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

=== 1.4.1 Baselines, Reference Periods and Anomalies ===

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Several baselines or reference periods are used consistently throughout AR6 WGI. Baseline refers to a period against which differences are calculated, whereas reference period is used more generally to indicate a time period of interest, or a period over which some relevant statistics are calculated (Glossary). Variations in observed and simulated climate variables over time are often presented as ‘anomalies’, that is, the differences relative to a baseline, rather than using the absolute values. This is done for several reasons.

First, anomalies are often used when combining data from multiple locations, because the absolute values can vary over small spatial scales which are not densely observed or simulated, whereas anomalies are representative for much larger scales (e.g., for temperature; [[#Hansen--1987|Hansen and Lebedeff, 1987]] ). Since their baseline value is zero by definition, anomalies are also less susceptible to biases arising from changes in the observational network. Second, the seasonality in different climate indicators can be removed using anomalies to more clearly distinguish variability from long-term trends.

Third, different datasets can have different absolute values for the same climate variable that should be removed to allow effective comparisons of variations over time. This is often required when comparing climate simulations with each other, or when comparing simulations with observations, as simulated climate variables are also affected by model bias that can be removed when they are presented as anomalies. It can also be required when comparing observational datasets or reanalyses ( [[#1.5.2|Section 1.5.2]] ) with each other, due to systematic differences in the underlying measurement system (Figure 1.11). Understanding the reasons for any absolute difference is important, but whether the simulated absolute value matters when projecting future change will depend on the variable of interest. For example, there is not a strong relationship between climate sensitivity of a model (which is an indicator of the degree of future warming) and the simulated absolute global surface temperature ( [[#Mauritsen--2012|Mauritsen et al., 2012]] ; [[#Hawkins--2016|Hawkins and Sutton, 2016]] ).

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'''Figure 1.11 |''' '''Choice of baseline matters when comparing observations and model simulations.''' Global mean surface air temperature (GSAT, grey) from a range of CMIP6 historical simulations (1850–2014; 25 models) and SSP1-2.6 (2015–2100) using absolute values '''(top)''' and anomalies relative to two different baselines: 1850–1900 '''(middle)''' and 1995–2014 '''(bottom)''' . An estimate of GSAT from a reanalysis (ERA-5, orange, 1979–2020) and an observation-based estimate of global mean surface air temperature (GMST) (Berkeley Earth, black, 1850–2020) are shown, along with the mean GSAT for 1961–1990 estimated by [[#Jones--1999|Jones et al. (1999)]] , light blue shading (14.0°C ± 0.5°C). Using the more recent baseline (bottom) allows the inclusion of datasets which do not include the periods of older baselines. The middle and bottom panels have scales which are the same size but offset. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).
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For some variables, such as precipitation, anomalies are often expressed as percentages in order to more easily compare changes in regions with very different climatological means. However, for situations where there are important thresholds (e.g., phase transitions around 0°C) or for variables which can only take a particular sign or be in a fixed range (e.g., sea ice extent or relative humidity), absolute values are normally used.

The choice of a baseline period has important consequences for evaluating both observations and simulations of the climate, for comparing observations with simulations, and for presenting climate projections. There is usually no perfect choice of baseline as many factors have to be considered and compromises may be required ( [[#Hawkins--2016|Hawkins and Sutton, 2016]] ). It is important to evaluate the sensitivity of an analysis or assessment to the choice of the baseline.

For example, the collocation of observations and reanalyses within the model ensemble spread depends on the choice of the baseline, and uncertainty in future projections of climate is reduced if using a more recent baseline, especially for the near term (Figure 1.11). The length of an appropriate baseline or reference period depends on the variable being considered, the rates of change of the variable and the purpose of the chosen period, but is usually 20 to 50 years long. The World Meteorological Organization (WMO) uses 30-year periods to define ‘climate normals’, which indicate conditions expected to be experienced in a given location.

For AR6WGI, the period 1995–2014 is used as a baseline to calculate the changes in future climate using model projections and also as a ‘modern’ or ‘recent past’ reference period when estimating past observed warming. The equivalent period in AR5 was 1986–2005, and in SR1.5, SROCC and SRCCL it was 2006–2015. The primary reason for the different choice in AR6 is that 2014 is the final year of the historical CMIP6 simulations. These simulations subsequently assume different emissions scenarios and so choosing any later baseline end date would require selecting a particular emissions scenario. For certain assessments, the most recent decade possible (e.g., 2010–2019 or 2011–2020, depending on the availability of observations) is also used as a reference period (Cross-Chapter Box 2.3).

