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VIII. Pedia Sapiens: A New Genesis Future

2. Global Climate Change as a Complex Dynamical System

This is new subsection added in 2011 about how the hyper-complex intricacy of world weather, which is traced from paleological times, is coming to be appreciated, distinguished, and quantified by the same nonlinear critically self-organizing, scalar dynamics as everywhere else. Again the universal one code is present even in this stormy realm. In regard, "global warming" phase is an unfortunate misnomer for these nonlinear currents then portend abrupt, catastrophic change as more likely. It would serve climate scientists, under siege from well-funded deniers, to cite themselves say as “physicians of the planet” givine wellness and illness reports. See Geosphere, Hydrospehre, and Atmosphere for further entries.

2020: As a viral pandemic ravages, it is said that the intense scientific and public effort being marshalled ought to next be applied to deal with and migate wild atmospheric climate changes, indeed a planetdemic for which we similarly need adapt sensible behaviors and expenditures.

Boers, Niklas, et al. Complex Networks Reveal Global Pattern of Extreme Rainfall Teleconnections. Nature Climate Change. January 30, 2019.

Fan, Jingfang, et al. Statistical Physics Approaches to the Complex Earth System. arXiv:2009.04918.

Franzke, Christian and Terence O’Kane, eds. Nonlinear and Stochastic Climate Dynamics. Cambridge: Cambridge University Press, 2017.

Lucarini, Valerio. Introduction to the Special Issue on the Statistical Mechanics of Climate. Journal of Statistical Physics. 179/5-6, 2020.

Lovejoy, Shaun and Daniel Schertzer. The Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge: Cambridge University Press, 2013.

Palmer, Tim and Bjorn Stevens. The Scientific Challenge of Understanding and Estimating Climate Change. Proceedings of the National Academy of Sciences. 116/24390, 2019.

Selvam, Amujuri Mary. Self-Organized Criticality and Predictability in Atmospheric Flows: The Quantum World of Clouds and Rain. International: Springer, 2017.

Yalcin, G. Cigdem, et al. Extreme Event Statistics of Daily Rainfall: Dynamical Systems Approach. Journal of Physics A. 49/154001, 2016.

American Physical Society Topical Group on the Physics of Climate. www.aps.org/units/gpc/index.cfm. As reported in the New York Times by Andrew Revkin on February 2, 2012, in “Two Nobelists Offer Views of Human-Driven Global Warming” about scientists now standing against deniers and smearers, this national organization has initiated this effort to apply physical and mathematical insights to our real planetary peril. The APS journal Physics Today, in its February 2012 issue, carries a similar report by Tom Feder “Climate Scientists not Cowed by Relentless Climate Change Deniers.”

The objective of the GPC shall be to promote the advancement and diffusion of knowledge concerning the physics, measurement, and modeling of climate processes, within the domain of natural science and outside the domains of societal impact and policy, legislation and broader societal issues. The objective includes the integration of scientific knowledge and analysis methods across disciplines to address the dynamical complexities and uncertainties of climate physics. Broad areas of initial scientific inquiry are described in the Areas of Interest below. These are expected to evolve with scientific progress, while remaining entirely within the domain of natural science.

Climate as a complex dynamical system, leading to a better understanding of the natural modes of the climate system, their coupling to each other and to exogenous forces. The physics of proxies used to infer the properties of past climates for which instrumental records are not available, leading to a better understanding of past climates and their relation to the present climate. The computational physics and statistical analysis of climate model and measurement systems, leading to a better understanding of the methods, capabilities, and limitations of climate models and climate simulation predictions. Specific natural science areas underlying these issues include fluid dynamics, modeling of nonlinear systems, the physics of complex systems, gas phase physics and chemistry, radiation/heat transfer, phase transitions, measurement science, computational physics, statistics, and biological physics. (Website)

Shaun Lovejoy Website. www.physics.mcgill.ca/~gang/Lovejoy.htm. The home site for the McGill University geophysicist at the forefront of understanding of earth’s atmosphere by way of nonlinear multifractal computations such as Mathematicia software and satellite imaging. The “gang” above is the “Group for the Analysis of Nonlinear variability in Geophysics,” whose interests run from soils and hydrology to cloud convections and aerosol emissions, each by way of multifractal dynamics. From this site many PDF papers can be accessed, with multiple authors, such as “Towards a New Synthesis for Atmospheric Dynamics” in press for the journal Atmospheric Research (96/01004, 2010). A New Scientist report “And Now the Forecast: Cloudy with a Chance of Fractals” extols these novel advances (November 7, 2009, search).

My research has been directly linked to a series of new geophysical paradigms. A particularly exciting one is the idea that atmospheric dynamics repeat scale after scale from large to small scales in a cascade-like way. The key is recognizing that as the scales get smaller, the horizontal gets “squashed” much more than the vertical so that the stratification which starts out being extreme (structures very flat at planetary scales) become rounder and rounder at small scales.

