Abrupt non-linear climate change, irreversibility and surprise

Abstract

Any discussion of the benefits of greenhouse gas (GHG) mitigation measures should take into consideration the full range of possible climate change outcomes, including impacts that remain highly uncertain, like surprises and other climate irreversibilities. Real-world coupling between complex systems can cause them to exhibit new collective behaviours that are not clearly demonstrable by models that do not include such coupling. Through examples from ocean circulation and atmosphere–biosphere interactions, this paper demonstrates that external forcings such as increases in GHG concentrations can push complex systems from one equilibrium state to another, with non-linear abrupt change as a possible consequence. Furthermore, the harder and faster a system is perturbed, the higher the likelihood of such surprises—a conclusion that has significant bearing on the assessment of the potential benefits of the timing and stringency of GHG abatement measures. The paper concludes with a perspective on how to better incorporate uncertainty and surprise into integrated assessment models of climate change.

Introduction

Strictly speaking, a surprise is an unexpected outcome. In the context of climate change, a surprise would be said to have occurred if a climate change-induced phenomenon with a very low probability of happening became reality or if an event never before imagined took place. In IPCC (1996), “surprises” are defined as rapid, non-linear responses of the climatic system to anthropogenic forcing, such as a collapse of the “conveyor belt” circulation in the North Atlantic Ocean or rapid deglaciation of polar ice sheets. Potential climate change, and more broadly, global environmental change, is replete with such surprises because of the enormous complexities of the processes and inter-relationships involved (such as coupled ocean, atmosphere, and terrestrial systems) and our insufficient understanding of them.

Unfortunately, most climate change assessments rarely consider low-probability, but high-consequence extreme events. Instead, they primarily consider scenarios that supposedly “bracket the uncertainty” rather than explicitly integrate unlikely events from the “tails of the distribution.” Although researchers may recognize the wide range of uncertainty surrounding global climate change, their analyses are typically surprise free. Thus, decision-makers reading the “standard” literature will rarely appreciate the full range of possible climate change outcomes, and thus might be more willing to risk adapting to prospective changes rather than attempting to avoid them through abatement than they would be if they were aware that some potentially unpleasant surprises could be lurking. (Pleasant ones might occur as well, but many individuals and policy-makers, via insurance premiums, tend to insure against negative outcomes preferentially.) In fact, it is not even clear all such surprises are actually “low probability”, just very uncertain at this point given the state of knowledge is still evolving.

Events that are not truly unanticipated are better defined as imaginable abrupt events. For other events–true surprises–while the outcome may be unknown, it may be possible to identify imaginable conditions for surprise. For example, if the rate of change of CO₂ concentrations is one imaginable condition for surprise (i.e., more rapid forcing increases the chances for surprises), we can deduce that the system would be less likely to undergo a “surprise” event if decision-makers chose as a matter of policy to slow down the rate at which human activities modify the atmosphere. To deal with such questions, the policy community needs to understand both the potential for surprises and how difficult it is for integrated assessment models (IAMs), and other models as well, to credibly evaluate the probabilities of currently imaginable “surprises”, let alone those not currently envisioned (Schneider et al., 1998).