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The Greenland Ice Sheet (GIS) and Atlantic Meridional Overturning Circulation (AMOC) are considered tipping elements in the climate system, where global warming exceeding critical threshold levels in forcing can lead to large-scale and nonlinear reductions in ice volume and overturning strength, respectively. The positive–negative feedback loop governing their interaction with a destabilizing effect on the AMOC due to ice loss and subsequent freshwater flux into the North Atlantic as well as a stabilizing effect of a net cooling around Greenland with an AMOC weakening may determine the long-term stability of both tipping elements. Here we explore the potential dynamic regimes arising from this positive–negative tipping feedback loop in a physically motivated conceptual model. Under idealized forcing scenarios we identify conditions under which different kinds of tipping cascades can occur: herein, we distinguish between overshoot/bifurcation tipping cascades, leading to tipping of both GIS and AMOC, and rate-induced tipping cascades, where the AMOC, despite not having crossed its own intrinsic tipping point, tips nonetheless due to the fast rate of ice loss from Greenland. The occurrence of these different cascades is affected by the ice sheet disintegration time and thus eventually by the imposed forcing and its timescales. Our results suggest that it is necessary not only to avoid surpassing the respective critical levels of the environmental drivers for the Greenland Ice Sheet and Atlantic Meridional Overturning Circulation, but also to respect safe rates of environmental change to mitigate potential domino effects. [ABSTRACT FROM AUTHOR]

In this review, we assess scientific evidence for tipping points in ocean and atmosphere circulations. The warming of oceans, modified wind patterns and increasing freshwater influx from melting ice hold the potential to disrupt established circulation patterns. The literature provides evidence for oceanic tipping points in the Atlantic Meridional Overturning Circulation (AMOC), the North Atlantic Subpolar Gyre (SPG), and the Antarctic Overturning Circulation, which may collapse under warmer and 'fresher' (i.e. less salty) conditions. A slowdown or collapse of these oceanic circulations would have far-reaching consequences for the rest of the climate system and could lead to strong impacts on human societies and the biosphere. Among the atmospheric circulation systems considered, we classify the West African monsoon as a tipping system. Its abrupt changes in the past have led to vastly different vegetation states of the Sahara (e.g. "green Sahara" states). Evidence about tipping of the monsoon systems over South America and Asia is limited however, there are multiple potential sources of destabilisation, including large-scale deforestation, air pollution, and shifts in other circulation patterns (in particular the AMOC). Although theoretically possible, there is currently little indication for tipping points in tropical clouds or mid-latitude atmospheric circulations. Similarly, tipping towards a more extreme or persistent state of the El Niño-Southern Oscillation (ENSO) is currently not fully supported by models and observations. While the tipping thresholds for many of these systems are uncertain, tipping could have severe socio-environmental consequences. Stabilising Earth's climate (along with minimising other environmental pressures, like aerosol pollution and ecosystem degradation) is critical for reducing the likelihood of reaching tipping points in the ocean-atmosphere system. [ABSTRACT FROM AUTHOR]

How do social networks tip? A popular theory is that a small minority can affect network, or population wide change. This effect is roughly consistent with the properties of the Pareto principle, a semi-quantitative law which suggests that in many systems, 80 % of effects are produced by only 20 % of the causes. In the context of the transition to net-zero emissions, this vital 20 % can be a critical instigator of social tipping, a process which can rapidly accelerate social norm change. In this work, we ask whether the Pareto effect can be observed in social systems by conducting a literature review with a focus on social norm diffusion and complex contagion on social networks. By collecting simulation and empirical results of social tipping events over a wide disciplinary, and parametric space, we are able to see the existence of shared behaviour across studies. Based on a compiled dataset, we show general support for the existence of a tipping point which occurs at around 25 % of the total population in susceptible social systems. Around this critical mass, there is a high likelihood of a social tipping event, where a large minority is then quickly "tipped". Additionally, we were able to show a range of critical masses where social tipping is possible, these values lie roughly between 10 % and 45 %. Finally, we also provide practical advice for facilitating norm changes under uncertainty, difficult social norm transitions, and social groups resistant to change. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet and Atlantic Meridional Overturning Circulation are considered tipping elements in the climate system, where global warming exceeding critical threshold levels in forcing can lead to large-scale and nonlinear reductions in ice volume and overturning strength, respectively. The positive-negative feedback loop governing their interaction (with a destabilizing effect on the AMOC due to ice loss and subsequent freshwater flux into the North Atlantic as well as a stabilizing effect of a net-cooling around Greenland with an AMOC weakening) may determine the long-term stability of both tipping elements. Here we explore the potential dynamic regimes arising from this positive-negative tipping feedback loop in a process-based conceptual model. Under idealized forcing scenarios we identify conditions under which different kinds of tipping cascades can occur: Herein, we distinguish between overshoot tipping cascades (leading to tipping of both GIS and AMOC) and rate-induced tipping cascades (where the AMOC despite not having crossed its own intrinsic tipping point tips nonetheless due to the fast rate of ice loss from Greenland). These different cascades occur within corridors of distinct tipping pathways that are affected by the GIS melting patterns and thus eventually by the imposed forcing and its time scales. Our results suggest that it is not only necessary to avoid breaching the respective critical levels of the environmental drivers for the Greenland Ice Sheet and Atlantic Meridional Overturning Circulation, but also to respect safe rates of environmental change to mitigate potential domino effects. [ABSTRACT FROM AUTHOR]

