The Tipping Point Modelling Intercomparison Project (TIPMIP) is an international initiative that aims to systematically improve our understanding of potential tipping dynamics in different components of the Earth system and to assess the associated uncertainties (www.tipmip.org). By linking and evaluating different models through a systematic framework, TIPMIP aims to fill critical knowledge gaps in Earth system and climate risks by improving their assessment at different levels of anthropogenic forcing and associated long-term commitments and irreversibilities. The Methods and Risk Assessment Working Group of TIPMIP will further develop the methodological foundations of this systematic approach to the study of tipping dynamics in domain-specific and coupled Earth system  numerical models to support future assessment reports and comprehensive risk analyses. In this contribution, we introduce the Methods and Risk Assessment Working Group within TIPMIP, and highlight relevant lines of methodological development to be pursued, including: (i) systematic and automated detection of tipping points and critical transitions in model output and Earth observation data for TIPMIP (e.g, the TOAD framework), (ii) detection of non-linear regime shifts in time series data for TIPMIP beyond amplitude shifts, e.g. transitions between more regular and more erratic variability (e.g. the pyunicorn toolkit), and (iii) probabilistic analysis and emulator approaches of risks for triggering tipping events and cascading tipping dynamics at different levels of anthropogenic forcing (e.g. the pycascades approach).

How to cite: Donges, J. F., Dennis, D. P., Loriani, S., Sakschewski, B., Wunderling, N., and Winkelmann, R.: Methodologies for climate tipping points analysis and risk assessments in TIPMIP, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18039, https://doi.org/10.5194/egusphere-egu24-18039, 2024.

Observations are increasingly used to detect critical slowing down (CSD) in potentially multistable components of the Earth system in order to warn of forthcoming critical transitions in these components. In addition, it has been suggested to use the statistical changes in these historical observations to extrapolate into the future and predict the tipping time. We argue that this extrapolation is too sensitive to uncertainties to give robust results. In particular, we raise concerns regarding (1) the modelling assumptions underlying the approaches to extrapolate results obtained from analyzing historical data into the future, (2) the representativeness of individual time series representing the variability of the respective Earth system components, and (3) the effect of uncertainties and preprocessing of the employed observational datasets, with focus on non-stationary observational coverage and the way gaps are filled. We explore these uncertainties both qualitatively and quantitatively for the Atlantic Meridional Overturning Circulation (AMOC). We argue that even under the assumption that these natural systems have a tipping point that they are getting closer to, the different uncertainties are too large to be able to estimate the time of tipping based on extrapolation from historical data.

How to cite: Ben Yami, M., Morr, A., Bathiany, S., and Boers, N.: Uncertainties too large to predict tipping times of major Earth system components, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5870, https://doi.org/10.5194/egusphere-egu24-5870, 2024.

To tip or not to tip? Many subsystems of the Earth are at risk of undergoing abrupt transitions from their current stable state to a drastically different and often less desired state due to anthropogenic climate change. These so-called tipping events often present severe consequences for ecosystems and human livelihood that are difficult to reverse. One common mechanism for tipping to occur is via forcing and driving a nonlinear system beyond a critical threshold that signifies self-amplifying feedbacks inducing tipping. However, previous work has shown that it is possible to briefly overshoot a critical threshold and avoid tipping. Specifically, the peak distance of an overshoot and the time a system can spend beyond a threshold are governed by an inverse square law relationship. In the real world or complex models, critical thresholds and other system features determining the permitted overshoot are highly uncertain. In this presentation, we look at how such uncertainties affect the probability of tipping from the perspective of uncertainty quantification. We show the importance of constraining uncertainty in the location of the critical threshold and the linear restoring rate to the stable state to reduce the uncertainty in the probability of tipping. Using a simple box model for the Atlantic Meridional Overturning Circulation, we highlight the need to constrain the high uncertainty found in wind-driven fluxes represented by a diffusive time scale within the box model to reduce uncertainty in the tipping probability for overshoot scenarios. 

How to cite: Ritchie, P. and Lux-Gottschalk, K.: Uncertainty quantification for overshoots of tipping thresholds, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8618, https://doi.org/10.5194/egusphere-egu24-8618, 2024.

Many potential tipping elements have been identified in the climate system over the last decade, although some of them are surrounded by large uncertainties. We perform an updated analysis of abrupt changes in current state-of-the-art climate models to re-evaluate the evidence of these shifts—whether they are tipping points or not. We examine all CMIP6 models (59 in total) under the 1pctCO2 scenario using a Canny edge detection method—adapted for spatiotemporal dimensions—to detect abrupt shifts in climate data. We perform this semi-automatic analysis on 83 two-dimensional variables of the ocean, atmosphere, and land. We aggregate the detected shifts that are connected spatially or temporally. This results in connected regions of abrupt shifts and allows us to map areas that are most at risk of these shifts according to CMIP6 models. We report statistics on number of abrupt changes detected, surface area of abrupt changes, and critical global mean temperature at which these abrupt changes occur. This is done for various climate subsystems and potential tipping elements, such as the Arctic sea ice, Antarctic sea ice and the North Atlantic subpolar gyre. We find evidence for abrupt changes in several systems, but not all models show them equally.

