Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-4593-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-4593-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Jul 2026
Data description article |
| 06 Jul 2026
| 06 Jul 2026
A four-decade global Lagrangian air-parcel trajectory dataset for atmospheric moisture and heat analysis
Victoria M. H. Deman
CORRESPONDING AUTHOR
Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium
Damián Insua-Costa
Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium
Jessica Keune
European Centre for Medium-Range Weather Forecasts, Bonn, Germany
Akash Koppa
Department of Geography and Environmental Science, University of Reading, Reading, United Kingdom
Diego G. Miralles
Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
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Short summary
We present a global dataset that follows the movement of air carrying water and heat through the atmosphere from 1979 to 2024. Using weather reanalysis data, we tracked millions of air parcels and recorded their physical properties as they moved through the atmosphere. The dataset can be used to reveal where rainfall and warming originate and how they travel across land and ocean. This dataset can support climate and water studies without the need for costly simulations.
We present a global dataset that follows the movement of air carrying water and heat through the...
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