In recent years research on positive social tipping dynamics in response to the climate crisis has produced invaluable insights. In contrast, relatively little attention has been given to the potentially negative social dynamics that might arise due to an increasingly destabilised Earth system, and how they might in turn reinforce social destabilisation dynamics and/or impede positive social change. In this paper, we identify potential negative tipping elements linked to Earth System destabilisation and draw on related research to understand the drivers and likelihood of these negative tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks. This first attempt to provide a first explorative conceptualisation of negative social tipping dynamics is intended to motivate further research into an under-researched area that is nonetheless crucial for our ability to respond to the climate crisis and for ensuring that positive social tipping dynamics are not averted by negative ones. [ABSTRACT FROM AUTHOR]

Effective climate change mitigation necessitates swift societal transformations. Social tipping processes, where small triggers initiate qualitative systemic shifts, are potential key mechanisms instigating societal change. A necessary foundation for societal tipping processes is the creation of enabling conditions. Here we assess future sea-level rise estimates and social survey data within the framework of a social activation model to exemplify the enabling conditions for tipping processes. We find that in many countries, climate change concern is sufficient, the enabling conditions and opportunities for social activation already exist. Further, drawing upon the interrelation between climate change concern and anticipation of future sea level rise, we report three qualitative classes of tipping potential that are regionally clustered, with greatest potential for tipping in Western Pacific rim and East Asian countries. These findings propose a transformative pathway where climate change concern increases the social tipping potential, while extended anticipation time horizons can trigger the system towards an alternative trajectory of larger social activation for climate change mitigation. [ABSTRACT FROM AUTHOR]

The stability of the Greenland Ice Sheet under global warming is governed by a number of dynamic processes and interacting feedback mechanisms in the ice sheet, atmosphere and solid Earth. Here we study the long-term effects due to the interplay of the competing melt–elevation and glacial isostatic adjustment (GIA) feedbacks for different temperature step forcing experiments with a coupled ice-sheet and solid-Earth model. Our model results show that for warming levels above 2 ∘ C, Greenland could become essentially ice-free within several millennia, mainly as a result of surface melting and acceleration of ice flow. These ice losses are mitigated, however, in some cases with strong GIA feedback even promoting an incomplete recovery of the Greenland ice volume. We further explore the full-factorial parameter space determining the relative strengths of the two feedbacks: our findings suggest distinct dynamic regimes of the Greenland Ice Sheets on the route to destabilization under global warming – from incomplete recovery, via quasi-periodic oscillations in ice volume to ice-sheet collapse. In the incomplete recovery regime, the initial ice loss due to warming is essentially reversed within 50 000 years, and the ice volume stabilizes at 61 %–93 % of the present-day volume. For certain combinations of temperature increase, atmospheric lapse rate and mantle viscosity, the interaction of the GIA feedback and the melt–elevation feedback leads to self-sustained, long-term oscillations in ice-sheet volume with oscillation periods between 74 000 and over 300 000 years and oscillation amplitudes between 15 %–70 % of present-day ice volume. This oscillatory regime reveals a possible mode of internal climatic variability in the Earth system on timescales on the order of 100 000 years that may be excited by or synchronized with orbital forcing or interact with glacial cycles and other slow modes of variability. Our findings are not meant as scenario-based near-term projections of ice losses but rather providing insight into of the feedback loops governing the "deep future" and, thus, long-term resilience of the Greenland Ice Sheet. [ABSTRACT FROM AUTHOR]

