ''high confidence'' ) and ''likely'' matches the level of observed warming to within ±20%. The SRCCL found with ''high confidence'' that over land, mean surface air temperature increased by 1.53°C ± 0.15°C between 1850–1900 and 2006–2015, or nearly twice as much as the global average. This observed warming has already led to increases in the frequency and intensity of climate and weather extremes in many regions and seasons, including heat waves in most land regions ( ''high confidence'' ), increased droughts in some regions ( ''medium confidence'' ), and increases in the intensity of heavy precipitation events at the global scale ( ''medium confidence'' ). These climate changes have contributed to desertification and land degradation in many regions ( ''high confidence'' ). Increased urbanization can enhance warming in cities and their surroundings (heat island effect), especially during heat waves ( ''high confidence'' ) '','' and intensify extreme rainfall ( ''medi'' ''um confidence'' ).

With respect to the ocean, SROCC assessed that it is ''virtually certain'' that the ocean has warmed unabated since 1970 and has taken up more than 90% of the excess heat contributed by global warming. The rate of ocean warming has ''likely'' more than doubled since 1993. Over the period 1982–2016, marine heatwaves have ''very likely'' doubled in frequency and are increasing in intensity ( ''very high confidence'' ). In addition, the surface ocean acidified further ( ''virtually certain'' ) and loss of oxygen occurred from the surface to a depth of 1000 m ( ''medium confidence'' ). The Report expressed ''medium confidence'' that the Atlantic Meridional Overturning Circulation (AMOC) weakened in 2004–2017 relative to 1850–1900.

Concerning the cryosphere, SROCC reported widespread continued shrinking of nearly all components. Mass loss from the Antarctic Ice Sheet tripled over the period 2007–2016 relative to 1997–2006, while mass loss doubled for the Greenland Ice Sheet ( ''likely'' , ''medium confidence'' ). The Report concludes with ''very high confidence'' that due to the combined increased loss from the ice sheets, global mean sea level (GMSL) rise has accelerated ( ''extremely likely'' ) . The rate of recent GMSL rise (3.6 ± 0.5 mm yr <sup>–1</sup> for 2006–2015) is about 2.5 times larger than for 1901–1990. The report also found that Arctic sea ice extent has ''very likely'' decreased for all months of the year since 1979 and that September sea ice reductions of 12.8 ± 2.3% per decade are ''likely'' unprecedented for at least 1000 years. Feedbacks from the loss of summer sea ice and spring snow cover on land have contributed to amplified warming in the Arctic ( ''high confidence'' ), where surface air temperature ''likely'' increased by more than double the global average over the last two decades. By contrast, Antarctic sea ice extent overall saw no statistically significant trend for the period 1979–2018 ( ''hi'' ''gh confidence'' ).

Box 1.2

The SROCC assessed that anthropogenic climate change has increased observed precipitation ( ''medium confidence'' ), winds ( ''low confidence'' ), and extreme sea level events ( ''high confidence'' ) associated with some tropical cyclones. It also found evidence for an increase in the annual global proportion of Category 4 or 5 tropical cyclones in recent decades ( ''l'' ''ow confidence'' ).

'''Drivers of climate change'''
The SRCCL stated that the land is simultaneously a source and sink of CO <sub>2</sub> , due to both anthropogenic and natural drivers. It estimates with ''medium confidence'' that agriculture, forestry and other land use (AFOLU) activities accounted for around 13% of CO <sub>2</sub> , 44% of CH <sub>4</sub> , and 82% of N <sub>2</sub> O emissions from human activities during 2007–2016, representing 23% (12.0 ± 3.0 GtCO <sub>2</sub> equivalent yr <sup>–1</sup> ) of the total net anthropogenic emissions of GHGs. The natural response of land to human-induced environmental change – such as increasing atmospheric CO <sub>2</sub> concentration, nitrogen deposition and climate change – caused a net CO <sub>2</sub> sink equivalent of around 29% of total CO <sub>2</sub> emissions ( ''medium confidence'' ); however, the persistence of the sink is uncertain due to climate change ( ''hi'' ''gh confidence'' ).

The SRCCL also assessed how changes in land conditions affect global and regional climate. It found that changes in land cover have led to both a net release of CO <sub>2</sub> , contributing to global warming, and an increase in global land albedo, causing surface cooling. However, the report estimated that the resulting net effect on globally averaged surface temperature was small over the historical period ( ''medi'' ''um confidence'' ).

The SROCC found that the carbon content of Arctic and boreal permafrost is almost twice that of the atmosphere ( ''medium confidence'' ), and assessed ''medium evidence'' with ''low agreement'' that thawing northern permafrost regions are currently releasing additional net CH <sub>4</sub> and CO <sub>2</sub> .

'''Projections of climate change'''

The SR1.5 concluded that global warming is ''likely'' to reach 1.5°C between 2030 and 2052 if it continues to increase at the current rate ( ''high confidence'' ). However, even though warming from anthropogenic emissions will persist for centuries to millennia and will cause ongoing long-term changes, past emissions alone are ''unlikely'' to raise global surface temperature to 1.5°C above 1850–1900 levels.

