Earth's Complexity Is Non-Computable: The Limits of Scaling Laws, Nonlinearity and Chaos.

Current physics commonly qualifies the Earth system as 'complex' because it includes numerous different processes operating over a large range of spatial scales, often modelled as exhibiting non-linear chaotic response dynamics and power scaling laws. This characterization is based on the fundamental assumption that the Earth's complexity could, in principle, be modeled by (surrogated by) a numerical algorithm if enough computing power were granted. Yet, similar numerical algorithms also surrogate different systems having the same processes and dynamics, such as Mars or Jupiter, although being qualitatively different from the Earth system. Here, we argue that understanding the Earth as a complex system requires a consideration of the Gaia hypothesis: the Earth is a complex system because it instantiates life-and therefore an autopoietic, metabolic-repair (M,R) organization-at a planetary scale. This implies that the Earth's complexity has formal equivalence to a self-referential system that inherently is non-algorithmic and, therefore, cannot be surrogated and simulated in a Turing machine. We discuss the consequences of this, with reference to in-silico climate models, tipping points, planetary boundaries, and planetary feedback loops as units of adaptive evolution and selection.

Value management and model pluralism in climate science.

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed "epistemic inequality": this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections.

Survival of the Systems.

Since Darwin, individuals and more recently genes, have been the focus of evolutionary thinking. The idea that selection operates on nonreproducing, higher-level systems including ecosystems or societies, has met with scepticism. But research emphasising that natural selection can be based solely on differential persistence invites reconsideration of their evolution. Self-perpetuating feedback cycles involving biotic as well as abiotic components are critical to determining persistence. Evolution of autocatalytic networks of molecules is well studied, but the principles hold for any 'self-perpetuating' system. Ecosystem examples include coral reefs, rainforests, and savannahs. Societal examples include agricultural systems, dominant belief systems, and economies. Persistence-based selection of feedbacks can help us understand how ecological and societal systems survive or fail in a changing world.

Multi-model ensembles in climate science: Mathematical structures and expert judgements.

Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: "How can ensemble studies be designed so that they probe uncertainty in desired ways?" This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by "plugging and playing" with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs.

Diverse manifestations of the mid-Pleistocene climate transition.

The mid-Pleistocene transition (MPT) is widely recognized as a shift in paleoclimatic periodicity from 41- to 100-kyr cycles, which largely reflects integrated changes in global ice volume, sea level, and ocean temperature from the marine realm. However, much less is known about monsoon-induced terrestrial vegetation change across the MPT. Here, on the basis of a 1.7-million-year δ13C record of loess carbonates from the Chinese Loess Plateau, we document a unique MPT reflecting terrestrial vegetation changes from a dominant 23-kyr periodicity before 1.2 Ma to combined 100, 41, and 23-kyr cycles after 0.7 Ma, very different from the conventional MPT characteristics. Model simulations further reveal that the MPT transition likely reflects decreased sensitivity of monsoonal hydroclimate to insolation forcing as the Northern Hemisphere became increasingly glaciated through the MPT. Our proxy-model comparison suggests varied responses of temperature and precipitation to astronomical forcing under different ice/CO2 boundary conditions, which greatly improves our understanding of monsoon variability and dynamics from the natural past to the anthropogenic future.

Trajectories of the Earth System in the Anthropocene.

We explore the risk that self-reinforcing feedbacks could push the Earth System toward a planetary threshold that, if crossed, could prevent stabilization of the climate at intermediate temperature rises and cause continued warming on a "Hothouse Earth" pathway even as human emissions are reduced. Crossing the threshold would lead to a much higher global average temperature than any interglacial in the past 1.2 million years and to sea levels significantly higher than at any time in the Holocene. We examine the evidence that such a threshold might exist and where it might be. If the threshold is crossed, the resulting trajectory would likely cause serious disruptions to ecosystems, society, and economies. Collective human action is required to steer the Earth System away from a potential threshold and stabilize it in a habitable interglacial-like state. Such action entails stewardship of the entire Earth System-biosphere, climate, and societies-and could include decarbonization of the global economy, enhancement of biosphere carbon sinks, behavioral changes, technological innovations, new governance arrangements, and transformed social values.

Model evidence for a seasonal bias in Antarctic ice cores.

Much of the global annual mean temperature change over Quaternary glacial cycles can be attributed to slow ice sheet and greenhouse gas feedbacks, but analysis of the short-term response to orbital forcings has the potential to reveal key relationships in the climate system. In particular, obliquity and precession both produce highly seasonal temperature responses at high latitudes. Here, idealized single-forcing model experiments are used to quantify Earth's response to obliquity, precession, CO2, and ice sheets, and a linear reconstruction methodology is used to compare these responses to long proxy records around the globe. This comparison reveals mismatches between the annual mean response to obliquity and precession in models versus the signals within Antarctic ice cores. Weighting the model-based reconstruction toward austral winter or spring reduces these discrepancies, providing evidence for a seasonal bias in ice cores.

Lessons on Climate Sensitivity From Past Climate Changes.

Over the last decade, our understanding of climate sensitivity has improved considerably. The climate system shows variability on many timescales, is subject to non-stationary forcing and it is most likely out of equilibrium with the changes in the radiative forcing. Slow and fast feedbacks complicate the interpretation of geological records as feedback strengths vary over time. In the geological past, the forcing timescales were different than at present, suggesting that the response may have behaved differently. Do these insights constrain the climate sensitivity relevant for the present day? In this paper, we review the progress made in theoretical understanding of climate sensitivity and on the estimation of climate sensitivity from proxy records. Particular focus lies on the background state dependence of feedback processes and on the impact of tipping points on the climate system. We suggest how to further use palaeo data to advance our understanding of the currently ongoing climate change.

Oscillators and relaxation phenomena in Pleistocene climate theory.

Ice sheets appeared in the northern hemisphere around 3 Ma (million years) ago and glacial-interglacial cycles have paced Earth's climate since then. Superimposed on these long glacial cycles comes an intricate pattern of millennial and sub-millennial variability, including Dansgaard-Oeschger and Heinrich events. There are numerous theories about these oscillations. Here, we review a number of them in order to draw a parallel between climatic concepts and dynamical system concepts, including, in particular, the relaxation oscillator, excitability, slow-fast dynamics and homoclinic orbits. Namely, almost all theories of ice ages reviewed here feature a phenomenon of synchronization between internal climate dynamics and astronomical forcing. However, these theories differ in their bifurcation structure and this has an effect on the way the ice age phenomenon could grow 3 Ma ago. All theories on rapid events reviewed here rely on the concept of a limit cycle excited by changes in the surface freshwater balance of the ocean. The article also reviews basic effects of stochastic fluctuations on these models, including the phenomenon of phase dispersion, shortening of the limit cycle and stochastic resonance. It concludes with a more personal statement about the potential for inference with simple stochastic dynamical systems in palaeoclimate science.