The stability of the Greenland Ice Sheet under global warming is governed by a number of dynamic processes and interacting feedback mechanisms in the ice sheet, atmosphere and solid Earth. Here we study the long-term effects due to the interplay of the competing melt-elevation and glacial isostatic adjustment (GIA) feedbacks for different temperature step forcing experiments with a coupled ice-sheet and solid-Earth model. Our model results show that for warming levels above 2 °C, Greenland could become essentially ice-free on the long-term, mainly as a result of surface melting and acceleration of ice flow. These ice losses can be mitigated, however, in some cases with strong GIA feedback even promoting the partial recovery of the Greenland ice volume. We further explore the full-factorial parameter space determining the relative strengths of the two feedbacks: Our findings suggest distinct dynamic regimes of the Greenland Ice Sheets on the route to destabilization under global warming - from recovery, via quasi-periodic oscillations in ice volume to ice-sheet collapse. In the recovery regime, the initial ice loss due to warming is essentially reversed within 50,000 years and the ice volume stabilizes at 61-93 % of the present-day volume. For certain combinations of temperature increase, atmospheric lapse rate and mantle viscosity, the interaction of the GIA feedback and the melt-elevation feedback leads to self-sustained, long-term oscillations in ice-sheet volume with oscillation periods of tens to hundreds of thousands of years and oscillation amplitudes between 15-70 % of present-day ice volume. This oscillatory regime reveals a possible mode of internal climatic variability in the Earth system on time scales on the order of 100,000 years that may be excited by or synchronized with orbital forcing or interact with glacial cycles and other slow modes of variability. Our findings are not meant as scenario-based near-term projections of ice losses but rather providing insight into of the feedback loops governing the "deep future" and, thus, long-term resilience of the Greenland Ice Sheet. [ABSTRACT FROM AUTHOR]

In the Anthropocene, the social dynamics of human societies have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling of the human World are needed to address these challenges. The current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth system models, to hybrid macro-economic integrated assessments models, to a plethora of models of socio-cultural dynamics. World–Earth models capable of simulating complex and entangled human–Earth system processes of the Anthropocene are currently not available. They will need to draw on and selectively integrate elements from the diverse range of fields and approaches; thus, future World–Earth modellers require a structured approach to identify, classify, select, combine and critique model components from multiple modelling traditions. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e. the usual components of Earth system models); (ii) socio-cultural, dominated by processes of human behaviour, decision-making and collective social dynamics (e.g. politics, institutions, social networks and even science itself); and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g. human bodies, natural resources and agriculture). We show how higher-order taxonomies can be derived for classifying and describing the interactions between two or more subsystems. This then allows us to highlight the kinds of social–ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World–Earth system model that endogenises the socially transmitted choice of discount rates in a greenhouse gas emissions game to illustrate the effects of social–ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World–Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mass loss from the Antarctic Ice Sheet is the main source of uncertainty in projections of future sea-level rise, with important implications for coastal regions worldwide. Central to ongoing and future changes is the marine ice sheet instability: once a critical threshold, or tipping point, is crossed, ice internal dynamics can drive a self-sustaining retreat committing a glacier to irreversible, rapid and substantial ice loss. This process might have already been triggered in the Amundsen Sea region, where Pine Island and Thwaites glaciers dominate the current mass loss from Antarctica, but modelling and observational techniques have not been able to establish this rigorously, leading to divergent views on the future mass loss of the West Antarctic Ice Sheet. Here, we aim at closing this knowledge gap by conducting a systematic investigation of the stability regime of Pine Island Glacier. To this end we show that early warning indicators in model simulations robustly detect the onset of the marine ice sheet instability. We are thereby able to identify three distinct tipping points in response to increases in ocean-induced melt. The third and final event, triggered by an ocean warming of approximately 1.2 ∘ C from the steady-state model configuration, leads to a retreat of the entire glacier that could initiate a collapse of the West Antarctic Ice Sheet. [ABSTRACT FROM AUTHOR]

