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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Ionuț Iosifescu Enescu, David Hanimann, Dominik Haas-Artho, Marius Rüetschi, Dirk Nikolaus Karger, Gian-Kasper Plattner, Martin Hägeli, Rebecca Kurup Buchholz, Lucia de Espona, Niklaus E. Zimmermann, and Loïc Pellissier
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Ionuț Iosifescu Enescu, David Hanimann, Dominik Haas-Artho, Marius Rüetschi, Dirk Nikolaus Karger, Gian-Kasper Plattner, Martin Hägeli, Rebecca Kurup Buchholz, Lucia de Espona, Niklaus E. Zimmermann, and Loïc Pellissier
Abstr. Int. Cartogr. Assoc., 3, 120, https://doi.org/10.5194/ica-abs-3-120-2021, https://doi.org/10.5194/ica-abs-3-120-2021, 2021
Abhijeet Mishra, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 14, 6467–6494, https://doi.org/10.5194/gmd-14-6467-2021, https://doi.org/10.5194/gmd-14-6467-2021, 2021
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Timber plantations are an increasingly important source of roundwood production, next to harvest from natural forests. However, timber plantations are currently underrepresented in global land-use models. Here, we include timber production and plantations in the MAgPIE modeling framework. This allows one to capture the competition for land between agriculture and forestry. We show that increasing timber plantations in the coming decades partly compete with cropland for limited land resources.
Matthias Mengel, Simon Treu, Stefan Lange, and Katja Frieler
Geosci. Model Dev., 14, 5269–5284, https://doi.org/10.5194/gmd-14-5269-2021, https://doi.org/10.5194/gmd-14-5269-2021, 2021
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To identify the impacts of historical climate change it is necessary to separate the effect of the different impact drivers. To address this, one needs to compare historical impacts to a counterfactual world with impacts that would have been without climate change. We here present an approach that produces counterfactual climate data and can be used in climate impact models to simulate counterfactual impacts. We make these data available through the ISIMIP project.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
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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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