Figure 1.12 shows changes in observed global mean surface temperature (GMST) relative to 1850–1900 and illustrates observed global warming levels for a range of reference periods that are either used in AR6 or were used in previous IPCC reports. This allows changes to be calculated between different periods and compared to previous assessments. For example, AR5 assessed the change in GMST from the 1850–1900 baseline to 1986–2005 reference period as 0.61 [0.55 to 0.67] °C, whereas it is now assessed to be 0.69 [0.52 to 0.82] °C using improved GMST datasets (Cross-Chapter Box 2.3).

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'''Figure 1.12 |''' '''Global warming over the instrumental period.''' Observed global mean surface temperature (GMST) from four datasets, relative to the average temperature of 1850–1900 in each dataset (see Cross-Chapter Box 2.3 and [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.1|Section 2.3.1.1]] for more details). The shaded grey band indicates the assessed ''likely'' range for the period around 1750 (Cross-Chapter Box 1.2). Different reference periods are indicated by the coloured horizontal lines, and an estimate of total GMST change up to that period is given, enabling a translation of the level of warming between different reference periods. The reference periods are all chosen because they have been used in AR6 or previous IPCC assessment reports. The value for the 1981–2010 reference period, used as a ‘climate normal’ period by the World Meteorological Organization, is the same as the 1986–2005 reference period shown. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).
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The commonly used metric for global surface warming tends to be GMST but, as shown in Figure 1.11, climate model simulations tend to use global surface air temperature (GSAT). Although GMST and GSAT are closely related, the two measures are physically distinct. GMST is a combination of land surface air temperature (LSAT) and sea surface temperature (SST), whereas GSAT is surface air temperatures over land, ocean and ice. A key development in AR6 is the assessment that long-term changes in GMST and GSAT differ by at most 10% in either direction, with ''low confidence'' in the sign of any differences (see Cross Chapter Box 2.3 for details).

Three future reference periods are used in AR6 WGI for presenting projections: ''near term'' (2021–2040), ''mid-term'' (2041–2060) and ''long-term'' (2081–2100; Figure 1.11). In AR6, 20-year reference periods are considered long enough to show future changes in many variables when averaging over ensemble members of multiple models, and short enough to enable the time dependence of changes to be shown throughout the 21st century. Projections with alternative recent baselines (such as 1986–2005 or the current WMO climate-normal period of 1981–2010) and a wider range of future reference periods are presented in the Interactive Atlas. Note that ‘long term’ is also sometimes used in a more general sense to refer to durations of centuries to millennia when examining past climate, as well as future climate change beyond the year 2100. Cross-Chapter Box 2.1 discusses the paleo-reference periods used in AR6.

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'''Cross-Chapter Box 1.2 | Changes in Global Temperature Betwee''' '''n 1750 and 1850'''

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'''Contributing Authors:''' Ed Hawkins (United Kingdom), Paul Edwards (United States of America), Piers Forster (United Kingdom), Darrell S. Kaufman (United States of America), Jochem Marotzke (Germany), Malte Meinshausen (Australia/Germany), Maisa Rojas (Chile), Bjørn H. Samset (Norway), Peter Thorne (Ireland/United Kingdom)

The Paris Agreement aims to limit global temperatures to specific thresholds ‘above pre-industrial levels’. In AR6 WGI, as in previous IPCC reports, observations and projections of changes in global temperature are generally expressed relative to 1850–1900 as an approximate pre-industrial state (SR1.5, [[#IPCC--2018|IPCC, 2018]] ). This is a pragmatic choice based upon data availability considerations, though both anthropogenic and natural changes to the climate occurred before 1850. The remaining carbon budgets, the chance of crossing global temperature thresholds, and projections of extremes and sea level rise at a particular level of global warming can all be sensitive to the chosen definition of the approximate pre-industrial baseline ( [[#Millar--2017b|Millar et al., 2017b]] ; [[#Schurer--2017|Schurer et al., 2017]] ; [[#Pfleiderer--2018|Pfleiderer et al., 2018]] ; [[#Rogelj--2019|Rogelj et al., 2019]] ; [[#Tokarska--2019|Tokarska et al., 2019]] ). This Cross-Chapter Box assesses the evidence on change in radiative forcing and global temperature from the period around 1750 to 1850–1900; variations in the climate before 1750 are discussed in Chapter 2.