Barnosky, Anthony, et al. Approaching a State Shift in Earth’s Biosphere. Nature. 486/52, 2012. Some 22 researchers from the University of California, Berkeley, Stanford University, Integrative Ecology Group, Estacion Biologica de Donana, Spain, University of New Mexico, University of Helsinki, Pontificia Universidad Catolica de Chile, Simon Fraser University, California Academy of Sciences, University of Wisconsin, and Missouri Botanical Garden, including Jordi Boscompte, James Brown, John Harte, Pablo Marquet, Geerat Vermeij, and Rosemary Gillespie, seriously worry by way of realistic nonlinear “planetary-scale critical transitions” about an increasingly imminent, forced, epochal climate change.

Localized ecological systems are known to shift abruptly and irreversibly from one state to another when they are forced across critical thresholds. Here we review evidence that the global ecosystem as a whole can react in the same way and is approaching a planetary-scale critical transition as a result of human influence. The plausibility of a planetary-scale ‘tipping point’ highlights the need to improve biological forecasting by detecting early warning signs of critical transitions on global as well as local scales, and by detecting feedbacks that promote such transitions. It is also necessary to address root causes of how humans are forcing biological changes. (Abstract)

Bathiany, Sebastion, et al. Abrupt Climate Change in an Oscillating World. Nature Scientific Reports. 8/5040, 2018. Wageningen University and University of Exeter researchers including Marten Scheffer and Tim Lenton push the concept of global weather as a dynamic complex nonlinear phenomenon to an inevitable consequence. As it becomes more energetically perturbed in small and large ways, a “tipping point” of maximum instability will be reached, untoward, whence the whole system will suddenly oscillate to a radical new set condition on its own.

Here we show how abrupt and sometimes even irreversible change may be evoked by even small shifts in the amplitude or time scale of such environmental oscillations. By using model simulations and reconciling evidence from previous studies we illustrate how these phenomena can be relevant for ecosystems and elements of the climate system including terrestrial ecosystems, Arctic sea ice and monsoons. Although the systems we address are very different and span a broad range of time scales, the phenomena can be understood in a common framework that can help clarify and unify the interpretation of abrupt shifts in the Earth system. (Abstract excerpt)

Berezin, Yehiel, et al. Stability of Climate Networks with Time. Nature Scientific Reports. 2/666, 2012. The online journal places this in a “Statistical Physics, Thermodynamics and Nonlinear Dynamics” section. With coauthors Avi Gozolchiani, Oded Guez, and Shlomo Havlin, Bar Ilan University physicists contribute to the imperative challenge of defining a “Systems Climatology,” whence nature’s universal intricacies can be equally availed in this ultra-complex local and global weather realm to better quantify, and surely mediate.

The pattern of local daily fluctuations of climate fields such as temperatures and geopotential heights is not stable and hard to predict. Surprisingly, we find that the observed relations between such fluctuations in different geographical regions yields a very robust network pattern that remains highly stable during time. Using a new systematic methodology we track the origins of the network stability. It is found that about half of this network stability is due to the spatial 2D embedding of the network, and half is due to physical coupling between climate in different locations. We also find that around the equator, the contribution of the physical coupling is significantly less pronounced compared to off–equatorial regimes. Finally, we show that there is a gradual monotonic modification of the network pattern as a function of altitude difference. (Abstract)

These latest advances show us the extent to which the climate system share common features with network models. Following these landmarks, a large body of theoretical works which emerged in the last 20 years can now be exploited in the field of climate. A similar scientific pathway was found useful in the research of food webs, protein molecules, social systems, human languages, infrastructures, finance, and interaction between physiological systems in our body, just to name a few. (1)

Bodai, Tamas and Tamas Tel. Annual Variability in a Conceptual Climate Model: Snapshot Attractors, Hysteresis in Extreme Events, and Climate Sensitivity. Chaos. 22/023110, 2012. Max Planck Institute, Physics of Complex Systems, researchers investigate such wild weather, which is seen to exhibit the classic features of dynamical phenomena.

We have investigated the effect of periodic driving on a conceptual climate model. In spite of the temporal simplicity of the driving, 2D snapshot attractors proved to be useful representations of the dynamics and show fractal features throughout the annual cycle, which owes to the fact that transient chaos and chaotic saddles are ubiquitous in the considered parameter regimes. (023110-9)

Boers, Niklas, et al. Complex Networks Reveal Global Pattern of Extreme Rainfall Teleconnections. Nature Climate Change. January 30, 2019. Six atmosphere physicists including Jurgen Kurths with postings in the UK, Germany, and Russia quantify how even this liquid feature of regional and world weather can be found to exhibit nature’s intrinsic dynamics and topologies.

