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

==== 1.4.4.3 Abrupt Change, Tipping Points and Surprises ====

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An ‘abrupt change’ is defined in this report as a change that takes place substantially faster than the rate of change in the recent history of the affected component of a system (Glossary). In some cases, abrupt change occurs because the system state actually becomes unstable, such that the subsequent rate of change is independent of the forcing. We refer to this class of abrupt change as a ‘tipping point’ '','' defined as a critical threshold beyond which a system reorganizes, often abruptly and/or irreversibly (Glossary; [[#Lenton--2008|Lenton et al., 2008]]). Some of the abrupt climate changes and climate tipping points discussed in this Report could have severe local climate responses, such as extreme temperature, droughts, forest fires, ice-sheet loss and collapse of the thermohaline circulation (Sections 4.7.2, 5.4.9, 8.6 and 9.2.3).

There is evidence of abrupt changes in Earth’s history, and some of these events have been interpreted as tipping points ([[#Dakos--2008|Dakos et al., 2008]]). Some of these are associated with significant changes in the global climate, such as deglaciations in the Quaternary (past 2.5 million years) and rapid warming at the Palaeocene–Eocene Thermal Maximum (around 55.5 million years ago; [[#Bowen--2015|Bowen et al., 2015]]; [[#Hollis--2019|Hollis et al., 2019]]). Such events changed the planetary climate for tens to hundreds of thousands of years, but at a rate that is actually much slower than projected anthropogenic climate change over this century, even in the absence of tipping points.

Such paleoclimate evidence has even fuelled concerns that anthropogenic GHGs could tip the global climate into a permanent hot state ([[#Steffen--2018|Steffen et al., 2018]]). However, there is no evidence of such non-linear responses at the global scale in climate projections for the next century, which indicates a near-linear dependence of global temperature on cumulative GHG emissions (Sections 1.3.5, 5.5 and 7.4.3.1). At the regional scale, abrupt changes and tipping points, such as Amazon rainforest dieback and permafrost collapse, have occurred in projections with Earth System Models ([[IPCC:Wg1:Chapter:Chapter-4#4.7.3|Section 4.7.3]]; [[#Drijfhout--2015|Drijfhout et al., 2015]]; [[#Bathiany--2020|Bathiany et al., 2020]]). In such simulations, tipping points occur in narrow regions of parameter space (e.g., CO <sub>2</sub> concentration or temperature increase), and for specific climate background states. This makes them difficult to predict using Earth system models (ESMs) relying on parmeterizations of known processes. In some cases, it is possible to detect forthcoming tipping points through time-series analysis that identifies increased sensitivity to perturbations as the tipping point is approached (e.g., ‘critical slowing-down’, [[#Scheffer--2012|Scheffer et al., 2012]]).

Some suggested climate tipping points prompt transitions from one steady state to another (Figure 1.17). Transitions can be prompted by perturbations such as climate extremes which force the system outside of its current well of attraction in the stability landscape; this is called noise-induced tipping (Figure 1.17a,b; [[#Ashwin--2012|Ashwin et al., 2012]]). For example, the tropical forest dieback seen in some ESM projections is accelerated by longer and more frequent droughts over tropical land ([[#Good--2013|Good et al., 2013]]).

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[[File:23aa7d4ef86b70d128c44c971f6234a3 IPCC_AR6_WGI_Figure_1_17.png]]

'''Figure 1.17 |''' '''Illustration of two types of tipping points: noise-induced (a, b) and bifurcation (c, d).''' '''(a)''' and '''(c)''' are example time-series (coloured lines) through the tipping point, with solid-black lines indicating stable climate states (e.g., low or high rainfall) and dashed lines representing the boundary between stable states. '''(b)''' and '''(d)''' are stability landscapes, which provide an intuitive understanding of the different types of tipping point. The ‘valleys’ represent different climate states the system can occupy, with ‘hilltops’ separating the stable states. The resilience of a climate state is implied by the depth of the valley. The current state of the system is represented by a ball. Both scenarios assume that the ball starts in the left-hand valley (dashed-black lines) and then through different mechanisms dependent on the type of tipping transitions to the right-hand valley (coloured lines). Noise-induced tipping events (a, b), for instance drought events causing sudden dieback of the Amazon rainforest, develop from fluctuations within the system. The stability landscape in this scenario remains fixed and stationary. A series of perturbations in the same direction, or one large perturbation, are required to force the system over the hilltop and into the alternative stable state. Bifurcation tipping events (c, d), such as a collapse of the thermohaline circulation in the Atlantic Ocean under climate change, occur when a critical level in the forcing is reached. Here the stability landscape is subjected to a change in shape. Under gradual anthropogenic forcing the left-hand valley begins to shallow and eventually vanishes at the tipping point, forcing the system to transition to the right-hand valley.

Alternatively, transitions from one state to another can occur if a critical threshold is exceeded; this is called ‘bifurcation tipping’ (Figure 1.17c,d; [[#Ashwin--2012|Ashwin et al., 2012]]). The new state is defined as ‘irreversible’ on a given time scale if the recovery from this state takes substantially longer than the time scale of interest, which is decades to centuries for the projections presented in this report. A well-known example is the modelled irreversibility of the ocean’s thermohaline circulation in response to North Atlantic changes such as freshwater input from rainfall and ice-sheet melt ([[#Rahmstorf--2005|Rahmstorf et al., 2005]]; [[#Alkhayuon--2019|Alkhayuon et al., 2019]]), which is assessed in detail in [[IPCC:Wg1:Chapter:Chapter-9|Chapter 9]] (Section 9.2.3).

The tipping point concept is most commonly framed for systems in which the forcing changes relatively slowly. However, this is not the case for most scenarios of anthropogenic forcing projected for the 21st century. Systems with inertia lag behind rapidly increasing forcing, which can lead to the failure of early warning signals or even the possibility of temporarily overshooting a bifurcation point without provoking tipping ([[#Ritchie--2019|Ritchie et al., 2019]]).

‘Surprises’ are a class of risk that can be defined as low-likelihood but well-understood events: they are events that cannot be predicted with current understanding. The risk from such surprises can be accounted for in risk assessments ([[#Parker--2015|Parker and Risbey, 2015]]). Examples relevant to climate science include: a series of major volcanic eruptions or a nuclear war, either of which would cause substantial planetary cooling ([[#Robock--2007|Robock et al., 2007]]; [[#Mills--2014|Mills et al., 2014]]); significant 21st century sea level rise due to marine ice sheet instability (MISI; Box 9.4); the potential for collapse of the stratocumulus cloud decks ([[#Schneider--2019|Schneider et al., 2019]]) or other substantial changes in climate feedbacks (Section 7.4); and unexpected biological epidemics among humans or other species, such as the COVID-19 pandemic (Cross-Chapter Box 6.1; [[#Forster--2020|Forster et al., 2020]]; [[#Le%20Quéré--2020|Le Quéré et al., 2020]]). The discovery of the hole in the ozone layerwas also a surprise even though some of the relevant atmospheric chemistry was known at the time. The term ‘unknownunknowns’ ([[#Parker--2015|Parker and Risbey, 2015]]) is also sometimes used in this context to refer to events that cannot be anticipated with presentknowledge or were of an unanticipated nature before they occurred.

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