![]() ![]() 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 An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. 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. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. 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. ![]() However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. ![]()
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