Articles | Volume 10, issue 5
https://doi.org/10.5194/gmd-10-1945-2017
https://doi.org/10.5194/gmd-10-1945-2017
Model evaluation paper
 | 
17 May 2017
Model evaluation paper |  | 17 May 2017

A non-linear Granger-causality framework to investigate climate–vegetation dynamics

Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman

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Latest update: 19 May 2024
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Short summary
Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.