Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year 4.890
  • CiteScore value: 4.49 CiteScore 4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Volume 11, issue 10 | Copyright
Geosci. Model Dev., 11, 4139-4153, 2018
https://doi.org/10.5194/gmd-11-4139-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 12 Oct 2018

Model evaluation paper | 12 Oct 2018

Global hydro-climatic biomes identified via multitask learning

Christina Papagiannopoulou1, Diego G. Miralles2, Matthias Demuzere2, Niko E. C. Verhoest2, and Willem Waegeman1 Christina Papagiannopoulou et al.
  • 1Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
  • 2Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium

Abstract. The most widely used global land cover and climate classifications are based on vegetation characteristics and/or climatic conditions derived from observational data. However, these classification schemes do not directly stem from the characteristic interaction between the local climate and the biotic environment. In this work, we model the dynamic interplay between vegetation and local climate in order to delineate ecoregions that share a coherent response to hydro-climate variability. Our novel framework is based on a multitask learning approach that discovers the spatial relationships among different locations by learning a low-dimensional representation of predictive structures. This low-dimensional representation is combined with a clustering algorithm that yields a classification of biomes with coherent behaviour. Experimental results using global observation-based datasets indicate that, without the need to prescribe any land cover information, the identified regions of coherent climate–vegetation interactions agree well with the expectations derived from traditional global land cover maps. The resulting global hydro-climatic biomes can be used to analyse the anomalous behaviour of specific ecosystems in response to climate extremes and to benchmark climate–vegetation interactions in Earth system models.

Publications Copernicus
Download
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 biomes correspond 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...
Citation
Share