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search.filters.applied.f.access: openAccess × Author: Donges, Jonathan F. × DDC: 550 × Has files: Yes × Publisher: Göttingen : Copernicus Publ. × Subject: Climate models ×

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    Earth system data cubes unravel global multivariate dynamics
    (Göttingen : Copernicus Publ., 2020) Mahecha, Miguel D.; Gans, Fabian; Brandt, Gunnar; Christiansen, Rune; Cornell, Sarah E.; Fomferra, Normann; Kraemer, Guido; Peters, Jonas; Bodesheim, Paul; Camps-Valls, Gustau; Donges, Jonathan F.; Dorigo, Wouter; Estupinan-Suarez, Lina M.; Gutierrez-Velez, Victor H.; Gutwin, Martin; Jung, Martin; Londoño, Maria C.; Miralles, Diego G.; Papastefanou, Phillip; Reichstein, Markus
    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. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
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    Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World–Earth modeling framework
    (Göttingen : Copernicus Publ., 2020) Donges, Jonathan F.; Heitzig, Jobst; Barfuss, Wolfram; Wiedermann, Marc; Kassel, Johannes A.; Kittel, Tim; Kolb, Jakob J.; Kolster, Till; Müller-Hansen, Finn; Otto, Ilona M.; Zimmerer, Kilian B.; Lucht, Wolfgang
    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. © Author(s) 2020.