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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]

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]

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]

Optimizing economic welfare in environmental governance has been criticized for delivering short-term gains at the expense of long-term environmental degradation. Different from economic optimization, the concepts of sustainability and the more recent safe operating space have been used to derive policies in environmental governance. However, a formal comparison between these three policy paradigms is still missing, leaving policy makers uncertain which paradigm to apply. Here, we develop a better understanding of their interrelationships, using a stylized model of human-environment tipping elements. We find that no paradigm guarantees fulfilling requirements imposed by another paradigm and derive simple heuristics for the conditions under which these trade-offs occur. We show that the absence of such a master paradigm is of special relevance for governing real-world tipping systems such as climate, fisheries, and farming, which may reside in a parameter regime where economic optimization is neither sustainable nor safe. [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]