There exists a range of subsystems in the climate system exhibiting threshold behaviour which could be triggered under global warming within this century resulting in severe consequences for biosphere and human societies. While their individual tipping thresholds are fairly well understood, it is of yet unclear how their interactions might impact the overall stability of the Earth's climate system. This cannot be studied yet with state-of-the-art Earth system models due to computational constraints as well as missing and uncertain process representations of some tipping elements. Here, we explicitly study the effects of known physical interactions between the Greenland and West Antarctic Ice Sheet, the Atlantic Meridional Overturning Circulation, the El-Nino Southern Oscillation 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, propagating uncertainties in critical temperature thresholds and interaction strengths via a Monte-Carlo approach. Overall, we find that the interactions tend to destabilise the network. Furthermore, our analysis reveals the qualitative role of each of the five tipping elements 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 implies 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. [ABSTRACT FROM AUTHOR]

Analysis of Earth system dynamics in the Anthropocene requires explicitly taking into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere and their growing feedback entanglement with those in the physical, chemical and biological systems of the planet. However, current state-of-the-art Earth system models do not represent dynamic human societies and their feedback interactions with the biogeophysical Earth system and macroeconomic integrated assessment models typically do so only with limited scope. This paper (i) proposes design principles for constructing world–Earth models (WEMs) for Earth system analysis of the Anthropocene, i.e., models of social (world)–ecological (Earth) coevolution on up to planetary scales, and (ii) presents the copan:CORE open simulation modeling framework for developing, composing and analyzing such WEMs based on the proposed principles. The framework provides a modular structure to flexibly construct and study WEMs. These can contain biophysical (e.g., carbon cycle dynamics), socio-metabolic or economic (e.g., economic growth or energy system changes), and sociocultural processes (e.g., voting on climate policies or changing social norms) and their feedback interactions, and they are based on elementary entity types, e.g., grid cells and social systems. Thereby, copan:CORE enables the epistemic flexibility needed for contributions towards Earth system analysis of the Anthropocene given the large diversity of competing theories and methodologies used for describing socio-metabolic or economic and sociocultural processes in the Earth system by various fields and schools of thought. To illustrate the capabilities of the framework, we present an exemplary and highly stylized WEM implemented in copan:CORE that illustrates how endogenizing sociocultural processes and feedbacks such as voting on climate policies based on socially learned environmental awareness could fundamentally change macroscopic model outcomes. [ABSTRACT FROM AUTHOR]

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model–data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model–data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model–data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. [ABSTRACT FROM AUTHOR]

Understanding Earth system dynamics in the light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing inter-disciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept ofEarth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model-data. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple time-scales; and (3) data-model integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. Latest developments in machine learning, causal inference, and model data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. [ABSTRACT FROM AUTHOR]

Changes to climate-carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate-carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate-carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate-carbon feedback; and concentration-carbon feedbacks may be more sensitive to future climate change than climate-carbon feedbacks. Simple models such as that developed here also provide "workbenches" for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models. [ABSTRACT FROM AUTHOR]

In the Anthropocene, social processes have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling are needed to address these challenges, but the current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth System Models, to hybrid macro-economic Integrated Assessments Models, to a plethora of models of socio-cultural dynamics. World-Earth models, currently not yet available, will need to integrate all these elements, so future World-Earth modellers require a structured approach to identify, classify, select, and combine model components. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e., the usual components of Earth system models), (ii) socio-cultural, dominated by processes of human behaviour, decision making and collective social dynamics (e.g., politics, institutions, social networks), and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g., human bodies, natural resource and agriculture). We show how higher-order taxonomies for interactions between two or more subsystems can be derived, highlighting the kinds of social-ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World-Earth system model of socially transmitted discount rates in a greenhouse gas emissions game to illustrate the effects of social-ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World-Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene. [ABSTRACT FROM AUTHOR]