How to cite: Terpstra, S., Falkena, S. K. J., Bastiaansen, R., Bathiany, S., Dijkstra, H. A., and von der Heydt, A.: Analysis of Abrupt Changes in CMIP6 Models Using Edge Detection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12295, https://doi.org/10.5194/egusphere-egu24-12295, 2024.

A tipping cascade is a series of tipping events in the Earth system where transitions in one subsystem can trigger further transitions in other subsystems. A concern for the future is that such a cascade could lock the Earth system in a pathway towards a so-called hothouse state. We investigate this possibility with SURFER, a reduced complexity model with a process-based carbon cycle that can reliably predict CO₂ concentrations, global mean temperatures, sea-level rise, and many ocean acidification metrics on timescales from decades to millions of years. We have incorporated in the model a network of interacting tipping elements and their feedback on the climate through albedo changes and additional greenhouse gas emissions. This has allowed for a systematic investigation of the effects of a family of realistic emission scenarios on the future trajectories of the Earth system. Our results show that a permanent shift to a hothouse state within the next few centuries is implausible. On longer time scales, however, tipping cascades can lead to enduring additional warming and particularly sea level rise.

How to cite: Couplet, V., Martínez Montero, M., and Crucifix, M.: Tipping cascades, future Earth system trajectories and the prospect of a hothouse: insights from the SURFER model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18045, https://doi.org/10.5194/egusphere-egu24-18045, 2024.

Rate-induced tipping (R-tipping) occurs when the forcing rate changes too rapidly for the system to track its quasi-equilibrium state, leading to an unexpected collapse. Currently, there is a lack of valid early warning signals (EWS) for R-tipping, particularly in the presence of noise perturbations. To address this deficiency, we employ a deep learning algorithm to extract the high-order structures hidden within time series data before R-tipping occurs. Then the trained neural networks are taken to provide real-time EWS for R-tipping, demonstrating skillful forecasts with a substantially long lead time, surpassing the performance of conventional critical slowing down indicators. Our progress underscores the predictability of R-tipping, offering the potential to improve the ability to deduce the safe operating space for a wider spectrum of complex systems.

How to cite: Huang, Y., Bathiany, S., Ashwin, P., and Boers, N.: Anticipating rate-induced tipping by a deep learning framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12187, https://doi.org/10.5194/egusphere-egu24-12187, 2024.

Recent studies utilizing the CMIP5 and CMIP6 model ensembles reveal that the subpolar North Atlantic (NA) is prone to deep convection collapsing leading to abrupt cooling of sea surface temperatures. Consequently, the latest comprehensive study on tipping points and the first report on global tipping points include the subpolar gyre (SPG) deep convection on the list of core tipping elements of Earth’s climate system.

Here, we investigate the drivers and impacts of a collapse of deep convection in the subpolar NA and the role of internal variability using a coupled climate model large ensemble (namely, the CESM2-LE consisting of 100 ensemble members) under the SSP3-7.0 forcing scenario. We identify that freshening of surface conditions leads to the negative surface density anomaly, eventually resulting in the cessation of deep mixing and the abrupt cooling of sea surface temperatures. The ensemble shows abrupt cooling occurring approximately in 2045 with internal variability leading to a spread of ±11 years. In each ensemble member, the subpolar NA transitions to a new state without deep convection, colder sea surface temperatures, strongly reduced heat loss to the atmosphere, and large circulation changes.

Internal variability does not determine if, but when abrupt cooling occurs, suggesting a forced response to larger-scale changes and a potential tipping point to be reached decades before the prominent abrupt cooling event. We provide evidence for the collapse of deep convection being a component of a positive feedback mechanism resulting in the SPG circulation transitioning to a weaker state. Without deep convection at the center of the circulation, the density gradient-driven part of the gyre circulation vanishes and the circulation strength decreases by approximately 50 %. The tipping point of the subpolar NA is therefore reached decades prior to the abrupt cooling and abrupt cooling is an inevitable consequence of the tipping event.

This points towards a potential misconception concerning drivers of abrupt climate
change in the subpolar NA, connected tipping points, and their thresholds, highlighting
the necessity for clarifying research efforts in the future.

How to cite: Müller, J., Zappa, G., and Bellucci, A.: North Atlantic Subpolar Gyre Deep Convection: A Tipping Point Reached Decades Ago?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5998, https://doi.org/10.5194/egusphere-egu24-5998, 2024.

