Articles | Volume 11, issue 1
https://doi.org/10.5194/esd-11-201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Earth system data cubes unravel global multivariate dynamics
Miguel D. Mahecha
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Michael Stifel Center Jena for Data-Driven and Simulation Science, Jena, Germany
Fabian Gans
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
Gunnar Brandt
Brockmann Consult GmbH, Hamburg, Germany
Rune Christiansen
Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
Sarah E. Cornell
Stockholm Resilience Center, Stockholm University, Stockholm, Sweden
Normann Fomferra
Brockmann Consult GmbH, Hamburg, Germany
Guido Kraemer
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Image Processing Lab, Universitat de València, Paterna, Spain
Jonas Peters
Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
Paul Bodesheim
Max Planck Institute for Biogeochemistry, Jena, Germany
Computer Vision Group, Friedrich Schiller University Jena, Jena, Germany
Gustau Camps-Valls
Image Processing Lab, Universitat de València, Paterna, Spain
Jonathan F. Donges
Stockholm Resilience Center, Stockholm University, Stockholm, Sweden
Earth System Analysis, Potsdam Institute for Climate Impact Research, PIK, Potsdam, Germany
Wouter Dorigo
Department of Geodesy and Geo-Information, TU Wien, Vienna, Austria
Lina M. Estupinan-Suarez
Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Geography, Friedrich Schiller University Jena, Jena, Germany
Victor H. Gutierrez-Velez
Department of Geography and Urban Studies, Temple University, Philadelphia, PA, USA
Martin Gutwin
Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Geography, Friedrich Schiller University Jena, Jena, Germany
Martin Jung
Max Planck Institute for Biogeochemistry, Jena, Germany
Maria C. Londoño
Alexander von Humboldt Biological Resources Research Institute, Bogotá, Colombia
Diego G. Miralles
Hydro-Climate Extremes Lab (H-CEL), Ghent, Belgium
Phillip Papastefanou
TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
Markus Reichstein
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Michael Stifel Center Jena for Data-Driven and Simulation Science, Jena, Germany
Model code and software
Final version of the Data cube paper code F. Gans https://doi.org/10.5281/zenodo.3670742
ESA Earth System Laboratory N. Fomferra https://github.com/esa-esdl
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
The ever-growing availability of data streams on different subsystems of the Earth brings...
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Final-revised paper
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