Basin stability and limit cycles in a conceptual model for climate tipping cascades (original) (raw)

Predicting Climate Tipping as a Noisy Bifurcation: A Review

International Journal of Bifurcation and Chaos, 2011

There is currently much interest in examining climatic tipping points, to see if it is feasible to predict them in advance. Using techniques from bifurcation theory, recent work looks for a slowing down of the intrinsic transient responses, which is predicted to occur before an instability is encountered. This is done, for example, by determining the short-term autocorrelation coefficient ARC(1) in a sliding window of the time series: this stability coefficient should increase to unity at tipping. Such studies have been made both on climatic computer models and on real paleoclimate data preceding ancient tipping events. The latter employ re-constituted time-series provided by ice cores, sediments, etc, and seek to establish whether the actual tipping could have been accurately predicted in advance. One such example is the end of the Younger Dryas event, about 11,500 years ago, when the Arctic warmed by 7 • C in 50 years. A second gives an excellent prediction for the end of 'greenhouse' Earth about 34 million years ago when the climate tipped from a tropical state into an icehouse state, using data from tropical Pacific sediment cores. This prediction science is very young, but some encouraging results are already being obtained. Future analyses will clearly need to embrace both real data from improved monitoring instruments, and simulation data generated from increasingly sophisticated predictive models.

Interacting tipping elements increase risk of climate domino effects under global warming

With progressing global warming, there is an increased risk that one or several tipping elements in the climate system might cross a critical threshold, resulting in severe consequences for the global climate, ecosystems and human societies. While the underlying processes are fairly well-understood, it is unclear how their interactions might impact the overall stability of the Earth's climate system. As of yet, this cannot be fully analysed with state-of-the-art Earth system models due to computational constraints as well as some missing and uncertain process representations of certain tipping elements. Here, we explicitly study the effects of known physical interactions among the Greenland and West Antarctic ice sheets, the Atlantic Meridional Overturning Circulation (AMOC) and the Amazon rainforest using a conceptual network approach. We analyse the risk of domino effects being triggered by each of the individual tipping elements under global warming in equilibrium experiments. In these experiments, we propagate the uncertainties in critical temperature thresholds, interaction strengths and interaction structure via large ensembles of simulations in a Monte Carlo approach. Overall, we find that the interactions tend to destabilise the network of tipping elements. Furthermore, our analysis reveals the qualitative role of each of the four tipping elements within the network, showing that the polar ice sheets on Greenland and West Antarctica are oftentimes the initiators of tipping cascades, while the AMOC acts as a mediator transmitting cascades. This indicates that the ice sheets, which are already at risk of transgressing their temperature thresholds within the Paris range of 1.5 to 2 • C, are of particular importance for the stability of the climate system as a whole.

Nonlinearities, Feedbacks and Critical Thresholds within the Earth's Climate System

Climatic Change, 2004

The Earth's climate system is highly nonlinear: inputs and outputs are not proportional, change is often episodic and abrupt, rather than slow and gradual, and multiple equilibria are the norm. While this is widely accepted, there is a relatively poor understanding of the different types of nonlinearities, how they manifest under various conditions, and whether they reflect a climate system driven by astronomical forcings, by internal feedbacks, or by a combination of both. In this paper, after a brief tutorial on the basics of climate nonlinearity, we provide a number of illustrative examples and highlight key mechanisms that give rise to nonlinear behavior, address scale and methodological issues, suggest a robust alternative to prediction that is based on using integrated assessments within the framework of vulnerability studies and, lastly, recommend a number of research priorities and the establishment of education programs in Earth Systems Science. It is imperative that the Earth's climate system research community embraces this nonlinear paradigm if we are to move forward in the assessment of the human influence on climate.