Although there is some evidence for human influence on climate before 1750 (e.g., [[#Ruddiman--2001|Ruddiman and Thomson, 2001]] ; [[#Koch--2019|Koch et al., 2019]] ), the magnitude of the effect is still disputed (Section 5.1.2.3; e.g., [[#Joos--2004|Joos et al., 2004]] ; J. [[#Beck--2018|]] [[#Beck--2018|Beck et al., 2018]] ), and most studies analyse the human influence on climate over the industrial period. Historically, the widespread use of coal-powered machinery started the Industrial Revolution in Britain in the late 18th century ( [[#Ashton--1997|Ashton, 1997]] ), but the global effects were small for several decades. In line with this, previous IPCC assessment reports considered changes in radiative forcing relative to 1750, and temperature changes were often reported relative to the ‘late 19th century’. The AR5 and SR1.5 made the specific pragmatic choice to approximate pre-industrial global temperatures by using the average of the 1850 – 1900 period, when permanent surface observing networks emerged that provide sufficiently accurate and continuous measurements on a near-global scale (Sections [[#1.3.1|1.3.1]] and [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.1|2.3.1.1]] ), and because model simulations of the historical period used 1850 as their start date. For the same reasons, to ensure continuity with previous assessments, and because of larger uncertainties and lower confidence in climatic changes before 1850 than after, AR6 makes the same choice to approximate pre-industrial global temperatures by using the the average of the 1850–1900 period.

Here weassess improvements in our understanding of climatic changes in the period 1750–1850. Anthropogenic influences on climate between 1750 and 1900 were primarily increased anthropogenic GHG and aerosol emissions, and changes in land use. Between 1750 and 1850 atmospheric CO <sub>2</sub> levels increased from about 278 ppm to about 285 ppm (equivalent to around 3 years of current rates of increase; Chapter 2, [[IPCC:Wg1:Chapter:Chapter-2#2.2.3|Section 2.2.3]] ), corresponding to about 55 GtCO <sub>2</sub> in the atmosphere. Estimates of emissions from fossil fuel burning (about 4 GtCO <sub>2</sub> , [[#Boden--2017|Boden et al., 2017]] ) cannot explain the pre-1850 increase, so CO <sub>2</sub> emissions from land-use changes are implicated as the dominant source. The atmospheric concentration of other GHGs also increased over the same period, and there was a cooling influence from other anthropogenic radiative forcings (such as aerosols and land-use changes), but with a larger uncertainty than for GHGs (Sections 2.2.6 and 7.3.5.2, and Cross-Chapter Box 1.2, Figure 1; e.g., [[#Carslaw--2017|Carslaw et al., 2017]] ; [[#Owens--2017|Owens et al., 2017]] ; [[#Hamilton--2018|Hamilton et al., 2018]] ). It is ''likely'' that there was a net anthropogenic forcing of 0.0 – 0.3 Wm <sup>–2</sup> in 1850 – 1900 relative to 1750 ( ''medium confidence'' ). The net radiative forcing from changes in solar activity and volcanic activity in 1850 – 1900, compared to the period around 1750, is estimated to be smaller than ±0.1 W m <sup>–2</sup> , but note there were several large volcanic eruptions between 1750 and 1850 (Cross-Chapter Box 1.2, Figure 1).

Several studies since AR5 have estimated changes in global temperatures following industrialisation and before 1850. [[#Hawkins--2017|Hawkins et al. (2017)]] used observations, radiative forcing estimates and model simulations to estimate the warming from 1720–1800 until 1986–2005 and assessed a ''likely'' range of 0.55°C–0.80°C, slightly broader than the equivalent range starting from 1850–1900 (0.6°C–0.7°C). From proxy evidence, [[#PAGES%202k%20Consortium--2019|PAGES 2k Consortium (2019)]] found that GMST for 1850–1900 was 0.02 [–0.22 to +0.16] °C warmer than the 30-year period centred on 1750. [[#Schurer--2017|Schurer et al. (2017)]] used climate model simulations of the last millennium to estimate that the increase in GHG concentrations before 1850 caused an additional ''likely'' range of 0.0°C –0.2°C global warming when considering multiple reference periods. [[#Haustein--2017|Haustein et al. (2017)]] implies an additional warming of around 0.05°C attributable to human activity from 1750 to 1850–1900, and the AR6 emulator (Section 7.3.5.3) estimates the ''likely'' range of this warming to be 0.04°C–0.14°C.

Combining these different sources of evidence, we assess that from the period around 1750 to 1850–1900 there was a change in global temperature of around 0.1 [–0.1 to +0.3] °C ( ''medium confidence'' ), with an anthropogenic component in a ''likely'' range of 0.0°C–0.2°C ( ''medi'' ''um confidence'' ).

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'''Cross-Chapter Box 1.2, Figure 1''' | '''Changes in radiative forcing from 1750–2019''' . The radiative forcing estimates from the AR6 emulator (Cross-Chapter Box 7.1) are split into GHG, other anthropogenic (mainly aerosols and land use) and natural forcings, with the average over the 1850–1900 baseline shown for each. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).
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