Articles | Volume 15, issue 6
https://doi.org/10.5194/essd-15-2445-2023
© Author(s) 2023. 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-15-2445-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Jun 2023
Data description paper |
| 12 Jun 2023
| 12 Jun 2023
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Dirk Nikolaus Karger
CORRESPONDING AUTHOR
Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903
Birmensdorf, Switzerland
Stefan Lange
Potsdam Institute for Climate Impact Research (PIK), Member of
Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Chantal Hari
Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903
Birmensdorf, Switzerland
Wyss Academy for Nature at the University of Bern, Kochergasse 4,
3011 Bern, Switzerland
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Christopher P. O. Reyer
Potsdam Institute for Climate Impact Research (PIK), Member of
Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Olaf Conrad
Institute of Geography, University of Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Niklaus E. Zimmermann
Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903
Birmensdorf, Switzerland
Katja Frieler
Potsdam Institute for Climate Impact Research (PIK), Member of
Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
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Latest update: 09 Mar 2025
Short summary
We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
We present the first 1 km, daily, global climate dataset for climate impact studies. We show...
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