Climatic observables can be correlated across long spatial distances, and extreme events, such as heat waves or floods, are often related to such teleconnection. Here we display the global coupling pattern of extreme rainfall events by detecting complex networks in satellite data. We find that the distance distribution of significant connections around the globe decays via a power law up to distances of about 2,500 kilometres. We show that extreme-rainfall events in the monsoon systems of south-central Asia, east Asia and Africa are significantly synchronized. Analysis of the atmospheric conditions that lead to these global teleconnections confirms Rossby waves as the physical mechanism underlying these patterns. (Abstract excerpt)

Boers, Niklas, et al. Prediction of Extreme Floods in the Eastern Central Andes based on a Complex Networks Approach. Nature Communications. 5/5199, 2014. Humboldt University, UC Santa Barbara, and University of Sao Paulo researchers including Jurgen Kurths achieve a working mathematical representation of such weather phenomena by way of dynamic nonlinear theories. See also Complex Network Analysis Helps to Identify Impacts of the El Nino Southern Oscillation on Moisture Divergence in South America in Climate Dynamics (45/3-4, 2015) and Complex Networks for Climate Model Evaluation with Application to Statistical versus Dynamical Modeling of South American Climate (44/5-6, 2015), by this team, and the full journal, for further progress.

Changing climatic conditions have led to a significant increase in the magnitude and frequency of extreme rainfall events in the Central Andes of South America. These events are spatially extensive and often result in substantial natural hazards for population, economy and ecology. Here we develop a general framework to predict extreme events by introducing the concept of network divergence on directed networks derived from a non-linear synchronization measure. We apply our method to real-time satellite-derived rainfall data and predict more than 60% (90% during El Niño conditions) of rainfall events above the 99th percentile in the Central Andes. In addition to the societal benefits of predicting natural hazards, our study reveals a linkage between polar and tropical regimes as the responsible mechanism: the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics. (Abstract)

Cheung, Kevin and Ugur Osturk. Synchronization of Extreme Rainfall During the Australian Monsoon: Complex Network Perspectives. Chaos. 30/6, 2020. Macquarrie University and GeoForschungsZentrum, Potsdam systems environmentalists describe how network centrality measures such as degree and local clustering are suitable for and can be graphed unto active stormy weather.

Dijkstra, Henk. Nonlinear Climate Dynamics. Cambridge: Cambridge University Press, 2013. A Professor of Dynamical Oceanography at the Institute for Marine and Atmospheric Research, Utrecht University, offers an overdue re-assessment of our ultra-intricate and variable local and global weather in terms of mathematical systems science. Chapters range from Climate Variability, Stochastic Dynamical Systems, and Climate Modelling Hierarchy, to the North Atlantic Oscillation, El Nino, Pleistocene Ice Ages, and onto Predictability. While still weighted more toward physical mechanism than self-organizing networks, a turn in a better direction if we are ever to understand and resolve.

This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic extension also forms the basis of modern (nonlinear) data analysis techniques, predictability studies and data assimilation methods. Early chapters apply the stochastic dynamical systems framework to a hierarchy of climate models to synthesize current knowledge of climate variability. Later chapters analyse phenomena such as the North Atlantic Oscillation, El Niño/Southern Oscillation, Atlantic Multidecadal Variability, Dansgaard-Oeschger Events, Pleistocene Ice Ages, and climate predictability. This book will prove invaluable for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology. (Publisher)

Dijkstra, Henk, et al. Networks in Climate. Cambridge: Cambridge University Press, 2019. Four authors posted in the Netherlands, Spain and Uruguay contribute to later 2010s abilities by which even world wild weather can be quantified and understood by way of nonlinear, self-organizing systems and topologies. Typical topics cover how to analyze the presence of atmospheric connectivities, oceanic El Nino wave dynamics, tipping behaviors, Indian monsoon and much more.

Donges, Jonathan, et al. Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World-Earth modeling framework. arXic:1909.13697. A dozen German and Swedish scientists with a main base at the Potsdam Institute for Climate Impact Research proceed with a comprehensive program going forward to gain ever better analyses, quantifications and hopefully sustainable remediations of our hyper-active global atmosphere and consumptive societal-industrial civilization. In regard we need to get a real sense of Earthkinder taking care of her/his self and do all we personally and collaboratively do to facilitate and survive.

Earth system dynamics in the Anthropocene need to well take into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere, along with their entanglement with physical, chemical and biological global systems. This paper (i) proposes design principles for constructing World-Earth Models (WEM) for Earth system analysis of the Anthropocene, i.e., models of social (World) - ecological co-evolution 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 modular principles. Thereby, copan:CORE enables the epistemic flexibility needed for Earth system analysis of the Anthropocene given the diverse theories and methodologies used for describing socio-metabolic/economic and socio-cultural processes. (Abstract)

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