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

=== 1.6.2 Global Warming Levels ===

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The global mean surface temperature change, or ‘global warming level’ (GWL), is a ‘dimension of integration’ that is highly relevant across scientific disciplines and socio-economic actors. First, global warming levels relative to pre-industrial conditions are the quantity in which the 1.5°C and ‘well below 2°C’ Paris Agreement goals were formulated. Second, global mean temperature change has been found to be almost-linearly related to a number of regional climate effects ( [[#Mitchell--2000|Mitchell et al., 2000]] ; [[#Mitchell--2003|Mitchell, 2003]] ; [[#Tebaldi--2014|Tebaldi and Arblaster, 2014]] ; [[#Seneviratne--2016|Seneviratne et al., 2016]] ; [[#Li--2020|Li et al., 2020]] ; [[#Seneviratne--2020|Seneviratne and Hauser, 2020]] ). Even where non-linearities are found, some regional climate effects can be considered to be almost scenario-independent for a given level of warming (Sections 4.2.4, 4.6.1, 8.5.3 and 10.4.3.1, and Cross-Chapter Box 11.1). Finally, the evolution of aggregated impacts with warming levels has been widely used and embedded in the assessment of the ‘Reasons for Concern’ (RFC) in IPCC WGII ( [[#Smith--2009|Smith et al., 2009]] ; [[#IPCC--2014a|IPCC, 2014a]] ). The RFC framework was further expanded in SR1.5 (2018), SROCC (2019) and SRCCL (2019) by explicitly describing the differential impacts of half-degree warming steps ( [[#1.4.4|Section 1.4.4]] and Cross-Chapter Box 12.1; cf. [[#King--2017|King et al., 2017]] ).

In this Report, the term ‘global warming level’ refers to the categorization of global and regional climate change, associated impacts, emissions and concentrations scenarios by GMST relative to 1850–1900, which is the period used as a proxy for pre-industrial levels (Cross-Chapter Box 11.1). By default, GWLs are expressed in terms of global surface air temperature (GSAT; [[#1.4.1|Section 1.4.1]] and Cross-Chapter Box 2.3).

As SR1.5 concluded, even half-degree global mean temperature steps carry robust differences in climate impacts (Chapter 11; SR1.5, [[#IPCC--2018|IPCC, 2018]] ; [[#Schleussner--2016a|Schleussner et al., 2016a]] ; [[#Wartenburger--2017|Wartenburger et al., 2017]] ). This Report adopts half-degree warming levels, which allows integration for climate projections, impacts, adaptation challenges and mitigation challenges within and across the three WGs. The core set of GWLs – 1.5°C, 2.0°C, 3.0°C and 4.0°C – are highlighted (Chapters 4, 8, 11, 12 and Atlas). Given that much impact analysis is based on previous scenarios, (i.e., RCPs or SRES), and climate change mitigation analysis is based on new emissions scenarios in addition to the main SSP scenarios, these GWLs assist in the comparison of climate states across scenarios and in the synthesis across the broader literature.

The transient and equilibrium states of certain global warming levels can differ in their climate impacts ( [[#IPCC--2018|IPCC, 2018]] ; [[#King--2020|King et al., 2020]] ). Climate impacts in a ‘transient’ world relate to a scenario in which the world is continuing to warm. On the other hand, climate impacts at the same warming levels can also be estimated from equilibrium states after a (relatively) short-term stabilization by the end of the21st century or at a (near-)equilibrium state after a long-term (multi-decadal to multi-millennial) stabilization. Different methods to estimate these climate states come with challenges and limitations ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.1|Section 4.6.1]] and Cross-Chapter Box 11.1). First, information can be drawn from GCM or ESM simulations that ‘pass through’ the respective warming levels (as used and demonstrated in the Interactive Atlas), also called ‘epoch’ or ‘time-shift’ approaches (Sections 4.2.4 and 4.6.1; [[#Herger--2015|Herger et al., 2015]] ; [[#James--2017|James et al., 2017]] ; Tebaldi and [[#Knutti--2018|Knutti, 2018]] ). Information from transient simulations can also be used through an empirical scaling relationship ( [[#Seneviratne--2016|Seneviratne et al., 2016]] , 2018; [[#Wartenburger--2017|Wartenburger et al., 2017]] ) or using ‘time sampling’ approaches, as described in [[#James--2017|James et al. (2017)]] . Second, information can be drawn from large ESM ensembles with prescribed SST at particular global warming levels ( [[#Mitchell--2017|Mitchell et al., 2017]] ), although an underrepresentation of variability can arise when using prescribed SST temperatures (E.M. [[#Fischer--2018|]] [[#Fischer--2018|Fischer et al., 2018]] ).

In order to fully derive climate impacts, warming levels will need to be complemented by additional information, such as their associated CO <sub>2</sub> concentrations (e.g., fertilization or ocean acidification), composition of the total radiative forcing (aerosols compared with GHGs, with varying regional distributions) or socio-economic conditions (e.g., to estimate societal impacts). More fundamentally, while a global warming level is a good proxy for the state of the climate (Cross-Chapter Box 11.1), it does not uniquely define a change in global or regional climate state. For example, regional precipitation responses depend on the details of the individual forcing mechanisms that caused the change ( [[#Samset--2016|Samset et al., 2016]] ); on whether the temperature level is stabilized or transient ( [[#King--2020|King et al., 2020]] ; [[#Zappa--2020|Zappa et al., 2020]] ); on the vertical structure of the troposphere ( [[#Andrews--2010|Andrews et al., 2010]] ); and, in particular, on the global distribution of atmospheric aerosols ( [[#Frieler--2012|Frieler et al., 2012]] ). Another aspect is how Earth system components with century-to-millennial response time scales, such as long-term sea level rise or permafrost thaw, are affected by global mean warming. For example, sea level rise 50 years after a 1°C warming will be lower than sea level rise 150 years after that same 1°C warming (Chapter 9).

Also, forcing or response patterns that vary in time can create differences in regional climates for the same global mean warming level, or can create non-linearities when scaling patterns from one warming level to another ( [[#King--2018|King et al., 2018]] ), depending on whether near-term transient climate, end of the century, equilibrium climate or climate states after an initial overshoot are considered.

In spite of these challenges, and thanks to recent methodological advances in quantifying or overcoming them, global warming levels provide a robust and useful integration mechanism. They allow knowledge from various domains within WGI and across the three WGs to be integrated and communicated (Cross-Chapter Box 11.1). In this report, Chapters 4, 8, 11, 12 and the [[IPCC:Wg1:Chapter:Atlas|Atlas]] provide information specific to certain warming levels, highlighting the regional differences, but also the approximate scalability of regional climate change, that can arise from even a 0.5°C shift in global mean temperatures. Furthermore, building on WGI insights into physical climate system responses (Cross-Chapter Box 7.1), WGIII will use peak and end-of-century global warming levels to classify a broad set of scenarios.

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