The SR1.5 also found that reaching and sustaining net zero anthropogenic CO <sub>2</sub> emissions and reducing net non-CO <sub>2</sub> radiative forcing would halt anthropogenic global warming on multi-decadal time scales ( ''high confidence'' ). The maximum temperature reached is then determined by (i) cumulative net global anthropogenic CO <sub>2</sub> emissions up to the time of net zero CO <sub>2</sub> emissions ( ''high confidence'' ) and (ii) the level of non-CO <sub>2</sub> radiative forcing in the decades prior to the time that maximum temperatures are reached ( ''medi'' ''um confidence'' ).

Furthermore, climate models project robust differences in regional climate characteristics between the present day and a global warming of 1.5°C, and between 1.5°C and 2°C, including mean temperature in most land and ocean regions and hot extremes in most inhabited regions ( ''high confidence'' ). There is ''medium confidence'' in robust differences in heavy precipitation events in several regions and the probability of droughts in some regions.

The SROCC projected that global-scale glacier mass loss, permafrost thaw, and decline in snow cover and Arctic sea ice extent will continue in the period 2031–2050 due to surface air temperature increases ( ''high confidence'' ). The Greenland and Antarctic ice sheets are projected to lose mass at an increasing rate throughout the 21st century and beyond ( ''high confidence'' ). Sea level rise will also continue at an increasing rate. For the period 2081–2100 with respect to 1986–2005, the ''likely'' ranges of GMSL rise are projected at 0.26–0.53 m for RCP2.6 and 0.51–0.92 m for RCP8.5. For the RCP8.5 scenario, projections of GMSL rise by 2100 are higher by 0.1 m than in AR5 due to a larger contribution from the Antarctic Ice Sheet ( ''medium confidence'' ). Extreme sea level events that occurred once per hundred years in the recent past are projected to occur at least once per year at many locations by 2050, especially in tropical regions, under all RCP scenarios ( ''high confidence'' ). According to SR1.5, by 2100 GMSL rise would be around 0.1 m lower with 1.5°C global warming compared to 2°C ( ''medium confidence'' ). If warming is held to 1.5°C, GMSL will still continue to rise well beyond 2100, but at a slower rate and a lower magnitude. However, instability and/or irreversible loss of the Greenland and Antarctic ice sheets, resulting in a multi-metre rise in sea level over hundreds to thousands of years, could be triggered at 1.5°C–2°C of global warming ( ''medium confidence'' ). According to SROCC, sea level rise in an extended RCP2.6 scenario would be limited to around 1 m in 2300 ( ''low confidence'' ) while under RCP8.5 multi-metre sea level rise is projected by then ( ''medi'' ''um confidence'' ).

The SROCC projected that over the 21st century, the ocean will transition to unprecedented conditions, with increased temperatures ( ''virtually certain'' ), further acidification ( ''virtually certain'' ), and oxygen decline ( ''medium confidence'' ). Marine heatwaves are projected to become more frequent ( ''very high confidence'' ) as are extreme El Niño and La Niña events ( ''medium confidence'' ). The AMOC is projected to weaken during the 21st century ( ''very likely'' ) , but a collapse is deemed ''very unlikely'' (albeit with ''medium confidence'' due to known biases in the climate models used for the assessment).

'''Emissions pathways to limit global warming'''

The SR1.5 focused on emissions pathways and system transitions consistent with 1.5°C global warming over the 21st century. Building upon the understanding from AR5 WGI of the quasi-linear relationship between cumulative net anthropogenic CO <sub>2</sub> emissions since 1850–1900 and maximum global mean temperature, the Report assessed the remaining carbon budgets compatible with the 1.5°C or 2°C warming goals of the Paris Agreement. Starting from year 2018, the remaining carbon budget for a one-in-two (50%) chance of limiting global warming to 1.5°C is about 580 GtCO <sub>2</sub> , and about 420 GtCO <sub>2</sub> for a two-in-three (66%) chance ( ''medium confidence).''

At constant 2017 emissions, these budgets would be depleted by about the years 2032 and 2028, respectively. Using GMST instead of GSAT gives estimates of 770 GtCO <sub>2</sub> and 570 GtCO <sub>2</sub> , respectively ( ''medium confidence'' ). Each budget is further reduced by approximately 100 GtCO <sub>2</sub> over the course of this century when permafrost and other less well represented Earth system feedbacks are taken into account.

It is concluded that all emissions pathways with no or limited overshoot of 1.5°C imply that global net anthropogenic CO <sub>2</sub> emissions would need to decline by about 45% from 2010 levels by 2030, reaching net zero around 2050, together with deep reductions in other anthropogenic emissions, such as methane and black carbon. To limit global warming to below 2°C, CO <sub>2</sub> emissions would have to decline by about 25% by 2030 and reach net zero around 2070.

<div id="1.4" class="h1-container"></div>

<span id="ar6-foundations-and-concepts"></span>