Articles | Volume 11, issue 10
https://doi.org/10.5194/gmd-11-4139-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-4139-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
12 Oct 2018
Model evaluation paper |
| 12 Oct 2018
| 12 Oct 2018
Global hydro-climatic biomes identified via multitask learning
Christina Papagiannopoulou
CORRESPONDING AUTHOR
Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
Diego G. Miralles
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
Matthias Demuzere
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
Niko E. C. Verhoest
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
Willem Waegeman
Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
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- Dynamics as a cause for the nanoscale organization of the genome R. Barth et al. 10.1080/19491034.2020.1763093
- Towards better characterization of global warming impacts in the environment through climate classifications with improved global models A. Navarro et al. 10.1002/joc.7527
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- Intensification of the dispersion of the global climatic landscape and its potential as a new climate change indicator Y. Guan et al. 10.1088/1748-9326/aba2a7
- Segmentation of global climate dataset into contiguous spatial units having quantitatively homogeneous climates P. Netzel & T. Stepinski 10.1002/joc.7606
- Effects of Drought on Vegetation Productivity of Farmland Ecosystems in the Drylands of Northern China X. Zhu et al. 10.3390/rs13061179
- Multi-target prediction: a unifying view on problems and methods W. Waegeman et al. 10.1007/s10618-018-0595-5
- Coherence of global hydroclimate classification systems K. McCurley Pisarello & J. Jawitz 10.5194/hess-25-6173-2021
- Multi-target prediction for dummies using two-branch neural networks D. Iliadis et al. 10.1007/s10994-021-06104-5
1 citations as recorded by crossref.
Latest update: 14 Dec 2024
Short summary
Common global land cover and climate classifications are based on vegetation–climatic characteristics derived from observational data, ignoring the interaction between the local climate and biome. Here, we model the interplay between vegetation and local climate by discovering spatial relationships among different locations. The resulting global
hydro-climatic biomescorrespond to regions of coherent climate–vegetation interactions that agree well with traditional global land cover maps.
Common global land cover and climate classifications are based on vegetation–climatic...
