Earth System Data Cubes: Avenues for Advancing Earth System Research

Abstract

Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spatio-temporal resolutions. Earth System Data Cubes (ESDCs) have emerged as one suitable solution for transforming this flood of data into a simple yet robust data structure. ESDCs achieve this by organising data into an analysis-ready format aligned with a spatio-temporal grid, facilitating user-friendly analysis and diminishing the need for extensive technical data processing knowledge. Despite these significant benefits, the completion of the entire ESDC life cycle remains a challenging task. Obstacles are not only of a technical nature but also relate to domain-specific problems in Earth system research. There exist barriers to realising the full potential of data collections in light of novel cloud-based technologies, particularly in curating data tailored for specific application domains. These include transforming data to conform to a spatio-temporal grid with minimum distortions and managing complexities such as spatio-temporal autocorrelation issues. Addressing these challenges is pivotal for the effective application of Artificial Intelligence (AI) approaches. Furthermore, adhering to open science principles for data dissemination, reproducibility, visualisation, and reuse is crucial for fostering sustainable research. Overcoming these challenges offers a substantial opportunity to advance data-driven Earth system research, unlocking the full potential of an integrated, multidimensional view of Earth system processes. This is particularly true when such research is coupled with innovative research paradigms and technological progress.

Publication
arXiv
David Montero
David Montero
PhD candidate / Earth System Data Science
Guido Kraemer
Guido Kraemer
Postdoctoral associate / Earth System Data Science
Ida Flik
Ida Flik
Research Fellow / Earth System Data Science
Sarah Habershon
Sarah Habershon
Research Fellow / Earth System Data Science
Chaonan Ji
Chaonan Ji
Postdoctoral fellow / Earth System Data Science
Francesco Martinuzzi
Francesco Martinuzzi
PhD candidate / Earth System Data Science
Martin Reinhardt
Martin Reinhardt
Postdoctoral fellow / Earth System Data Science
Maximilian Söchting
Maximilian Söchting
PhD candidate / Earth System Data Science
Khalil Teber
Khalil Teber
PhD candidate / Earth System Data Science
Miguel D. Mahecha
Miguel D. Mahecha
Professor for Earth System Data Science