The Atlantic Meridional Overturning Circulation (AMOC) is projected to weaken due to the increase in buoyancy caused by anthropogenic warming and consequent freshening during the 21^st century and beyond. Atmosphere-ocean general circulation models simulate this AMOC weakening due to warming of the surface ocean, changes in the hydrological cycle that shift the North Atlantic salt budget, melting sea-ice, and changes in the atmospheric circulation. However, the freshwater contribution from the melting Greenland ice sheet is often either only considered in idealized scenarios or entirely omitted due to computational constraints. This simplification contributes to the large uncertainty surrounding the possibility of the AMOC crossing a tipping point in the forthcoming centuries. Here we employ the fully coupled Earth system model of intermediate complexity Bern3D v3, which dynamically simulates all ice-ocean-atmosphere interactions. We conduct a set of simulations driven by idealized CO₂ concentration paths to investigate the impact of the melting Greenland ice sheet on the stability of the AMOC over the next 3000 years. We find that for a slow CO₂ increase of 0.5%/yr up to twice pre-industrial levels, the general trends of the AMOC evolution are independent of whether Greenland meltwater is taken into account, with an initial weakening, but long-term recovery. Yet, the additional meltwater results in a further weakening of about 3 Sv after 100 years, but without leading to a full collapse of the circulation. This effect is due to melt rates remaining relatively low for the initial 100 years and only reaching their peak after 500 years. In the long-term, the curtailed AMOC and hence northward heat transport substantially slows down the disintegration of the Greenland ice sheet. Only in scenarios where the melt rates are kept artificially high, the AMOC does not recover. This highlights that the meltwater-induced AMOC weakening stabilizes the Greenland ice sheet, which in turn limits further AMOC weakening. This suggests that the potential for cascading interactions may be limited.

How to cite: Pöppelmeier, F. and Stocker, T. F.: Impact of future Greenland ice sheet melt on the stability of the Atlantic Meridional Overturning Circulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3874, https://doi.org/10.5194/egusphere-egu24-3874, 2024.

Recent quasi-equilibrium studies performed in the Community Earth System Model (CESM) have revealed a bi-stable regime of the Atlantic Meridional Overturning Circulation (AMOC) in this model. This suggests that the present-day AMOC might exist in a bi-stable regime, emphasizing the need for accurate predictions regarding the probability of an AMOC collapse over the next decades. However, the CESM exhibits notable biases, with a critical freshwater transport bias at 34°S in the Atlantic emerging as a key determinant of AMOC stability. Specifically, this bias enhances the stability of the AMOC, rendering the CESM unable to accurately predict the likelihood of AMOC tipping.

In this study, we establish a direct connection between the freshwater transport bias in the CESM and a corresponding freshwater content bias in the Indian Ocean. By investigating the detailed freshwater balance, we identify specific regions within the Indian Ocean that exert a significant influence on the Atlantic freshwater transport bias at 34°S. This quantitative analysis enables us to construct an optimal surface-flux correction, which reduces the model biases. This physics-based surface-flux correction allows us to adjust the AMOC to its correct stability regime in the CESM without imposing unrealistic flux adjustments

How to cite: Vanderborght, E., Dijkstra, H., and Westen, R.: Origin in of the AMOC fresh water transport biases in a state-of-the-art climate model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11804, https://doi.org/10.5194/egusphere-egu24-11804, 2024.

The present-day Atlantic Meridional Overturning Circulation (AMOC) is considered to be a prominent tipping element and its collapse would have grave consequences on the global climate. Hence, it is important to determine probabilities and pathways for noise-induced tipping events. However, as there is no observational evidence for an AMOC transition over the historical period, a noise-induced transition is expected to be a rare event in models and simple Monte Carlo techniques are not suited for such low-probability events. Here, we use Large Deviation Theory to directly compute the most probable transition pathways for the collapse and recovery of the AMOC in a box model of the World Ocean calibrated to the FAMOUS-model, where we added stochastic freshwater forcing. This allows us to determine the physical mechanisms of noise-induced AMOC transitions. We show that the most likely path of an AMOC collapse starts paradoxically with a strengthening of the AMOC followed by an immediate drop within a couple of years due to a short but relatively strong freshwater pulse. The recovery on the other hand is a slow process, where the North Atlantic Ocean needs to be gradually salinified over a course of decades, and its dynamics are quite close to the recovery in a bifurcation tipping event. The proposed method provides several benefits, including an estimate of probability ratios of collapse between various freshwater noise scenarios, showing that the AMOC is most vulnerable to freshwater forcing into the Atlantic thermocline region.

How to cite: Soons, J., Grafke, T., and Dijkstra, H. A.: Optimal Transition Paths for AMOC Collapse and Recovery in a Stochastic Box Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4021, https://doi.org/10.5194/egusphere-egu24-4021, 2024.