Details
| Original language | English |
|---|---|
| Article number | e2025EA004762 |
| Journal | Earth and Space Science |
| Volume | 12 |
| Issue number | 10 |
| Early online date | 14 Oct 2025 |
| Publication status | Published - Oct 2025 |
Abstract
Climate variability affects multiple processes on Earth, with significant system effects driving hydrometeorological, glaciological, atmospheric, and geophysical variability. Research into these fields is driven by acquisition and processing of voluminous amount of data at multiple spatial and temporal scales. Intersection of data and tools to work around this complexity, to extract a consistent and useful picture of the effects of climate change in the Earth System, requires handling of big data sets and their processing tools. This effort is generating novel approaches to the analysis of big data sets and new perspective on the predictive power of the tools used. For this reason, in March 2023, AGU launched the Special Collection Analyzing Big Data for Understanding Climate Variability, Natural Phenomena, and Rapid Environmental Changes, inviting contributions to showcase the latest advances and the role of machine learning and deep learning in climate data analysis. In this introduction, we outline the key findings and insights presented in 16 articles published in the special collection, and we highlight the emerging trends within this field of research. The following journals participated in the special collection: Journal of Geophysical Research: Solid Earth, Journal of Geophysical Research: Atmospheres, Geophysical Research Letters, and Earth and Space Science.
ASJC Scopus subject areas
- Environmental Science(all)
- Environmental Science (miscellaneous)
- Earth and Planetary Sciences(all)
- General Earth and Planetary Sciences
Sustainable Development Goals
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In: Earth and Space Science, Vol. 12, No. 10, e2025EA004762, 10.2025.
Research output: Contribution to journal › Editorial in journal › Research › peer review
}
TY - JOUR
T1 - Introduction to the Special Collection
T2 - Analyzing Big Data for Understanding Climate Variability, Natural Phenomena, and Rapid Environmental Changes
AU - Montillet, J. P.
AU - Caprarelli, G.
AU - Kermarrec, G.
AU - Forootan, E.
AU - Haberreiter, M.
AU - He, X.
AU - Fernandes, R.
AU - Xie, Z.
AU - Manighetti, I.
N1 - Publisher Copyright: © 2025. The Author(s). Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union.
PY - 2025/10
Y1 - 2025/10
N2 - Climate variability affects multiple processes on Earth, with significant system effects driving hydrometeorological, glaciological, atmospheric, and geophysical variability. Research into these fields is driven by acquisition and processing of voluminous amount of data at multiple spatial and temporal scales. Intersection of data and tools to work around this complexity, to extract a consistent and useful picture of the effects of climate change in the Earth System, requires handling of big data sets and their processing tools. This effort is generating novel approaches to the analysis of big data sets and new perspective on the predictive power of the tools used. For this reason, in March 2023, AGU launched the Special Collection Analyzing Big Data for Understanding Climate Variability, Natural Phenomena, and Rapid Environmental Changes, inviting contributions to showcase the latest advances and the role of machine learning and deep learning in climate data analysis. In this introduction, we outline the key findings and insights presented in 16 articles published in the special collection, and we highlight the emerging trends within this field of research. The following journals participated in the special collection: Journal of Geophysical Research: Solid Earth, Journal of Geophysical Research: Atmospheres, Geophysical Research Letters, and Earth and Space Science.
AB - Climate variability affects multiple processes on Earth, with significant system effects driving hydrometeorological, glaciological, atmospheric, and geophysical variability. Research into these fields is driven by acquisition and processing of voluminous amount of data at multiple spatial and temporal scales. Intersection of data and tools to work around this complexity, to extract a consistent and useful picture of the effects of climate change in the Earth System, requires handling of big data sets and their processing tools. This effort is generating novel approaches to the analysis of big data sets and new perspective on the predictive power of the tools used. For this reason, in March 2023, AGU launched the Special Collection Analyzing Big Data for Understanding Climate Variability, Natural Phenomena, and Rapid Environmental Changes, inviting contributions to showcase the latest advances and the role of machine learning and deep learning in climate data analysis. In this introduction, we outline the key findings and insights presented in 16 articles published in the special collection, and we highlight the emerging trends within this field of research. The following journals participated in the special collection: Journal of Geophysical Research: Solid Earth, Journal of Geophysical Research: Atmospheres, Geophysical Research Letters, and Earth and Space Science.
UR - http://www.scopus.com/inward/record.url?scp=105018775687&partnerID=8YFLogxK
U2 - 10.1029/2025EA004762
DO - 10.1029/2025EA004762
M3 - Editorial in journal
AN - SCOPUS:105018775687
VL - 12
JO - Earth and Space Science
JF - Earth and Space Science
SN - 2333-5084
IS - 10
M1 - e2025EA004762
ER -