Anthropocene Climate Bifurcation

2020

This article presents the results of a bifurcation analysis of a simple energy balance model (EBM) for the future climate of the Earth. The main focus is on the following question: can the nonlinear processes intrinsic to atmospheric physics, including natural positive feedback mechanisms, cause a mathematical bifurcation of the climate state, as a consequence of continued anthropogenic forcing by rising greenhouse gas emissions? Our analysis shows that such a bifurcation could cause an abrupt change to a drastically different climate state in the EBM, which is warmer and more equable than any climate existing on Earth since the Pliocene epoch. In previous papers, with this EBM adapted to paleoclimate conditions, it was shown to exhibit saddlenode and cusp bifurcations, as well as hysteresis. The EBM was validated by the agreement of its predicted bifurcations with the abrupt climate changes that are known to have occurred in the paleoclimate record, in the Antarctic at the Eocene-Oligocene transition (EOT) and in the Arctic at the Pliocene-Paleocene transition (PPT). In this paper, the EBM is adapted to fit Anthropocene climate conditions, with emphasis on the Arctic and Antarctic climates. The four Representative Concentration Pathways (RCP) considered by the IPCC (Intergovernmental Panel on Climate Change) are used to model future CO 2 concentrations, corresponding to different scenarios of anthropogenic activity. In addition, the EBM investigates four naturally occurring nonlinear feedback processes which magnify the warming that would be caused by anthropogenic CO 2 emissions alone. These four feedback mechanisms are ice-albedo feedback, water vapour feedback, ocean heat transport feedback, and atmospheric heat transport feedback. The EBM predicts that a bifurcation resulting in a catastrophic climate change, to a pre-Pliocenelike climate state, will occur in coming centuries for an RCP with unabated anthropogenic forcing, amplified by these positive feedbacks. However, the EBM also predicts that appropriate reductions in carbon emissions may limit climate change to a more tolerable continuation of what is observed today. The globally averaged version of this EBM has an equilibrium climate sensitivity (ECS) of 4.34 K, near the high end of the likely range reported by the IPCC.

Potential analysis reveals changing number of climate states during the last 60 kyr

Climate of the Past, 2010

We develop and apply a new statistical method of potential analysis for detecting the number of states of a geophysical system, from its recorded time series. Estimation of the degree of a polynomial potential allows us to derive the number of potential wells in a system. The method correctly detects changes in the number of wells in artificial data. In ice-core proxy records of Greenland paleotemperature, a reduction in the number of climate states from two to one is detected sometime prior to the last glacial maximum (LGM), 23-19 kyr BP. This result is also found in analysis of Greenland Ca data. The bifurcation can be interpreted as loss of stability of the warm interstadial state of the Dansgaard-Oeschger (DO) events. The proposed method can be applied to a wide range of geophysical time series exhibiting bifurcations.

Changing climate states and stability: from Pliocene to present

Climate Dynamics

We present a recently developed method of potential analysis of time series data, which comprises (1) derivation of the number of distinct global states of a system from time series data, and (2) derivation of the potential coefficients describing the location and stability of these states, using the unscented Kalman filter (UKF). We test the method on artificial data and then apply it to climate records spanning progressively shorter time periods from 5.3 Myr ago to the recent observational record. We detect various changes in the number and stability of states in the climate system. The onset of Northern Hemisphere glaciation roughly 3 Myr BP is detected as the appearance of a second climate state. During the last ice age in Greenland, there is a bifurcation representing the loss of stability of the warm interstadial state, followed by the total loss of this state around 25 kyr BP. The Holocene is generally characterized by a single stable climate state, especially at large scales. However, in the historical record, at the regional scale, the European monthly temperature anomaly temporarily exhibits a second, highly degenerate (unstable) state during the latter half of the eighteenth century. At the global scale, temperature is currently undergoing a forced movement of a single stable state rather than a bifurcation. The method can be applied to a wide range of geophysical systems with time series of sufficient length and temporal resolution, to look for bifurcations and their precursors.

Edge states in the climate system: exploring global instabilities and critical transitions

Nonlinearity

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