Possible future trajectories of the Earth system in the Anthropocene are determined by the increasing entanglement of processes operating in the physical, chemical and biological systems of the planet, as well as in human societies, their cultures and economies. Here, we introduce the copan:CORE open source software library that provides a framework for developing, composing and running World-Earth models, i.e., models of social-ecological co-evolution up to planetary scales. It is an object-oriented software package written in Python designed for different user roles. It allows model end users to run parallel simulations with already available and tested models. Furthermore, model composers are enabled to easily implement new models by plugging together a broad range of model components, such as opinion formation on social networks, generic carbon cycle dynamics, or simple vegetation growth. For the sake of a modular structure, each provided component specifies a meaningful yet minimal collection of closely related processes. These processes can be formulated in terms of various process types, such as ordinary differential equations, explicit or implicit functions, as well as steps or events of deterministic or stochastic fashion. In addition to the already included variety of different components in copan:CORE, model developers can extend the framework with additional components that are based on elementary entity types, i.e., grid cells, individuals and social systems, or the fundamental process taxa environment, social metabolism, and culture. To showcase possible usage we present an exemplary World-Earth model that combines a variety of model components and interactions thereof. As the framework allows a simple activation and deactivation of certain components and related processes, users can test for their specific effects on modeling results and evaluate model robustness in a controlled way. Hence, copan:CORE allows developing process-based models of global change and sustainable development in planetary social-ecological systems and thus fosters a better understanding of crucial mechanisms governing the co-evolutionary dynamics between societies and the natural environment. Due to its modular structure, the framework enhances the development and application of stylized models in Earth system science but also climatology, economics, ecology, or sociology, and allows combining them for interdisciplinary studies at the interface between different areas of expertise. [ABSTRACT FROM AUTHOR]

Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR), identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log-log space. For instance, networks with ≈100 randomly placed sites in Europe yield a ≥90% chance of detecting the eight largest (typically very large) extreme events; but only a ≥50% chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON) reliably detect the largest extremes, but that the extreme event detection rates are not higher than would be achieved by randomly designed networks. Spatio-temporal expansions of ecological in situ monitoring networks should carefully consider the size distribution characteristics of extreme events if the aim is also to monitor the impacts of such events in the terrestrial biosphere. [ABSTRACT FROM AUTHOR]

Changes to climate-carbon cycle feedbacks may significantly affect the Earth System's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth System Models (ESMs). Here, we construct a stylized global climate-carbon cycle model, test its output against complex ESMs, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon-cycle feedbacks and the operation of the carbon cycle. We use our results to analytically study the relative strengths of different climate-carbon cycle feedbacks and how they may change in the future, as well as to compare different feedback formalisms. Simple models such as that developed here also provide "workbenches" for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the Planetary Boundaries, that are currently too uncertain to be included in complex ESMs. [ABSTRACT FROM AUTHOR]

Human societies depend on the resources ecosystems provide. Particularly since the last century, human activities have transformed the relationship between nature and society at a global scale. We study this coevolutionary relationship by utilizing a stylized model of private resource use and social learning on an adaptive network. The latter process is based on two social key dynamics beyond economic paradigms: boundedly rational imitation of resource use strategies and homophily in the formation of social network ties. The private and logistically growing resources are harvested with either a sustainable (small) or non-sustainable (large) effort. We show that these social processes can have a profound influence on the environmental state, such as determining whether the private renewable resources collapse from overuse or not. Additionally, we demonstrate that heterogeneously distributed regional resource capacities shift the critical social parameters where this resource extraction system collapses. We make these points to argue that, in more advanced coevolutionary models of the planetary social-ecological system, such socio-cultural phenomena as well as regional resource heterogeneities should receive attention in addition to the processes represented in established Earth system and integrated assessment models. [ABSTRACT FROM AUTHOR]

The planetary boundaries framework provides guidelines for defining thresholds in environmental variables. Their transgression is likely to result in a shift in Earth system functioning away from the relatively stable Holocene state. As the climate system is approaching critical thresholds of atmospheric carbon, several climate engineering methods are discussed, aiming at a reduction of atmospheric carbon concentrations to control the Earth's energy balance. Terrestrial carbon dioxide removal (tCDR) via afforestation or bioenergy production with carbon capture and storage are part of most climate change mitigation scenarios that limit global warming to less than 2 °C. We analyse the co-evolutionary interaction of societal interventions via tCDR and the natural dynamics of the Earth's carbon cycle. Applying a conceptual modelling framework, we analyse how the degree of anticipation of the climate problem and the intensity of tCDR efforts with the aim of staying within a "safe" level of global warming might influence the state of the Earth system with respect to other carbon-related planetary boundaries. Within the scope of our approach, we show that societal management of atmospheric carbon via tCDR can lead to a collateral transgression of the planetary boundary of land system change. Our analysis indicates that the opportunities to remain in a desirable region within carbon-related planetary boundaries only exist for a small range of anticipation levels and depend critically on the underlying emission pathway. While tCDR has the potential to ensure the Earth system's persistence within a carbon-safe operating space under low-emission pathways, it is unlikely to succeed in a business-as-usual scenario. [ABSTRACT FROM AUTHOR]

Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering. [ABSTRACT FROM AUTHOR]

Changes in land-use systems in tropical regions, including deforestation, are a key challenge for global sustainability because of their huge impacts on green-house gas emissions, local climate and biodiversity. However, the dynamics of land-use and land-cover change in regions of frontier expansion such as the Brazilian Amazon is not yet well understood because of the complex interplay of ecological and socio-economic drivers. In this paper, we combine Markov chain analysis and complex network methods to identify regimes of land-cover dynamics from land-cover maps (TerraClass) derived from high-resolution (30 m) satellite imagery. We estimate regional transition probabilities between different land-cover types and use clustering analysis and community detection algorithms on similarity networks to explore patterns of dominant land-cover transitions. We find that land-cover transition probabilities in the Brazilian Amazon are heterogeneous in space and adjacent subregions tend to be assigned to the same clusters. When focusing on transitions from single land-cover types, we uncover patterns that reflect major regional differences in land-cover dynamics. Our method is able to summarize regional patterns and thus complements studies performed at the local scale. [ABSTRACT FROM AUTHOR]

Safely achieving the goals of the Paris Climate Agreement requires a world-wide transformation to carbon-neutral societies within the next 30 years. Despite decades-long efforts in international negotiations, not much progress has been achieved and few are convinced that business-as-usual technological progress and gradual policy implementations will deliver emissions reductions at rates sufficiently fast to avoid crossing dangerous tipping points in the Earth's climate system. Here, we present historical, recent empirical and theoretical evidence supporting the potential of social tipping elements (STEs) as drivers of the required disruptive change. STEs are subdomains of the planetary socio-economic system where targeted policy interventions can activate contagious processes of rapid spreading of technologies, behaviors and social norms that can ultimately propel a sufficiently fast reduction in anthropogenic greenhouse gas emissions. We identify six outstanding candidates for STEs and their associated critical intervention points based on online expert elicitation, a subsequent expert workshop, and a literature review. These critical social tipping interventions include (i) removing fossil fuel subsidies and incentivizing distributed energy generation (STE1: energy production and storage systems), (ii) building carbon-neutral cities (STE2: human settlements), (iii) divestments from assets linked to fossil fuels (STE3: financial markets), (iv) revealing the moral implications of fossil fuels (STE4: norms and value systems), (v) strengthened climate education and engagement (STE5: education system) and (vi) greenhouse gas emissions information disclosure (STE6: information feedbacks). Larger-scale empirical and modelling efforts are needed to understand the potentials of STE dynamics and their role in climate change mitigation pathways in more detail. [ABSTRACT FROM AUTHOR]

Analysis of Earth system dynamics in the Anthropocene requires to explicitly take into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere and their growing entanglement with those in the physical, chemical and biological systems of the planet. This work (i) introduces design principles for constructing World-Earth models (WEM), i.e., models of social-ecological co-evolution on up to planetary scales, and (ii) presents the copan:CORE open source software library that provides a simulation modeling framework for developing, composing and running such WEMs based on the proposed principles. copan:CORE is an object-oriented software package currently implemented in Python. It provides components of meaningful yet minimal collections of closely related processes in the Earth System that can be plugged together in order to compose and run WEMs. Developers can supplement the already existing model components with additional components that are based on elementary entity types, e.g., grid cells, or fundamental process taxa, e.g., environment or culture. To illustrate the capabilities of the framework, this paper presents a WEM example implemented in copan:CORE that combines a variety of model components and interactions thereof. Due to its modular structure, the simulation modeling framework enhances the development and application of integrated models in Earth system science but also climatology, economics, ecology, or sociology, and allows combining them for interdisciplinary studies such as risk assessment including explicitly the dynamics of human behavior and decision making. [ABSTRACT FROM AUTHOR]